Kubernetes Security Checklist: 50 Best Practices (2025) Part II

Category 4: Secrets & Configuration Management (Practices 31-40)

Practice 31: Encrypt Kubernetes Secrets at Rest

Implementation: Ensure secrets are encrypted at rest in etcd and any underlying storage.

For managed clusters, enable provider-managed encryption (EKS, GKE, AKS all support etcd/secret encryption configurations).

For self-managed clusters, configure an EncryptionConfiguration for the API server:

kind: EncryptionConfiguration
apiVersion: apiserver.config.k8s.io/v1
resources:
  - resources:
      - secrets
    providers:
      - aescbc:
          keys:
            - name: key1
              secret: <base64-encoded-32-byte-key>
      - identity: {}

Then start the API server with:

--encryption-provider-config=/path/to/encryption-config.yaml
            

Why it matters: By default, secrets are only base64-encoded, not truly encrypted. If an attacker gains access to etcd or underlying disk snapshots, they can read all secrets. Encryption at rest ensures an additional layer of protection even if storage is compromised.

Compliance: CIS Kubernetes Benchmark (Secret Encryption), SOC 2 (CC6.x), PCI-DSS 4.0 (Strong Cryptography for Sensitive Data)

Practice 32: Use an External Secrets Manager (Vault, AWS Secrets Manager, etc.)

Implementation: Store sensitive values in an external secrets manager and sync them into Kubernetes using an operator like External Secrets Operator, Secrets Store CSI Driver, or Vault Agent Injector.

Example (External Secrets Operator + AWS Secrets Manager):

apiVersion: external-secrets.io/v1beta1 kind: ExternalSecret metadata:
              name: app-db-credentials
              namespace: production spec:
              refreshInterval: 1h
              secretStoreRef:
                name: aws-secrets
                kind: ClusterSecretStore
              target:
                name: app-db-secret
                creationPolicy: Owner
              data:
              - secretKey: username
                remoteRef:
                  key: prod/app/db
                  property: username
              - secretKey: password
                remoteRef:
                  key: prod/app/db
                  property: password 

Why it matters: External managers give you strong access controls, auditing, rotation, and key management capabilities that Kubernetes alone doesn’t provide. Kubernetes then only holds short-lived copies of secrets needed at runtime.

Compliance: SOC 2 (CC6.x, CC7.x), PCI-DSS (3.x, 7.x), HIPAA (164.312(a))

Practice 33: Keep Secrets Out of Git (Git Hygiene)

Implementation:

• Never commit real passwords, API keys, or certificates to Git.
• Use placeholders in manifests (e.g., {{DB_PASSWORD}}) and populate them from a CI/CD or GitOps tool using environment variables or secret stores.
• Add .env, secrets/*.yaml, and similar files to .gitignore.
• Use automated secret scanners (TruffleHog, GitLeaks, GitHub secret scanning) and pre-commit hooks.

Example pre-commit configuration:

repos:
  - repo: https://github.com/gitleaks/gitleaks
    rev: v8.18.0
    hooks:
      - id: gitleaks

If secrets were accidentally committed, revoke & rotate them; do not just delete the file from Git history.

Why it matters: Once a secret is in Git, it’s effectively permanent clones, forks, and backups can expose it indefinitely. Git is for code, not real credentials.

Compliance: SOC 2 (Change Management & Access Control), PCI-DSS (Secure Development Practices), OWASP ASVS (V1.9 Secret Management)

Practice 34: Implement Regular Secret Rotation

Implementation:

Define rotation intervals per secret type (e.g., API keys every 90 days, DB passwords every 30–60 days).

Use your external secrets manager’s rotation features (AWS Secrets Manager, Vault, etc.).

In Kubernetes, rely on operators that auto-refresh secrets used by workloads.

Example (ExternalSecret with automatic refresh):

apiVersion: external-secrets.io/v1beta1 kind: ExternalSecret metadata:
              name: app-api-key
              namespace: production spec:
              refreshInterval: 15m  # pick based on rotation policy
              secretStoreRef:
                name: aws-secrets
                kind: ClusterSecretStore
              target:
                name: app-api-key
              data:
              - secretKey: api-key
                remoteRef:
                  key: prod/app/api
                  property: key 

Workloads should reload secrets either via rolling deployments (triggered by secret changes) or by watching mounted volumes.

Why it matters: Long-lived credentials are easier to abuse and harder to revoke if leaked. Regular rotation reduces attacker dwell time and limits blast radius.

Compliance: PCI-DSS (password/API key rotation), SOC 2 (CC6.x), NIST 800-53 (IA-5)

Practice 36: Use Sealed Secrets / Encrypted Manifests for GitOps

Implementation: Use tools like Sealed Secrets, SOPs, or SOPS + KMS to store encrypted secret manifests in Git, so they are only decrypted inside the cluster.

Example (Bitnami SealedSecret):

apiVersion: bitnami.com/v1alpha1 kind: SealedSecret metadata:
              name: app-db-secret
              namespace: production spec:
              encryptedData:
                username: AgBsdY...
                password: AgC34k...
              template:
                type: Opaque
                metadata:
                  name: app-db-secret
                  namespace: production 

The controller in the cluster decrypts this into a normal Secret object. The private key never leaves the cluster; Git only sees encrypted values.

Why it matters: This enables GitOps workflows while still keeping real secret values encrypted at rest in version control. Even if the repo leaks, the attacker cannot read the plaintext secrets.

Compliance: GitOps + Secret Management Best Practices, SOC 2 (Change Management), PCI-DSS (protect stored sensitive data)

Practice 37: Enable Audit Logging for Secret Access

Implementation:

• Enable Kubernetes API audit logs (or the managed equivalent) and ensure get / list calls on secrets are logged with user identity.
• Forward audit logs to a central log system (Loki, ELK, cloud-native logging, SIEM).
• Create alerts for:
  • Unusual spikes in get secrets calls
  • Attempts from unexpected service accounts or users
  • Access to secrets in restricted namespaces

Conceptual example (high-level only):

• Enable an audit policy that includes:

resources: ["secrets"]
verbs: ["get", "list"]
level: RequestResponse

• Ship logs to a SIEM and create detections.

Why it matters: Without audit logs, you can’t answer “who accessed which secret and when?” during an incident. Audit trails are essential for investigations and compliance.

Compliance: PCI-DSS (10.x – logging), SOC 2 (CC7.2 – detect anomalies), HIPAA (audit controls)

Practice 38: Separate Secrets by Environment and Namespace

Implementation:

• Use separate namespaces and secrets per environment: dev, staging, production.
• Avoid sharing the same secret object across environments.
• Use clear naming conventions, for example:

Namespace: production
Secret names:
  app-db-credentials
  app-payment-api
  app-jwt-keys
Namespace: staging
Secret names:
  app-db-credentials
  app-payment-api
  app-jwt-keys

Combined with network and RBAC rules, this ensures dev/stage workloads never access production secrets.

Why it matters: Mixing environments increases the risk of a lower-security environment (dev) being used as a stepping stone to production secrets. Environment isolation is foundational to a secure deployment model.

Compliance: PCI-DSS (segregation of environments), SOC 2 (Change Management & Segregation of Duties)

Practice 39: Version and Track Secret Changes

Implementation:

• Use your secret manager’s versioning features (e.g., AWS Secrets Manager versions, Vault versions).
• In GitOps, treat secret definitions (templates/placeholders) like any other config—code review, PRs, approvals.
• Add annotations/labels to Kubernetes Secrets to record purpose and rotation information:

apiVersion: v1
kind: Secret
metadata:
  name: app-db-secret
  namespace: production
  labels:
    app: backend
  annotations:
    security.squareops.com/owner: "platform-team"
    security.squareops.com/rotation-frequency: "30d"
    security.squareops.com/last-rotated: "2025-01-10"
type: Opaque
data:
  username: ...
  password: ...

• Ensure every change to secret values is traceable to:
  • Who initiated it
  • When it was done
  • Why it changed (ticket/PR reference)

Why it matters: Versioning and traceability help you roll back quickly if a change breaks something and provide evidentiary records for audits and incident analysis.

Compliance: SOC 2 (Change Management & Auditability), PCI-DSS (configuration & change control), ISO 27001 (A.12.1.2)

Practice 40: Monitor Secret Expiration and Misconfigurations

Implementation:

• Track expiration of:
  • TLS certificates
  • API keys and tokens
  • Database credentials (where applicable)
• Use monitoring tools or custom scripts/CronJobs that:
  • Parse certificates stored in Secrets
  • Check notAfter dates
  • Emit metrics or logs when certificates are close to expiry (e.g., < 30 days)

Example (conceptual CronJob):

apiVersion: batch/v1
kind: CronJob
metadata:
  name: cert-expiry-checker
  namespace: platform
spec:
  schedule: "0 2 * * *"
  jobTemplate:
    spec:
      template:
        spec:
          serviceAccountName: cert-checker
          containers:
          - name: checker
            image: your-registry/cert-checker:latest
            args:
              - "--namespace=production"
              - "--warning-days=30"
          restartPolicy: OnFailure

• Alert on:
  • Secrets nearing expiry
  • Secrets without rotation annotations
  • Secrets with overly broad access (identified via periodic RBAC review)

Why it matters: Many outages and incidents are caused by expired certificates or forgotten tokens. Proactive monitoring turns expiration from an emergency into a routine maintenance task and reduces the risk of unexpected downtime.

Compliance: SOC 2 (Availability & Security), PCI-DSS (certificate/key lifecycle management), NIST 800-53 (Key Management & Maintenance)

Practice 41: Keep Kubernetes Updated with Security Patches

Implementation:

• Track the Kubernetes version lifecycle (end-of-support dates) for your distribution or cloud provider.
• Standardize on a set of supported versions (e.g., N-1 or N-2 from the latest stable).
• Use managed cluster upgrade mechanisms (EKS/GKE/AKS) or automation (kOps, kubeadm, Cluster API) to:
  • Upgrade control plane first.
  • Then upgrade worker nodes using rolling node pool/node group updates.
• Test upgrades in a staging cluster before production and verify key workloads/CI/CD flows.
• Combine with node OS patching (managed node images, golden images, or OS patch management tools).

Why it matters: Older Kubernetes versions lose security support and may contain known vulnerabilities and deprecated APIs. Regular cluster and node OS patching closes known CVEs, keeps your environment compatible with modern tooling, and is often required by compliance frameworks.

Compliance: CIS Kubernetes Benchmark, SOC 2 (Change Management & Security), PCI-DSS (system components must be kept current with security patches), ISO 27001 (A.12.6.1)

Practice 42: Enforce Admission Controls (OPA Gatekeeper / Kyverno)

Implementation:

• Deploy a policy engine such as OPA Gatekeeper or Kyverno as an admission controller.
• Define policies that enforce baseline security rules, for example:
  • No privileged containers.
  • No hostPath volumes unless explicitly allowed.
  • Only approved container registries.
  • Mandatory labels/annotations for ownership and environment.
• Start in audit mode to see violations without blocking deployments, then gradually switch to enforce mode.

Example (Kyverno policy to block privileged containers):

apiVersion: kyverno.io/v1
kind: ClusterPolicy
metadata:
  name: disallow-privileged
spec:
  validationFailureAction: enforce
  rules:
    - name: validate-privileged
      match:
        resources:
          kinds:
            - Pod
      validate:
        message: "Privileged containers are not allowed."
        pattern:
          spec:
            containers:
              - securityContext:
                  privileged: false

Why it matters: Admission controllers are the last checkpoint before workloads land in the cluster. They prevent risky configurations from ever being created and standardize security requirements across teams and namespaces.

Compliance: CIS Kubernetes Benchmark (Admission Control), SOC 2 (preventive controls), PCI-DSS (secure configuration & change control)

Practice 43: Disable or Strongly Secure the Kubernetes Dashboard

Implementation:

• Best option: Do not deploy the legacy Kubernetes Dashboard in production. Use managed UIs (EKS/GKE/AKS consoles) or a hardened third-party dashboard.
• If you must run it:
  • Never expose it directly to the public internet.
  • Require authentication via OIDC/SSO or a short-lived kubeconfig.
  • Bind it only to least-privileged service accounts (no cluster-admin by default).
  • Restrict access using NetworkPolicies, firewall rules, or VPN-only access.

Why it matters: Historically, misconfigured dashboards have been a frequent cause of full-cluster compromise. An exposed, high-privilege dashboard is effectively a remote root console for your cluster.

Compliance: CIS Kubernetes Benchmark (Dashboard), SOC 2 (Access Control), PCI-DSS (restrict access to management interfaces)

Practice 44: Enforce ResourceQuotas and LimitRanges

Implementation:

• Define ResourceQuota per namespace to limit total CPU, memory, and object counts (pods, services, PVCs).
• Define LimitRange to ensure containers set sensible requests and limits and to cap max usage per container/pod.
• Apply stricter quotas for multi-tenant or shared namespaces.

Example (ResourceQuota and LimitRange):

apiVersion: v1
kind: ResourceQuota
metadata:
  name: prod-quota
  namespace: production
spec:
  hard:
    requests.cpu: "20"
    requests.memory: 40Gi
    limits.cpu: "40"
    limits.memory: 80Gi
    pods: "200"

---
apiVersion: v1
kind: LimitRange
metadata:
  name: prod-limits
  namespace: production
spec:
  limits:
    - type: Container
      default:
        cpu: "500m"
        memory: 512Mi
      defaultRequest:
        cpu: "100m"
        memory: 128Mi
      max:
        cpu: "4"
        memory: 4Gi

Why it matters: Without quotas and limits, a single misbehaving workload can starve the node or cluster (CPU/memory exhaustion), causing cascading outages. Resource controls are a reliability and security boundary for multi-tenant clusters.

Compliance: SOC 2 (Availability & Capacity Management), SRE Best Practices (multi-tenant isolation), PCI-DSS (availability of critical services)

Practice 45: Use PodDisruptionBudgets (PDBs) for Safer Upgrades

Implementation:

• Define PodDisruptionBudget for critical deployments and stateful services to control how many pods can be voluntarily disrupted at once (e.g., during node drains, upgrades, or autoscaling).
• Use either:
  • minAvailable – minimum number of replicas that must stay running, or
  • maxUnavailable – maximum number of replicas that can be down simultaneously.
• Validate that rolling upgrades and node maintenance respect the PDB and keep enough healthy pods serving traffic.

Example (PodDisruptionBudget for a 3-replica deployment):

apiVersion: policy/v1
kind: PodDisruptionBudget
metadata:
  name: backend-pdb
  namespace: production
spec:
  minAvailable: 2
  selector:
    matchLabels:
      app: backend

Why it matters: Without PDBs, automated node drains or rolling updates can briefly take down all replicas of a service, causing outages even when the overall system is healthy. PDBs enforce availability guarantees during planned disruptions.

Compliance: SOC 2 (Availability), SRE Best Practices (graceful maintenance), PCI-DSS (maintain availability of systems that store, process, or transmit cardholder data)

Practice 46: Monitor Runtime Threats with Falco (or Similar)

Implementation:

• Deploy a runtime security tool such as Falco, Sysdig Secure, or other eBPF-based detectors to watch for suspicious behavior at the node and container level.
• Use built-in Falco rules to detect:
  • Shell spawned inside containers
  • Unexpected file changes in system directories
  • Privilege escalation attempts
  • Unexpected outbound connections or port scans
• Configure Falco to send alerts to your logging stack or incident response tools (Slack, PagerDuty, SIEM, etc.).
• Start with alert-only mode, then refine rules and severities to reduce noise.

Example (simplified Falco rule to detect a shell in a container):

- rule: Terminal shell in container
  desc: Detect interactive shell in a container
  condition: >
    spawned_process and container and
    proc.name in (bash, sh, zsh, ash)
  output: >
    Shell spawned in container (user=%user.name container_id=%container.id
    image=%container.image.repository:%container.image.tag cmdline=%proc.cmdline)
  priority: WARNING
  tags: [container, shell, mitre_execution]

Why it matters: Static scans and policies catch misconfigurations before deployment, but attackers (or buggy apps) can still behave maliciously at runtime. Runtime threat detection adds a final layer of defense by spotting abnormal behavior inside containers and nodes.

Compliance: SOC 2 (CC7.x – detect and respond to anomalies), PCI-DSS (11.x – intrusion detection), NIST 800-53 (SI family – Security Monitoring)

Practice 47: Implement Backup & Disaster Recovery for Cluster State and Data

Implementation:

• Back up:
  • Cluster state (etcd or control-plane config for self-managed clusters).
  • Kubernetes objects (Deployments, Services, Ingresses, CRDs, etc.).
  • Persistent volume data (databases, file stores) using tools like Velero or storage provider snapshots.
• Use Velero (or similar) to back up namespaces, resources, and volumes to an object store (S3/GCS/Azure Blob/minio).
• Define and regularly test restore procedures in a separate cluster or environment.
• Document RPO/RTO targets and verify backups meet those requirements.

Example (Velero backup schedule):

apiVersion: velero.io/v1
kind: Schedule
metadata:
  name: daily-prod-backup
  namespace: velero
spec:
  schedule: "0 1 * * *" # daily at 01:00
  template:
    includedNamespaces:
      - production
    ttl: 168h # retain for 7 days
    snapshotVolumes: true

Why it matters: Even with strong security, accidents happen: bad deployments, corruption, or cloud-region incidents. Without tested backups and DR, you risk extended downtime and data loss. A hardened cluster must be recoverable, not just secure.

Compliance: SOC 2 (Availability & Processing Integrity), PCI-DSS (12.x – backup & DR), ISO 27001 (A.17 – Business continuity)

Practice 48: Harden Worker Nodes and Underlying OS

Implementation:

• Use minimal, Kubernetes-optimized OS images (e.g., EKS-optimized AMIs, COS, Flatcar, or other hardened images).
• Restrict SSH access:
  • Disable SSH entirely where possible or allow only via bastion/VPN.
  • Enforce key-based auth, no password login, and short-lived access.
• Apply OS-level hardening:
  • Enable automatic security updates or frequent patching.
  • Disable unnecessary services/daemons.
  • Configure firewall rules (iptables/nftables/security groups) with least privilege.
• Harden cloud metadata access (IMDSv2 only, restricted hops) so pods cannot freely read instance credentials.
• Use nodegroups or autoscaling groups with immutable images (bake changes into new images and roll out).

Why it matters: Kubernetes security depends on the host OS. If an attacker escapes a container or exploits a kernel vulnerability, poorly hardened nodes can give them full control. A secure, patched, minimal OS dramatically reduces this risk.

Compliance: CIS Benchmarks (Linux/OS hardening), SOC 2 (Infrastructure Security), PCI-DSS (system hardening & patching), NIST 800-53 (SC & CM families)

Practice 49: Run Regular Security Audits with kube-bench and Other Scanners

Implementation:

• Use kube-bench to check your cluster against the CIS Kubernetes Benchmark regularly (manually or via scheduled jobs).
• Complement with:
  • kube-hunter or similar tools for network-facing vulnerabilities.
  • kubescape or Trivy Kubernetes to evaluate cluster posture & workload misconfigurations.
• Integrate these tools into CI/CD or a periodic scanning job and store reports centrally.
• Track remediation of high/critical findings like normal vulnerability management (tickets, SLAs, owners).

Example (running kube-bench as a Job):

apiVersion: batch/v1
kind: Job
metadata:
  name: kube-bench
  namespace: security
spec:
  template:
    spec:
      serviceAccountName: kube-bench
      hostPID: true
      containers:
        - name: kube-bench
          image: aquasec/kube-bench:latest
          securityContext:
            privileged: true
          volumeMounts:
            - name: var-lib-kubelet
              mountPath: /var/lib/kubelet
              readOnly: true
            - name: etc-systemd
              mountPath: /etc/systemd
              readOnly: true
            - name: etc-kubernetes
              mountPath: /etc/kubernetes
              readOnly: true
      restartPolicy: Never
      volumes:
        - name: var-lib-kubelet
          hostPath:
            path: /var/lib/kubelet
        - name: etc-systemd
          hostPath:
            path: /etc/systemd
        - name: etc-kubernetes
          hostPath:
            path: /etc/kubernetes

Why it matters: Security posture drifts over time—new components are added, configs change, and best practices evolve. Regular automated audits make sure your cluster continues to meet hardening baselines instead of relying on one-time setups.

Compliance: CIS Kubernetes Benchmark, SOC 2 (ongoing risk assessment), PCI-DSS (vulnerability management), ISO 27001 (A.12.6 – Technical vulnerability management)

Practice 50: Establish Continuous Security & Compliance Monitoring

Implementation:

• Define a minimal set of security SLOs/metrics for your clusters, such as:
  • Number of critical vulnerabilities open > X days
  • Number of policy violations (privileged pods, hostPath usage)
  • Mean time to detect (MTTD) and mean time to respond (MTTR) for incidents
• Centralize:
  • Logs (audit, application, system)
  • Metrics (Prometheus, cloud monitoring)
  • Security events (Falco, IDS, scanners) into a SIEM or observability platform.
• Create dashboards that show:
  • Current security posture for each cluster/environment.
  • Trend of vulnerabilities, misconfigurations, and policy violations.
• Set up recurring security reviews (e.g., monthly or quarterly) to:
  • Review findings and incidents.
  • Prioritize remediation work.
  • Update policies and controls as the platform evolves.
• Integrate alerts into your on-call / incident management process so security signals are handled like reliability incidents.

Why it matters: Security is not a one-time checklist. Without continuous monitoring and feedback loops, even a well-hardened cluster will slowly drift into an unknown and risky state. Continuous visibility and regular reviews keep Kubernetes security aligned with business and compliance needs.

Compliance: SOC 2 (monitoring & governance), PCI-DSS (continuous monitoring & improvement), ISO 27001 (ISMS continual improvement), NIST CSF (Detect & Respond Functions)

How Atmosly Automates Kubernetes Security

Pre-Configured Security Controls

Atmosly implements many of these 50 practices automatically:

• RBAC Automation: Pre-configured roles (super_admin, read_only, devops) following least privilege, automatic ServiceAccount creation, proper subject binding
• Pod Security Enforcement: Auto-applies Pod Security Standard labels (restricted for prod, baseline for staging)
• Vulnerability Scanning: Scans deployed workloads, reports CVEs by severity
• Network Policy Recommendations: Analyzes traffic patterns, suggests policies
• Secrets Management: Integrates with Vault, AWS Secrets Manager, tracks rotation
• Compliance Reporting: CIS Kubernetes Benchmark compliance dashboard
• Runtime Threat Detection: AI-powered anomaly detection for suspicious pod behavior
• Audit Logging: Centralized audit trail of all Atmosly-initiated actions

Continuous Security Monitoring

Atmosly continuously monitors for security violations:

• Privileged containers running in production (Policy violation)
• Pods without resource limits (DoS risk)
• ServiceAccounts with cluster-admin (Over-privilege)
• Secrets without encryption at rest
• Images with HIGH/CRITICAL CVEs in production
• Network policies missing from critical namespaces

Alerts with specific remediation guidance and kubectl commands to fix. 

Implementing the Checklist: Prioritized Roadmap

Phase 1: Critical (Week 1) - Practices that prevent immediate breaches

• Practice 1: Enable RBAC ✅
• Practice 4: Remove cluster-admin from regular users ✅
• Practice 11: Enforce Pod Security Standards ✅
• Practice 12: Never run as root ✅
• Practice 21: Default deny Network Policies ✅
• Practice 31: Encrypt secrets at rest ✅

Practice 41: Update Kubernetes (patch CVEs) ✅

Phase 2: High Priority (Week 2–3) – Defense in Depth

These practices strengthen cluster defenses beyond the basics and significantly reduce lateral movement, privilege escalation, and secret exposure risks.

Practice 13: Enforce strict container capabilities (drop all, add minimal) ✅

Practice 14: Enforce read-only root filesystem where possible ✅

Practice 15: Enforce seccomp profiles (RuntimeDefault or custom) ✅

Practice 16: Configure AppArmor/SELinux policies for workloads ✅

Practice 17: Use non-root, dedicated service accounts per workload ✅

Practice 22: Implement egress restrictions with Network Policies ✅

Practice 23: Segment namespaces by environment (dev/stage/prod isolation) ✅

Practice 24: Enforce ingress controls & restrict load balancer exposure ✅

Practice 25: Use cluster-wide DNS & identity-based access controls ✅

Practice 32: Adopt an external secrets manager (Vault, AWS Secrets Manager, etc.) ✅

Practice 33: Keep all secrets out of Git (Git hygiene + scanners) ✅

Practice 34: Automate secret rotation at defined intervals ✅

Practice 35: Ensure secret versioning and access traceability ✅

Practice 36: Use Sealed Secrets or SOPS for GitOps-safe encryption ✅

Practice 42: Enforce admission controls (OPA Gatekeeper / Kyverno)
Prevent privileged pods, hostPath mounts, unapproved registries. ✅

Practice 43: Disable or secure the Kubernetes Dashboard (SSO-only) ✅

Practice 44: Apply ResourceQuotas + LimitRanges for resource boundaries ✅

Practice 45: Use PodDisruptionBudgets for safe upgrades/rollouts ✅

This phase creates defense-in-depth, ensuring that even if one control fails, multiple layers still protect the cluster.

Phase 3: Medium Priority (Month 1) – Hardening, Stability & Compliance

These practices finalize your production-grade security posture, ensuring long-term compliance, resilience, and operational integrity.

Practice 18: Configure image pull policies and restrict image tags (no latest) ✅

Practice 19: Enforce immutable images and pinned digests ✅

Practice 20: Scan container images for vulnerabilities (CI/CD + runtime) ✅

Practice 26: Set up multi-layer network segmentation for internal services ✅

Practice 27: Harden cluster ingress (TLS, WAF, mTLS when possible) ✅

Practice 28: Configure node-level firewall rules & metadata protection ✅

Practice 29: Harden API server, kubelet, and control-plane access ✅

Practice 30: Apply least-privilege IAM roles for cloud integrations ✅

Practice 37: Enable audit logging for secret access & API actions ✅

Practice 38: Separate secrets by environment and namespace ✅

Practice 39: Track secret versions and changes for compliance ✅

Practice 40: Monitor secret expiration (TLS certs, API tokens, DB credentials) ✅

Practice 46: Monitor runtime threats using Falco or eBPF sensors ✅

Practice 47: Implement backup & disaster recovery (Velero, snapshots) ✅

Practice 48: Harden worker nodes and underlying OS image ✅

Practice 49: Run regular CIS + vulnerability audits (kube-bench, Trivy, Kubescape) ✅

Practice 50: Establish continuous security & compliance monitoring ✅

By the end of Phase 3, your clusters reach a fully hardened, audit-ready, compliance-aligned state that meets SOC 2, PCI-DSS, ISO 27001, and CIS Kubernetes Benchmark requirements.

Conclusion: Building a Secure, Automated Kubernetes Foundation

Securing Kubernetes isn’t about one tool or one policy it’s about layering protection across every part of the cluster. Practices 31–50 reinforce the most critical layers of that defense-in-depth approach: encrypted secrets, strong admission controls, hardened nodes, runtime threat detection, and continuous auditing. Together, these controls ensure your clusters remain resilient, compliant, and ready for real-world production demands.

Critical Priorities to Get Right:

Encrypt and protect secrets using external secret managers

Keep secrets out of Git and enforce regular rotation

Enable audit logging for secret access and policy violations

Harden worker nodes and apply OS-level security patches

Enforce admission controls (Gatekeeper/Kyverno)

Implement runtime threat detection (Falco or similar)

Back up cluster state and persistent data regularly

Continuously scan and audit cluster posture (kube-bench, Trivy, Kubescape)

Manually implementing and maintaining these controls across multiple clusters is complex and resource-intensive. Atmosly eliminates that friction by automating security enforcement, detecting misconfigurations in real time, and providing compliance dashboards aligned with CIS, SOC 2, PCI-DSS, and ISO 27001.

Atmosly ensures your clusters stay secure not just on day one, but every day.