Projectious Work Aibox Kubernetes Basics

Kubernetes Basics

Intro

Kubernetes is a declarative system: you write manifests, the API server stores them in etcd, and controllers reconcile reality toward that desired state. Confirm the active context, prefer declarative apply over imperative commands, and always check events and logs before poking at YAML.

Overview

Cluster context

Always confirm the active cluster and namespace before making changes:

kubectl config current-context
kubectl config get-contexts
kubectl get ns

Switch context/namespace explicitly rather than relying on defaults:

kubectl config use-context <name>
kubectl config set-context --current --namespace=<ns>

Core resources

Use Deployments for stateless workloads and StatefulSets for stateful ones. Never create bare Pods in production — they are not rescheduled on failure.

• Pod — smallest deployable unit, one or more containers
• Deployment — manages ReplicaSets, handles rolling updates
• StatefulSet — stable network identity and persistent storage per replica
• DaemonSet — one pod per node (logging, monitoring agents)
• Job / CronJob — run-to-completion and scheduled tasks

Networking

Services expose pods internally or externally:

• ClusterIP (default) — internal only
• NodePort — exposes on each node's IP at a static port
• LoadBalancer — provisions an external LB (cloud providers)

Ingress routes external HTTP/HTTPS to services by host/path. Always set ingressClassName. Pods resolve services via DNS at <svc>.<ns>.svc.cluster.local.

Network policies default to allow-all. Define explicit ingress/egress rules to restrict traffic between namespaces or pods.

Storage

• PersistentVolume (PV) — cluster-level storage resource
• PersistentVolumeClaim (PVC) — namespace-scoped request for storage
• StorageClass — dynamic provisioning template

Use storageClassName in PVCs. For StatefulSets, use volumeClaimTemplates to create per-replica PVCs automatically. Always set accessModes and resources.requests.storage.

Configuration

• ConfigMap — non-sensitive key-value config; mount as files or env vars
• Secret — base64-encoded sensitive data; same mount options

Prefer mounting as volumes over env vars for config files. Use kubectl create secret generic for quick creation. In production, use an external secrets operator or sealed-secrets.

Helm

Helm manages templated releases:

helm repo add <name> <url>
helm repo update
helm search repo <chart>
helm install <release> <chart> -n <ns> --create-namespace -f values.yaml
helm upgrade <release> <chart> -n <ns> -f values.yaml
helm rollback <release> <revision> -n <ns>
helm list -n <ns>
helm uninstall <release> -n <ns>

Inspect before installing: helm template to render, helm show values for defaults. Pin chart versions in CI with --version.

Troubleshooting order

When debugging, start broad and narrow down:

1. kubectl get events --sort-by=.lastTimestamp — cluster events
2. kubectl describe pod <pod> — scheduling, image pull, probes
3. kubectl logs <pod> [-c container] [--previous] — app logs
4. kubectl exec -it <pod> -- sh — interactive shell
5. kubectl top pod / kubectl top node — resource usage

Applying changes safely

Always kubectl diff before kubectl apply to preview changes. Prefer declarative apply over imperative create/edit. Use --dry-run=client -o yaml to validate without submitting. For production rollouts, watch with kubectl rollout status and reach for kubectl rollout undo if something goes wrong.

Gotchas

Agent-specific failure modes — provider-neutral pause-and-self-check items:

• Not confirming the active context before making changes. kubectl apply -f operates against whichever cluster context is currently active. Running a destructive operation in production because the context was left pointing at prod from a previous debugging session is among the most common Kubernetes incidents. Always run kubectl config current-context before any write operation, and use a tool or alias that shows the context in the prompt.
• Bare Pods in production instead of Deployments. A bare Pod that crashes is not rescheduled — it stays in Error or CrashLoopBackOff until manually deleted and recreated. A Deployment's ReplicaSet controller reschedules it automatically and supports rolling updates and rollbacks. Never create bare Pods for any workload that must stay up.
• Missing readiness probes on Services. A Service will send traffic to all pods that match its selector, including pods that are starting, initializing, or currently unhealthy but have not yet been killed by the liveness probe. Without a readiness probe, traffic hits unready pods and users see errors. The liveness probe kills bad pods; the readiness probe keeps traffic away from them until they are ready.
• No resource requests or limits. Without resources.requests, the scheduler has no signal for node placement and a noisy pod can be scheduled on an already-overloaded node. Without resources.limits, a memory-leaking pod can OOMKill neighboring pods on the same node. Set both on every container; start with generous values, observe with kubectl top, then tighten.
• latest image tags in Deployment manifests. A Deployment with image: myapp:latest will pull whatever latest resolves to at each restart — silently deploying a different version than the one you tested. Always pin to a specific immutable tag (typically a Git SHA or build number) so rollouts are deterministic and kubectl rollout undo restores the exact previous version.
• Blind kubectl apply without reviewing kubectl diff first. kubectl apply without a preceding kubectl diff is a production change made without preview. Fields set out-of-band (via kubectl edit, autoscalers, or admission webhooks) may be silently overwritten. Always kubectl diff -f manifest.yaml before kubectl apply -f manifest.yaml in production.
• Using -target or imperative kubectl edit as a normal workflow. Imperative edits (kubectl edit, kubectl scale) and -target applies produce configuration that diverges from the version-controlled manifests. The next declarative apply will overwrite the change without warning. All production changes must go through version-controlled manifests applied via CI/CD.

Full reference

Control plane architecture

kubectl apply -f deployment.yaml
    |
    v
API Server: validates, stores in etcd
    |
    v
Deployment controller -> ReplicaSet -> Pod objects (Pending)
    |
    v
Scheduler: assigns Pods to nodes (filtering + scoring)
    |
    v
kubelet: pulls image, starts containers on the node
    |
    v
kube-proxy: updates iptables/IPVS rules for Service endpoints

Components:

• API server — front door; validates and persists to etcd
• etcd — distributed KV store holding all cluster state; HA with 3 or 5 members; back up with etcdctl snapshot save
• Scheduler — filters then scores nodes for unscheduled pods
• Controller manager — runs reconcile loops (ReplicaSet, Deployment, Node, Job, Endpoint, ServiceAccount controllers)
• kubelet — node agent; manages Pod lifecycle via the CRI
• kube-proxy — programs iptables/IPVS/nftables for Services
• Container runtime — containerd or CRI-O; Docker Engine was removed as a direct runtime in v1.24

Resource YAML cheatsheet

Deployment with resources, probes, config, storage:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp
spec:
  replicas: 3
  selector:
    matchLabels:
      app: myapp
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0
  template:
    metadata:
      labels:
        app: myapp
    spec:
      containers:
        - name: app
          image: myapp:1.0.0
          ports:
            - containerPort: 8080
          resources:
            requests:
              cpu: 100m
              memory: 128Mi
            limits:
              cpu: 500m
              memory: 256Mi
          livenessProbe:
            httpGet:
              path: /healthz
              port: 8080
            initialDelaySeconds: 5
            periodSeconds: 10
          readinessProbe:
            httpGet:
              path: /ready
              port: 8080
            initialDelaySeconds: 3
            periodSeconds: 5
          envFrom:
            - configMapRef:
                name: myapp-config
          volumeMounts:
            - name: data
              mountPath: /data
      volumes:
        - name: data
          persistentVolumeClaim:
            claimName: myapp-data

Service types:

apiVersion: v1
kind: Service
metadata:
  name: myapp
spec:
  selector:
    app: myapp
  ports:
    - port: 80
      targetPort: 8080
---
apiVersion: v1
kind: Service
metadata:
  name: myapp-lb
spec:
  type: LoadBalancer
  selector:
    app: myapp
  ports:
    - port: 443
      targetPort: 8080

Ingress with TLS:

apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: myapp
spec:
  ingressClassName: nginx
  tls:
    - hosts: [myapp.example.com]
      secretName: myapp-tls
  rules:
    - host: myapp.example.com
      http:
        paths:
          - path: /
            pathType: Prefix
            backend:
              service:
                name: myapp
                port:
                  number: 80

ConfigMap, Secret, PVC:

apiVersion: v1
kind: ConfigMap
metadata:
  name: myapp-config
data:
  APP_ENV: production
  LOG_LEVEL: info
---
apiVersion: v1
kind: Secret
metadata:
  name: myapp-secret
type: Opaque
stringData:
  DB_PASSWORD: s3cret
---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: myapp-data
spec:
  accessModes: [ReadWriteOnce]
  storageClassName: standard
  resources:
    requests:
      storage: 10Gi

Job and CronJob:

apiVersion: batch/v1
kind: CronJob
metadata:
  name: nightly-backup
spec:
  schedule: "0 2 * * *"
  concurrencyPolicy: Forbid
  successfulJobsHistoryLimit: 3
  failedJobsHistoryLimit: 3
  jobTemplate:
    spec:
      template:
        spec:
          restartPolicy: OnFailure
          containers:
            - name: backup
              image: myapp:1.0.0
              command: ["./backup.sh"]

kubectl cheatsheet

# Viewing
kubectl get pods -n <ns> -o wide
kubectl get all -n <ns>
kubectl describe pod <pod> -n <ns>
kubectl get events --sort-by=.lastTimestamp

# Applying
kubectl apply -f manifest.yaml
kubectl apply -f ./manifests/ -R
kubectl diff -f manifest.yaml
kubectl create secret generic db \
  --from-literal=password=s3cret -n <ns>

# Debugging
kubectl logs <pod> -n <ns>
kubectl logs <pod> -c <container> --previous
kubectl logs -l app=myapp -n <ns> --tail=100
kubectl exec -it <pod> -n <ns> -- sh
kubectl port-forward svc/myapp 8080:80 -n <ns>
kubectl top pod -n <ns>
kubectl top node

# Rollouts
kubectl scale deploy myapp --replicas=5 -n <ns>
kubectl rollout status deploy/myapp -n <ns>
kubectl rollout history deploy/myapp -n <ns>
kubectl rollout undo deploy/myapp -n <ns>
kubectl rollout restart deploy/myapp -n <ns>

# Deleting
kubectl delete -f manifest.yaml
kubectl delete pod <pod> --grace-period=0 --force

Troubleshooting patterns

Pod Pending (not scheduled). Read the events:

kubectl describe pod <pod> -n <ns>   # look at Events section

CrashLoopBackOff. Get logs from the crashed container:

kubectl logs <pod> -n <ns> --previous
kubectl get pod <pod> -n <ns> \
  -o jsonpath='{.status.containerStatuses[0].lastState.terminated}'

Exit code 137 is OOMKilled — raise the memory limit. Exit code 1 with no logs usually means a bad command/args. A failing liveness probe restarts the container on a loop.

ImagePullBackOff. Almost always a wrong tag, a private registry without imagePullSecrets, or Docker Hub rate limiting:

kubectl create secret docker-registry regcred \
  --docker-server=ghcr.io \
  --docker-username=<user> \
  --docker-password=<token> \
  -n <ns>

Reference it in the pod spec via spec.imagePullSecrets.

Service not reachable. Endpoints tell you if the selector matches any pods:

kubectl get svc <svc> -n <ns>
kubectl get endpoints <svc> -n <ns>
# Empty endpoints = selector mismatch OR no pods are Ready
kubectl get pods -n <ns> --show-labels
kubectl run curl --image=curlimages/curl --restart=Never --rm -it -- \
  curl -v http://<svc>.<ns>.svc.cluster.local:<port>

Check: selector labels match pod labels exactly, targetPort matches the container's listening port, readiness probe is passing, NetworkPolicy is not blocking.

DNS issues inside the cluster.

kubectl run dnstest --image=busybox:1.36 --restart=Never --rm -it -- \
  nslookup <svc>.<ns>.svc.cluster.local
kubectl get pods -n kube-system -l k8s-app=kube-dns
kubectl logs -n kube-system -l k8s-app=kube-dns --tail=50

ndots:5 can cause slow external lookups — use a fully-qualified name with a trailing dot to force a direct lookup.

Resource limits and OOM.

• requests = typical usage, used for scheduling
• limits = maximum allowed; memory overrun is OOMKill, CPU overrun is throttling
• Start with generous limits, monitor with kubectl top, then tighten
• CPU limits are often best omitted — throttling is less harmful than OOMKill

kubectl top pod -n <ns> --containers
kubectl get pods -n <ns> -o json | \
  jq '.items[] | select(.status.containerStatuses[]?.lastState.terminated.reason=="OOMKilled") | .metadata.name'

Node pressure and eviction.

kubectl describe node <node> | grep -A 5 Conditions
# Common: MemoryPressure, DiskPressure, PIDPressure
kubectl get pods -n <ns> --field-selector=status.phase=Failed | grep Evicted

Helm upgrade with rollback safety

helm upgrade myrelease mychart/app -n prod -f prod-values.yaml \
  --atomic --timeout 5m
# --atomic auto-rolls back on failure
helm history myrelease -n prod

Debug containers and RBAC checks

# Ephemeral debug container (K8s 1.23+)
kubectl debug -it <pod> -n <ns> --image=busybox:1.36 --target=<container>

# Copy a running pod
kubectl debug <pod> -n <ns> --copy-to=debug-pod --container=app -- sh

# RBAC checks
kubectl auth can-i create deployments -n <ns>
kubectl auth can-i '*' '*' --all-namespaces
kubectl auth can-i get pods --as=system:serviceaccount:<ns>:<sa>

Anti-patterns

• Bare Pods in production — use Deployments or StatefulSets
• Missing readiness probes — Services will send traffic to pods that aren't ready
• No resource requests/limits — scheduler has nothing to go on, noisy neighbors can starve you
• Hardcoded namespace in manifests — pass via -n or kustomize
• latest image tags — rollouts become non-deterministic
• Ignoring kubectl diff — blind apply can silently remove fields that were set out-of-band

Source: projectious-work/aibox — distributed by TomeVault.