Cloud Infrastructure Maintenance

99% of teams are overengineering their Kubernetes deployments. They choose the wrong tool and pay for it later lol After managing 100+ Kubernetes clusters and debugging 100s of broken deployments, I’ve seen most teams picking up Helm, Kustomize, or Operators based on popularity, not use case. (1) 𝗜𝗳 𝘆𝗼𝘂’𝗿𝗲 𝗱𝗲𝗽𝗹𝗼𝘆𝗶𝗻𝗴 <10 𝘀𝗲𝗿𝘃𝗶𝗰𝗲𝘀 → 𝗦𝘁𝗮𝗿𝘁 𝘄𝗶𝘁𝗵 𝗛𝗲𝗹𝗺 ► Use public charts only for commodities: NGINX, Cert-Manager, Ingress. ► Always fork & freeze charts you rely on. ► Don’t template environment-specific secrets in Helm values. Cost trap: Over-provisioned replicas from Helm defaults = 25–40% hidden spend. Always audit values.yaml. (2) 𝗪𝗵𝗲𝗻 𝘆𝗼𝘂 𝗵𝗶𝘁 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝗲𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁𝘀 → 𝗦𝘄𝗶𝘁𝗰𝗵 𝘁𝗼 𝗞𝘂𝘀𝘁𝗼𝗺𝗶𝘇𝗲 ► Helm breaks when you need deep overlays (staging, perf, prod, blue/green.) ► Kustomize is declarative, GitOps-friendly, and patch-first. ► Use base + overlay patterns to avoid value sprawl. ► If you’re not diffing kustomize build outputs in CI before every push, you will ship misconfigs. Pro tip: Pair Kustomize with ArgoCD for instant visual diffs → you’ll catch 80% of config drift before prod sees it. (3) 𝗦𝘁𝗮𝘁𝗲𝗳𝘂𝗹 𝘄𝗼𝗿𝗸𝗹𝗼𝗮𝗱𝘀 & 𝗱𝗼𝗺𝗮𝗶𝗻 𝗹𝗼𝗴𝗶𝗰 → 𝗢𝗽𝗲𝗿𝗮𝘁𝗼𝗿𝘀 𝗼𝗿 𝗯𝘂𝘀𝘁 ► Operators shine when apps manage themselves: DB failovers, cluster autoscaling, sharded messaging queues. ► If your app isn’t managing state reconciliation, an Operator is expensive theatre. But when you need one: Write controllers, don’t hack CRDs. Most “custom” Operators fail because the reconciliation loop isn’t designed for retries at scale. Always isolate Operator RBAC (they’re the #1 privilege escalation vector in clusters.) 𝐌𝐲 𝐇𝐲𝐛𝐫𝐢𝐝 𝐅𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤 At 50+ services across 3 regions, we use: ► Helm → Install “standard” infra packages fast. ► Kustomize → Layer custom patches per env, tracked in GitOps. ► Operators → Manage stateful apps (DBs, queues, AI pipelines) automatically. Which strategy are you using right now? Helm-first, Kustomize-heavy, or Operator-led?

I’ve spent 7 years obsessing over the perfect Kubernetes Stack. These are the best-practices I would recommend as a basis for every Kubernetes cluster. 1. Implement an Observability stack A monitoring stack prevents downtime and helps with troubleshooting. Best-practices: - Implement a Centralised logging solution like Loki. Logs will otherwise disappear, and it makes it easier to troubleshoot. - Use a central monitoring stack with pre-built dashboards, metrics and alerts. - For microservices architectures, implement tracing (e.g. Grafana Tempo). This gives better visibility in your traffic flows. 2. Setup a good Network foundation Networking in Kubernetes is abstracted away, so developers don't need to worry about it. Best practices: - Implement Cilium + Hubble for increased security, performance and observability - Setup a centralised Ingress Controller (like Nginx Ingress). This takes care of all incoming HTTP traffic in the cluster. - Auto-encrypt all traffic on the network-layer using cert-manager. 3. Secure your clusters Kubernetes is not secure by default. Securing your production cluster is one of the most important things for production. Best practices: - Regularly patch your Nodes, but also your containers. This mitigates most vulnerabilities - Scan for vulnerabilities in your cluster. Send alerts when critical vulnerabilities are introduced. - Implement a good secret management solution in your cluster like External Secrets. 4. Use a GitOps Deployment Strategy All Desired State should be in Git. This is the best way to deploy to Kubernetes. ArgoCD is truly open-source and has a fantastic UI. Best practices: - Implement the app-of-apps pattern. This simplifies the creation of new apps in ArgoCD. - Use ArgoCD Autosync. Don’t rely on sync buttons. This makes GIT your single-source-of-truth. 5. Data Try to use managed (cloud) databases if possible. This makes data management a lot easier. If you want to run databases on Kubernetes, make sure you know what you are doing! Best practices - Use databases that are scalable and can handle sudden redeployments - Setup a backup, restore and disaster-recovery strategy. And regularly test it! - Actively monitor your databases and persistent volumes - Use Kubernetes Operators as much as possible for management of these databases Are you implementing Kubernetes, or do you think your architecture needs improvement? Send me a message, I'd love to help you out! #kubernetes #devops #cloud

Routing traffic into Kubernetes? You’re not just choosing a tool, you’re choosing a paradigm. 𝐈𝐧𝐠𝐫𝐞𝐬𝐬 got us started. 𝐆𝐚𝐭𝐞𝐰𝐚𝐲 API is where we’re headed. Let’s talk about why this shift isn’t just about new YAML, it’s a mindset change. 𝐈𝐧𝐠𝐫𝐞𝐬𝐬 𝐰𝐚𝐬 𝐠𝐫𝐞𝐚𝐭… 𝐮𝐧𝐭𝐢𝐥 𝐢𝐭 𝐰𝐚𝐬𝐧’𝐭. It gave us a simple way to handle HTTP routing through a controller. But once clusters scaled and teams grew, it began to show its age: 🔸 Hard-to-manage configs 🔸 No native multi-tenancy 🔸 Limited protocol support 🔸 Inconsistent behavior across vendors It did the job, until the job got too complex. 𝐆𝐚𝐭𝐞𝐰𝐚𝐲 𝐀𝐏𝐈 𝐢𝐬 𝐛𝐮𝐢𝐥𝐭 𝐟𝐨𝐫 𝐰𝐡𝐚𝐭 𝐜𝐨𝐦𝐞𝐬 𝐧𝐞𝐱𝐭. Designed by Kubernetes SIG-Network, it brings: 🔸 Native support for HTTP, TCP, and UDP 🔸 True multi-tenant gateway deployments 🔸 Clean separation of infrastructure (Gateways) from routing logic (Routes) 🔸 Extensibility and cloud-provider awareness baked in 𝐇𝐞𝐫𝐞’𝐬 𝐭𝐡𝐞 𝐛𝐨𝐭𝐭𝐨𝐦 𝐥𝐢𝐧𝐞: 𝐈𝐧𝐠𝐫𝐞𝐬𝐬 is a resource. 𝐆𝐚𝐭𝐞𝐰𝐚𝐲 is a framework. And in modern Kubernetes environments, that difference matters. As apps go multi-protocol, clusters scale out, and teams demand better boundaries. Gateway API isn’t a nice-to-have. It’s the standard Kubernetes has been waiting for. So… Still patching Ingress? Or already designing with Gateways? #Kubernetes #GatewayAPI #CloudNative #DevOps #Ingress #PlatformEngineering #SystemDesign

🚀 Kubernetes Best Practices You Can’t Ignore Managing Kubernetes at scale is tough — one wrong step can cause downtime or security risks. I’ve been diving into some battle-tested practices that every engineer should know: 1. Multi-tenancy & Isolation: • Use Namespaces for logical separation of teams/workloads. • Apply RBAC and Azure AD for precise access control. 2. Scheduling & Resource Management: • Enforce resource quotas and Pod Disruption Budgets (PDBs). • Use taints & tolerations to dedicate nodes for critical workloads. 3. Security First: • Scan container images and disable root privileges. • Regularly patch and upgrade Kubernetes clusters. 4. Networking & Storage: • Implement network policies and WAF for traffic security. • Use dynamic provisioning and regular backups for persistent volumes. 5. Enterprise Workloads: • Plan for multi-region deployments with traffic routing and geo-replication. ⸻ 🔔 Follow me for more Kubernetes & DevOps insights. ⸻ #Kubernetes #K8s #CloudNative #DevOps #InfrastructureAsCode #KubernetesBestPractices #AzureKubernetesService #Security #RBAC #Helm #CI_CD #PlatformEngineering #CloudEngineering

Azure Private AKS with External Access: A reference architecture implemented in Terraform. One of the trickiest and hardest topics in Kubernetes on Azure: you want your cluster locked down, but you still need the outside world to reach your apps. ✅ Here's an architecture pattern that solves this elegantly, built with Azure best practices and battle tested for production. Private AKS clusters are great for security, no public API server exposure. But "private" can also mean "isolated" if you're not careful about how external traffic gets in. 📌 The Solution: Hub & Spoke with strategic public touch points. This architecture uses a hub-spoke network model where: • The hub VNet centralizes your security controls (Azure Firewall, Bastion, jumpbox). • The spoke VNet hosts your AKS workloads in isolation. VNet peering connects them privately. • External access comes through an Application Gateway with WAF. This is your single, controlled entry point. Everything else stays internal. 🚀 What makes it production-ready 1/ Security layers that actually work together: • Private endpoints for ACR, Key Vault, and Storage (no public blob URLs floating around) • Azure Firewall controlling egress (your nodes can't phone home to unexpected places) • Bastion + jumpbox for management access (no SSH exposed, ever) Managed identities throughout (no secrets to rotate) 2/ Operational foundations: • Log Analytics integration from day one • Proper RBAC with least-privilege role assignments • Separate node pools for workload isolation 3/ IaC: The entire architecture is implemented in Terraform (automatically generated and tested for policies, naming conventions, and costs) and can easily be deployed in Brainboard.co or in your own CI/CD solution. ⚠️ Most teams skip the private DNS zones, because they're usually not easy to set up, but they're what makes private endpoints actually work → This architecture includes them for AKS, ACR, Key Vault, and Storage, because partial private networking is often worse than none at all. This reference architecture is ideal for: • Regulated industries requiring network isolation • Multi-tenant platforms where blast radius matters • Any production workload where "secure by default" isn't optional ❤️ Besides that, the architecture is modular enough to strip out what you don't need. Not everyone needs Traffic Manager across regions or the full firewall setup for dev environments. That's why it is highly flexible. Get it here for free: https://lnkd.in/eZYJKgJx What's your experience been with private AKS? #Azure #Kubernetes #AKS #Terraform #CloudArchitecture #DevOps #InfrastructureAsCode