Istio Security#

Istio provides three security capabilities that are difficult to implement without a service mesh: automatic mutual TLS between services, fine-grained authorization policies, and egress traffic control. These features work at the infrastructure layer, meaning applications do not need any code changes.

Automatic mTLS with PeerAuthentication#

Istio’s sidecar proxies can automatically encrypt all pod-to-pod traffic with mutual TLS. The key resource is PeerAuthentication. There are three modes:

• PERMISSIVE – Accepts both plaintext and mTLS traffic. This is the default and exists for migration. Do not leave it in production.
• STRICT – Requires mTLS for all traffic. Plaintext connections are rejected.
• DISABLE – Turns off mTLS entirely.

Enable strict mTLS across the entire mesh:

Istio Service Mesh#

Istio adds a proxy sidecar (Envoy) to every pod in the mesh. These proxies handle traffic routing, mutual TLS, retries, circuit breaking, and telemetry without changing application code. The control plane (istiod) pushes configuration to all sidecars.

When You Actually Need a Service Mesh#

You need Istio when you have multiple services requiring mTLS, fine-grained traffic control (canary releases, fault injection), or consistent observability across service-to-service communication. If you have fewer than five services, standard Kubernetes Services and NetworkPolicies are sufficient. A service mesh adds operational complexity – more moving parts, higher memory usage per sidecar, and a learning curve for proxy-level debugging.

Jenkins Debugging#

Jenkins failures fall into a few categories: builds stuck waiting, cryptic pipeline errors, performance degradation, and Kubernetes agent pods that refuse to launch.

Builds Stuck in Queue#

When a build sits in the queue and never starts, check the queue tooltip in the UI – it tells you why. Common causes:

No agents with matching labels. The pipeline requests agent { label 'docker-arm64' } but no agent has that label. Check Manage Jenkins > Nodes to see available labels.

Jenkins Kubernetes Integration#

The kubernetes plugin gives Jenkins elastic build capacity. Each build spins up a pod, runs its work, and the pod is deleted. No idle agents, no capacity planning, no snowflake build servers.

The Kubernetes Plugin#

The plugin creates agent pods on demand. When a pipeline requests an agent, a pod is created from a template, its JNLP container connects back to Jenkins, the build runs, and the pod is deleted.

Jenkins Setup and Configuration#

Jenkins is a self-hosted automation server. Unlike managed CI services, you own the infrastructure, which means you control everything from plugin versions to executor capacity. This guide covers the three main installation methods and the configuration patterns that make Jenkins manageable at scale.

Installation with Docker#

The fastest way to run Jenkins locally or in a VM:

docker run -d \
  --name jenkins \
  -p 8080:8080 \
  -p 50000:50000 \
  -v jenkins_home:/var/jenkins_home \
  jenkins/jenkins:lts-jdk17

Port 8080 is the web UI. Port 50000 is the JNLP agent port for inbound agent connections. The volume mount is critical – without it, all configuration and build history is lost when the container restarts.

kind Validation Templates#

kind (Kubernetes IN Docker) runs Kubernetes clusters using Docker containers as nodes. It was designed for testing Kubernetes itself, which makes it an excellent tool for validating infrastructure changes. It starts fast, uses fewer resources than minikube, and is disposable by design.

This article provides copy-paste cluster configurations and complete lifecycle scripts for common validation scenarios.

Cluster Configuration Templates#

Basic Single-Node#

The simplest configuration. One container acts as both control plane and worker. Sufficient for validating that deployments, services, ConfigMaps, and Secrets work correctly.

Knative: Serverless on Kubernetes#

Knative brings serverless capabilities to any Kubernetes cluster. Unlike managed serverless platforms, you own the cluster – Knative adds autoscaling to zero, revision-based deployments, and event-driven invocation on top of standard Kubernetes primitives. This gives you the serverless developer experience without vendor lock-in.

Knative has two independent components: Serving (request-driven compute that scales to zero) and Eventing (event routing and delivery). You can install either or both.

kubectl Debugging#

When something breaks in Kubernetes, you need to move through a specific sequence of commands. Here is every debugging command you will reach for, plus a step-by-step workflow for a pod that will not start.

Logs#

kubectl logs <pod-name> -n <namespace>                           # basic
kubectl logs <pod-name> -c <container-name> -n <namespace>       # specific container
kubectl logs <pod-name> --previous -n <namespace>                # previous crash (essential for CrashLoopBackOff)
kubectl logs -f <pod-name> -n <namespace>                        # stream in real-time
kubectl logs --since=5m <pod-name> -n <namespace>                # last 5 minutes
kubectl logs -l app=payments-api -n payments-prod --all-containers  # all pods matching label

The --previous flag is critical for crash-looping pods where the current container has no logs yet. The --all-containers flag captures init containers and sidecars.

Kubernetes API Deprecation Guide#

Kubernetes deprecates and removes API versions on a predictable schedule. When an API version is removed, any manifests or Helm charts using the old version will fail to apply on the upgraded cluster. Workloads already running are not affected – they continue to run – but you cannot create, update, or redeploy them until the manifests are updated. This guide walks through the complete workflow for detecting and fixing deprecated APIs before an upgrade.

Kubernetes API Server: Architecture, Authentication, Authorization, and Debugging#

The API server (kube-apiserver) is the front door to your Kubernetes cluster. Every interaction – kubectl commands, controller reconciliation loops, kubelet status updates, admission webhooks – goes through the API server. It is the only component that reads from and writes to etcd. If the API server is down, the cluster is unmanageable. Everything else (scheduler, controllers, kubelets) can tolerate brief API server outages because they cache state locally, but no mutations happen until the API server is back.