How DevOps Teams Can Boost Kubernetes Performance

Kubernetes (also called K8s) remains the most in-demand container for developers. Originally developed by engineers at Google, K8s has achieved global fame as the go-to solution for hosting across on-premise, public, private, or hybrid clouds. Insights from Statista show the Kubernetes market share of the public cloud went from 16% in 2021 to 45% in 2022. Another report on the state of Kubernetes in 2022 by VMware revealed that the adoption of Kubernetes has skyrocketed among large enterprises with 1,000 employees or more— from 27% in 2018 to 48% in 2020.  

However, despite its rise in popularity, some challenges persist, disallowing DevOps teams from reaping the full benefits of building cloud-native applications with K8s. How do they walk the tightrope and deliver their best projects? Let’s take a quick trip together.

Observability Is Key

Kubernetes has a lot going for it, as several nodes and touchpoints exist within the container ecosystem. This makes it a challenging task to gain a comprehensive view of the entire K8s environment. In fact, users of K8s know better than trying to understand their containers manually. However, the solution to this challenge, according to Shahar Azulay— CEO and co-founder at Groundcover— lies in observability solutions.

By using observability tools, DevOps teams can gain comprehensive insights into everything happening in Kubernetes, from logs to metrics and traces. This enables DevOps teams to quickly fix bugs and build applications at scale. “Instead of collecting and analyzing every bit of data available or sampling it randomly, developers can intelligently sample it by identifying the most interesting data right at the source, then select only that data to send to their observability platform,” Azulay says.

With observability, DevOps teams can reduce downtime, cut down costs, and ultimately increase performance. Some of the most popular observability tools today include Grafana, groundcover, and Prometheus. Azulay further notes that groundcover represents a new iteration in observability because “it breaks the customary APM model, offering minimized resource consumption, comprehensive observability, and simplified transparent pricing.”

Keep Security Top-Of-The-Mind 

Focusing only on observability is not enough, as that would mean fixing only half the problem. There’s more ahead, especially regarding security. In a report by Red Hat on the State of Kubernetes security in 2023, 94% of respondents experienced a security incident in the last 12 months, while 64% reported delaying or slowing down deployment due to K8s security concerns. 30% of the respondents also identified vulnerabilities as their biggest worry for their container and K8s environment.

The need to stay secure while running applications within the Kubernetes environment is crystal clear. Failure to put security top-of-the-mind can adversely impact performance, increase remediation costs, and have a lasting, devastating impact. When using K8s, the price for effective performance is eternal vigilance.

Box Craig, VP of open source and community at ARMO, an open-source security provider and creator of one of today’s most popular Kubernetes security tools Kubescape, notes that “as with all cloud software, it’s important to ensure that you have suitable guardrails when you delegate Kubernetes access to teams.”

Craig further notes that some steps to take in ensuring security include (but aren’t limited to):

• Regular security patches and updates.
• Follow industry best practices when configuring K8s clusters.
• Check and verify images for malicious codes, incorrect configurations, and other vulnerabilities.
• Disallow access to cloud API metadata.
• Leverage role-based access control (RBAC), allowing users access to K8s resources only based on their roles and functions.
• Secure your IDE, CI/CD pipelines, and clusters with security tools like Kubecsape.

Fix Storage Issues

Additional storage while using Kubernetes comes at a cost and bears the bulk of the cost incurred by developers and organizations. In trying to effectively reduce deployment friction for developers, large organizations often move to a public cloud environment and reduce reliance on local servers. 

One way to solve this issue, according to Ben Hirschberg— CTO and cofounder at ARMO— is to “analyze data at the source, minimizing the need to move large amounts of data for observation. By analyzing data right inside the nodes or applications, not all data needs to be moved to external storage or observability platforms. By storing data locally, DevOps teams can avoid unnecessary data transfer costs while ensuring the necessary data is readily available if needed.”

Prioritize Interoperability 

Another issue with K8s that most developers face is interoperability, which is the ability of applications to communicate with one another within K8s. Communication between interoperable cloud-native applications on K8s is not as straightforward as it appears. As this article notes, lack of interoperability can “impact cluster deployment because app instances it contains may have issues running on individual nodes in the cluster.”

One way to solve that challenge is to take advantage of collaborative projects across several organizations— like AWS, Google, IBM, SAP, and Red Hat— to provide their services for your cloud-native applications.

Final Thoughts 

The best of K8s practices are not one-time fixes; they come from consistently learning from mistakes and retooling the bottom line. That can be a lot of work for DevOps teams that are already bogged down by technical work and the need to deploy containers at record speed. Luckily, observability tools can pinpoint where to focus attention and help direct, impactful steps regarding critical issues of security, interoperability, storage, and more.