🚢 5 Common Mistakes to Avoid When Deploying Kubernetes

Avoid These Pitfalls to Build a Scalable, Secure, and Production-Ready Kubernetes Deployment.

Kubenatives Newsletter - Edition #1

Kubernetes offers flexibility, scalability, and automation, making it a powerful tool for DevOps teams. However, many engineers—especially those new to Kubernetes—often fall into common pitfalls that lead to security risks, performance bottlenecks, and operational headaches.

In this edition of my newsletter, I’ll walk you through five common mistakes to avoid when deploying Kubernetes and best practices to help you build a robust, production-ready cluster.

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🚧 1. Not Configuring Resource Requests and Limits

The Mistake

Many teams deploy their applications without specifying CPU and memory requests and limits in their Kubernetes manifests. This leads to resource contention, where some pods consume more resources than expected, starving other critical workloads.

Why It Matters

Without resource constraints, the Kubernetes scheduler cannot effectively distribute workloads, leading to unpredictable performance and even Out of Memory (OOM) kills.

Best Practice

Always define requests and limits in your deployment YAML:

resources:
  requests:
    memory: "256Mi"
    cpu: "250m"
  limits:
    memory: "512Mi"
    cpu: "500m"

• Requests define the minimum resources a pod needs to run.

• Limits set the maximum resources a pod can consume.

This ensures fair resource allocation and prevents a single pod from exhausting node resources.

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🔒 2. Ignoring Kubernetes Security Best Practices

The Mistake

Running containers as root, using default service accounts, and exposing services without authentication are security missteps that make clusters vulnerable to attacks.

Why It Matters

A misconfigured Kubernetes cluster can be an easy target for attackers, leading to data breaches, crypto-mining exploits, or service disruptions.

Best Practice

• Use Pod Security Standards (PSS) or Pod Security Admission (PSA) to enforce security policies.

• Avoid running containers as root by adding this to your security context:

securityContext:
  runAsUser: 1000
  runAsGroup: 3000
  fsGroup: 2000

• Enable Role-Based Access Control (RBAC) to restrict permissions.

• Use network policies to isolate pods and limit exposure.

• Scan container images for vulnerabilities before deployment.

Bonus: Implement OIDC authentication with Kubernetes API Server to integrate with identity providers like Okta or AWS IAM.

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⚠️ 3. Overlooking Proper Logging and Monitoring

The Mistake

Teams often deploy applications without setting up proper logging and monitoring, making it difficult to debug issues when something goes wrong.

Why It Matters

Without centralized logging and monitoring, you won’t have visibility into pod crashes, performance issues, or security incidents.

Best Practice

• Use a centralized logging solution like Fluentd + Elasticsearch + Kibana (EFK) or Loki + Grafana to collect logs.

• Set up Prometheus for cluster-wide monitoring.

• Define proper liveness and readiness probes to detect and recover from failures.

Example readiness probe:

readinessProbe:
  httpGet:
    path: /healthz
    port: 8080
  initialDelaySeconds: 5
  periodSeconds: 10

With proper observability, you can proactively detect issues before they impact users.

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⚡ 4. Misconfiguring Ingress and Networking

The Mistake

Deploying an application without understanding Kubernetes networking, resulting in connectivity issues, misconfigured Ingress rules, or security vulnerabilities.

Why It Matters

Networking is a critical component of Kubernetes. If improperly configured, you may experience:

• Services failing to communicate within the cluster.

• Ingress misconfigurations leading to broken endpoints.

• Publicly exposed services that should be private.

Best Practice

• Use Ingress controllers like NGINX, Traefik, or AWS ALB Ingress Controller.

• Implement TLS encryption using cert-manager and Let's Encrypt.

• Use NetworkPolicies to control inter-service communication:

apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: restrict-db-access
spec:
  podSelector:
    matchLabels:
      app: database
  policyTypes:
    - Ingress
  ingress:
    - from:
        - podSelector:
            matchLabels:
              app: backend

This prevents unauthorized pods from accessing the database.

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🔄 5. Not Implementing Proper CI/CD and Rollback Strategies

The Mistake

Deploying applications manually without a proper CI/CD pipeline and rollback mechanism increases downtime and risk.

Why It Matters

Without automation, deployments become prone to human errors, downtime, and difficult rollbacks in case of failures.

Best Practice

• Use GitOps with Argo CD for declarative Kubernetes deployments.

• Automate CI/CD pipelines with GitHub Actions, GitLab CI, or Jenkins.

• Use Helm for managing Kubernetes manifests with version control.

• Implement rolling updates to prevent downtime:

strategy:
  type: RollingUpdate
  rollingUpdate:
    maxUnavailable: 1
    maxSurge: 1

• Use Kubernetes Rollbacks to quickly revert failed deployments:

kubectl rollout undo deployment my-app

With a well-defined CI/CD strategy, you can safely release updates with minimal disruption.

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🚀 Wrapping Up

Kubernetes is a powerful but complex system. Avoiding these common mistakes will help you build scalable, secure, and production-ready deployments.

🔑 Key Takeaways:

✅ Always define resource requests and limits.
✅ Implement Kubernetes security best practices.
✅ Set up logging, monitoring, and observability.
✅ Configure Ingress and networking properly.
✅ Automate deployments with CI/CD and rollback strategies.

By following these best practices, you’ll set yourself up for success in your Kubernetes journey.

👉 Did you find this useful? Reply and let me know your biggest Kubernetes challenges!

🔗 Stay tuned for more Kubernetes deep dives in the next edition!

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