Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIMuseMuseDotsDots+21 more

    DevSecOps Expert — AI CI/CD & Kubernetes Automation Agent ⭐

    1

    Design and audit secure CI/CD pipelines, Kubernetes manifests, and Terraform infrastructure using DevSecOps best practices.

    $9.99

    Secure checkout via Stripe

    Money-back guarantee

    Converts to your local currency at checkout

    Security scanned
    DevSecOps Expert — AI CI/CD & Kubernetes Automation Agent ⭐

    DevSecOps Expert — AI CI/CD & Kubernetes Automation Agent ⭐

    Example session with this skill installed

    Review my Kubernetes deployment for a Node.js API. I need resource limits, liveness probes, and a GitHub Actions pipeline that includes container scanning and a production approval gate.

    • Read your context and instructions
    • Compiled the devsecops expert

    I have reviewed the requirements for your Node.js API deployment. The following plan focuses on production stability and supply-chain security using a multi-stage delivery model.

    DevSecOps Deployment Plan

    ComponentRecommendationSecurity Impact
    Container BaseUse node:20-bookworm-slimReduces attack surface and image size
    ResourcesSet requests at 256MiB/0.5 CPU, limits at 512MiB/1.0 CPUPrevents noisy neighbor issues and OOM kills
    ProbeslivenessProbe on /healthz with 10s initial delayAutomated recovery for deadlocked processes
    ScanningIntegrate trivy in CI pipelineDetects OS and application vulnerabilities before push
    PromotionManual environment approval for productionPrevents unauthorized deployments to stable envs

    Kubernetes Manifest & Pipeline Snippets

    
# deployment.yaml snippets
apiVersion: apps/v1
kind: Deployment
metadata:
  name: api-service
spec:
  template:
    spec:
      containers:
      - name: api
        image: registry.tld/api:${IMAGE_TAG}
        resources:
          requests:
            memory: "256Mi"
            cpu: "500m"
          limits:
            memory: "512Mi"
            cpu: "1000m"
        livenessProbe:
          httpGet:
            path: /healthz
            port: 3000
          initialDelaySeconds: 10
          periodSeconds: 5

    
# .github/workflows/deploy.yml
jobs:
  security-scan:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Run Trivy vulnerability scanner
        uses: aquasecurity/trivy-action@master
        with:
          image-ref: 'registry.tld/api:${{ github.sha }}'
          format: 'table'
          exit-code: '1'
          severity: 'CRITICAL,HIGH'

  deploy-prod:
    needs: security-scan
    environment: production
    runs-on: ubuntu-latest
    steps:
      - name: Deploy to K8s
        run: kubectl apply -f k8s/

    Next steps

    1. Implement the /healthz endpoint in your Node.js application logic.
    2. Configure GitHub Environment Secrets for the production environment.
    3. Apply the updated deployment.yaml to your staging cluster for resource profiling.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Software delivery is often slowed down by manual gates, insecure defaults, and fragmented infrastructure logic. This skill provides a structured DevSecOps framework to automate and secure the entire lifecycle from commit to production. It moves beyond basic scripts to design maintainable CI/CD pipelines, Infrastructure as Code (IaC) architectures, and Kubernetes deployment strategies that prioritize least-privilege security and observability.

    What it does

    • CI/CD pipeline design builds multi-stage workflows covering build, test, security, and progressive deployment.
    • Infrastructure as Code review audits Terraform or cloud-native templates for drift, dependency ordering, and security risks.
    • Kubernetes workload planning configures resource limits, probes, RBAC, and secret management for production readiness.
    • Security integration embeds SAST, SBOM generation, container scanning, and secret detection into the delivery flow.
    • GitOps workflow design establishes repository-driven desired states with environment promotion and drift detection.
    • Observability mapping defines health checks, log aggregation, metrics, and automated rollback triggers.

    How it works

    1. Provide your repository structure, current pipeline files, cloud provider, and Kubernetes setup.
    2. The agent analyzes the stack to identify gaps in security, reliability, or automation.
    3. It generates a comprehensive DevSecOps plan including target architecture and ordered implementation tasks.
    4. You receive specific configuration artifacts like GitHub Actions YAML, Terraform modules, or K8s manifests tailored to your environment.

    Frameworks & tools

    Works with GitHub Actions, GitLab CI, Terraform, Kubernetes, Docker, ArgoCD, Flux, and major cloud providers (AWS, Azure, GCP). Supports security tools like Snyk, Trivy, and Open Policy Agent.

    Why this beats prompting it yourself

    Generic prompts often miss the interplay between infrastructure and application security, leading to overly permissive IAM roles or brittle deployment scripts. This skill follows a DISCOVER-to-IMPROVE workflow that forces consideration of supply-chain security, artifact provenance, and rollback triggers that generic LLMs typically ignore.

    Use cases

    • Auditing a legacy Jenkins pipeline to migrate it to a secure, containerized GitHub Actions workflow.
    • Designing a GitOps-based multi-environment promotion strategy for a microservices architecture on EKS.
    • Hardening a Terraform-managed cloud environment with least-privilege RBAC and policy-as-code gates.
    • Implementing automated canary releases and health-based rollbacks for a high-traffic production service.

    Known limitations

    Does not execute actual code or provision cloud resources. Cannot verify if a generated pipeline succeeds without user-provided logs or execution evidence.

    Does not perform live infrastructure provisioning. Requires user to provide stack details and logs for accurate troubleshooting. Cannot bypass existing organizational security controls.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

    Reviews

    No reviews yet

    Be one of the first to try it. Every listed skill goes through the trust checks below.

    Security scanned

    Checked by our 8-point scan before listing

    Fresh listing

    Recently published to Agensi

    Money-back guarantee

    Doesn't do what its page promises? You get your money back.

    Trust & safety

    Security scan

    Security scan passed 12 days ago

    Permissions

    No special permissions declared or detected

    Listed12 days ago

    What's inside

    Frequently Asked Questions

    This skill automates the transition from manual, insecure software delivery to a robust DevSecOps pipeline, ensuring your Kubernetes workloads and Terraform infrastructure follow strict security and reliability standards.

    The skill works with major LLMs that support repository and file analysis, providing the best results when integrated with agents that can process GitHub Actions, GitLab CI, and Terraform configurations.

    You receive the specialized logic for designing secure CI/CD workflows, Infrastructure as Code modules, and Kubernetes manifests, along with a structured framework for auditing and hardening your existing environments.

    Simply provide the agent with your current repository structure, cloud provider details, and pipeline files; it will immediately begin identifying security gaps and generating optimized configuration code.

    While it designs the architecture and generates the necessary YAML or HCL code, it does not have the authority to provision cloud resources or execute scripts directly in your production environment.

    Yes, the skill is updated to reflect the latest security best practices and version changes for core tools like Terraform, Kubernetes, and popular GitOps controllers like ArgoCD.

    New in DevOps & Cloud