DevSecOps CI/CD Pipeline with SAST, DAST & GKE Deployment

The Problem and Why It Mattered

I built a fully automated, security-integrated CI/CD pipeline — from commit to production on GKE — with security scanning embedded at every stage, not bolted on at the end. The relevant technical and business risk is the cost of leaving this workflow, control, or product boundary unclear, manual, insecure, or difficult to operate. The case study focuses on the decisions used to make that risk manageable.

Objectives and Success Criteria

• Deliver the capability described in the project objective using a maintainable technical design.
• Make the main workflow, control boundary, and operational responsibilities explicit.
• Produce reviewable implementation evidence without publishing confidential values or customer data.

Requirements and Constraints

The delivery design had to be repeatable across environments, minimise direct production access, and retain enough evidence to investigate and roll back change safely.

My Role and Ownership

I owned the technical design and implementation described in this portfolio record, including the technology choices, core system boundaries, and the documentation of the resulting approach. Related organisational decisions, vendor operations, and formal certification decisions remain outside the scope of this technical case study unless stated explicitly.

Solution Overview

The solution is built around GitHub Actions, Trivy, Snyk. Its implementation is organised as the components below so that the architecture, control points, and operating model can be evaluated separately rather than treated as a list of tools.

Architecture and System Design

The public architecture description follows the path from the initiating user, workload, or operator action through the relevant devops components. Access boundaries, data or state handling, and operational controls are described at a safe level; secrets, private addresses, and client-sensitive implementation details are intentionally omitted.

Technology Decisions and Trade-Offs

I selected GitHub Actions, Trivy, Snyk because they support the project objective and make the critical engineering boundaries explicit. The trade-off is operational and platform complexity: the design depends on documented configuration, controlled access, and ongoing review rather than assuming that a managed service or framework removes engineering responsibility.

Implementation Walkthrough

The following implementation notes describe the components that matter most to the project outcome. They are intentionally focused on technical decisions and operating behaviour instead of reproducing entire source files or sensitive configuration.

Implementation: Stage 1 — Static Application Security Testing (SAST)

On every pull request, Snyk Code scans the application source for security vulnerabilities. Findings above a configurable severity threshold fail the build immediately, with a detailed report posted as a PR comment. Semgrep runs custom rules: no hardcoded secrets, no eval() usage, no direct SQL string concatenation.

Implementation: Stage 2 — Dependency & Container Scanning

After the Docker image is built, Trivy scans both the base image and all installed packages for known CVEs. Snyk Open Source audits the dependency tree simultaneously. Images that fail CVE thresholds are rejected — they never enter Artifact Registry. A weekly scheduled scan re-checks existing images as new CVEs are disclosed.

Implementation: Stage 3 — Image Build & Signing with Binary Authorization

Clean images are pushed to GCP Artifact Registry and signed using Binary Authorization. The GKE cluster policy refuses to run any image that hasn't been signed by the CI pipeline's attestor service account — closing the gap where someone could push a malicious image directly to the registry.

Implementation: Stage 4 — Infrastructure Scanning with Checkov

Terraform plan output is fed through Checkov before any infrastructure changes are applied — validating no public Cloud Storage buckets, no GKE nodes with public IPs, no firewall rules allowing 0.0.0.0/0 on management ports.

Implementation: Stage 5 & 6 — GKE Deployment & DAST

Approved artifacts deploy through Google Cloud Deploy. GKE manifests enforce security contexts: non-root containers, read-only root filesystems, all capabilities dropped, resource limits on every workload. Once staging is live, OWASP ZAP runs an authenticated scan probing for runtime vulnerabilities: open redirects, authentication bypasses, CSRF gaps, misconfigured CORS headers.

Implementation: Results

Average time from PR merge to staging deployment: 12 minutes. Zero critical CVEs reached production in 6 months. Reduced manual security review time by 80%.

Challenges, Failures and Corrections

This portfolio record does not invent deployment failures, client incidents, or corrective actions that are not supported by the published project evidence. Where operational details are confidential or were not captured for public release, the case study documents the design boundary and lesson instead of presenting an unsupported narrative.

Security, Compliance and Risk

The implementation is described with least privilege, traceability, controlled configuration, and evidence boundaries in mind. Where the project supports a regulated environment, these are technical safeguards and audit-readiness contributions, not a claim that an application or product is independently certified.

Testing, Validation and Evidence

The evidence published for this project is the documented implementation, its stated architecture and controls, and the portfolio record. Average time from PR merge to staging deployment: 12 minutes. Zero critical CVEs reached production in 6 months. Reduced manual security review time by 80%. Claims are limited to the implementation details and outcomes documented in this case study.

Results and Evidence

Average time from PR merge to staging deployment: 12 minutes. Zero critical CVEs reached production in 6 months. Reduced manual security review time by 80%.

What I Learned

This project reinforced that devops work is not a technology checklist. The durable value comes from making boundaries, trade-offs, ownership, and evidence clear enough for another engineer or stakeholder to review and operate the system responsibly.

What I Would Improve Next

• Expand automated validation around the most important workflow and control boundaries.
• Add or deepen operational evidence, such as dashboards, test artefacts, or an architecture diagram where it is safe to publish one.
• Review the design against the next expected scale, reliability, and governance requirement before extending the system.

Final Takeaway

This devops and platform engineering case study addresses a defined technical problem through GitHub Actions, Trivy, Snyk. It demonstrates my ability to turn requirements into an explainable design, implement the important controls, and document outcomes and limitations without overstating what the evidence proves.