Businesses typically overspend on the cloud by roughly 35%, reflecting a significant gap in effective cloud cost management. And one of the biggest contributors to cloud cost bill shock is idle resources, along with unallocated resources. Wouldn't it be wonderful if we could switch off the idle cloud resources when they're not in use, and then turn them back on when needed? What if this could be automated? What if this automation, which resonates with the principles of FinOps, could be seamlessly integrated?
Here, we are introducing Harness Intelligent Cloud AutoStopping Rules to manage your idle resources both dynamically and automatically. AutoStopping Rules make sure that your non-production resources run only when used, and never when idle. Furthermore, they let you run your workloads on fully orchestrated spot instances without having to worry about any spot interruptions. With AutoStopping Rules configured, you will:
AutoStopping Rules are a dynamic and powerful resource orchestrator for non-production workloads. The following are some of the most significant advantages of incorporating AutoStopping Rules into your cloud resources:
You can also use the AutoStopping dashboard to view a summary of all of the AutoStopping Rules that you have created in a simple and intuitive interface.
Before AutoStopping Rules, there were only resource schedulers that dealt with comparable issues. However, they came with various imitations:
The following are some of the most significant advantages of adopting AutoStopping Rules:
You now have a better understanding of the power and uniqueness of AutoStopping Rules. Let's explore how AutoStopping Rules can help you with your K8s clusters.
AutoStopping Rules support:
The steps for creating AutoStopping Rules are simple:
First, select the cloud account in which workloads are running that you want to manage using AutoStopping Rules (AWS, GCP, or Azure).
Second, define the AutoStopping Rule. Here, you also specify the idle time for your resources. This is the time that the AutoStopping Rule will wait before stopping the idle resources.
Third, select the resources that you want to manage using this rule. You can also specify advanced configurations, for example, adding dependencies between two or more AutoStopping Rules. This is useful for when you want one rule to make one or more rules be active based on its/their traffic.
Fourth, update the resource definition YAML of the Kubernetes AutoStopping Rule that will be applied to the cluster.
The specification in the YAML file is the same as a Kubernetes Ingress/Non-Ingress with additional metadata. These are the configurations for the Ingress/Non-Ingress that the AutoStopping Rule will create for your Service.
Ingress Example With AutoStopping Enabled:
nginx.ingress.kubernetes.io/configuration-snippet: 'more_set_input_headers "AutoStoppingRule: default-testK8s";'
- host: <replace with your domain name, for example, qa.harness.com>
- path: /
name: <replace your service name, for example, test>
number: <replace with your service port, for example, 80>
Non-Ingress Example With AutoStopping Enabled:
Cluster autoscaler automatically adjusts the Kubernetes cluster size when one of the following conditions is true:
As per Google Cloud, cluster autoscaler works on a per-node pool basis. When you configure a node pool with cluster autoscaler, you specify a minimum and maximum size for the node pool.
Cluster autoscaler increases or decreases the node pool size automatically by adding or removing virtual machine (VM) instances in the underlying Compute Engine Managed Instance Group (MIG) for the node pool. Cluster autoscaler makes these scaling decisions based on the resource requests (rather than the actual resource utilization) of Pods running on that node pool's nodes. It periodically checks the statuses of Pods and nodes, and takes action:
However, AutoStopping Rules provide cloud cost savings to the most granular extent. It is a dynamic and powerful resource orchestrator for non-production workloads. We have already discussed its uniqueness and capabilities.
The following example shows how idle resources in the K8s clusters are handled and autostopped according to the defined rule. View the cumulative savings for your resources by autostopping the idle resources.
Harness' AutoStopping solution also realizes that, under certain conditions, you may require your resources to be up-and-running regardless of the defined rules. You can configure an ECG heartbeat agent and/or fixed schedules with the rules to provide a solution for this.
By using AutoStopping Rules, you can automatically turn off cloud resources when idle, and then turn them back on when required. Furthermore, you define the number of minutes that the AutoStopping Rule should wait before stopping the idle resources.
By default, AutoStopping Rules listens to HTTP/HTTPS traffic. On the other hand, a resource could be working on long-running background jobs, such as machine learning (ML). In this case, using network traffic alone to detect resource idleness may not be the best strategy. Therefore, you can configure a heartbeat agent called ECG with AutoStopping Rules.
Moreover, you can assume ECG as an event emitter or a listener for your rule. It will send the usage record for the configured rules.
ECG comes with the following pre-installed watchers:
Configure either metrics or process watchers for your rules. The metrics watcher lets you send heartbeat signals when the specified metric threshold is reached. The process watcher watches for the existence of processes that match the given condition.
# A heartbeat will be sent when the metrics are greater than or equal to the configured threshold
cpu = "40"
memory = "5Gb"
# A heartbeat will be sent when a process with the matching condition is found
condition = "python*"
Fixed schedules are also supported by AutoStopping Rules. In certain scenarios, you wouldn’t want your resources to go down or up. For example, every Friday at 5 p.m., you want your ABC resource to go down. AutoStopping Rules makes this very simple. You can schedule downtime for your ABC resource. During this window, the resource will be forced to go down regardless of the defined rule. Furthermore, you can specify uptime for your resources in the same way.
Embarking on your journey towards cloud cost savings and efficient cloud finops has never been easier. The next logical question would be how to start using this intelligent and automatic cloud cost management solution:
Start maximizing your cloud investments today with Harness, your trusted partner in cloud financial operations.
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