Correct Kubernetes Configuration is Key to Better Efficiency and Reliability

Although container security is often considered the most pressing topic in Kubernetes, it is inextricably linked to issues of efficiency and reliability, two key elements in the cloud native world. To effectively run Kubernetes, organizations must work with intention to ensure workloads are both reliable and efficient by default. Because even though Kubernetes provides some level of self-healing when things go wrong, applications require the proper settings to work correctly and to take full advantage of the built-in capabilities in the underlying Kubernetes platform.

When issues of reliability and efficiency are not properly addressed through best practices, critical elements like cost optimization and performance are severely compromised. The two areas of reliability and efficiency need to be looked at as one interconnected challenge, to be solved through the singular strategy of proper Kubernetes configuration. With regular checks around general reliability of workloads, practitioners can ensure their organization remains resource efficient and cost effective. In this way, misconfigurations sit at the heart of reliability and efficiency issues, two key attributes to running happy Kubernetes clusters. 

We discuss this problem at length in our newest white paper, “The Good, The Bad & The Misconfigured,” which you can download for free anytime. 

Configuration Management

Often known in the industry as configuration management or infrastructure as code (IaC) scanning, this process is manually doable in small teams with only a few Kubernetes clusters; however, the problem grows more challenging as organizations try to scale, with many developers deploying to multiple clusters. Without IaC scanning or some type of configuration management, DevOps teams, along with platform and security leaders, can quickly lose visibility and control into what is happening. This reality points to the need for automation and policies to enforce consistency and provide the appropriate guardrails across the organization.


IaC Scanning affects Kubernetes efficiency in a variety of ways. First, it provides the visibility needed to identify where resources like time, money and expertise are being wasted. Misconfigurations of Kubernetes workloads often involve inefficient provisioning of compute resources—and that leads to an oversized bill for cloud compute. To maximize CPU efficiency and memory utilization for a workload, teams need to set resource limits and requests properly, as mentioned earlier. But here is the catch—knowing the right limits to set for smooth application performance can be tricky at best. This is where visibility comes in.

Gaining visibility into application resource usage can help teams better understand how their application performs with different CPU and memory settings. These can then be adjusted to improve app performance or to increase the efficiency of Kubernetes compute resources, ultimately helping organizations save money in the cloud and capacity in their data centers.


In Kubernetes, reliability is about building a stable platform so development teams can streamline their development process and ship applications faster. Configuration management or IaC affects reliability in the way it gives DevOps teams methods for avoiding downtime and production incidents. Platform engineering and operations teams are responsible for monitoring the health of Kubernetes clusters, which is implemented and orchestrated through a set of best practices. Platform engineering teams must partner with development to ensure workloads are configured reliably from the start—and truth be told, Kubernetes misconfigurations happen a lot.

Kubernetes offers a framework where distributed systems are built with microservices and containers to run applications reliently. This model means separate teams own different layers of the stack, a fundamental concept of Kubernetes service ownership, and developers are specifically responsible for getting their applications to Kubernetes with proper configurations. This pervasive DevSecOps-like model of service ownership frees up operations teams from handling deployment configuration and allows them to focus on policy enforcement and actionable developer feedback.

Workload configuration, typically made in YAML files and Helm charts, affect the security and reliability of services, as well as the efficiency of workloads in a cluster. There are numerous factors to consider when assembling a stable and reliable Kubernetes cluster, including the potential need for application changes and alterations to cluster configuration. These considerations include things like setting resource requests and limits, autoscaling pods with the right metrics and using liveness and readiness probes.

Proper Configuration

IaC scanning solutions, such as those available in Fairwinds Insights, can inspect YAML and Helm configurations when developers make a pull request. Like traditional infrastructure as code scanning solutions, Insights examines configuration for security violations, like privilege escalation. The software goes further by also incorporating efficiency and reliability checks for platform engineering teams, who rely on them for running stable and scalable infrastructure.

Here are some examples of reliability checks that enable correct configuration:

  • Limits must be set on resource consumption to keep pods from consuming all the available memory and CPU on a node, otherwise known as the “noisy neighbor problem.”
  • Containers across multiple nodes and availability zones should be scheduled in the cloud for high availability.
  • Anti-affinity should be used to constrain which nodes are eligible for scheduling based on pod labels, rather than on nodes.
  • Fault tolerance must be planned by deploying redundant instances to avoid a single point of failure.
  • Liveness and readiness probes should be applied to ensure the availability of services and to check cluster performance.

Because misconfigurations are so common, building a stable, reliable and secure cluster only happens when the best practices outlined here are followed. And this level of governance only comes through a trusted partner, well-versed in the process of unifying teams, simplifying complexity and building on Kubernetes expertise to save time, reduce risk and configure with confidence.

Expertise and Partnership 

Fairwinds Insights offer this level of professional expertise and partnership. As a security and governance platform for Kubernetes, Insights provides DevOps teams with a safety net for scalability, reliability, resource efficiency and security while also empowering developers to innovate and ship faster.

Get Kubernetes security, cost allocation and avoidance, compliance and guardrails in one platform for free with Fairwinds Insights.

DevOps teams can then prevent misconfigurations throughout the CI/CD pipeline and provide remediation advice to developers, free from manual intervention. With Fairwinds Insights, managing multiple clusters and teams across the enterprise becomes easier—and in many cases, possible—as it operationalizes open source tools into a single platform for better oversight and management.

To learn more, check out our white paper on Kubernetes misconfigurations. You can download it for free HERE anytime. 

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