Common Kubernetes Mistakes in Real-World Deployments

I've broken more Kubernetes clusters than I’d like to admit. Probably 500+ times in the last 13 years. So here are 13 real mistakes I’ve made in production and what I do differently now. 1. replicas: 1 in production. (One node died. So did our app.) Now: Minimum 2 replicas for everything customer-facing. Always. 2. Forgot readinessProbe. (Traffic hit cold containers. Result: timeouts.) Now: Every service gets a basic HTTP check. No exceptions. 3. Used :latest as the image tag. (Deployment pulled the wrong build mid-rollout.) Now: Every image is pinned + SHA verified in CI. 4. Didn’t set resources.requests. (Pod got evicted under load.) Now: We baseline every workload and bake it into Helm. 5. Set only limits without requests. (Burstable QoS. Crashed when the node got noisy.) Now: requests and limits are always paired. 6. Mounted full ConfigMap without subPath. (A config reload restarted everything.) Now: Only mount the files we need. Nothing else. 7. No terminationGracePeriodSeconds. (App got killed mid-request.) Now: We measure shutdown time and tune accordingly. 8. Hardcoded hostPort. (Multi-tenant cluster blew up.) Now: No hostPort unless strictly necessary. 9. Skipped liveness probes. (Hung processes sat “healthy” for hours.) Now: Every app with state gets a liveness probe. 10. Ignored kubectl get events. (Missed critical CNI errors for hours.) Now: Events are always step 2 after describing. 11. Assumed HPA = auto-healing. (HPA scaled replicas but rollout broke one-by-one.) Now: We separate recovery logic from autoscaling logic. 12. Forgot to set revisionHistoryLimit. (Old ReplicaSets flooded the cluster.) Now: We cap every Deployment’s history to 3 versions. 13. No resource quota in non-prod. (Someone spun up 50 pods in dev. Took down the cluster.) Now: Every namespace gets a budget. So, what’s the most painful mistake you’ve ever made in Kubernetes? Love to read in the comments.

#DAY142 #ErrorHandlingSeries with #SoftSkills – Day 3/5 🚨 Incident Report: The Case of the Disappearing Containers 📅 Time: Wednesday, 2:37 PM 📍 Environment: Production 🔍 Symptom: All containers suddenly vanished 🔎 The Investigation Everything was running fine—until it wasn’t. Our monitoring dashboard lit up with alerts. CPU dropped to zero. No active containers. Just… emptiness. We checked: ✅ Cluster status? Healthy. ✅ Node health? Fine. ✅ Recent deployments? No changes. So… where did everything go?! 🕵️ The Root Cause After 15 minutes of digging, we found it: A misconfigured rolling update policy in Kubernetes. The deployment spec had: strategy: type: RollingUpdate rollingUpdate: maxUnavailable: 100% Translation? Every pod was allowed to go down at the same time. Instead of a smooth rollout, Kubernetes wiped everything out before bringing new pods up. Oops. 🔥 The Aftermath 🚫 Zero running services 📉 API downtime = Angry customers 🛠️ Emergency rollback = Stress levels maxed out And of course… incident post-mortem scheduled. 🧠 Soft Skill Takeaway: Attention to Detail Kubernetes did exactly what it was told. The problem wasn’t the tool—it was human oversight. Before making changes, pause and ask: ✔️ What’s the worst-case scenario? ✔️ If something fails, how do we recover? ✔️ Is there a safety net in place? Automation is powerful—but without risk awareness, it can backfire spectacularly. ✅ Lessons Learned 1️⃣ Default settings aren’t always safe. 💡 Soft Skill: Read the fine print before deploying. 2️⃣ Always test configs in staging first. 💡 Soft Skill: Don’t assume—it’ll cost you. 3️⃣ Set maxUnavailable to a safer value (like 25%). 💡 Soft Skill: Balance speed with reliability. 4️⃣ Have an emergency rollback plan. 💡 Soft Skill: Preparedness beats panic. “No Kubernetes deployments without a second pair of eyes.” Because double-checking takes seconds—but fixing production takes hours.

Using unverified container images, over-permissioning service accounts, postponing network policy implementation, skipping regular image scans and running everything on default namespaces…. What do all these have in common ? Bad cybersecurity practices! It’s best to always do this instead; 1. Only use verified images, and scan them for vulnerabilities before deploying them in a Kubernetes cluster. 2. Assign the least amount of privilege required. Use tools like Open Policy Agent (OPA) and Kubernetes' native RBAC policies to define and enforce strict access controls. Avoid using the cluster-admin role unless absolutely necessary. 3. Network Policies should be implemented from the start to limit which pods can communicate with one another. This can prevent unauthorized access and reduce the impact of a potential breach. 4. Automate regular image scanning using tools integrated into the CI/CD pipeline to ensure that images are always up-to-date and free of known vulnerabilities before being deployed. 5. Always organize workloads into namespaces based on their function, environment (e.g., dev, staging, production), or team ownership. This helps in managing resources, applying security policies, and isolating workloads effectively. PS: If necessary, you can ask me in the comment section specific questions on why these bad practices are a problem. #cybersecurity #informationsecurity #softwareengineering

DevOps engineers working with Kubernetes often encounter various errors and challenges. 𝐇𝐞𝐫𝐞 𝐚𝐫𝐞 𝐬𝐨𝐦𝐞 𝐜𝐨𝐦𝐦𝐨𝐧 𝐞𝐫𝐫𝐨𝐫𝐬 𝐢𝐧 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐟𝐨𝐫 𝐃𝐞𝐯𝐎𝐩𝐬 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐬 𝐚𝐧𝐝 𝐡𝐨𝐰 𝐭𝐨 𝐚𝐝𝐝𝐫𝐞𝐬𝐬 𝐭𝐡𝐞𝐦: 1. 𝐏𝐨𝐝 𝐒𝐜𝐡𝐞𝐝𝐮𝐥𝐢𝐧𝐠 𝐅𝐚𝐢𝐥𝐮𝐫𝐞𝐬:   - 𝐄𝐫𝐫𝐨𝐫: Pods not scheduling due to resource constraints or node affinity/anti-affinity rules.   - 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Ensure proper resource requests and limits, adjust scheduling rules, or scale your cluster as needed. 2. 𝐂𝐨𝐧𝐭𝐚𝐢𝐧𝐞𝐫 𝐈𝐦𝐚𝐠𝐞 𝐈𝐬𝐬𝐮𝐞𝐬:   - 𝐄𝐫𝐫𝐨𝐫: Pulling or running container images fails.   - 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Verify image availability, credentials, and ensure the correct image name and version. 3. 𝐊𝐮𝐛𝐞𝐫𝐧𝐞𝐭𝐞𝐬 𝐀𝐏𝐈 𝐑𝐚𝐭𝐞 𝐋𝐢𝐦𝐢𝐭𝐢𝐧𝐠:   - 𝐄𝐫𝐫𝐨𝐫: Frequent 429 (Too Many Requests) errors from the Kubernetes API.   - 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Implement rate limiting and retries in your applications, or consider horizontal pod autoscaling to handle increased API requests. 4. 𝐍𝐞𝐭𝐰𝐨𝐫𝐤𝐢𝐧𝐠 𝐏𝐫𝐨𝐛𝐥𝐞𝐦𝐬:   - 𝐄𝐫𝐫𝐨𝐫: Services or pods cannot communicate with each other.   - 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Check network policies, DNS resolution, firewall rules, and ensure that pods are in the correct namespaces. 5. 𝐒𝐭𝐨𝐫𝐚𝐠𝐞 𝐈𝐬𝐬𝐮𝐞𝐬:   - 𝐄𝐫𝐫𝐨𝐫: Persistent Volume (PV) or Persistent Volume Claim (PVC) issues, like access mode conflicts or insufficient storage.   - 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Verify PV/PVC configurations, adjust access modes, and monitor storage usage. 6. 𝐂𝐫𝐚𝐬𝐡𝐋𝐨𝐨𝐩𝐁𝐚𝐜𝐤𝐎𝐟𝐟:   - 𝐄𝐫𝐫𝐨𝐫: Pods enter a continuous restart loop.   - 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Inspect pod logs, check for misconfigurations, and address application errors. 7. 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞 𝐄𝐱𝐡𝐚𝐮𝐬𝐭𝐢𝐨𝐧:   - 𝐄𝐫𝐫𝐨𝐫: Cluster nodes or resources running out of capacity.   - 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Monitor resource utilization, autoscale clusters, and optimize resource requests/limits. 8. 𝐒𝐞𝐜𝐫𝐞𝐭𝐬 𝐌𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭:   - 𝐄𝐫𝐫𝐨𝐫: Secrets exposed or misconfigured.   - 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Use Kubernetes-native secret management, rotate secrets regularly, and limit access to sensitive information. 9. 𝐑𝐁𝐀𝐂 (𝐑𝐨𝐥𝐞-𝐁𝐚𝐬𝐞𝐝 𝐀𝐜𝐜𝐞𝐬𝐬 𝐂𝐨𝐧𝐭𝐫𝐨𝐥) 𝐏𝐫𝐨𝐛𝐥𝐞𝐦𝐬:   - 𝐄𝐫𝐫𝐨𝐫: Permission issues or unauthorized access.   - 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Review RBAC policies and roles, grant appropriate permissions, and practice the principle of least privilege. 10. 𝐂𝐥𝐮𝐬𝐭𝐞𝐫 𝐔𝐩𝐠𝐫𝐚𝐝𝐞𝐬:   - 𝐄𝐫𝐫𝐨𝐫: Problems during cluster upgrades.   -𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Follow Kubernetes upgrade documentation carefully, backup critical data, and test upgrades in a non-production environment first. 11. 𝐂𝐮𝐬𝐭𝐨𝐦 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞 𝐃𝐞𝐟𝐢𝐧𝐢𝐭𝐢𝐨𝐧 (𝐂𝐑𝐃) 𝐈𝐬𝐬𝐮𝐞𝐬:   - 𝐄𝐫𝐫𝐨𝐫: Problems with custom resource definitions and controllers.   - 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: Debug CRD controllers, validate CRD configurations, and ensure compatibility with Kubernetes versions. #devops #kubernetes #errors

Think your Kubernetes setup is solid? Look closer. Most clusters are hiding misconfigurations that can lead to serious issues: containers running as root, ungoverned public registry pulls, missing resource limits, and no traffic controls between pods. These aren’t edge cases. They’re common oversights. And most teams only catch them after something goes wrong. Need help? This is where #Kyverno comes in. Kyverno is a powerful, open-source, Kubernetes-native policy engine from Nirmata that helps you catch misconfigurations early, enforce smart defaults, and bring consistency to your deployments. But like any powerful tool, it must be used responsibly, with care, context, and collaboration. Build guardrails, not roadblocks. Here’s how to shift from reactive to resilient.

𝗧𝗼𝗽 𝟱 𝗠𝗶𝘀𝘁𝗮𝗸𝗲𝘀 𝗧𝗲𝗮𝗺𝘀 𝗡𝗲𝘄 𝘁𝗼 𝗞𝘂𝗯𝗲𝗿𝗻𝗲𝘁𝗲𝘀 𝗠𝗮𝗸𝗲 Are you diving into the world of Kubernetes? While this powerful container orchestration platform can significantly help your deployment strategy, many teams stumble in their early adoption. Here are the five most common pitfalls I've observed: 𝗡𝗲𝗴𝗹𝗲𝗰𝘁𝗶𝗻𝗴 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲 𝗟𝗶𝗺𝗶𝘁𝘀 𝗮𝗻𝗱 𝗥𝗲𝗾𝘂𝗲𝘀𝘁𝘀 Without proper resource configurations, your pods may consume excessive resources or get evicted during high-demand periods. Always set appropriate CPU and memory requests and limits for each container. 𝗢𝘃𝗲𝗿𝗹𝗼𝗼𝗸𝗶𝗻𝗴 𝗣𝗲𝗿𝘀𝗶𝘀𝘁𝗲𝗻𝘁 𝗦𝘁𝗼𝗿𝗮𝗴𝗲 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 Many teams treat Kubernetes like a stateless-only platform. Remember that persistent volume claims and storage classes are essential for stateful applications, and data requires careful planning. 𝗜𝗻𝘀𝘂𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 𝗮𝗻𝗱 𝗢𝗯𝘀𝗲𝗿𝘃𝗮𝗯𝗶𝗹𝗶𝘁𝘆 Kubernetes environments demand robust monitoring solutions. Teams often struggle when they haven't implemented proper logging, metrics collection, and alerting before issues arise in production. 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗮𝘀 𝗮𝗻 𝗔𝗳𝘁𝗲𝗿𝘁𝗵𝗼𝘂𝗴𝗵𝘁 From inadequate RBAC policies to running containers as root, security vulnerabilities abound when teams rush to deploy without proper security practices. Implement pod security contexts, network policies, and least-privilege principles from day one. 𝗖𝗼𝗺𝗽𝗹𝗲𝘅𝗶𝘁𝘆 𝗪𝗶𝘁𝗵𝗼𝘂𝘁 𝗡𝗲𝗰𝗲𝘀𝘀𝗶𝘁𝘆 The most successful Kubernetes implementations start simple. Many teams attempt to use every feature immediately, creating unnecessary complexity. Begin with essential workloads and gradually expand your usage as your team's expertise grows. #AWS #awscommunity

My fellow engineers in security, Kubernetes, and DevSecOps, always remember: ➤ If you leave your Kubernetes dashboard open to the internet, one day you’ll wake up to your cluster hijacked for crypto mining. ➤ If you don’t set up proper access controls, you’ll watch someone accidentally delete your whole environment, no undo button. ➤ If you trust public container images without checking them, sooner or later you’ll be racing to fix a security hole you never saw coming. ➤ If you hardcode passwords in your code, it’ll eventually show up in a public repo or get leaked by mistake, game over. ➤ If you skip network policies, you’ll spend a weekend tracking down why two services are talking when they shouldn’t. ➤ If youuse default usernames and passwords, you’ll find your app getting hit by bots within hours of going live. ➤ If you avoid resource limits, you’ll see one bad deployment eat up every CPU and memory, crashing the rest. ➤ If you never enable logging or audit trails, when something breaks or gets hacked, you’ll have zero idea who did what. ➤ If you don’t patch your images or dependencies, old vulnerabilities will get exploited while you’re busy with new features. ➤ If you let staging and production use the same configs, a “harmless” test will bring down the real system. Every engineer has stories like these, most of us learned the hard way. Mess up once, and you’ll never forget the lesson. The more chaos you’ve handled, the sharper your instincts get. Keep going. The scars turn into skills. — Follow saed for more & subscribe to the newsletter: https://lnkd.in/eD7hgbnk I am now on Instagram: instagram.com/saedctl say hello, DMs are open