Kubernetes CI/CD Best Practices for Scalable, Secure Deployments | Harness Blog

Kubernetes has changed modern CI/CD by making deployments faster, infrastructure more declarative, and systems more resilient. It takes away a lot of the manual work that comes with managing environments, but it doesn't mean that you don't need to follow strict CI/CD rules. Kubernetes makes deployments go faster and in an automated way, which makes strong pipelines more important than ever.

Teams can safely use Kubernetes' strengths by following best practices like using ephemeral build runners, immutable artifacts, automated testing, and strong health checks. When used with modern delivery platforms like Harness, these practices help companies automate deployments, lower risk, and confidently scale up software delivery.

Core Kubernetes Concepts That Impact CI/CD

At its core, Kubernetes operates on the concept of desired state. Using declarative YAML manifests, engineers decide how an app should look, how many copies it should have, what resources it can use, and what networking rules it should follow. Kubernetes continuously works to bring the actual state in line with the desired state after it has been applied.

If a pod crashes, Kubernetes recreates it. If traffic increases, replicas can be scaled. This reconciliation loop is powerful, but it also means CI/CD systems must be designed with immutability and repeatability in mind. Every deployment should be reproducible, every artifact traceable, and every change auditable.

For teams that are new to Kubernetes, the first time they deploy can seem very easy. With just a small Deployment YAML and a kubectl apply, an app is up and running. Rolling updates happen automatically, replacing pods one at a time without any downtime. Kubernetes can feel almost easy compared to older platforms where rolling updates needed complicated scripting.

However, this ease of deployment can be deceptive. Without well-structured CI/CD pipelines, teams may deploy untested changes, introduce configuration drift, or lose visibility into what is running in production. Kubernetes enhances CI/CD, but it does not replace it.

Best Practices for CI and Kubernetes

Continuous Integration (CI) focuses on build automation and early validation. In a Kubernetes-based workflow, this typically includes compiling code, running tests, building container images, and packaging deployment manifests.

Because containers are immutable, any change to the code, dependencies, or configuration creates a new image. This means that CI pipelines are run a lot, sometimes even on every commit. Because of this, CI workloads can be very demanding on infrastructure and need to be able to scale up and down easily.

Running CI workloads on Kubernetes is a natural fit. Modern CI systems leverage Kubernetes to create ephemeral build runners that spin up on demand and shut down when jobs complete. This model provides several benefits:

• Efficient use of compute resources
• Strong isolation between builds
• Reduced risk of cross-build contamination

Confidence-building steps such as unit tests, integration tests, and security scans are well-suited to ephemeral containers. Container image scanning, in particular, can be resource-heavy, as it involves analyzing layers and dependencies. Running these scans on every build is critical, since each image may introduce new vulnerabilities.

Artifact Management and Image Promotion

While ephemeral build runners are ideal for CI execution, build outputs must be durable. A key responsibility of CI is publishing artifacts to long-lived storage systems such as artifact repositories or container registries.

In Kubernetes-centric workflows, CI pipelines often produce:

• Container images
• Helm charts
• Kustomize or Jsonnet configurations
• Versioned Kubernetes manifests

These artifacts should be stored in a way that doesn't change and with consistent versioning. Instead of making new images for each environment, the best way to do things is to promote the same artifact through different environments (for example, dev → staging → production). This lowers the risk and makes sure that what was tested is what is actually used.

Many teams choose managed or SaaS solutions over hosting artifact repositories directly on Kubernetes clusters because they need a lot of storage and high availability. Artifact repositories connect CI and CD, no matter where they are running.

Best Practices for CD and Kubernetes

Best Practices for Continuous Delivery (CD) is all about safely making changes to production. Kubernetes makes deployments quick, but quickness doesn't always mean safety. The fact that you can deploy right away makes automated safeguards even more important.

Kubernetes can handle aggressive strategies like "recreate," which replaces all pods at once. However, most production workloads need rolling updates or progressive delivery to avoid downtime. CD pipelines need to slow down deployments on purpose so that they can be checked and rolled back if needed.

Pre-Kubernetes deployment confidence checks, such as integration tests, performance testing, and approval gates, are still relevant. In addition, Kubernetes introduces new validation concerns, including:

• Cluster conformance testing
• Resource quota validation
• Network and policy enforcement

Running directly on Kubernetes is helpful for many CD steps. It's much easier to set up temporary test environments, run smoke tests, and then tear everything down again on a cluster than on static infrastructure. But depending on the state and length of the orchestration logic and long-running workflows, some CD steps may still need outside systems.

Release Strategies and Deployment Safety

Kubernetes enables advanced deployment strategies that significantly reduce risk when releasing new versions. Common approaches include:

• Blue-green deployments for instant rollback
• Canary releases for gradual traffic shifting
• Feature flags for decoupling deployment from release

You can use Kubernetes manifests to implement these strategies by hand, but specialized CD tools make orchestration, traffic management, and automated decision-making easier.

Health checks are an important part of safe deployments. Properly configured liveness and readiness probes allow Kubernetes and CD platforms to determine whether a deployment is healthy before proceeding. Without these signals, progressive delivery strategies lose much of their effectiveness.

The need for deployment safety didn't go away with Kubernetes. Instead, when used correctly, Kubernetes gives you better building blocks to use.

Observability, Feedback Loops, and Automation

Modern CI/CD does not stop at deployment. Observability data, metrics, logs, and traces, plays a critical role in determining whether a release is successful.

By integrating monitoring and observability tools into CD pipelines, teams can automate decisions such as:

• Continuing a rollout
• Pausing for investigation
• Automatically rolling back

Kubernetes gives you the basic tools you need to react, but higher-level platforms can look at signals and do something about them. This closes the feedback loop and turns CI/CD from a straight line into a system that is always changing and adapting.

Governance, Security, and GitOps

As Kubernetes blurs the line between infrastructure and application, governance becomes increasingly important. Historically, production deployments were mediated by CI/CD platforms with explicit approvals and controls. Kubernetes’s flexibility can bypass these controls if not managed carefully.

GitOps has emerged as a powerful model to address this challenge. By treating Git as the source of truth, teams can:

• Enforce standards through pull requests
• Detect and remediate configuration drift
• Enable self-healing deployments

In this model, the authors define the desired state, but automated systems enforce it. This balance helps organizations scale Kubernetes usage without sacrificing security or compliance.

Furthering the Journey

Kubernetes has fundamentally changed how software is built and delivered, but it has not replaced the need for disciplined CI/CD practices. Instead, it raises the bar.

By combining ephemeral CI execution, durable artifact management, progressive delivery strategies, and automated feedback loops, teams can safely move faster than ever before. Platforms such as the Harness Software Delivery Platform demonstrate how Kubernetes-native CI/CD can evolve to include governance, security, and intelligent automation.

As organizations continue their Kubernetes journey, the most successful teams will be those that embrace new paradigms without forgetting the hard-earned lessons of CI/CD discipline that existed long before Kubernetes entered the picture.