Cloud Cost Management Blogs

The Problem with Ignoring Cost in CI/CD

If you’ve ever pushed a feature branch that quietly triggered multiple production deployments—and only realized the impact when the AWS bill jumped 240% month-over-month—you already understand the problem.

Cost awareness in CI/CD pipelines isn’t about slowing teams down. It’s about avoiding financial surprises that lead to tense finance meetings and urgent cost-cutting exercises.

Many platform engineering teams treat cloud spend as something to review after deployment. Code ships. Infrastructure scales. Services consume resources. Weeks later, someone from finance posts a Slack screenshot of a sharply rising spend graph. By that point, the expensive workload has been running for days or weeks. Rolling it back risks disruption. And the engineers who shipped it are already focused on the next sprint.

That reactive model might work when cloud usage is stable and margins are wide. It breaks down quickly as deployment velocity increases and systems become more complex. Without pipeline cost visibility built into your workflows, teams optimize purely for speed—without seeing the financial impact of each merge.

Why CI/CD Cost Awareness Fails by Default

Traditional pipelines are designed for one purpose: delivering code to production quickly and reliably. Teams track build duration, deployment success rates, and test coverage. But cloud cost governance pipelines? That usually sits outside the CI/CD system.

This creates a structural gap.

Engineers making deployment decisions rarely see the cost implications of those decisions in real time. You can monitor CPU usage, memory, and latency—but not that your new microservice is quietly generating $400 per day in cross-region data transfer charges.

That disconnect leads to friction:

• Engineers optimize for performance and functionality.
• Finance focuses on budgets and spend controls.
• Platform teams are left reconciling the two after costs have already accumulated.

By the time a cost spike is discovered, the context behind the deployment is often lost. The feedback loop is simply too slow.

At enterprise scale, small inefficiencies compound. One team’s cost regression might be negligible. Ten teams introducing cost-heavy services every week becomes a serious budget issue. Without infrastructure cost tracking at the pipeline level, you can’t clearly attribute increases to specific deployments or commits. You see total spend rising—but not what caused it.

Building Cost Awareness into CI/CD Workflows

The goal isn’t to introduce manual approvals or slow down delivery. The goal is to make cost data visible early enough for teams to make smarter decisions before code hits production.

1. Automated Cost Feedback Loops

One of the most effective ways to enable CI/CD cost optimization is by integrating automated cost feedback loops directly into pipeline stages.

Before a deployment completes, your system should estimate the incremental cost impact and surface it alongside build and test results.

For example:

• Deploying a Kubernetes service? Estimate compute, storage, and networking costs based on the manifest.
• Provisioning infrastructure via Terraform? Calculate projected monthly run rate before applying changes.
• Scaling a service? Predict resource usage and associated cost impact.

The estimates don’t need to be perfect. Directional accuracy is enough to catch major regressions. If a deployment is projected to increase monthly spend by 30%, that’s a signal to pause and evaluate. If the cost delta is minimal, the pipeline proceeds normally.

This approach enables build pipeline cost control without adding unnecessary friction.

2. Pipeline Cost Visibility and Budget Guardrails

Once cost data flows through your pipelines, the next step is establishing budget guardrails.

Pipeline cost visibility allows you to define thresholds—for example, triggering a review if service-level spend increases by more than 20%. This doesn’t block innovation; it simply ensures cost increases are intentional.

With this model:

• Teams deploy freely within defined cost parameters.
• Significant cost jumps trigger additional context or approval.
• Cost regressions are caught before they become financial escalations.

Infrastructure cost tracking at the pipeline level also improves attribution. Instead of reviewing spend by account or department, you can tie cost increases directly to individual pipeline runs and commits. That clarity makes DevOps cost management far more actionable.

3. Shifting Cost Ownership Left

True FinOps CI/CD integration means shifting cost ownership closer to the engineers making infrastructure decisions.

Cost becomes a first-class operational metric—alongside performance, reliability, and security.

When cost data lives in the same interface as builds and deployments, teams naturally factor it into trade-offs. You reduce the need for reactive enforcement because engineers can see and adjust in real time.

This alignment benefits everyone:

• Engineers maintain speed.
• Platform teams maintain control.
• Finance gains visibility and predictability.

Cloud cost governance pipelines work best when they support engineering velocity—not compete with it.

How Harness Cloud Cost Management Enables Pipeline-Level Cost Awareness

Harness Cloud Cost Management is designed to connect DevOps execution with financial accountability.

Unlike traditional tools that focus on billing-level reporting, Harness embeds pipeline cost visibility directly into CI/CD workflows. Engineers receive real-time cost feedback in the same system where they manage builds and deployments.

Key capabilities include:

• Service- and pipeline-level cost analysis
• Cost anomaly detection and trend monitoring
• Policy-based budget thresholds and governance controls
• Cost allocation, showback, and chargeback models

If a deployment exceeds predefined thresholds, the pipeline can automatically flag it or enforce policy-based controls—supporting consistent build pipeline cost control across teams.

By connecting cost allocation directly to services, teams, and pipeline runs, organizations gain granular insight into what drives spend. Conversations between finance and engineering become fact-based and collaborative rather than reactive.

For teams already using Harness CI/CD, adding cost awareness becomes a natural extension of existing workflows—no context switching required.

Learn more about Harness Cloud Cost Management and explore the cost visibility and governance capabilities available in the platform.

Embedding Cost Discipline Without Slowing Teams Down

Cloud cost management at scale can’t rely on monthly budget reviews or occasional optimization sprints. It has to be embedded where cost decisions actually happen: inside your CI/CD pipelines.

When engineers see cost impact in real time, they make smarter trade-offs.
When platform teams enforce guardrails programmatically, they prevent regressions early.
When finance has attribution tied to specific deployments, discussions become clearer and more productive.

Cost awareness in CI/CD pipelines isn’t friction—it’s context.

The teams that succeed with CI/CD cost optimization don’t treat cost as a constraint. They treat it as an operational signal that improves engineering decisions.

If your organization has struggled with unexpected cloud spend or unclear attribution, it may be time to rethink where cost visibility lives. Embedding DevOps cost management directly into your CI/CD workflows gives you the speed of modern delivery—without sacrificing financial control.

What Is Shift-Left FinOps?

Shift-Left FinOps reframes cloud cost optimization as an engineering responsibility rather than a retrospective financial review.

Instead of analyzing cloud spend after infrastructure has already been deployed, organizations integrate FinOps automation and cost governance directly into development workflows.

Developers receive immediate feedback about the financial impact of infrastructure changes during development, not weeks later during billing reconciliation.

This approach aligns FinOps best practices with modern platform engineering workflows built around:

• Infrastructure as Code (IaC)
• automated CI/CD pipelines
• Policy as Code governance
• real-time cost visibility
  

The result is proactive cost management, where waste is prevented before resources ever reach production.

Why Traditional FinOps Creates Cloud Cost Governance Gaps

Most organizations still treat FinOps as a retrospective discipline.

Finance teams review monthly cloud bills, identify anomalies, and ask engineering teams to investigate cost spikes.

This approach worked when infrastructure provisioning happened slowly through manual processes.

Modern cloud environments operate differently.

Teams now deploy infrastructure changes dozens or even hundreds of times per day through automated pipelines.

By the time billing data arrives, the operational context behind those provisioning decisions has already disappeared.

This delay introduces several operational challenges.

Cost Attribution Becomes Difficult

Without consistent tagging and governance policies, organizations struggle to determine:

• which team owns specific resources
• which service generated costs
• which environment the infrastructure belongs to
  

Missing metadata makes cloud financial management and cost attribution significantly harder.

Optimization Becomes Reactive Remediation

When cost issues are discovered weeks later, teams must retrofit governance controls onto already-running infrastructure.

This reactive approach introduces operational risk and disrupts delivery schedules.

Instead of preventing waste, teams are forced into post-deployment cloud cost optimization efforts.

Developers Lack Cost Visibility

Developers often make infrastructure decisions without understanding their financial implications.

Without real-time cost visibility, engineers cannot evaluate tradeoffs between:

• instance sizes
• storage tiers
• managed service configurations
  

Shift-Left FinOps addresses these problems by embedding Infrastructure as Code cost control and governance earlier in the development lifecycle.

Core Components of Shift-Left FinOps Implementation

Implementing Shift-Left FinOps requires three foundational capabilities:

1. Policy as Code governance
2. Infrastructure as Code cost control integration
3. Automated cost visibility and feedback loops
   

Together, these capabilities enable FinOps automation and proactive cost management across cloud environments.

Codifying Cloud Cost Governance with Policy as Code

Policy as Code frameworks translate financial governance requirements into enforceable rules.

These rules automatically evaluate infrastructure definitions before resources are deployed.

Instead of relying on documentation or manual enforcement, policy as code provides automated cloud cost governance directly within engineering workflows.

Effective cost governance policies typically address three categories of waste.

Tagging Enforcement

Policies ensure every resource includes metadata required for cost attribution.

Examples include:

• environment
• team ownership
• cost center
  

Resource Sizing Policies

Governance rules prevent developers from provisioning oversized instances for workloads that do not require maximum capacity.

This supports long-term cloud cost optimization and prevents overprovisioning.

Lifecycle Management Policies

Policies identify resources missing automated shutdown schedules, retention rules, or lifecycle controls.

These controls prevent idle resources from generating unnecessary costs.

Example conceptual tagging policy:

With Policy as Code enforcement, developers receive immediate feedback during infrastructure validation rather than after deployment.

Integrating Infrastructure as Code Cost Control into Development Workflows

Infrastructure as Code provides the technical foundation for shift-left cloud cost governance.

IaC allows infrastructure changes to be:

• reviewed
• tested
• validated
• audited
  

before deployment.

These characteristics create natural enforcement points for Infrastructure as Code cost control policies.

Local Development Validation

Developers run policy checks locally before committing infrastructure changes.

This prevents cost policy violations from entering shared repositories.

Early validation enables proactive cost management during development.

CI/CD Pipeline Enforcement

Pull request pipelines automatically validate infrastructure definitions against governance policies.

If cost policies fail, the merge is blocked.

Example validation workflow:

This ensures consistent cloud cost governance across all infrastructure deployments.

Deployment Pipeline Validation

Production deployment pipelines include a final validation step before infrastructure changes are applied.

This layered validation model creates defense in depth for FinOps automation:

• development validation prevents wasted effort
• CI/CD validation prevents policy drift
• deployment validation prevents actual cost impact

Enabling Real-Time Cost Visibility for Developers

Shift-Left FinOps only works when developers have access to cost insights during infrastructure planning.

Without cost visibility, governance policies feel arbitrary and difficult to follow.

Cost estimation should occur during infrastructure planning stages, not after deployment.

When developers run terraform plan, they should also see estimated monthly costs associated with proposed infrastructure changes.

This allows developers to evaluate architectural tradeoffs such as:

• instance sizing
• storage tier selection
• service configuration

Integrating cost feedback into existing workflows improves adoption.

Examples include:

• pull request comments showing cost impact
• budget alerts routed to engineering channels
• optimization recommendations during infrastructure review
  

These feedback loops support FinOps best practices by making cost awareness part of everyday development work.

Common Pitfalls in Shift-Left FinOps Implementation

Organizations implementing shift-left cloud cost governance frequently encounter predictable challenges.

Understanding these patterns helps teams implement FinOps automation successfully.

Overly Restrictive Policies

Governance policies that generate frequent false positives slow developer velocity.

Developers may attempt to bypass governance controls.

Policies should focus on real sources of cloud cost waste.

Manual Governance Processes

Shift-left cost governance fails when platform teams must manually review every infrastructure change.

All governance rules should be automated through Policy as Code and CI/CD validation pipelines.

Lack of Cost Context

Providing policies without cost visibility creates confusion.

Developers need both:

• clear governance rules
• cost impact insights
  

Disrupting Developer Workflows

Successful governance systems integrate into existing workflows such as:

• Terraform development
• pull request review
• CI/CD deployment pipelines
  

The most effective governance systems remain invisible until violations occur.

Implementing Proactive Cost Management with Harness Cloud Cost Management

Harness Cloud Cost Management enables organizations to implement Shift-Left FinOps and proactive cost management at scale.

The platform integrates FinOps automation and cost governance directly into platform engineering workflows.

Harness CCM connects cloud environments across:

• AWS
• Azure
• GCP
  

This provides unified cost visibility across multi-cloud infrastructure.

Real-time cost allocation allows developers to see cost breakdowns during infrastructure provisioning rather than waiting for billing cycles.

Teams can enforce governance policies such as:

• tagging requirements
• resource sizing policies
• budget constraints

These policies automatically validate infrastructure changes during development and CI/CD pipelines.

Harness CCM also supports cloud cost optimization through automated insights and recommendations, including:

• rightsizing underutilized instances
• deleting orphaned resources
• optimizing storage tiers
  

These capabilities help organizations implement modern cloud financial management practices while maintaining developer velocity.

Frequently Asked Questions

How does Shift-Left FinOps support cloud cost optimization?

Shift-Left FinOps prevents waste before resources are deployed by embedding cost governance directly into development workflows.

This proactive model improves cloud cost optimization and cloud financial management outcomes.

What tools enable Policy as Code cost governance?

Typical implementations include:

• Infrastructure as Code tools such as Terraform
• policy frameworks like Open Policy Agent
• CI/CD pipeline integrations
  

These technologies enable automated cloud cost governance through policy as code.

Does shift-left governance slow developer velocity?

No. When implemented correctly, automated cost policies provide immediate feedback without manual approvals.

This improves delivery speed while maintaining cost control and FinOps automation.

How do organizations enforce governance across multiple clouds?

Organizations define standardized governance policies that apply across AWS, Azure, and GCP.

These policies focus on universal patterns such as:

• tagging
• resource sizing
• lifecycle management
  

This approach supports consistent multi-cloud cost governance and financial management.

Conclusion

Shift-Left FinOps transforms cloud cost optimization from a reactive financial process into a proactive engineering practice.

By embedding Policy as Code governance, Infrastructure as Code cost control, and automated FinOps workflows into development pipelines, organizations prevent waste before infrastructure reaches production.

The result is stronger cloud cost governance, improved cloud financial management, and more efficient cloud operations.

Developers gain real-time cost insights.
Platform teams enforce governance automatically.
Finance teams gain accurate cost attribution across environments.

At the scale of modern cloud infrastructure, proactive cost management is essential for sustainable cloud growth.

If cloud cost optimization feels like a never-ending game of whack-a-mole—new recommendations every 30 days, the same debates with engineering, another set of dashboards no one trusts—you’re not alone.

But what if your cloud cost optimization strategy is the reason your AWS bill keeps climbing?

Not the lack of one.
Not poor execution.
The strategy itself.

We've seen this pattern dozens of times: teams implement tagging standards, build dashboards, schedule monthly FinOps reviews, and still watch costs spiral. The infrastructure is tagged. The metrics exist. The meetings happen. Yet every quarter, the CFO asks the same uncomfortable question:

“Why are we spending this much?”

The problem usually isn’t the idea of optimization. It’s the approach: too reactive, too late in the lifecycle, and too disconnected from how software is actually built and shipped.

And in high-velocity engineering environments, that gap between deployment and optimization review is exactly where runaway spend lives.

Why Traditional Cloud Cost Optimization Strategies Fail at Scale

Most organizations adopt a cloud cost management approach that sounds reasonable:

Deploy infrastructure → monitor spend → identify anomalies → remediate issues → repeat.

This is the classic “observe and optimize” model, borrowed from decades of on-premises capacity planning.

It breaks in the cloud.

In traditional datacenters, provisioning took weeks. Infrastructure decisions went through multiple approval layers. The natural friction slowed spend.

In cloud environments, engineers can provision thousands of dollars of compute in minutes. The speed that makes cloud infrastructure powerful also makes reactive cost optimization dangerously slow.

The Monthly Treadmill Problem

A huge reason teams feel like they’re starting over every month is that the default workflow looks like this:

Spend happens
A report shows waste
FinOps sends recommendations
Engineering says “not now”
Repeat next month

Even if your team is doing all the “right” things—rightsizing, commitments, idle cleanup, non-prod shutdown—you’re still reacting to what already happened.

And if your cloud spending optimization depends on sporadic human follow-through, you’ll keep reliving the same cycle.

The Reporting Trap

The most common failure mode we encounter is what we call “the reporting trap.”

Organizations invest heavily in cost visibility dashboards, allocation reports, and trend analysis, then wonder why costs don't improve.

The reports show what happened.
They rarely prevent what’s about to happen.

Consider a typical scenario: an engineering team deploys a new microservice on Friday. It includes an RDS instance sized for anticipated peak load, plus a few EC2 instances running 24/7 for background processing.

The deployment succeeds. The service works.

Two weeks later, someone notices the RDS instance costs $3,000/month and runs at 12% utilization. By the time this surfaces in a cost review, you’ve burned $6,000.

Reporting-based infrastructure cost optimization identifies problems. It doesn’t prevent them.

And in CI/CD environments shipping multiple times per day, prevention matters far more than detection.

The Allocation Illusion

Another common broken strategy: obsess over cost allocation and chargeback models.

Get the tagging right.
Assign every dollar to a team.
Generate showback reports.
Declare victory.

Allocation solves an accounting problem. It doesn’t solve an engineering problem.

Knowing which team caused overspend doesn’t stop the next deployment from repeating the same mistake. It creates visibility into financial responsibility without creating controls that prevent waste.

Effective cloud cost governance requires allocation and guardrails. You need to know who’s spending—but you also need mechanisms that stop obviously wasteful configurations from ever reaching production.

FinOps Best Practices: Finance + DevOps (And That’s the Point)

A lot of cloud cost optimization strategies fail because they treat FinOps as:

• a tool
• a tagging project
• a finance initiative
• a savings sprint
• “finance trying to cut engineering’s budget”

But mature FinOps best practices are built around collaboration:

Finance, engineering, infrastructure/platform teams, and business owners operating from the same data and goals—even if their priorities differ.

• Finance wants predictability and accountability
• Engineering wants velocity and reliability
• Platform teams want consistency and governance
• Business owners want clear unit economics and value delivery

When those groups operate in silos, cloud bills become a mystery, optimization becomes political, and waste becomes “the cost of doing business.”

A mature cloud cost optimization strategy flips that. It makes spend a shared responsibility—with shared context.

What Cloud Cost Optimization Should Actually Look Like

A working cost optimization framework starts from a different premise:

Cost decisions should happen at the same place and time as infrastructure decisions.

Not in a dashboard two weeks later.
Not in a quarterly business review.

In the pull request.
In the Terraform plan.
In the CI/CD pipeline before deployment.

Shift Cost Controls Left (Shift-Left FinOps)

The biggest step-change happens when you stop treating cloud cost reduction strategy work as an operational clean-up task—and start treating cost governance as a software delivery design constraint.

That’s what “shift left” means in a cost context: bringing optimization upstream into the provisioning and deployment workflow before overspend becomes production reality.

Because engineers don’t overprovision out of malice. They do it because their job is reliability:

• “Let’s size for the spike.”
• “Let’s pick the robust instance.”
• “Let’s over-allocate just in case.”

And then utilization never reaches what was provisioned.

Shift-left changes the default by putting guardrails and approved patterns into the path engineers already use to ship software—so cost control doesn’t require constant cost review meetings.

Think Roads, Not Speeding Tickets

A useful mental model is roads and cars:

Applications are the cars.
Infrastructure is the road system.
Roads set the rules—speed limits, exits, lanes—not the cars.

When your platform and provisioning workflows define the safe, optimized options, you reduce chaos and make the right choice the easy choice.

That’s what scalable cloud cost governance actually looks like.

“Zero Drift”: Don’t Just Set Guardrails—Keep Them

Once you shift left, the next question is:

How do you prevent teams from gradually drifting away from the intended standard?

That’s where the concept of zero drift comes in.

Zero drift is the idea that the desired state (cost-aware, governed, optimized) is continuously enforced through automation—so you aren’t babysitting optimization forever.

Humans shouldn’t be the control plane.

In practice, zero drift means:

• provisioning is standardized and policy-driven
• instance/cluster choices are constrained to approved configurations
• optimization actions (like rightsizing) can be automated with confidence
• anomalies are monitored, investigated, and resolved without breaking the system

Instead of monthly restarts, you get continuous alignment.

This is the difference between a cloud cost management approach that scales and one that collapses under velocity.

Tagging: Necessary, Painful… and Still a Common Failure Mode

Let’s address the elephant in the room: visibility.

If you can’t reliably answer “who is spending what, and why?” you can’t run FinOps at scale.

And yet, even in large organizations, tagging quality is frequently the weak link. Many companies can’t attribute the vast majority of spend with high confidence.

That’s not just an administrative issue—it’s a blocker for automation.

You can’t automate decisions against spend you can’t confidently attribute.

The takeaway is simple:

Treat attribution as foundational, but don’t stop there. Mature FinOps doesn’t end at “better tags.” It moves toward system-enforced governance and workload-level controls that reduce dependence on perfect tagging for every single decision.

The Pivot: From Savings to Unit Economics (and Business Value)

Most teams eventually hit diminishing returns on classic savings levers:

• Reserved instances / savings plans
• basic rightsizing
• cleaning up idle resources
• non-prod stopping
• commitment discounts

At some point, you’ve harvested the low-hanging fruit.

The next question becomes:

How do we define—and improve—the value of every cloud dollar going forward?

That’s where unit economics comes in.

Instead of asking “How much did we save?” you ask:

• What does it cost per customer?
• Per transaction?
• Per workload?
• Per feature, environment, or product line?

This reframes cloud cost reduction strategy work from “cost cutting” to “value engineering.”

And it’s one of the clearest signals that your cloud cost optimization strategy has matured.

How Harness Cloud Cost Management Approaches This Problem

Harness Cloud Cost Management is built around the premise that cost optimization happens in the engineering workflow, not after it.

Instead of treating cost management as a separate finance function, it integrates cost visibility and governance directly into CI/CD pipelines, infrastructure provisioning workflows, and day-to-day development processes.

Cost Visibility Across Your Entire Cloud Estate

Harness provides unified cost visibility across AWS, Azure, GCP, and Kubernetes clusters, with automatic allocation by team, service, environment, and business unit.

You get real-time dashboards showing exactly where spend is happening, down to individual workloads and namespaces.

Cost anomaly detection highlights unexpected changes automatically, with alerts routed directly to responsible engineering teams.

This supports both showback and chargeback models—without creating manual reporting overhead. Teams see their spend in real time, not weeks after the invoice closes.

In-Workflow Cost Governance

Where Harness differs from traditional tools is how governance works.

Cost policies enforce directly in CI/CD pipelines and infrastructure-as-code workflows.

Before a Terraform plan applies, Harness evaluates estimated costs against defined budgets and thresholds. If a deployment would exceed limits, the pipeline fails with clear feedback on what needs to change.

This creates a natural feedback loop where engineers see cost impacts immediately—while they still have full context on the infrastructure decisions being made.

It prevents expensive mistakes from reaching production rather than identifying them later through reporting.

Harness also supports automated optimization recommendations, including:

• rightsizing suggestions
• idle resource cleanup
• non-prod stopping automation
• commitment-based discount opportunities

Teams can implement these recommendations directly through the same pipelines they use for regular infrastructure changes.

Built for Engineering-Led Cost Optimization

Harness treats cloud cost management as an engineering problem, not a finance problem.

The platform integrates with existing tools (GitHub, GitLab, Jira, Slack) and workflows (Terraform, CloudFormation, Kubernetes) rather than requiring separate processes.

Engineers interact with cost data in the same interfaces they already use for infrastructure management.

Policy enforcement is flexible but opinionated:

Default guardrails prevent common waste patterns (idle resources, oversized instances, untagged infrastructure) while allowing teams to define exceptions for legitimate use cases.

The goal is to make cost-efficient choices the path of least resistance—not to create approval bottlenecks.

For organizations managing cost at scale, Harness supports advanced workflows like:

• environment-based budgets (dev/staging/production)
• cost allocation hierarchies (business units, products, teams)
• integration with business metrics for cost-per-transaction analysis

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Fixing Your Cloud Cost Optimization Approach

If your current cloud cost optimization strategy feels broken, you’re probably optimizing the wrong thing.

Cost visibility and allocation are necessary, but they’re not sufficient.

Real cost control happens when engineers see cost impacts before deployment, not when finance reviews invoices after.

A working cost optimization framework:

• embeds cost awareness directly into CI/CD and IaC workflows
• combines proactive guardrails with real-time visibility
• uses automation to prevent drift
• measures success by cost efficiency and unit economics—not just raw spend reduction

Reactive cloud spending optimization scales poorly in high-velocity engineering environments.

Proactive cloud cost governance scales effortlessly.

Ready to shift cost controls left? Start with Harness Cloud Cost Management and see what engineering-native cost optimization looks like in practice.

‍

What To Go Deeper?

Watch our webinar, Cloud Cost Optimization Isn't Broken_The Approach is to learn more. 

Learn more about how Harness Cloud Cost Management works or explore the CCM documentation.

Kubernetes is a powerhouse of modern infrastructure — elastic, resilient, and beautifully abstracted. It lets you scale with ease, roll out deployments seamlessly, and sleep at night knowing your apps are self-healing.

But if you’re not careful, it can also silently drain your cloud budget.

In most teams, cost comes as an afterthought — only noticed when the monthly cloud bill starts to resemble a phone number. The truth is simple:

Kubernetes isn’t expensive by default.

Inefficient scheduling decisions are.

These inefficiencies don’t come from massive architectural mistakes. It’s the small, hidden inefficiencies — configuration-level choices — that pile up into significant cloud waste.

In this post, let’s unpack the hidden costs lurking in your Kubernetes clusters and how you can take control using smarter scheduling, bin packing, right-sizing, and better node selection.

The Hidden Costs Nobody Talks About

Over-Provisioned Requests and Limits

Most teams play it safe by over-provisioning resource requests — sometimes doubling or tripling what the workload needs. This leads to wasted CPU and memory that sit idle, but still costs money because the scheduler reserves them.

Your cluster is “full” — but your nodes are barely sweating.

Low Bin-Packing Efficiency

Kubernetes’s default scheduler optimizes for availability and spreading, not cost. As a result, workloads are often spread across more nodes than necessary. This leads to fragmented resource usage, like:

• A node with 2 free cores that no pod can “fit” into
• Nodes stuck at 5–10% utilization because of a single oversized pod
• Non-evictable pods holding on to almost empty nodes

Wrong Node Choices (Intel vs AMD, Spot vs On-Demand)

Choosing the wrong instance type can be surprisingly expensive:

• AMD-based nodes are 20–30% cheaper in many clouds
• Spot instances can cut costs dramatically for stateless workloads up to 70%
• ARM (e.g., Graviton in AWS) can offer up to 40% savings

But without node affinity, taints, or custom scheduling, workloads might not land where they should.

Zombie Workloads and Forgotten Jobs

Old cron jobs, demo deployments, and failed jobs that never got cleaned up — they all add up. Worse, they might be on expensive nodes or keeping the autoscaler from scaling down.

Node Pool Fragmentation

Mixing too many node types across zones, architectures, or families without careful coordination leads to bin-packing failure. A pod that fits only one node type can prevent the scale-down of others, leading to stranded resources.

Always-On Clusters and Idle Infrastructure

Many Kubernetes environments run 24/7 by default, even when there is little or no real activity. Development clusters, staging environments, and non-critical workloads often sit idle for large portions of the day, quietly accumulating cost.

This is one of the most overlooked cost traps.
Even a well-sized cluster becomes expensive if it runs continuously while doing nothing.

Because this waste doesn’t show up as obvious inefficiency — no failed pods, no over-provisioned nodes — it often goes unnoticed until teams review monthly cloud bills. By then, the cost is already sunk.

Idle infrastructure is still infrastructure you pay for.

Smarter Scheduling: Cost-Aware Techniques

Kubernetes doesn’t natively optimize for cost, but you can make it.

Bin Packing with Intent: Taints, Affinity, and Custom Schedulers

Encourage consolidation by:

• Using taints and tolerations to isolate high-memory or GPU workloads
• Applying pod affinity/anti-affinity to co-locate or separate workloads
• Leveraging Cluster Orchestrator with Karpenter to intelligently place pods based on actual resource availability and cost
• Use Smart Placement Strategies to place non-evictable pods efficiently

In addition to affinity and anti-affinity, teams can use topology spread constraints to control the explicit distribution of pods across zones or nodes. While they’re often used for high availability, overly strict spread requirements can work against bin-packing and prevent efficient scale-down, making them another lever that needs cost-aware tuning.

Scheduled Scaledown of Idle Resources

All of us go through a state where all of our resources are running 24/7 but are barely getting used and racking up costs even when everything is idle.A tried and proved way to avoid this is to scale down these resources either based on schedules or based on idleness.

Harness CCM Kubernetes AutoStopping let’s you scale down your Kubernetes workloads, AutoScaling Groups, VMs and many more based on either their activity or based on Fixed schedules to save you from these idle costs.

Cluster Orchestrator can help you to scale down the entire cluster or specific Nodepools when they are not needed, based on schedules

Right-Sizing Workloads

It’s often shocking how many pods can run on half the resources they’re requesting. Instead of guessing resource requests:

• Try Cluster Orchestrator’s Vertical Pod Autoscaler (VPA) with a single click
• Use Prometheus metrics to measure actual usage
• Analyze reports from visibility tools

Leverage Spot, AMD, or ARM-based Nodes

Make architecture and pricing work in your favor:

• Use node selectors or affinity rules to schedule less critical workloads to Spot nodes. You can use Harness’s Cluster Orchestrator to run your workloads partially in Spot instances. Spot nodes are up to 90% cheaper compared to On-Demand nodes
• Prefer AMD or Graviton nodes for stateless or batch jobs
• Separate workloads by architecture to avoid mixed pools

Use Fewer, More Efficient Node Pools

Instead of 10 specialized pools, consider:

• Consolidating into fewer, well-utilized pools
• Using node-level bin-packing strategies via Karpenter or Cluster Orchestrator
• Tuning autoscaler thresholds to enable more aggressive scale-down

Invisible Decisions Are Expensive

One overlooked reason why Kubernetes cost optimization is hard is that most scaling decisions are opaque. Nodes appear and disappear, but teams rarely know why a particular scale-up or scale-down happened.

Was it CPU fragmentation? A pod affinity rule? A disruption budget? A cost constraint?

Without decision-level visibility, teams are forced to guess — and that makes cost optimization feel risky instead of intentional.

Cost-aware systems work best when they don’t just act, but explain. Clear event-level insights into why a node was added, removed, or preserved help teams build trust, validate policies, and iterate safely on optimization strategies.

Scheduled Scale-Down of Idle Resources

One of the most effective ways to eliminate idle cost is time- or activity-based scaling. Instead of keeping clusters and workloads always on, resources can be scaled down when they are not needed and restored only when activity resumes.

With Harness CCM Kubernetes AutoStopping, teams can automatically scale down Kubernetes workloads, Auto Scaling Groups, VMs, and other resources based on usage signals or fixed schedules. This removes idle spend without requiring manual intervention.

Cluster Orchestrator extends this concept to the cluster level. It enables scheduled scale-down of entire clusters or specific node pools, making it practical to turn off unused capacity during nights, weekends, or other predictable idle windows.

Sometimes, the biggest savings come from not running infrastructure at all when it isn’t needed.

Treat Cost Like a First-Class Metric

Cost is not just a financial problem. It’s an engineering challenge — and one that we, as developers, can tackle with the same tools we use for performance, resilience, and scalability.

Start small. Review a few workloads. Test new node types. Measure bin-packing efficiency weekly.

You don’t need to sacrifice performance — just be intentional with your cluster design.

Check out Cluster Orchestrator by Harness CCM today!

Kubernetes doesn’t have to be expensive — just smarter.

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Harness Commitment Orchestrator: A Modernized FinOps Experience

Cloud cost management shouldn’t feel like guesswork, but for most organizations, balancing Reserved Instances (RIs), Savings Plans (SPs), and on-demand usage is exactly that. Too many, and you end up paying for unused commitments. Too few, and you’re stuck paying on-demand rates for resources that could have been discounted.

With the modernized Commitment Orchestrator FinOps experience, Harness has reimagined how teams manage cloud commitments. This update introduces a refreshed interface, enhanced visibility, and the foundation for upcoming AI-powered insights. It also delivers faster performance and streamlined workflows that make it easier than ever to understand commitments and make confident, data-driven decisions.

The Challenge: Finding Balance in a World of Constant Change

Cloud commitments like RIs and SPs were designed to save money, but managing them manually often creates new problems. Workloads evolve, pricing models shift, and business priorities change. Over time, commitments that once made sense can lead to inefficiency or lock-in.

The result is familiar to most teams:

• Over-commitment: Paying for unused reservations of savings plans.
• Under-commitment: Missing out on deep discounts.
• Complex management overhead: Manual tracking, error-prone forecasting, and fragmented visibility across AWS tools.

Harness Commitment Orchestrator helps organizations strike the right balance by unifying visibility, automating insights, and simplifying commitment planning.

What’s New: A Revamped Experience Built for FinOps Teams

A Refreshed Dashboard

The Commitments Dashboard has been completely redesigned with a cleaner, more intuitive layout. It surfaces the key data FinOps practitioners care about most—compute coverage, utilization, savings, and spend trends—in a single view. Teams can filter by account, region, or instance family and visualize commitments over time, drilling down daily or monthly to see exactly where their savings come from.

New Inventory View

The new inventory view centralizes RI and Savings Plan data into one dashboard to provide visibility across utilization, expirations, and renewal schedules. This unified inventory eliminates the need for separate AWS views or manual exports, giving you complete visibility directly inside Harness.

Net Amortized vs. Unblended Cost Views

Understanding true savings requires more than raw numbers. Harness now supports both Net Amortized and Unblended Cost views. This brings full parity with AWS Cost Explorer and enables accurate, actionable reporting across Finance and Engineering teams.

Compute Coverage by Cost and Hours

You can now view compute coverage by both dollar value and time (hours) across both SP and RI’s simultaneously for a 1:1 comparison with AWS Cost Explorer. This flexibility allows teams to analyze coverage in multiple ways.

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Spot Spend Inclusion

For the first time, Spot Instances are fully integrated into your commitments analysis. Teams can now understand total compute coverage across on-demand, RI, SP, and Spot usage in one place.

AI-Powered Insights (Coming Soon)

AI capabilities are already being integrated into the Commitment Orchestrator. Upcoming updates will surface AI-driven explanations and recommendations, such as:

• Why commitment utilization rates are trending down
• Where you have coverage gaps or underutilized commitments
• What actions—renewals, exchanges, or purchases—will optimize savings automatically

Harness vs AWS: A Deep Dive into Recommendations

AWS Cost Explorer’s recommendation engine for RIs/Savings Plans relies on short historical look-back windows (typically 7, 30 or 60 days) rather than long-term usage forecasting, which can make it less accurate in reflecting upcoming changes in demand or growth.

Harness takes a more holistic approach:

• Extended Lookback Analysis: Broader historical data for context-aware recommendations.
• Unified Platform: Manage RIs, SPs, Spot, and on-demand usage in one place.
• Enhanced Filters and Metrics: Cost- and hour-based coverage, amortized spend, and detailed utilization breakdowns.
• Modern Interface: Intuitive charts, trends, and real-time tracking built for FinOps teams.
• AI Roadmap: Automated insights and actions that turn raw data into optimization opportunities.

Harness moves teams from visibility to action, helping them continuously optimize spend without manual overhead.

Built for Action

Harness Commitment Orchestrator doesn’t just visualize your commitments, it helps you act on them. Users can view Harness recommendations for RI exchanges, new Savings Plan purchases, or renewals, and approve or reject them directly in the interface. These insights refresh automatically as spend patterns change, ensuring recommendations are always current and relevant.

Additionally Harness can automate in a fully automated mode that does not require manual review or approval of recommendations. In this mode, Harness will optimize maximum utilization coverage and savings based on one time user preferences during set up. 

Understanding RIs vs. Savings Plans: Why Strategy Still Matters

AWS offers several ways to reduce on-demand compute costs. The right approach depends on flexibility, term length, and how often your workloads change.

Convertible Reserved Instances (RIs) and Compute Savings Plans provide a strong balance between savings and agility. They typically offer up to 66% savings compared to on-demand pricing. 

Harness takes a FinOps-first approach to commitment management through an Atomization strategy. This method breaks large, long-term commitments into smaller recurring units that renew on a monthly cadence. It reduces lock-in risk, smooths spending, and makes it easier to adjust coverage as usage patterns change.

The platform models multiple commitment scenarios, predicts break-even points, and automatically executes purchases or modifications at scale. The result is higher coverage, lower risk, and complete transparency into cost efficiency without the complexity of manual forecasting or renewals.

Why It Matters

This modernized experience brings FinOps teams closer to true commitment management maturity by uniting visibility, governance, and AI-driven automation within a single platform.

Key benefits include:

• Unified visibility across all commitment types
• Accurate, amortized cost data aligned with AWS billing
• Transparent inventory and expiration tracking
• Smarter coverage metrics by cost and time
• A modern UI built for collaboration
• Additional AI capabilities on the horizon

The Future of FinOps Is Intelligent

This is more than a visual refresh, it’s the foundation for the next evolution of autonomous cloud cost management. Harness is embedding AI into every part of the FinOps workflow, enabling systems that explain, predict, and act on behalf of teams.

The modernized Commitment Orchestrator experience sets the stage for that future, helping customers save more, react faster, and operate smarter.

Get Started

Harness Commitment Orchestrator is available today within the Harness Cloud Cost Management (CCM) platform.

Log in to your Harness account to explore the new dashboard, or book a demo to see how Harness can help you achieve unified commitment visibility, smarter savings, and a clear path towards AI-powered FinOps.

Harness: Turning cloud commitment complexity into clarity.

How we built a scalable system of generating recommendations for cloud cost optimization

Overview

As cloud adoption continues to rise, efficient cost management demands a robust and automated strategy. Native cloud provider recommendations, while helpful, often have limitations — they primarily focus on vendor-specific optimizations and may not fully align with unique business requirements. Additionally, cloud providers have little incentive to highlight cost-saving opportunities beyond a certain extent, making it essential for organisations to implement customised, independent cost optimization strategies.

At Harness, we developed a Policy-Based Cloud Cost Optimization Recommendations Engine that is highly customisable and operates across AWS, Azure, and Google Cloud. This engine leverages YAML-based policies powered by Cloud Custodian, allowing organisations to define and execute cost-saving rules at scale. The system continuously analyses cloud resources, estimates potential savings, and provides actionable recommendations, ensuring cost efficiency across cloud environments.

Benefits of a policy based Cloud Cost Optimization Recommendations Engine

• Customisability: Users can define policies tailored to their organisation’s cost optimization strategy. Policies allow filtering resources based on conditions such as resource metrics, operational state (e.g., running, stopped), lifecycle phase (e.g., age, creation date), and compliance attributes to enforce governance and cost optimization.
• Multi-Cloud Support: Works across AWS, Azure, and GCP, ensuring a consistent and unified cost-saving strategy. Avoids vendor lock-in by not relying solely on provider-native cost recommendations.
• Automated Cost Optimization: Automatically applies policies across multiple accounts and regions to detect and remediate cost inefficiencies. Continuously refines recommendations as cloud resources evolve.
• Transparent and Scalable Approach: Cost-saving logic is fully visible in YAML policies, unlike opaque cloud provider recommendations. Scales effortlessly as new resources and accounts are added.

Key Components Involved

Cloud Custodian

Cloud Custodian, an open-source CNCF-backed tool, is at the core of our policy-based engine. It enables defining governance rules in YAML, which are then executed as API calls against cloud accounts. This allows seamless policy execution across different cloud environments.

Cloud Cost Data Sources

The system relies on detailed billing and usage reports from cloud providers to calculate cost savings:

• AWS Cost and Usage Report (CUR) — Provides granular cost breakdowns at a per-resource level.
• Azure Billing Report — Offers insights into cloud usage, pricing models, and applied discounts.
• Google Cloud Cost Usage Report — Captures detailed billing data, including SKU-level pricing and committed use discounts.

Solution Overview

The solution leverages Cloud Custodian to define YAML-based policies that identify cloud resources based on specific filters. The cost of these resources is retrieved from relevant cost data sources (AWS Cost and Usage Report (CUR), Azure Billing Report, and GCP Cost Usage Data). The identified cost is then multiplied by the predefined savings percentage to estimate the potential savings from the recommendation.

The diagram above illustrates the workflow of the recommendation engine. It begins with user-defined or Harness-defined cloud custodian policies, which are executed across various accounts and regions. The Harness application processes these policies, fetches cost data from cloud provider reports (AWS CUR, Azure Billing Report, GCP Cost Usage Data), and computes savings. The final output is a set of cost-saving recommendations that help users optimize their cloud spending.

How It Works — A Step-by-Step Breakdown with an example

Below is an example YAML rule that deletes unattached Amazon Elastic Block Store (EBS) volumes. When this policy is executed against any account and region, it filters out and deletes all unattached EBS volumes.

• Policy Definition: YAML policies are written using Cloud Custodian to target specific resource inefficiencies.
• Policy Execution: Policies are executed across multi-cloud accounts and regions, filtering unoptimized resources.
• Cost Data Integration: The system retrieves the cost of filtered resources from AWS CUR, Azure Billing Report, and GCP Cost Usage Data.
• Savings Calculation: The estimated cost savings is derived by applying the predefined savings percentage associated with each policy.
• Recommendation Generation: The final output is a set of actionable cost-saving recommendations that users can review and apply.

Conclusion

Harness CCM’s Policy-Based Recommendation Engine offers an intelligent, automated, and scalable approach to optimizing cloud costs. Unlike native cloud provider tools, it is designed for multi-cloud environments, allowing organisations to define custom cost-saving policies and gain transparent, data-driven insights for continuous optimization.

With over 50 built-in policies and full support for user-defined rules, Harness enables businesses to maximise savings, enhance cost visibility, and automate cloud cost management at scale. By reducing unnecessary cloud spend, companies can reinvest those savings into innovation, growth, and core business initiatives — rather than increasing the profits of cloud vendors.

Sign up for Harness CCM today and experience the power of automated cloud cost optimization firsthand!

In too many cloud organizations, finance and engineering operate like two planets in orbit. Finance speaks in forecasts, budgets, billing codes. Engineering speaks in uptime, latency, error rates. The result? Misalignment, friction, and cloud spend that often drifts 30%+ out of control with a continuous blame game loop. 

At Harness, we believe FinOps isn’t a “cost-cutting team”. It’s the connective tissue that transforms cloud spend from expense into strategic investment. In this post, we’ll lay out the common challenges, the keys to closing the gap, and how a real FinOps culture can elevate both engineering velocity and financial stewardship.

The Fundamental Disconnect (And Why It’s Normal)

Let’s be blunt: finance and engineering speak different native languages, and that’s okay. The gap doesn’t mean failure, it just means you need a translator to align goals that are just tuned differently:

• Finance cares about predictability, accountability, and getting real insight into how every dollar is spent.
• Engineering focuses on reliability, performance, availability and rarely prioritizes cost until something breaks or surprises arrive.

Without a shared language, neither side truly understands the constraints the other faces. Engineers often treat cloud as “elastic credit,” with a deploy first, optimize later mindset. Finance receives cloud bills with little context. That mismatch is a recipe for blame, distortions, and hidden waste.

FinOps: The Bridge That Changes the Conversation

FinOps doesn’t just optimize costs, it reframes the conversation. A mature FinOps practice enables all teams to speak the same language and ask the same question:

“What business value are we getting from this cloud spend?”

Here’s how FinOps acts as a bridge:

• Shared framework & personas: It gives both finance and engineering a vocabulary for cost, usage, and accountability.
• Value-centric narrative: Instead of “cut this,” the discussion becomes “optimize this to support feature delivery.”
• Trust-building transparency: When engineers see how spend maps to their workloads, and finance sees how changes affect performance, blame gives way to collaboration.
• Guardrails, not gates: It isn’t “cost policing”, it’s control without stagnating innovation.

At Harness, our Cloud Cost Management (CCM) platform is built with this philosophy baked in: real-time visibility, context-aware cost linkage, and mechanisms to act, not just report.

Where Teams Commonly Stumble

Even well-intentioned FinOps efforts can crack under pressure. Here are breakdowns we often see:

• Lack of shared visibility:  Finance dashboards don’t align with what engineers see, so everyone debates the metrics and interprets cloud spend differently.
• Leadership underestimates FinOps: Executives may see it as a side “cost project” instead of a strategic practice.
• Recommendations ignored: Engineers skip or postpone optimization advice often because the “why of context” or timing is misaligned.
• No structural cadence: without regular rituals (e.g. cross-team reviews), cost initiatives vanish.
• Unclear ownership: if no one “owns” the action, waste drifts.

These breakpoints ultimately stem from one root cause: miscommunication.

Key Practices That Move the Needle

Based on what we’ve seen at Harness (and what we help customers do), here’s a tactical no-nonsense playbook that we have built into CCM:

1. Deliver Early, Visible Wins

Start with low-hanging fruit: rightsizing idle VMs, shutting dev clusters at night, reclaiming unattached or orphan storage. Early wins create credibility, trust, and urgency.

2. Lead with Transparency

Surface cost data at the workload, team, and tag level. Show engineers their “cost budget” and cloud footprint; show finance how it rolls up.

3. Celebrate & Scale

Recognize the teams that act and showcase wins across the company. This signals that FinOps is a force for value, not policing.

4. Automate & Guard

Don’t wait for manual tasks. Use anomaly detection, policy-as-code, and auto-shutdown rules to prevent waste before it goes too far. CCM’s governance and auto-stopping features are built for exactly this.

5. Executive Alignment & Sponsorship

FinOps won’t stick unless executives treat cloud spend as a board-level concern. Sponsor regular reviews, tie cloud KPIs into executive dashboards, and make it clear: FinOps is cross-functional, not siloed.

Red Flags That Your Program Needs Course Correction

If you see any of these, it’s time to recalibrate:

• Cloud waste drifts above 30%
• Teams regularly ignore recommendations
• No one “owns” optimization actions or are held accountable
• Executive or budget reviews never involve engineering
• Finance and engineering don’t meet on cloud cost or topics

These symptoms usually point to a breakdown in the feedback loop or lack of aligned incentives.

Starting Strong: A FinOps Launch Checklist

Here’s a practical starting roadmap for teams beginning (or rethinking) their FinOps strategy:

1. Adopt the FinOps Foundation framework: Use the inform–optimize–operate phases and personas as guardrails.
2. Assemble a cross-functional kickoff team: Bring finance, engineering, DevOps, cloud ops, and product into the conversation.
3. Map value to goals: Define shared KPIs (e.g., cost per feature, cost per throughput) rather than pure dollar thresholds.
4. Integrate tools fully: Don’t partially adopt: tie cost data into existing workflows (JIRA, ServiceNow, alerting) so nothing lives in isolation.
5. Zero-drift mindset: Hold every cloud dollar accountable: regularly review unused resources, drift, and tag compliance.

Aligning Incentives: From Silo to Symphony

At its core, the biggest barrier isn’t technical, it’s a cultural mindshift of the humans using the technology. If engineers never see their cost impact, and finance never sees the reliability tradeoffs, alignment will always be aspirational.

In a mature FinOps culture:

• Engineers understand that saving cloud costs can free up budget for new features.
• Finance respects that some margin must be reserved for flexibility and experimentation.
• Both sides speak to value, not blame.

That’s the shift we aim to catalyze at Harness.

The Role of Tools and Why a Platform Matters

Tools without alignment are just dashboards that are nice to have, but easily ignored. The real magic happens when tools are embedded into the existing workflows your teams already use.

At Harness, our CCM platform plays this role:

• Deep visibility into usage and cost across cloud providers and Kubernetes (without requiring burdensome tagging).
• Automation of idle shutdowns, cost governance, and commitment utilization.
• Integration with development and ops systems to convert insight into action, not just reports.

When you combine a FinOps mindset with an operational platform, the friction vanishes, alignment sticks, and cost becomes a lever instead of a burden.

The FinOps Mindshift: From Savings to Value

Let’s be clear: FinOps is not just about saving money or cutting costs in the cloud. It’s about maximizing business value. You do this by making smarter infrastructure choices, driving engineering velocity, and ensuring every cloud dollar supports product goals.

The mindset should be “You’re not overspending, you’re under-saving.” It’s a subtle but powerful shift that drives long-term cloud efficiency and turns FinOps from cost control into value creation.

Want to go deeper? 

Watch our webinar, Bridging the Gap: FinOps Strategies That Align Engineering and Finance, FinOps Strategies That Align Engineering and Finance, where FinOps leaders from Starbucks and Wells Fargo share how they built their programs from the ground up.

Or, explore it for yourself. Sign up for a demo to see how Harness CCM can help your teams connect cost and performance.

Idle cloud infrastructure is one of the most persistent and expensive problems in cloud cost management, costing companies an estimated $44.5B a year on underutilized resources. At Harness, we didn’t just build a workaround—we built a smarter way to eliminate it entirely. And now, we’re excited to share that our Cloud AutoStopping technology is officially patented.

This validates a fundamentally new way to tackle one of the biggest challenges in cloud operations today: eliminating idle, wasteful cloud resources without disrupting workflows or adding manual overhead.

Whether you’re a DevOps engineer, a FinOps lead, or an infrastructure architect, understanding what makes this technology different—and why it matters—can help you rethink how to control cloud spend in your own organization.

The Reality of Cloud Waste

Every engineering leader knows the scenario: development environments running 24/7 while teams work standard business hours, staging infrastructure consuming resources between deployment cycles, and test environments sitting idle for days at a time. Traditional approaches to managing this waste—primarily time-based scheduling—create their own problems.

Consider a distributed team spanning multiple time zones. Static schedules that work for one region create barriers for another. A developer in London starting early finds their environment offline. A team in San Francisco working late hits a hard cutoff. The result? Teams either accept the disruption or abandon cost controls altogether, choosing reliability over efficiency.

How Cloud AutoStopping Delivers Intelligent Automation

Cloud AutoStopping is Harness’s proprietary technology that addresses these challenges through dynamic, context-aware automation that responds to actual usage rather than predetermined schedules. The system continuously monitors real-time network traffic and usage patterns, making intelligent decisions about when to power down resources and when to keep them available.

Unlike traditional methods, which rely on static, time-based schedules that can be inflexible and error-prone, AutoStopping leverages real-time traffic analysis and usage patterns. This lets the system make nuanced, context-aware decisions about when to stop and start resources, based entirely on actual demand.

This technology is an integral part of Harness Cloud Cost Management (CCM), working seamlessly alongside other optimization and governance capabilities to deliver continuous, automated cost savings. By embedding AutoStopping within CCM, organizations can manage, optimize, and govern cloud costs holistically, without disrupting day-to-day operations.

The result is a solution that dramatically reduces cloud waste while maintaining a seamless user experience and zero manual intervention.

Measurable Impact Across Team Structures

The results speak to the effectiveness of this approach. Organizations typically see 60-70% reductions in non-production cloud spend—even teams with co-located members working similar schedules. 

Non-production environments—such as development, testing, staging, and QA—often account for up to 80% of cloud infrastructure in some organizations. Yet these environments are also the most underutilized, frequently running when no one is actively using them. This creates massive waste that traditional tools fail to address. Cloud AutoStopping’s intelligent automation ensures that resources in these environments only consume what’s truly needed, when it’s needed.

For globally distributed teams, the impact is even more significant. Cloud AutoStopping scales resources precisely to match actual demand across time zones, eliminating the choice between cost efficiency and team productivity.

The Broader Impact on Cloud Operations

This patent milestone reflects Harness's commitment to advancing intelligent automation in cloud operations. As organizations increasingly adopt cloud-native architectures and distributed development practices, the need for sophisticated cost management tools becomes critical to sustainable growth.

Cloud AutoStopping represents a new category of cost management—one that adapts to actual usage patterns rather than requiring teams to adapt to rigid cost controls. This approach enables organizations to optimize costs without compromising the developer experience or operational reliability that modern software delivery requires.

This kind of flexibility is becoming even more important as the way we build and run software keeps evolving. With the rise of AI, faster release cycles, and increasingly complex infrastructure, old-school cost management tools—things like static schedules or manual processes—just can’t keep up. Teams need smarter, automated solutions that adjust in real time, without creating extra work or slowing anyone down.

Looking Forward

As organizations face increasing pressure to optimize cloud investments while maintaining development velocity, solutions that provide both cost efficiency and operational excellence become essential.

Harness remains committed to pushing the boundaries of intelligent, automated FinOps—helping engineering and finance teams work smarter, save more, and focus on what really matters.

Want to see Cloud AutoStopping in action?

Schedule a demo to explore how it can reduce cloud waste without disrupting your teams – or join us at the FinOps Excellence Summit to hear how leaders are driving cost efficiency through automation.

Cloud cost management is crucial for organizations seeking to optimize their cloud spending while achieving maximum return on investment. With the rapid growth of cloud services, managing costs has become increasingly complex, and data teams often struggle to track and analyze spending effectively. This complexity makes it essential for organizations to implement effective cost reporting processes that can provide visibility into cloud expenses and enable informed decision-making.

Importance of Cloud Cost Reporting

Cloud cost reporting is critical for tracking, analyzing, and controlling cloud expenditures to ensure that the investment in cloud services aligns with business goals. Here’s why cloud cost reporting is essential and how it supports better decision-making, cost control, and overall financial management.

• Enhancing Financial Visibility
  Cloud cost reporting gives businesses a clear view of where and how they are spending their resources across various cloud services. Without a detailed report, costs can quickly spiral out of control, especially in complex, multi-cloud environments.

• Improving Budgeting and Forecasting
  A well-documented report on cloud expenses enables accurate budgeting and forecasting. Data teams, for example, can predict future cloud spending based on past usage trends and seasonal demand variations. Budgeting becomes more strategic when teams can see not only the current spending but also how those costs might change based on usage patterns.

• Supporting Cost Optimization Efforts
  Cloud cost reports often highlight areas where resources are underutilized or unnecessarily duplicated. By reviewing these reports, organizations can identify optimization opportunities, such as rightsizing resources, terminating idle instances, or shifting workloads to more cost-effective options..

• Enabling Accountability Across Teams
  A breakdown of cloud expenses across departments and projects can promote accountability. With cost allocation tags and perspectives, teams gain ownership of their cloud spending, leading to more mindful consumption of resources. When departments have transparency in their spending, they are more likely to take proactive measures to stay within budget.

• Facilitating Decision-Making and Strategic Planning
  Detailed cloud cost reporting helps stakeholders make data-driven decisions on resource allocation, tool investment, and scaling strategies. When cloud costs are accurately reported, organizations can align their technology spend with business goals and adjust their cloud strategy based on financial performance and expected returns.

Best Practices for Cloud Cost Reporting

• Define Clear Objectives and KPIs
  Define specific goals for cloud cost reporting, like reducing spend or improving transparency, and set measurable Key Performance Indicators (KPIs) that align with these objectives.

• Use Cost Allocation and Tagging Standards
  Establish and enforce a consistent tagging strategy to label cloud resources by meaningful attributes (e.g., project, department, environment) to improve cost tracking. Consistent tagging allows for accurate cost allocation, accountability, and budgeting across teams, while grouping resources using Cost Categories further enhances reporting precision by organizing expenses according to logical divisions like business units or departments.

• Implement Role-Based Perspectives for Cost Visibility
  Customize cloud cost reports for different roles by configuring perspectives that present relevant information to finance, engineering, and executive teams. Perspectives allow you to break down costs by team, project, or service, giving stakeholders a clear view of their impact on cloud spend.

• Regularly Review and Optimize Reports
  Analyze cloud cost trends to identify savings opportunities and ensure reports remain accurate and relevant over time. This includes periodically reviewing data sources and tagging practices, adjusting reporting metrics to reflect evolving business needs, and validating that each report’s data is current. Routine review of reports supports informed decision-making and sustained cost optimization.

• Maintain Real-Time Cost Visibility Through Dashboards
  Use custom dashboards to monitor key metrics and cloud cost trends in real time, helping teams stay informed and make timely adjustments. Role-specific dashboards reduce information overload by presenting only relevant data to each team, while visualizing recurring patterns, like weekly cost spikes, reveals insights into seasonal spending. 

• Use Anomaly Detection to Prevent Overspending
  Establish a baseline cost expectation for each department or service to help detect anomalies, using tools like Harness CCM that compare historical spending with current costs to flag unusual expenses. When anomalies occur, investigate root causes promptly and take corrective actions. Anomaly detection minimizes overspending by identifying issues like waste or misconfigurations before they escalate.

• Monitor Resource Utilization and Rightsize as Needed
  Regularly assess resource utilization to identify idle or underused assets that could be decommissioned or downsized, and apply rightsizing based on current workload demands to avoid unnecessary costs. For workloads that aren’t time-sensitive, consider scheduling usage during off-peak hours to capitalize on lower-cost periods. Proactive monitoring and rightsizing can significantly reduce wasted cloud spend.

Harness Cloud Cost Management (CCM) for Effective Cloud Cost Reporting

Harness Cloud Cost Management (CCM) offers comprehensive reporting tools designed to help businesses gain visibility and control over their cloud expenses. Harness CCM’s has different components that contribute to CCM's reporting capabilities, making it easier to track, analyze, and optimize cloud costs across various platforms.

The anomaly detection feature in CCM helps organizations proactively monitor and manage cloud expenses by identifying instances of abnormally high costs. 

Perspectives allow users to organize cloud resources in ways that align with specific business needs, such as by department, project, or region.

CCM's dashboards provide an interactive platform for visualizing and analyzing cloud cost data. Users can create custom dashboards to monitor various metrics relevant to their business, aiding in data-driven decision-making.

The Cost Categories feature in CCM enables users to organize and allocate costs effectively. By grouping expenses by business units, projects, or departments, users can gain a detailed view of where money is being spent. This feature is ideal for organizations that need to allocate cloud costs accurately across various internal groups or external clients.

Learn more about Cloud Cost Management by Harness, or book a demo today.

Managing and predicting cloud costs can be challenging in today's dynamic cloud environments, especially when infrastructure changes occur frequently. Many organizations struggle to maintain visibility into their cloud spending, which can lead to budget overruns and financial inefficiencies. This issue is exacerbated when infrastructure is provisioned and modified frequently, making it hard to predict and control costs.

Integrating Infrastructure as Code (IaC) practices with robust cost management tools can provide a solution to these challenges. By enabling cost estimates and enforcing budgetary policies at the planning stage of infrastructure changes, teams can gain greater visibility and control over their cloud expenses. This approach not only helps in avoiding surprise costs but also ensures that resources are used efficiently and aligned with business goals.

How Do IaC and Cost Management Help?

Infrastructure as Code Management (IaCM): IaCM allows teams to define, provision, and manage cloud resources using code, making infrastructure changes repeatable and consistent. This method of managing infrastructure comes with the added benefit of predictability. By incorporating cost estimation directly into the IaC workflow, teams can preview the financial impact of proposed changes before they are applied. This capability is crucial for planning and budgeting, enabling organizations to avoid costly surprises and make data-driven decisions about infrastructure investments.

Cloud Cost Management (CCM): While IaC provides a foundation for controlled and predictable infrastructure changes, Cloud Cost Management tools take this a step further by offering continuous visibility into cloud spending. CCM tools allow teams to monitor and analyze costs in real time, set spending thresholds, and receive alerts when costs approach or exceed these limits. This ongoing oversight is essential for maintaining financial discipline, especially in dynamic environments where infrastructure usage and costs can fluctuate rapidly.

Consider the Following Scenario

A development team is tasked with launching a new feature that requires additional cloud infrastructure. Before deploying, they use their IaC tool to define the necessary resources and run a cost estimation. The estimation reveals that the proposed changes will significantly increase the monthly cloud spend, prompting the team to reassess their approach. 

They decide to implement an automated policy that checks whether the total monthly cost of any proposed infrastructure exceeds a predefined threshold. If this threshold is crossed, the policy triggers an alert or blocks the deployment, ensuring costs stay within expected limits. While some companies might not be price-sensitive, they aim to allocate resources effectively, prioritizing value and strategic impact over cost alone. To further optimize spending, they schedule certain environments to be scaled down or temporarily decommissioned during weekends when they are not needed.

Such proactive measures can be instrumental in ensuring that cloud costs remain within budget, while still allowing for the flexibility to scale infrastructure as needed.

Combining IaC with Cloud Cost Management: IaCM

When you combine the power of IaCM with Cloud Cost Management, you create a robust system that enables continuous optimization of cloud infrastructure with cost control in mind. This combination, IaCM for Cost Management, has the potential to automate, optimize, and provide cost transparency across the entire cloud environment. While IaCM handles provisioning and scaling, Cloud Cost Management (CCM) tools are essential for monitoring and tracking cloud expenses after resources have been provisioned. When you combine IaCM with CCM, organizations gain continuous cost visibility and real-time feedback on resource usage.

IaC for Automating Cost Optimization

With IaC, you can define your cloud infrastructure in code and apply cost-saving policies directly within your infrastructure definitions. For example, if you're using OpenTofu or Terraform, you can incorporate best practices like:

• Rightsizing Instances: Automatically adjust the size of instances based on historical usage patterns, ensuring that you're not overprovisioning resources.
• Automating Scaling: Automatically scale resources up or down based on demand, ensuring you only pay for what you use.
• De-provisioning Idle Resources: Automatically shut down or deallocate resources when they are no longer needed (e.g., deallocating unused databases or instances after working hours).

By incorporating these cost-saving measures into your IaC pipeline, cost optimization becomes a native part of your infrastructure provisioning process, reducing the likelihood of unnecessary waste in the long run.

Continuous Monitoring and Cost Tracking

IaCM isn't just about provisioning infrastructure — it also includes ongoing cost tracking and monitoring. With automated reporting and cost analysis tools, organizations can continuously track how their cloud spending evolves over time. This makes it easier to pinpoint areas of overspending or inefficiency that need attention.

Real-time Cost Insights

By integrating CCM tools, such as Harness CCM, into your IaCM workflow, teams can receive real-time feedback on resource usage and costs as infrastructure is deployed and scaled. This integration helps track the following:

• Spending Trends: Real-time data allows organizations to track their cloud costs across all environments, giving stakeholders insights into whether they are on track with their budget or if there is an unexpected cost spike. These insights help teams adjust IaC code before the over-provisioning or under-utilization results in higher bills.
• Cost Anomalies: Advanced CCM solutions leverage machine learning and predictive analytics to identify cost anomalies, such as an unexpected spike in storage usage or an increase in computing costs. These tools can integrate with IaC processes to automatically scale down resources or shut down unused services, preventing further unplanned expenditures.
• Tagging and Allocation: CCM tools allow for cost allocation and tagging, helping break down cloud costs by team, department, or project. When you apply consistent tagging as part of your IaC definition, it’s easy to trace costs back to their source. For example, a project that consumes more resources than planned can be flagged, and further actions can be automated (like reviewing the code or applying restrictions on additional provisioning)

Automated Governance for Cloud Spending

Cloud cost governance is an essential aspect of any cost management strategy, ensuring that teams do not overspend and stay within their allocated budgets. With IaCM, you can automate governance policies to ensure cloud resources are provisioned in accordance with business rules and financial guidelines.

For instance, you can enforce policies such as:

• Tagging Resources: Automatically apply tags for cost allocation across different projects, teams, or departments.
• Budget Alerts: Set budget limits for specific teams or services, and trigger alerts when those limits are close to being exceeded.
• Cost-Based Restrictions: Set rules to prevent certain types of high-cost resources from being provisioned, such as prohibiting large EC2 instances or disallowing specific high-cost services unless approved.

Where can I get these features?

Harness IaCM allows you to enable cost estimation at the workspace level, ensuring that you know the approximate cost of your infrastructure changes ahead of time before applying those changes. For example, the team can implement an automated policy that checks whether the total monthly cost of any proposed infrastructure exceeds a predefined threshold. If this threshold is crossed, the policy triggers an alert or blocks the deployment altogether, preventing unexpected financial strain.

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This policy automatically denies any changes if the total monthly cost of the infrastructure exceeds $100, helping to maintain budgetary control and avoid unexpected expenses. Additionally, the team can set policies to ensure that the cost of changes does not increase significantly compared to the previous plan, providing an extra layer of cost governance.

Key Takeaways

When integrating Infrastructure as Code and Cloud Cost Management into your workflows, consider the following strategies:

• Predict and Prevent Cost Overruns: Use IaC tools to estimate costs before changes are applied, allowing teams to make informed decisions and avoid unplanned expenses.
• Automate Budget Enforcement: Implement policies that automatically enforce cost thresholds, preventing deployments that could lead to budget overruns.
• Monitor and Adjust in Real-Time: Use cost management tools to track spending continuously and adjust infrastructure as needed to optimize resource use.
• Optimize for Low Usage Periods: Reduce costs by scaling down or decommissioning non-critical environments during low-usage times, such as nights or weekends.
• Foster a Culture of Cost Awareness: Encourage teams to think about costs as an integral part of the development process, not just an afterthought.

Conclusion

Bringing together the capabilities of Infrastructure as Code and Cloud Cost Management can significantly enhance your organization’s ability to manage cloud costs effectively. By integrating these practices, teams can gain better visibility into their spending, enforce budgetary controls, and optimize resource usage—all critical components for running efficient, cost-effective cloud operations.

For more information on implementing these strategies, check out Harness Infrastructure as Code Management and Harness Cloud Cost Management.

Also, check out our recent webinar on how to whip your cloud costs into shape.

Request a demo

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What is Cloud Cost Automation?

Cloud cost automation refers to the use of automated tools and processes to manage and optimize cloud spending. It involves the implementation of technologies that automatically analyze billing data, track resource utilization, and manage cloud resources in real-time. By automating tasks such as resource provisioning, scaling, and monitoring, organizations can efficiently control their cloud costs without manual intervention. 

Cloud cost optimization can be achieved using cloud cost management tools. These tools track and categorize all cloud-related expenses, attributing them to the respective teams responsible for their consumption. This promotes accountability, encouraging teams to use resources judiciously while discouraging wasteful practices.

Ultimately, by implementing effective cloud cost management strategies and leveraging appropriate tools, organizations can achieve greater financial efficiency and align their cloud spending with business objectives and key results (OKRs). This proactive approach not only safeguards profit margins but also positions organizations for sustainable growth in a dynamic cloud landscape.

The Benefits of Using Cloud Cost Automation Tools for Cloud Cost Management

Utilizing external tools for cloud cost management brings a range of significant advantages that enhance financial efficiency and strategic alignment for organizations leveraging cloud services. Here are some of the key benefits:

• Accurate Forecasting and Budgeting: By analyzing historical data and usage patterns, these tools can predict future costs and help avoid unexpected surges in spending that could disrupt cash flow.

• Empowering Engineering Teams: With access to detailed cost analytics, engineering teams can see the financial impact of their work. This visibility encourages accountability and informed decision-making.

• Insight into Profitability: External tools allow organizations to identify their least profitable technologies, customers, and projects within the cloud. This insight enables data-driven decisions.

• Optimizing Resource Utilization: Cloud cost management tools help organizations assess the effectiveness of load balancing, autoscaling, capacity reservation, and volume discounts. This analysis allows companies to make informed decisions about which services to use for specific use cases. 

What to Consider When Choosing a Cloud Cost Management Tool

Selecting the right cloud cost management tool is essential for optimizing your cloud spending and ensuring operational efficiency. Here are some key factors to consider in more detail:

• Cost Visibility: A robust cloud cost management tool should provide clear and transparent visibility into your cloud costs. It should break down expenses by service, team, project, or other relevant metrics, allowing you to pinpoint where your money is being spent. 
• Cost Optimization Recommendations: Look for a tool that not only tracks costs but also provides actionable recommendations for optimizing spending. This may include insights on rightsizing resources (adjusting resource allocations based on usage patterns), utilizing Reserved Instances, or identifying idle resources that can be decommissioned or downsized. Such recommendations can significantly improve your cost efficiency.
• Real-Time Monitoring and Alerts: Real-time monitoring capabilities allow you to track your cloud spending as it occurs. Choose a tool that offers alerts to notify you of unexpected cost spikes or anomalies. This enables you to take immediate corrective action, ensuring you stay within budget and avoid unnecessary overspending.
• Integration with Multiple Cloud Providers: Your cloud cost management tool should seamlessly integrate with all the cloud providers your organization uses, whether it’s AWS, Microsoft Azure, Google Cloud, or others. This integration ensures a unified view of costs across different cloud services, simplifying management and reporting processes.
• Budgeting and Forecasting: Effective cloud cost management involves setting budgets and forecasting future spending. The tool should facilitate budget creation, allowing you to track projected versus actual costs. This capability helps you manage financial resources more effectively and make informed decisions based on accurate projections.
• Scalability: Ensure the cloud cost management tool can scale with your organization. It should handle increased cloud usage as your business grows and be able to support additional cloud providers. A scalable tool will provide long-term value and adaptability as your cloud strategy evolves.

The Best Cloud Cost Management Tools

• Harness CCM
  Harness Cloud Cost Management is designed to empower engineers and DevOps teams with detailed, real-time visibility into cloud costs.Harness Cloud Cost Management provides comprehensive tools to optimize cloud spending. It allows you to group resources based on business needs for improved cost tracking and classify expenses through cost categories for better allocation. Features like anomaly detection automatically identify unexpected cost spikes, while customizable dashboards offer a clear visualization of spending. 
  The platform also provides recommendations to optimize resource usage and reduce costs, with AutoStopping preventing unnecessary expenses by shutting down idle resources. Additional tools like the Cluster Orchestrator for AWS EKS (beta) and Commitment Orchestrator help manage Kubernetes clusters and maximize savings from reserved instances. Asset governance ensures compliance with resource utilization rules, and budgets help track spending by setting thresholds and receiving alerts when limits are approached.
  Each feature emphasizes CCM’s focus on making cloud cost management accessible and actionable for engineers and DevOps teams.

• AWS Cloud Financial Management Tools
  AWS offers tools like consolidated billing, budgeting, and pricing optimization to help users control cloud costs. AWS Cost Explorer provides detailed cost analysis, while AWS Budgets lets users set spending limits with alerts. Cost Allocation Tags allow for transparent cost assignment to projects or departments. AWS Reserved Instances offer discounted rates for upfront commitments, and Cost Anomaly Detection uses machine learning to flag unusual cost spikes for quick resolution.

• Azure Cost Management + Billing
  Azure’s Cost Management + Billing helps businesses optimize cloud spend by providing visibility and accountability. Users can monitor expenses, set budgets, and receive cost optimization suggestions through the Azure portal. Key features include granular cost analysis, AI-driven anomaly detection, and reserved instance optimization for discounts. Azure’s integration with other tools ensures streamlined resource management.

• Google Cloud Cost Management
  Google Cloud provides cost management tools through its Cloud Console, offering insights into spending via Cloud Billing Reports and Cost Tables. Users can set budgets, receive alerts, and get cost-saving recommendations. Detailed reports break down spending by projects or resources, while reserved instance management simplifies cost predictability. Integration with other Google Cloud tools ensures effective cost control and resource management.

• Spot by NetApp
  Spot by NetApp (formerly Spot.io) is a CloudOps platform that automates the deployment and operation of cloud infrastructure, focusing on cost efficiency and reliability. By leveraging machine learning, Spot continuously analyzes cloud resource usage to identify cost-saving opportunities and automatically scale workloads across various cloud providers. While Spot excels in automating cloud cost control, it does have some limitations, such as the absence of resource scheduling guidelines and real-time pricing details.

• Flexera Cloud Cost Management
  Flexera Cloud Cost Management is ideal for teams seeking enhanced visibility across multi-cloud environments. It offers essential cost management features like cost analysis, reporting, and forecasting, while also supporting cost allocation by cost center and team. The platform provides automatic budget alerts and delivers insights into both private and public cloud environments, helping users track and optimize cloud spend effectively.

• Zesty
  ‍Zesty’s cloud cost management technology allows users to optimize costs by adjusting cloud usage in real time. Initially focused on storage optimization, Zesty has expanded to include commitment discount optimization through its Zesty Commitment Manager, available exclusively for AWS users. This feature automates the buying and selling of AWS Reserved Instances (RIs) based on real-time application needs. Additionally, Zesty Disk optimizes storage costs by dynamically resizing disk capacity to align with actual usage, ensuring efficient resource utilization.

• Turbonomic
  ‍IBM Turbonomic is a cloud automation platform that offers robust cloud optimization features, including cloud cost management. It supports cost management and optimization for traditional on-premises systems, cloud-native applications, and hybrid cloud environments. Turbonomic provides detailed resource usage data, covering compute, databases, containers, network I/O, and reserved instances. Its key strength lies in automating resource scaling to ensure both optimal performance and cost efficiency. Like other tools, Turbonomic Cloud Cost Management helps identify idle resources, extend discount coverage, find rightsizing opportunities, and generate cost-saving recommendations.

• Cast AI
  Cast.ai is a comprehensive Kubernetes management platform with advanced cost management features. It continuously uses AI to monitor your clusters and applies real-time cost optimization changes to ensure they are optimally configured. These automated changes include cluster hibernation, rightsizing, and instant rebalancing. In addition to cost optimization, Cast.ai provides container security monitoring to prevent issues that could lead to unnecessary cloud expenses. The platform integrates seamlessly with Kubernetes services like EKS, AKS, GKE, KoPs, and OpenShift for AWS environments. 

• ProsperOps
  ProsperOps is an automated cloud optimization service that manages AWS and GCP purchase commitments, maximizing savings while minimizing risk. Its algorithms continuously monitor usage and adjust Reserved Instances and Savings Plans without manual intervention, ensuring flexible and cost-efficient operations. Using its Effective Savings Rate (ESR) approach, ProsperOps simplifies cloud cost management, delivering greater savings 24/7. Although it doesn't manage Spot instances, the platform is Spot-aware for seamless integration into your cloud strategy.

• Stacklet
  Stacklet is a cloud governance platform powered by Cloud Custodian, designed to help organizations manage cloud cost, security, and compliance efficiently. It goes beyond identifying governance issues by actively engaging engineering teams with automated workflows that quickly address wasteful resources and risky configurations. With customizable, multi-step remediation workflows, Stacklet ensures that cloud infrastructure is continuously optimized and compliant with organizational policies.
  Stacklet also prevents unnecessary spending and misconfigurations by enforcing policy guardrails across the entire cloud infrastructure lifecycle, from build to runtime. Its AssetDB offers real-time inventory and automated tagging, cutting governance reporting time by 80%, and providing faster insights for cost control and compliance. Built on an open-source foundation, Stacklet provides broad resource and policy coverage across all major cloud providers, giving FinOps and security teams the tools to adapt to evolving business needs.

What is Backstage?

Backstage is an open-source platform developed by Spotify that helps manage and centralize software development infrastructure. It's designed to serve as a developer portal, providing a unified interface for accessing tools, services, documentation, and resources within an organization.

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Why Backstage Matters

Backstage is gaining traction for centralizing the developer experience, offering a unified portal for tools and services. Its service catalog improves discoverability, while templates automate workflows and reduce developer effort. As an open-source platform, it supports customization and integrations, making it a key solution for improving productivity and standardizing practices in modern software development.

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Within this powerful ecosystem, we're excited to introduce Harness's Cloud Cost Management Plugin. This new addition to the Backstage platform brings comprehensive cloud cost visibility directly into your developer portal, addressing a critical need in modern software development.

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Introducing Cloud Cost Management Plugin for Backstage

As organizations increasingly rely on cloud infrastructure, managing and optimizing cloud costs has become a crucial aspect of software development. However, many teams struggle with limited visibility into their cloud expenses, difficulty in aligning costs with business contexts, and the time-consuming process of accessing and interpreting cost data.

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Cloud Cost Management’s plugin offers several powerful features to enhance your Backstage experience:

• Unified Cost Visibility: Access CCM Perspectives in a single, unified portal where developers can find everything they need, significantly reducing the time spent searching for resources.
• Custom Resource Grouping: Utilize Perspectives to group your resources in ways that are more meaningful to your business needs, allowing for better cost allocation and understanding.
• Detailed Cost Breakdown: Gain higher visibility into costs, including service and system-level cost information, providing developers and teams with granular insights into their cloud spending.
• Savings Tracker: View overall Harness savings, helping teams understand the impact of their cost optimization efforts.
• Team-Specific Cost Awareness: Drive cost awareness for individual teams by providing relevant, team-specific cost information directly within their Backstage environment.

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Each of these features was carefully designed to empower development teams with the information they need to make cost-effective decisions and manage cloud resources more efficiently.

Getting Started: Installation and Usage

Installing and configuring the Harness Cloud Cost Management Plugin for Backstage is straightforward. Follow these steps to get started:

1. Install the plugin in your Backstage instance: 

yarn add @harnessio/backstage-plugin-harness-ccm

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2. Import and use the plugin in your Backstage app: 

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import {

  isHarnessCcmAvailable,

  EntityCcmContent,

} from '@harnessio/backstage-plugin-harness-ccm';

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const ccmContent = (

  <EntitySwitch.Case if={isHarnessCcmAvailable}>

    <EntityHarnessCcmContent />

  </EntitySwitch.Case>

);

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3. Configure the Perspective. Add the following annotation to your component’s YAML file:

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apiVersion: backstage.io/v1alpha1

kind: Component

metadata:

  annotations:

    harness.io/perspective-url: <harness_ccm_perspective_url>

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Replace <harness_ccm_perspective_url> with your actual Harness Perspective URL. The plugin will use the group by, aggregation, time range, and visualization settings defined in this Perspective.

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Advanced Capabilities with Harness IDP Integration

Harness’s Internal Developer Portal (IDP) offers a seamless integration with the CCM plugin, enhancing the development process with cost management insights.

• CI/CD Pipeline Integration: Automatically check cost implications after deployments and view forecasted costs based on deployment patterns.
• Feature Flag Integration: Understand how toggling feature flags affects cloud costs, helping you make informed release decisions.
• Infrastructure as Code Management (IACM) Integration: Track real-time cost implications after infrastructure changes to enhance cost management and inform decision-making.

By embedding cloud cost visibility directly into daily workflows, the CCM plugin ensures developers can make informed, cost-conscious decisions without needing to switch between tools.

Elevate Cost Management with Harness CCM for Backstage

Harness’s Cloud Cost Management (CCM) Plugin for Backstage brings real-time cost tracking and financial insights directly into the developer’s environment. This integration allows teams to make cost-efficient decisions, optimize cloud spend, and accelerate software delivery—all within a unified portal, driving productivity and financial control.

Explore the Plugin

To learn more about the Harness Cloud Cost Management plugin, check out the plugin repository on GitHub. Sign up for free to start using Harness CCM and IDP today.

Explore more resources about CCM: Automating Cloud Cost Management

Learn about Harness CCM in comparison to some other tools: Harness CCM v.s. Anodot, Harness CCM v.s. Cast AI , Harness CCM v.s. Finout , Harness CCM v.s. CloudCheckr , Harness CCM v.s. Zesty, Harness CCM v.s. AWS Cost Management, Harness CCM v.s. DoiT, Harness CCM v.s. Aurea CloudFix, Harness CCM v.s. AWS, Harness CCM v.s. Stacklet

Cloud Cost Governance is the strategic framework that organizations adopt to manage, control, and optimize cloud spending effectively. It encompasses a set of practices, policies, and tools aimed at ensuring that cloud resources are used in a financially responsible manner while still aligning with broader business objectives.

Cloud Cost Governance is about gaining visibility into cloud expenditure, implementing cost-saving measures, and enforcing accountability across teams. It enables companies to monitor their cloud usage in real-time, identify inefficiencies, and set clear budgets to prevent cost overruns. This governance model plays a vital role in maintaining financial prudence while leveraging the flexibility and scalability of cloud platforms.

Key elements of Cloud Cost Governance include:

• Cloud Cost Visibility: Ensuring transparency into cloud usage and costs across different business units, applications, and services.  
• Budgeting and Forecasting: Setting and managing cloud budgets based on current and projected usage trends to avoid overspending.
• Cost Allocation: Allocating cloud costs to specific departments or projects, enabling better tracking of financial performance and accountability.
• Resource Optimization: Identifying underutilized resources and eliminating waste, such as unused instances or over-provisioned infrastructure, to reduce costs.
• Policy Enforcement: Using automation tools and governance policies to enforce spending limits, resource tagging, and termination of idle resources.
• Cost Control Tools: Leveraging tools to automate monitoring, generate reports, and flag any anomalies or unexpected spikes in cloud spending.

The Importance of Cloud Cost Governance

Cloud Cost Governance is essential for organizations seeking to harness the full potential of cloud computing while maintaining financial discipline. As cloud environments become more complex, businesses need structured approaches to ensure they remain cost-effective, compliant, and aligned with strategic goals. Here’s why Cloud Cost Governance is crucial:

• Improved Visibility: With comprehensive monitoring and reporting, Cloud Cost Governance provides transparency into cloud usage and expenditure. It offers a clear view of how different departments and projects utilize cloud resources, ensuring that no hidden costs go unnoticed.
• Alignment with Business Objectives: By linking cloud spending to business goals, Cloud Cost Governance ensures that investments in the cloud directly contribute to the organization’s broader strategic outcomes. It helps businesses prioritize their cloud usage according to value-driven initiatives.
• Enhanced Budgeting and Forecasting: With a better grasp of current usage patterns, organizations can predict future costs more accurately. This allows for more effective budgeting, ensuring that cloud resources are used efficiently without financial surprises.‍
• Cost Optimization: A well-governed cloud environment facilitates the identification of waste, such as underutilized resources or redundant services. By rightsizing instances and improving resource management, organizations can significantly reduce their cloud expenditure.‍
• Streamlined Operations and Reduced Overhead: Automated governance processes minimize manual tasks such as tracking costs or ensuring compliance. This reduces administrative overhead, enabling IT teams to focus on more strategic tasks.

The 6 Pillars of Cloud Governance 

1. Security and Compliance
   Security is at the heart of cloud governance. While vendor-managed services often provide robust protection, it's the responsibility of internal security teams to fine-tune these systems according to business policies and compliance requirements. Controls such as access privileges, password management, and logging systems may need to be customized to meet specific security goals.
2. Cost Optimization
   Tools and resources are expensive, and without optimizing them strategically, security budgets can easily exceed limits. A well-defined financial management policy helps cut costs by balancing people, processes, and tools effectively. Cloud governance tools streamline this process, preventing resource sprawl while ensuring compliance and budget adherence.
3. Performance Management
   This is used to find out how well your cloud system is functioning and identify places for improvement. Performance management cares about the actual performance of hardware and virtual systems and checks workload and memory usage.
4. Operations management
   Operations management ensures cloud resources deliver services efficiently by defining processes for deploying applications, setting SLAs, and monitoring performance. It addresses IAM, resource estimates, and logging requirements. Strong practices prevent shadow IT and support effective cost and performance management.
5. Asset and Configuration management
   Asset management involves the assets your business uses to deliver IT and cloud services. Configuration management involves tracking the relationship between IT or cloud service components. Together this principle monitors cloud services and deliverables to ensure consistency and quality.
6. Data management
   As cloud complexity grows, effective data governance requires clear end-to-end lifecycle policies. Classify data by sensitivity, encrypt sensitive information like PII, and automate management with compliance tools. Implement safeguards such as MFA, access controls, and DLP to ensure data integrity.

Cloud Cost Governance with Harness CCM

Harness Cloud Asset Governance automatically eliminates cloud waste, ensuring compliance and freeing engineers to focus on innovation. Think of it like managing your cloud infrastructure like you would a busy shared refrigerator. Over time, if no one takes charge, things can get messy—forgotten resources pile up, and inefficiencies grow, just like expired food taking up valuable space. This clutter not only wastes money but creates compliance and security risks, much like a neglected fridge could lead to health hazards.

Harness Cloud Asset Governance offers a better solution by automating cloud asset governance and providing clear visibility into cloud spend and efficiency. This tool helps organizations prevent cloud waste, optimize costs, and ensure resources align with corporate standards, all through a policy-driven governance-as-code approach.

Harness Cloud Asset Governance leverages Cloud Custodian, a widely adopted CNCF-backed open-source tool designed to streamline multi-cloud governance. While Cloud Custodian excels in policy support, it has some limitations: no GUI, no centralized reporting, and high management overhead, among other challenges. Harness eliminates these pain points by integrating AI Development Assistant (AIDA™), a natural language interface that simplifies policy creation and offers out-of-the-box governance rules.

Harness Cloud Asset Governance automates cloud cost governance, reduces cloud waste, and ensures compliance through a robust governance-as-code approach, ultimately empowering organizations to focus on innovation and efficiency.

Contact a Harness expert

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Explore resources: Tackling Cloud Spend Challenges at Discover Dollar

What is Cloud Cloud Visibility?

Cloud cost visibility is the process of tracking, analyzing, and understanding the expenses associated with cloud services, including applications, resources, and infrastructure. It provides organizations with a clear view of how their cloud resources are utilized and how much they are spending. This visibility is essential for making informed decisions about optimizing cloud costs.

Cloud cost visibility is not just about having access to the data but also about organizing and presenting it in a way that makes it easy to understand and act upon - in the form of dashboards, graphs or any other representation. Well-structured and well-analyzed data enables businesses to gain insights into cloud usage patterns, identify inefficiencies, and take corrective actions. With accurate visibility, organizations can forecast future cloud costs and allocate resources more efficiently, ensuring they are not overspending or underutilizing their cloud environment.

Why is Cloud Cost Visibility Important?

• Cost Optimization: With enhanced cloud cost visibility, organizations can identify opportunities to reduce excess spending. Organizations can track and analyze spending across the company, connect cloud costs to business value, and identify the areas where resources are being underutilized or whether the needs are met. This leads to a better allocation of cloud resources and a reduction in unnecessary expenses.
• Resource Optimization: Understanding how cloud resources are consumed is important for making informed decisions to achieve cloud cost optimization. Cloud cost visibility helps organizations monitor who uses what resources and how efficiently they are managed.
• Budget Planning: Accurate visibility into cloud costs helps organizations forecast and plan their budgets more effectively. It helps them prepare in a better manner. By analyzing current and future workloads, tracking usage trends, and accounting for unexpected expenses, businesses can create more reliable budget plans. Also, with cloud cost visibility, organizations can gain valuable insights into how different parts of the business utilize cloud resources, allowing them to optimize spending and maximize return on investment (ROI).

7 Key Approaches to Achieve Cloud Cost Visibility

1. Build a FinOps Team

The first step is understanding that cloud cost visibility is a group effort. Building a FinOps team with members from development, operations, engineering, and finance ensures that everyone understands what visibility is and how it works or what results it will yield. This collaboration helps in aligning cloud cost management practices with business objectives. Identify all the people who are involved in this process and are decision-makers and understand how they can work together to get the most out of the cloud spend.

2.  Establish the Foundation with Data

Data is the backbone of cloud cost visibility. To ensure the data you have gives the most accurate insights, you need to make sure that the data is accumulated from all the cloud service providers, is accurate and latest, and is granular enough to derive conclusions and patterns. Storing huge amounts of data can be a challenge though, but it is very important for historical data, comparisons and when setting budgets for the future. 

3. Leverage Dashboards and Granular Reports

Granular data helps create detailed reports which in turn allows you to monitor which cloud resources are consuming the most budget, how Reserved Instances are utilized, and helps you to track trends over time. You can have a huge bunch of data but converting them into dashboards and reports are critical for visualizing cloud cost data and extracting actionable insights. The key idea is simple - data must be arranged in a way that’s easy to interpret and act on. 

4. Create a Tagging Strategy

Tags act as labels that tie cloud resources to specific departments, projects, or teams. A well-defined tagging strategy involves consistently labeling all resources so that no cloud spend is untracked or misallocated. Manual tagging might become very cumbersome but automating the tagging process can alleviate the burden on development teams. An effective tagging strategy makes it easier to forecast, budget, and identify cost-saving opportunities.

5. Implement Anomaly Detection

Anomaly detection, driven by AI and machine learning, allows you to stay on top of unexpected cloud usage spikes even when you’re not actively monitoring your reports. Anomaly detection tools help detect instances of abnormally high costs and promptly notify users of these occurrences. You can use tools like Harness CCM to detect cost anomalies for your Kubernetes clusters and cloud accounts. CCM cost anomalies compare the previous cloud cost spending with the current spending to detect cost anomalies. Harness CCM uses statistical anomaly detection techniques and forecasting at scale to determine cost anomalies. These methods can detect various types of anomalies, such as a one-time cost spike, and gradual, or consistent cost increases.

6. Use Budgeting and Forecasting Tools

Effective budgeting and forecasting are key to achieving full cloud cost visibility. A robust cloud cost management system should allow you to track past, present, and future spending. AI-powered tools can help predict future cloud costs based on past usage trends, enabling more accurate financial planning. Budget alerts, proactive notifications, and tailored forecasts ensure that every team has the visibility needed to manage cloud costs efficiently.

7. Use Tools Like Harness CCM

At Harness, we leverage the power of AI and machine learning to streamline cloud cost management. Harness Cloud Cost Management (CCM) provides comprehensive tracking of cloud spending, enabling optimized expenditure.
From CCM Dashboards that help you visualize cloud cost data across clusters and cloud accounts Anomaly Detection that detects instances of abnormally high costs and promptly notify users of these occurrences, Harness ensures everything is automatically managed, allowing you to focus on your core business while significantly reducing costs.

Learn more about Cloud Cost Management by Harness, or book a demo today.

Contact a Harness expert

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What is AWS Cloud Cost Management?

AWS Cloud Cost Management refers to the processes, tools, and practices used to plan, organize, report, analyze, and control the usage of Amazon Web Services (AWS) resources and their associated costs. Unlike simply categorizing its tools as cost management, AWS adopts the term "cloud financial management," encompassing a broader range of services and optimization techniques.

The AWS cost management process involves the following:

1. Cost Visibility: Continuously improving visibility into cloud expenditures to understand spending patterns and identify cost drivers.
2. Resource Optimization: Selecting and allocating just enough computing power, storage, and other cloud resources to ensure efficient task execution while minimizing waste.
3. Forecasting and Budgeting: Predicting future costs based on usage trends and establishing budgets to control spending.

AWS Cost Management is essential for organizations looking to optimize their cloud spending and enhance financial control. By implementing best practices for AWS Cost Management, companies can maximize their cloud investments, ensuring optimal performance while minimizing unnecessary expenses. 

Why is AWS Cloud Cost Management Important?

• Cost Optimization: AWS cost management enables enterprises to gain valuable insights into their costs and usage. This helps identify opportunities for cost savings by pinpointing underutilized resources, eliminating wasteful spending, and optimizing overall AWS expenses. For example, organizations can identify EC2 instances that are not fully utilized and either resize or shut them down to reduce costs. Additionally, examining unexpected data transfer costs can lead to better strategies.
• Predictability: Effective cost management tools can predict future AWS costs based on historical usage patterns. This predictability helps organizations budget more accurately, avoid cost overruns, and ensure that spending aligns with business objectives.
• Resource Optimization: With detailed insights into resource usage, AWS cost management practices allow organizations to optimize their resource allocation. This ensures that businesses maximize the value of their AWS investments by utilizing resources efficiently.
• Effective Governance: AWS cost management supports strong governance by enabling organizations to establish budgets, set alerts, and create policies around AWS usage and spending. This helps maintain control over costs and ensures compliance with financial goals.

AWS Cost Management Tools for Managing Cloud Costs

Amazon Web Services (AWS) offers a suite of free tools designed to help businesses monitor, analyze, and control their cloud costs. Below, we explore some of the key tools offered by AWS that can help you achieve better financial control over your cloud resources.

1. AWS Cost Management Console and Billing Console
   These two consoles serve as the primary interfaces for managing AWS costs. The AWS Cost Management Console provides a comprehensive view of spending, featuring a dashboard that summarizes costs and a detailed cost and usage report categorized by service, account, and region. The Billing Console offers in-depth billing reports and allows users to set up cost allocation tags for granular tracking of AWS expenses.
2. AWS Cost Explorer
   AWS Cost Explorer offers a visual interface to analyze AWS costs and usage. Users can review historical costs, forecast future expenses, and identify spending trends. This tool helps pinpoint which services, accounts, and regions are contributing most to AWS costs.
3. AWS Cost Anomaly Detection
   This tool leverages machine learning to monitor spending patterns continuously and detect unusual cost or usage activities. When an anomaly is identified, alerts are sent to users, allowing them to quickly address issues without the need for manual monitoring, ultimately saving time and preventing unnecessary costs.
4. AWS Budgets
   AWS Budgets allows organizations to set custom spending thresholds and receive notifications when costs exceed these limits. This tool ensures companies remain informed about their AWS spending, preventing unexpected overspending. Users can create budgets for specific services, accounts, or usage dimensions.

View the entire details here:  AWS Cost Management

5 Strategies to Manage AWS Cloud Costs

1. Use Reserved Instances and Savings Plans

To help reduce cloud costs, AWS offers customers special discounted rates against on-demand costs. These discounts are mostly in the form of RIs (Reserved Instances) or SPs(Savings Plans).

• Reserved Instances: Reserved Instances are a pricing model offered by cloud service providers that allows customers to reserve and commit to a specific amount of computing capacity in advance for a term of one or three years. This commitment comes with a significant discount compared to on-demand pricing, making it a cost-effective option for workloads with predictable and sustained usage.
• Savings Plans: Savings Plans are a flexible pricing model introduced by cloud service providers that offer customers significant discounts on their usage in exchange for committing to a consistent amount of usage, measured in dollars per hour, for a one- or three-year term. Unlike Reserved Instances, Savings Plans offer more flexibility in terms of instance type, region, and operating system, making them suitable for workloads with variable usage patterns.

To maximize these benefits, analyze your usage patterns to determine which option best meets your needs. This proactive approach helps ensure that you are making cost-effective commitments. You can also use external tools to manage your commitments in the cloud.

2. Optimize Resource Utilization

Regularly reviewing and optimizing resource utilization is very important when it comes to AWS cloud cost management. Tools like AWS Trusted Advisor and AWS Compute Optimizer can identify underutilized or idle resources. You can also use external tools like Harness CCM to optimize the use of resources. Also, Right-sizing instances and implementing Auto Scaling will ensure that resource allocation matches the demand such that there is no wastage or any added costs. Striking the right balance between provisioning enough resources and avoiding overprovisioning will prevent any unnecessary expense.

3. Consolidate Accounts

For organizations with multiple AWS accounts, consolidating them into a single organization can simplify billing and AWS cost management. With consolidated billing, you can view combined AWS costs across all accounts, which will, in turn, provide a clearer understanding of overall spending. This way, you can also access the volume discounts offered by AWS.

4. Use Spot Instances

Spot Instances represent a cost-effective way to leverage spare Amazon EC2 compute capacity at significant discounts compared to On-Demand prices. Spot instances offer discounts of up to 90% for the same performance of On-Demand instances, which makes them a great option for cost savings and can help you achieve a good amount of savings. 

But, please note, that their availability is subject to Amazon's two-minute interruption notice. For Amazon EKS, to avoid this, Harness provides Cluster Orchestrator for EKS (currently in Beta). The Harness Cluster Orchestrator for Amazon Elastic Kubernetes Service (EKS), a component of the Harness Cloud Cost Management (CCM) module scales EKS cluster nodes according to actual workload requirements. Additionally, by leveraging CCM’s distributed Spot orchestration capability, you can save up to 90% on cloud costs with Amazon EC2 Spot Instances.

5. Use Tools Like Harness CCM

At Harness, we leverage the power of AI and machine learning to streamline cloud cost management. Harness Cloud Cost Management (CCM) provides comprehensive tracking of cloud spending, enabling optimized expenditure. From Recommendations that help you better manage and allocate resources to AutoStopping rules that automatically shut down idle resources when not in use, Harness ensures everything is automatically managed, allowing you to focus on your core business while significantly reducing costs. Learn more about Cloud Cost Management by Harness, or book a demo today.

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