---
title: "devops-arch"
---

import DynamicNotebook from '@/components/DynamicNotebook';
import nb from './devops-arch/devops-arch.ipynb';

<DynamicNotebook ipynb={nb} />


1) What you already have (and what I'm keeping)
From your diagram, the core path is:

Work mgmt: Azure DevOps Boards (and likely repos linking to stories)
Dev: IDEs + GitHub Copilot
PR flow: PR request → approval gates → merge
CI: GitHub Actions (build + unit tests)
Security: TruffleHog + Snyk (security scans)
Build/Release: GitHub Actions → artifacts
Artifacts: JFrog Artifactory
Notify: MS Teams
Deploy environments with SNOW approvals: Dev → QA → UAT → Prod
Testing: BrowserStack (smoke/regression), Selenium/Playwright, manual UAT, JMeter perf
Resilience: Gremlin
Change mgmt: ServiceNow
Observability: Datadog (incl. synthetic tests shown)
That's a solid baseline.

2) Enterprise enhancements I'm adding (still aligned to your diagram)
These are the upgrades that make the same pipeline workable across hundreds of teams and regulated products:

A) Supply-chain security (build provenance + SBOM + signing)
Add to CI/CD:

SBOM generation (CycloneDX or SPDX)
Artifact signing (Sigstore/cosign or an enterprise signing service)
Provenance/attestations (SLSA-style)
Why it matters: auditors (and internal security) want to prove what shipped, from what source, built by what pipeline, and what dependencies it contains.

B) Policy-as-code guardrails (consistent gates everywhere)
Add a central gate that evaluates:

Snyk severity thresholds (e.g., no Critical/High unless exception)
license allow/deny rules
mandatory reviewers (CODEOWNERS), required checks, branch protection
environment deployment rules (e.g., UAT/Prod must have SNOW change)
Implementation options (pick what your org supports):

GitHub branch rulesets + required checks
OPA/Conftest for policy checks in pipeline
A "shared pipeline template" repo (platform engineering)
C) Secrets + identity hardening (no long-lived credentials in CI)
Add:

OIDC federation from GitHub Actions to AWS (short-lived credentials)
Secrets stored in AWS Secrets Manager / HashiCorp Vault / Azure Key Vault (whichever enterprise standard you have)
Secret scanning stays (TruffleHog), but prevention improves by removing static secrets entirely.
D) Environment isolation (multi-account / multi-VPC is typical in large enterprises)
Your Dev → QA → UAT → Prod approvals are good; enterprise usually adds:

Separate AWS accounts per environment (and often per product domain)
Separate KMS keys, secret stores, and network boundaries
IaC "drift detection" + least privilege deploy roles
E) Automated evidence into ServiceNow (reduce manual change effort)
Instead of a human attaching screenshots:

pipeline automatically pushes evidence: scan results, test results, SBOM link, approval chain, deployment ID, rollback plan
"standard change" path for low-risk changes; "normal change" for high-risk
F) Progressive delivery + automatic rollback (reduce blast radius)
Add:

feature flags (LaunchDarkly or equivalent)
canary or blue/green (even if you keep the same environments)
Datadog SLO-based post-deploy verification, triggering rollback if needed
3) Updated "Tailored to your stack" diagram (Mermaid)
You can paste this into docs/wiki that support Mermaid.