16 Kubernetes Worst Practices to Avoid
Kubernetes can transform how organizations deploy and manage applications, but ignoring best practices often leads to costly mistakes. Understanding Kubernetes worst practices is crucial to maintain efficiency, security, and scalability. Drawing on our experience with hundreds of customers, we’ve identified 16 pitfalls that organizations frequently encounter—and how to avoid them.
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1. Kubernetes worst practices of Using In-Tree Storage Drivers
In-tree storage drivers are no longer supported in Kubernetes v1.26 and beyond. Instead, use the Container Storage Interface (CSI). CSI provides a standardized API to connect various storage systems to your containerized workloads. By migrating to CSI, you ensure future compatibility and smoother storage management.
2. Not Defining Pod Disruption Budgets
Skipping Pod Disruption Budgets (PDBs) can jeopardize your application availability. PDBs protect your workloads during node scaling or maintenance. Without them, critical pods may be evicted, causing downtime or data loss. The Kubernetes Node Autoscaler respects PDB rules, ensuring safe node scaling.
3. Setting Overly Restrictive Pod Disruption Budgets
Conversely, overly strict PDBs can block essential operations, such as node draining or patching. Define PDBs based on minimum required replicas. Avoid setting them for single-replica pods like metrics-server, which could cause operational issues during updates.
4. Isolating Workloads Without Real Needs
Workload isolation increases cost and reduces performance. Many teams create isolated node groups unnecessarily, often due to misunderstood compliance requirements. Instead, use namespaces, resource requests, limits, and network policies for “soft isolation.” Separating production and non-production clusters remains a recommended practice.
5. Mixing NodeAffinity and NodeSelectors
NodeSelectors are simple but limited, while NodeAffinity is more flexible. Mixing them can create conflicts, causing pods to fail scheduling. Choose one approach consistently for reliable workload placement.
6. Kubernetes worst practices of Lacking Observability
Without observability, troubleshooting becomes a nightmare. Capture logs, metrics, and traces centrally using stdout and stderr streams. Observability enables faster problem detection and remediation. ZippyOPS can help implement robust monitoring and observability solutions.
7. Relying on Burstable Instances
Burstable cloud instances may seem cost-effective but often lead to poor, inconsistent performance. Well-sized pods with horizontal scaling generally outperform burstable instances while maintaining predictable costs.
8. Kubernetes Worst Practices Excessive Cross-AZ Traffic
Spreading workloads across multiple availability zones can improve resiliency but increases costs if cross-AZ traffic is high. Use Kubernetes Topology Aware Routing to route traffic within the same zone, reducing latency and cloud bills.
9. Not Setting Resource Requests
Kubernetes schedules workloads based on requests. Omitting them may result in CPU throttling or pod OOM kills. Always define requests and limits to ensure reliable scheduling and cluster stability.
10. Skipping Liveness and Readiness Probes
Kubernetes liveness and readiness probes automatically monitor pod health. Liveness probes restart failing containers, while readiness probes manage traffic routing. Implementing these probes reduces manual intervention and improves resilience.
11. Manually Scaling Workload Replicas
Static replica counts in production are inefficient. Use Horizontal Pod Autoscaler (HPA) or KEDA to scale workloads based on business metrics, such as user sessions or job queues. This ensures responsive scaling and cost optimization.
12. Running a Self-Hosted Control Plane
Managing your own Kubernetes control plane is rarely necessary. Cloud-managed solutions like GKE, EKS, and AKS provide automated upgrades, scalability, and high availability at minimal cost, avoiding operational headaches.
13. Kubernetes Worst Practices of Ignoring Namespaces
Keeping everything in the default namespace leads to chaos as clusters grow. Use namespaces, labels, and annotations to organize workloads and improve security, maintainability, and observability.
14. Missing Wildcard Tolerations on Essential DaemonSets
DaemonSets like CNI, CSI, and logging agents must run on all nodes. Wildcard tolerations ensure they are scheduled on tainted nodes, preventing blind spots in observability and infrastructure coverage.
15. Running Business Logic in DaemonSets
DaemonSets are meant for infrastructure tasks, not business logic. Adding application functionality can cause outages, mismanagement, and resource contention. Keep business workloads separate from infrastructure DaemonSets.
16. Applications That Cannot Terminate Gracefully
Applications must shut down quickly without risking data loss. Graceful termination reduces operational complexity, supports opportunistic scheduling, and improves cost efficiency. Kubernetes was designed for resilient applications, and adopting this mindset is essential.
Conclusion: Avoid Kubernetes Worst Practices
Ignoring these Kubernetes worst practices can create cascading issues, inefficiencies, and stress. Following them ensures better performance, cost optimization, and reliability.
ZippyOPS helps organizations implement these practices through consulting, implementation, and managed services for DevOps, Cloud, Microservices, and Security. Explore our services or solutions, or watch our YouTube playlist to see best practices in action.
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External Reference:
For more on Kubernetes best practices, see the CNCF Kubernetes Documentation.
