Day 2 Kubernetes Cost Challenges

Kubernetes provides a powerful container orchestration platform, enabling you to efficiently deploy, scale and manage containerized applications. But like any other technology, Kubernetes comes with its own long-term challenges that could be costly to your bottom line.

After adopting Kubernetes, many organizations realize there are cost visibility and management challenges, inflated cloud waste for CPU/memory requests and issues with upgrades and security. All of these are referred to as “Kubernetes Day 2 problems,” and businesses must be prepared to tackle them to maximize the platform’s benefits.

Here, I’ll explain common Kubernetes Day 2 challenges that your business might encounter and provide guidance on preventing their potential cost impacts.

Common Kubernetes Day 2 Challenges

Cost Optimization

One of the key challenges of Day 2 in Kubernetes is cost optimization. Since Kubernetes costs are dynamic and difficult to track, you need to stay mindful of how you run and scale your clusters.

Make spending transparent

The first step to optimizing costs in Kubernetes is to visualize your spending. But because Kubernetes provides a high degree of abstraction, it’s not always easy to gain visibility into the underlying infrastructure and resource usage.

Start with your monthly bill. Most cloud providers such as GKE, AKS, and EKS offer detailed billing and usage reports to help you track and stay on top of your Kubernetes cluster and application costs. By looking closely into these reports, you can identify areas where you can optimize usage and reduce spending.

If you want more granularity, you can monitor resource usage through Kubernetes Resource Metrics API or a tool like Prometheus.

Finally, a cost allocation and optimization tool like Finout will centralize your Kubernetes costs and break them down by cluster, namespace, team, and even customer.

Right-size nodes

Selecting the right node size and scaling up or down as needed can help you avoid overprovisioning, where you’re paying for resources that you don’t need, as well as underprovisioning, where you don’t have enough resources to support your workload.

Before you start right-sizing nodes, think of your application’s resource requirements, traffic patterns, and scaling needs. Again, you can use a tool like Kubernetes Resource Metrics API or Prometheus to monitor resource usage and see which nodes need adjusting.

This will be an ongoing process as your workload and infrastructure needs change over time. Make sure you monitor resource usage on a regular basis to ensure your Kubernetes cluster stays optimized for performance and cost-effectiveness.

Use autoscaling

Because Kubernetes groups application resources into pods, you can use autoscaling to keep the pods provisioned with the right amount of resources to run efficiently. This can result in significant cost savings, as you only pay for the resources you actually use.

There are three ways to autoscale pods in Kubernetes: Vertically, horizontally or in clusters.

Vertical pod autoscaling (VPA) works on an individual pod level to make changes to their resource requests and limits based on usage data. To use VPA, you’ll need to enable the VPA admission controller in your Kubernetes cluster and define VPA profiles for your pods. You can use the Kubernetes API or a tool like the VPA operator to do this.

Horizontal pod autoscaling (HPA) automatically increases or decreases the number of pod replicas to handle changes in workload. To use HPA, you’ll need to define the resource utilization threshold that triggers scaling and the maximum number of replicas that should be running at any given time. HPA is especially useful if your workload is CPU bound rather than I/O bound.

Cluster autoscaling changes the actual node count in a cluster. When the resource demands of your pods increase beyond the capacity of your existing nodes, Cluster Autoscaler automatically adds new nodes to your cluster. Conversely, the autoscaler will remove nodes from your cluster to free up resources when pod demands decrease.

While autoscaling is a powerful feature in Kubernetes, you should use it carefully and monitor the changes regularly to ensure everything works as expected. To set constraints correctly, DevOps teams should have a solid understanding of their application performance as well as pod and container needs.

For an in-depth guide to Kubernetes autoscaling, check out this article.

Create namespaces

Namespaces can help you organize your Kubernetes resources and provide a logical separation between different teams, applications or environments.

For example, you can use namespaces to limit resource usage and prevent resource contention between different applications or teams. You can also implement resource quotas and limit the amount of CPU, memory or storage a particular namespace or application can use.

Similarly, by defining RBAC rules at a namespace level, you can control who has access to specific resources within your Kubernetes cluster. And for an additional layer of security, you can define network policies to control data flow between namespaces and applications.

Log monitoring

Kubernetes generates a large volume of log data from various sources, such as pods, nodes and containers.

Collecting, storing and analyzing this data can be challenging, especially with regard to log rotation, maintaining log security and compliance and troubleshooting log-related issues.

But log monitoring is a crucial part of Day 2 operations in Kubernetes as it allows you to detect security, availability and performance issues.

With a centralized logging mechanism, you can easily search through all the logs generated by your application to identify the source of a performance issue. You might find that one of your services is experiencing high CPU utilization or that requests are being throttled by a particular resource, like a database or a cache.

With automated monitoring, you can also set up alerts to notify you when certain performance metrics reach a threshold, such as response time or error rate. This helps you proactively detect and resolve issues before they become more serious and impact your users.

Backups and disaster recovery

Data loss and system outages can occur at any time, especially in a highly distributed and dynamic system that works across multiple nodes and clusters. Backups and disaster recovery strategies are crucial for ensuring the reliability and availability of your Kubernetes-based applications and services.

Various backup options are available for Kubernetes, including snapshots, volume backups and cluster-level backups. In any case, ensure you have a robust backup strategy to ensure business continuity and avoid data loss or system failures.

Finally, you should regularly test your backup and disaster recovery procedures to ensure they work correctly. Testing backups by restoring data to a test environment can identify issues before a disaster occurs.

Managing upgrades and updates

Kubernetes is continually evolving, with new versions and updates released regularly. Managing upgrades and updates can be challenging, particularly in production environments where stability and availability are non-negotiable.

Upgrading Kubernetes may be time-consuming and complicated since it may require updating the control plane, worker nodes and add-ons. Compatibility concerns can also arise when upgrading or updating software components, resulting in unexpected behavior or system failures, especially when upgrading older systems or switching between versions. Before upgrading or updating, make sure to test all components for compatibility.

Security

Security is a top priority in Day 2 Kubernetes operations, especially in production settings where mission-critical applications are located. Kubernetes offers various security features, including RBAC, network policies and secrets management. But you must ensure you configure these features correctly and adhere to security best practices. You should also monitor your Kubernetes clusters for security vulnerabilities and apply security patches regularly.

In many cases, you must comply with various regulations and standards, such as HIPAA, GDPR and PCI-DSS, which can be challenging. Compliance management can be time-consuming and resource-intensive and failure to comply can result in significant financial or even legal penalties.

Final Thoughts

As you can see, running a Kubernetes app isn’t all about just setting up your environment and calling it a day. You’ll have to face a variety of Day 2 challenges relevant to your specific use case and take proactive steps to address them.

While Kubernetes itself is open source and free to use, the costs of deploying and managing a Kubernetes cluster can quickly add up, making cost visibility a necessity. You need a granular view of costs for pods, deployments, namespaces and other cluster resources.

Next, you need a cost optimization strategy to find a balance between your application’s performance and cost-effectiveness.

Finally, thinking about log cost management, monitoring, backups, updates and security early on will help ensure your application is running smoothly and should be an essential part of Day 2 operations in your Kubernetes environment.