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Capstone: End-to-End Agent Pipeline

From code commit to running agent. That's the entire journey this capstone walks you through.

You've built your FastAPI agent in Part 6. You've containerized it with Docker (Lesson 49). You've deployed it with Kubernetes (Chapter 50). You've managed it with Helm (Chapter 51). Now you'll automate the entire path: push code, trigger tests, build a container, push to a registry, detect the new image in Git, and sync it automatically to your cluster.

This capstone is specification-first. Before writing a single YAML file, you'll write the specification that defines what your pipeline does, when it triggers, and how it validates. Then you'll implement it using GitHub Actions (CI) and ArgoCD (CD). Finally, you'll demonstrate the complete flow: code push → deployment → validation → rollback.

This lesson produces a fully automated, auditable pipeline for your agent. Every deployment is version-controlled, every rollback is a git revert, and every step is automated.

Pipeline Specification

Intent

Deploy your FastAPI agent from code push to accessible endpoint with full automation:

  • Trigger: Every push to main branch automatically starts the pipeline
  • CI Stage: Run tests, build container image, push to registry with SHA tag
  • CD Stage: ArgoCD detects new image, syncs automatically, health checks confirm service is ready
  • Validation: Agent endpoint responds to requests within 30 seconds of deployment
  • Rollback: Git revert triggers ArgoCD to deploy previous version

Success Criteria

  • ✅ Push to main triggers GitHub Actions within 30 seconds
  • ✅ Tests pass with minimum 80% coverage before image build
  • ✅ Container image pushed to registry in under 10 minutes
  • ✅ ArgoCD detects new image and syncs within 3 minutes of registry push
  • ✅ Agent endpoint returns HTTP 200 after deployment
  • ✅ Rollback via git revert restores previous version within 5 minutes
  • ✅ Complete flow logs are visible in GitHub Actions UI and ArgoCD UI

Components

ComponentPurposeOwnership
.github/workflows/ci.yamlBuild, test, push imageGitHub Actions
gitops-repo/fastapi-agent/Git source of truthGit repository
gitops-repo/kustomization.yamlKustomize configurationGit repository
argocd/fastapi-agent.yamlArgoCD ApplicationKubernetes cluster
Image registry (GHCR/DockerHub)Container storageExternal service

Non-Goals

  • Multi-environment deployments (dev/staging/prod) — Lesson 10 covers this with ApplicationSets
  • Progressive delivery (canary/blue-green) — Lesson 13 covers this with Argo Rollouts
  • Secrets management — Lesson 14 covers sealed secrets and external secrets
  • Multi-cluster sync — Lesson 15 covers hub-spoke patterns

Part 1: GitHub Actions CI Workflow

Your GitHub Actions workflow automates the CI stage: trigger → test → build → push.

The flow:

Push to main

[GitHub Actions triggered]

[Run pytest: coverage >80%?]
↓ NO → Pipeline fails
↓ YES
[Build Docker image with SHA tag]

[Push to GHCR]

[Update image reference in Git]

[Done — ArgoCD watches Git and syncs]

GitHub Actions Workflow File

Create .github/workflows/ci.yaml:

name: CI - Build and Push Agent

on:
push:
branches:
- main
paths:
- 'app/**'
- 'tests/**'
- 'pyproject.toml'
- 'poetry.lock'
- '.github/workflows/ci.yaml'
pull_request:
branches:
- main

env:
REGISTRY: ghcr.io
IMAGE_NAME: ${{ github.repository }}/fastapi-agent

jobs:
test:
name: Run Tests
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v4

- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: "3.11"

- name: Install dependencies
run: |
pip install poetry
poetry install

- name: Run pytest with coverage
run: |
poetry run pytest tests/ \
--cov=app \
--cov-report=xml \
--cov-report=term \
--cov-fail-under=80

- name: Upload coverage to Codecov
uses: codecov/codecov-action@v3
with:
files: ./coverage.xml
flags: unittests

build-and-push:
name: Build and Push Image
needs: test
runs-on: ubuntu-latest
permissions:
contents: read
packages: write

steps:
- name: Checkout code
uses: actions/checkout@v4

- name: Set up QEMU (multi-arch builds)
uses: docker/setup-qemu-action@v3

- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3

- name: Log in to Container Registry
uses: docker/login-action@v3
with:
registry: ${{ env.REGISTRY }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}

- name: Extract metadata
id: meta
uses: docker/metadata-action@v5
with:
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
tags: |
type=sha,prefix={{branch}}-
type=ref,event=branch
type=semver,pattern={{version}}
type=semver,pattern={{major}}.{{minor}}

- name: Build and push image
uses: docker/build-push-action@v5
with:
context: .
platforms: linux/amd64,linux/arm64
push: true
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
cache-from: type=gha
cache-to: type=gha,mode=max

- name: Output image digest
run: echo "Image pushed with digest ${{ steps.build.outputs.digest }}"

update-gitops:
name: Update GitOps Repository
needs: build-and-push
runs-on: ubuntu-latest
steps:
- name: Checkout main repo
uses: actions/checkout@v4

- name: Checkout GitOps repo
uses: actions/checkout@v4
with:
repository: ${{ github.repository_owner }}/gitops-repo
path: gitops-repo
token: ${{ secrets.GITOPS_REPO_TOKEN }}

- name: Update image tag in kustomization
run: |
cd gitops-repo/fastapi-agent

# Extract new image SHA
IMAGE_SHA=${{ github.sha }}

# Update kustomization.yaml with new image
kustomize edit set image fastapi-agent=${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:main-${IMAGE_SHA:0:7}

cat kustomization.yaml

- name: Commit and push update
run: |
cd gitops-repo

git config user.name "github-actions[bot]"
git config user.email "github-actions[bot]@users.noreply.github.com"

git add fastapi-agent/kustomization.yaml
git commit -m "chore: update fastapi-agent image to ${{ github.sha }}"
git push origin main

- name: Create deployment notification
run: |
echo "Deployment started"
echo "Image: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:main-${{ github.sha }}"
echo "GitOps commit: $(cd gitops-repo && git rev-parse HEAD)"

Output when successful:

✓ Test stage passed (coverage: 92%)
✓ Image built: ghcr.io/org/repo/fastapi-agent:main-a1b2c3d
✓ Image pushed to GHCR
✓ GitOps repository updated with new image tag
✓ ArgoCD watching gitops-repo detects change
→ ArgoCD begins syncing new image

What This Workflow Does

  1. Trigger: Every push to main (and PRs for safety checks)
  2. Test Job: Runs pytest, enforces 80% coverage, uploads to Codecov
  3. Build Job: Waits for test success, builds multi-platform image, caches layers
  4. Push Job: Authenticates to GHCR with GitHub token, pushes image with SHA tag
  5. Update Job: Checks out GitOps repo, updates image reference in kustomization.yaml, commits and pushes

The entire flow is auditable: every commit links to a workflow run, which links to a container image, which links to a GitOps commit.


Part 2: GitOps Repository Structure

ArgoCD watches a Git repository for your desired state. The structure tells ArgoCD what to deploy.

Create a separate repository called gitops-repo (not the code repo):

gitops-repo/
├── README.md
├── fastapi-agent/
│ ├── kustomization.yaml ← Updates here from CI
│ ├── base/
│ │ ├── deployment.yaml ← K8s Deployment
│ │ ├── service.yaml ← K8s Service
│ │ └── kustomization.yaml ← Base configuration
│ └── overlays/
│ └── production/
│ ├── kustomization.yaml
│ └── patches/
│ └── replicas.yaml
├── argocd/
│ └── applications/
│ └── fastapi-agent.yaml ← ArgoCD watches this
└── helmcharts/
└── [future: helm-based deployments]

Kustomization Configuration

File: gitops-repo/fastapi-agent/base/kustomization.yaml

apiVersion: kustomize.config.k8s.io/v1beta1
kind: Kustomization

namespace: agents

resources:
- deployment.yaml
- service.yaml

commonLabels:
app: fastapi-agent
part: part-6
managed-by: argocd

images:
- name: fastapi-agent
newName: ghcr.io/org/repo/fastapi-agent
newTag: main-a1b2c3d # ← CI updates this

File: gitops-repo/fastapi-agent/base/deployment.yaml

apiVersion: apps/v1
kind: Deployment
metadata:
name: fastapi-agent
labels:
app: fastapi-agent
spec:
replicas: 2
strategy:
type: RollingUpdate
rollingUpdate:
maxSurge: 1
maxUnavailable: 0
selector:
matchLabels:
app: fastapi-agent
template:
metadata:
labels:
app: fastapi-agent
annotations:
prometheus.io/scrape: "true"
prometheus.io/port: "8000"
prometheus.io/path: "/metrics"
spec:
serviceAccountName: fastapi-agent
containers:
- name: agent
image: fastapi-agent:latest # ← Kustomize overwrites this
imagePullPolicy: IfNotPresent
ports:
- name: http
containerPort: 8000
protocol: TCP
env:
- name: ENVIRONMENT
value: "production"
livenessProbe:
httpGet:
path: /health
port: 8000
initialDelaySeconds: 5
periodSeconds: 10
failureThreshold: 3
readinessProbe:
httpGet:
path: /ready
port: 8000
initialDelaySeconds: 3
periodSeconds: 5
failureThreshold: 2
resources:
requests:
memory: "256Mi"
cpu: "250m"
limits:
memory: "512Mi"
cpu: "500m"
affinity:
podAntiAffinity:
preferredDuringSchedulingIgnoredDuringExecution:
- weight: 100
podAffinityTerm:
labelSelector:
matchExpressions:
- key: app
operator: In
values:
- fastapi-agent
topologyKey: kubernetes.io/hostname

File: gitops-repo/fastapi-agent/base/service.yaml

apiVersion: v1
kind: Service
metadata:
name: fastapi-agent
labels:
app: fastapi-agent
spec:
type: ClusterIP
ports:
- port: 80
targetPort: http
protocol: TCP
name: http
selector:
app: fastapi-agent

Output when kustomize applies this:

namespace: agents (created if not exists)
Deployment fastapi-agent (2 replicas)
- Image: ghcr.io/org/repo/fastapi-agent:main-a1b2c3d
- Health checks enabled
- Resource requests: 256Mi RAM, 250m CPU
Service fastapi-agent (ClusterIP on port 80)

Part 3: ArgoCD Application

ArgoCD watches the GitOps repository and syncs changes to your cluster.

File: argocd/applications/fastapi-agent.yaml

apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
name: fastapi-agent
namespace: argocd
# Finalizers ensure proper cleanup on deletion
finalizers:
- resources-finalizer.argocd.argoproj.io
spec:
project: default

# Where to deploy FROM (the Git repo)
source:
repoURL: https://github.com/org/gitops-repo
targetRevision: main
path: fastapi-agent/base

# WHERE to deploy TO (your cluster)
destination:
server: https://kubernetes.default.svc
namespace: agents

# HOW to sync
syncPolicy:
# Auto-sync on Git changes (required for CI → CD integration)
automated:
prune: true # Delete K8s resources if removed from Git
selfHeal: true # Resync if cluster diverges from Git
allowEmpty: false # Prevent accidental deletion of all resources

# Sync options
syncOptions:
- CreateNamespace=true # Create namespace if missing
- RespectIgnoreDifferences=true

# Wait for resources to reach healthy state
retry:
limit: 5
backoff:
duration: 5s
factor: 2
maxDuration: 3m

# Health assessment
ignoreDifferences:
- group: apps
kind: Deployment
jsonPointers:
# Ignore timestamp fields that change on every sync
- /spec/template/metadata/annotations/deployment.kubernetes.io/revision

# Notifications (optional: requires Slack/webhook setup from Lesson 12)
info:
- name: "GitHub"
value: "https://github.com/org/repo"
- name: "Slack"
value: "#deployments"

Apply this to your cluster:

kubectl apply -f argocd/applications/fastapi-agent.yaml

Output:

application.argoproj.io/fastapi-agent created

Verify with:
argocd app get fastapi-agent

Name: fastapi-agent
Namespace: argocd
Project: default
Server: https://kubernetes.default.svc
Namespace: agents
Repo: https://github.com/org/gitops-repo
Target Branch: main
Path: fastapi-agent/base
Sync Status: Synced
Health Status: Healthy

Part 4: Image Update Automation

When CI pushes a new image to the registry, how does ArgoCD know?

The answer: The CI workflow updates kustomization.yaml in the GitOps repo. ArgoCD watches Git. When Git changes, ArgoCD syncs.

Kustomize Image Updater

The update-gitops job in your CI workflow updates the image tag:

# In .github/workflows/ci.yaml
update-gitops:
name: Update GitOps Repository
needs: build-and-push
runs-on: ubuntu-latest
steps:
- name: Checkout GitOps repo
uses: actions/checkout@v4
with:
repository: ${{ github.repository_owner }}/gitops-repo
path: gitops-repo
token: ${{ secrets.GITOPS_REPO_TOKEN }}

- name: Update image tag
run: |
cd gitops-repo/fastapi-agent
kustomize edit set image fastapi-agent=ghcr.io/org/repo/fastapi-agent:main-${GITHUB_SHA:0:7}

- name: Commit and push
run: |
cd gitops-repo
git config user.name "github-actions[bot]"
git config user.email "github-actions[bot]@users.noreply.github.com"
git add fastapi-agent/kustomization.yaml
git commit -m "chore: update image to ${{ github.sha }}"
git push origin main

What kustomize edit does:

kustomize edit set image fastapi-agent=ghcr.io/org/repo/fastapi-agent:main-a1b2c3d

Output: fastapi-agent/base/kustomization.yaml now contains:

images:
- name: fastapi-agent
newName: ghcr.io/org/repo/fastapi-agent
newTag: main-a1b2c3d

ArgoCD sees this change in Git, pulls the new image reference, and syncs.

Alternative: Helm Values Update

If using Helm instead of Kustomize:

update-gitops:
steps:
- name: Update Helm values
run: |
cd gitops-repo/fastapi-agent

# Update values.yaml
sed -i "s/tag:.*/tag: main-${GITHUB_SHA:0:7}/" values.yaml

cat values.yaml

This updates values.yaml:

image:
repository: ghcr.io/org/repo/fastapi-agent
tag: main-a1b2c3d # ← Updated by CI
pullPolicy: IfNotPresent

Part 5: End-to-End Validation

After deployment, validate that your pipeline worked.

Step 1: Trigger the Pipeline

Push code to main:

cd your-agent-repo
git add app/main.py
git commit -m "feat: add new endpoint"
git push origin main

Expected output: GitHub Actions workflow starts automatically (check Actions tab in GitHub).

Step 2: Monitor GitHub Actions

In your GitHub repository → Actions tab:

✓ CI - Build and Push Agent [00:02 started]
├─ test (in progress)
│ ├─ Checkout code ✓
│ ├─ Set up Python ✓
│ ├─ Install dependencies ✓
│ └─ Run pytest (3/5 tests passing...)
├─ build-and-push (waiting for test)
└─ update-gitops (waiting for build-and-push)

Wait for all three jobs to complete. Total time: 8-12 minutes.

Output when complete:

✓ test (2:34 elapsed)
✓ build-and-push (4:12 elapsed)
✓ update-gitops (1:45 elapsed)

Summary:
Test coverage: 92%
Image: ghcr.io/org/repo/fastapi-agent:main-a1b2c3d
GitOps commit: 3f2a1c0 "chore: update image to a1b2c3d"

Step 3: Verify Image in Registry

# List images in GHCR
curl -H "Authorization: Bearer $GITHUB_TOKEN" \
https://ghcr.io/v2/org/repo/fastapi-agent/tags/list

# Output:
# {
# "name": "org/repo/fastapi-agent",
# "tags": ["main-a1b2c3d", "main-9z8y7x6"]
# }

Step 4: Verify GitOps Repository Updated

cd gitops-repo
git log --oneline | head -5

# Output:
# 3f2a1c0 chore: update image to a1b2c3d
# 8e7d6c5 Initial commit

Check the image tag in kustomization:

grep -A 3 "^images:" fastapi-agent/base/kustomization.yaml

# Output:
# images:
# - name: fastapi-agent
# newName: ghcr.io/org/repo/fastapi-agent
# newTag: main-a1b2c3d

Step 5: Verify ArgoCD Synced

# Get ArgoCD app status
argocd app get fastapi-agent

# Output:
Name: fastapi-agent
Project: default
Repo: https://github.com/org/gitops-repo
Branch: main
Path: fastapi-agent/base
Sync Status: Synced ← Git and cluster match
Health Status: Healthy ← All pods running

Step 6: Verify Agent is Running

Get the Service IP:

kubectl get svc fastapi-agent -n agents

# Output:
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
fastapi-agent ClusterIP 10.98.123.45 <none> 80/TCP 2m

Test the agent endpoint (port-forward or use external IP):

kubectl port-forward -n agents svc/fastapi-agent 8000:80 &

curl -s http://localhost:8000/health | jq .

# Output:
# {
# "status": "healthy",
# "version": "1.0.0",
# "timestamp": "2025-12-23T14:32:10Z"
# }

Test an agent endpoint:

curl -s -X POST http://localhost:8000/tasks \
-H "Content-Type: application/json" \
-d '{"title": "Test task", "description": "Validate pipeline"}' | jq .

# Output:
# {
# "id": 1,
# "title": "Test task",
# "description": "Validate pipeline",
# "status": "created",
# "created_at": "2025-12-23T14:32:15Z"
# }

Validation Checklist

  • ✅ GitHub Actions workflow completed with all three jobs passing
  • ✅ Test coverage ≥ 80%
  • ✅ Container image pushed to registry with correct SHA tag
  • ✅ GitOps repository updated with new image reference
  • ✅ ArgoCD app status shows "Synced" and "Healthy"
  • ✅ All Deployment pods are Running and Ready (2/2 replicas)
  • ✅ Agent endpoint responds with HTTP 200
  • ✅ Health check endpoint returns healthy status
  • ✅ Agent can process requests (create tasks, etc.)

If all checks pass, your complete CI/CD pipeline is working. From code push to running agent: fully automated.


Part 6: Rollback Demonstration

Production issue? A commit introduced a bug? Kubernetes makes rollback trivial: revert the Git commit.

Scenario: Detect an Issue

Your agent is running with the new deployment. You get a bug report:

User: "Agent is timing out on long requests"
Version: main-a1b2c3d (the latest you just deployed)

Step 1: Identify the Problem Commit

cd your-agent-repo
git log --oneline | head -10

# Output:
# a1b2c3d feat: add timeout handling (← this broke things)
# 9z8y7x6 feat: improve response caching
# ...

Step 2: Revert the Commit

# Revert the problematic commit
git revert a1b2c3d --no-edit

# Output:
# [main 2d4e5f6] Revert "feat: add timeout handling"
# 1 file changed, 5 insertions(+), 5 deletions(-)

Step 3: Push the Revert

git push origin main

Expected output: GitHub Actions triggers automatically.

Step 4: Monitor the Rollback

In GitHub Actions:

✓ test - (pytest passes with reverted code)
✓ build-and-push - (new image built with reverted code)
✓ update-gitops - (GitOps repo updated with previous image version)

Image built: ghcr.io/org/repo/fastapi-agent:main-2d4e5f6 (the reverted version)

Step 5: Watch ArgoCD Sync Old Version

# Monitor ArgoCD
argocd app wait fastapi-agent --sync

# Or watch in real-time:
watch -n 2 "argocd app get fastapi-agent | grep -E 'Sync|Health'"

# Output:
# Sync Status: Syncing (ArgoCD detecting Git change)
# Sync Status: Synced (old image deployed)
# Health Status: Progressing
# Health Status: Healthy (pods healthy with reverted code)

Step 6: Verify Rollback Successful

# Check deployment image
kubectl get deployment fastapi-agent -n agents -o yaml | grep image:

# Output:
# image: ghcr.io/org/repo/fastapi-agent:main-2d4e5f6 ← Previous version

# Verify pods restarted with old image
kubectl get pods -n agents -l app=fastapi-agent

# Output:
# NAME READY STATUS RESTARTS AGE
# fastapi-agent-7f8c9d3e2-abc12 1/1 Running 0 45s
# fastapi-agent-7f8c9d3e2-def56 1/1 Running 0 48s

Test the endpoint again:

curl -s http://localhost:8000/health | jq .

# Output should be successful again:
# {
# "status": "healthy",
# "version": "1.0.0",
# "timestamp": "2025-12-23T14:33:45Z"
# }

Timeline of Rollback

14:32:10 - Bug detected in production
14:32:15 - Developer identifies commit: a1b2c3d
14:32:30 - Run: git revert a1b2c3d
14:32:45 - Run: git push origin main
14:33:00 - GitHub Actions triggered (automatically)
14:36:15 - New image built (reverted code)
14:36:30 - ArgoCD detects Git change
14:37:45 - Old image deployed and pods healthy
14:38:00 - Rollback complete, service restored

Total time: 6 minutes from detection to deployed fix

Complete Pipeline Reference

Here's the entire automation flow in one diagram:

┌─────────────────────────────────────────────────────────────┐
│ 1. Developer pushes code to main │
│ git push origin main │
└──────────────────┬──────────────────────────────────────────┘

┌─────────────────────────────────────────────────────────────┐
│ 2. GitHub Actions triggered (within 30 seconds) │
│ Workflow: .github/workflows/ci.yaml │
└──────────────────┬──────────────────────────────────────────┘

┌─────────┴─────────┐
↓ ↓
┌─────────┐ ┌─────────┐
│ TEST │ │ BUILD │
│ Stage │ (runs │ + PUSH │
│ ──── │ first) │ Stage │
│ pytest │ │ ────────│
│ >80% │ │ Docker │
│ │ ──→ │ image │
└─────────┘ │ SHA tag │
↓ │ GHCR │
PASS? YES └────┬────┘
│ ↓
↓ PUSH? SUCCESS?
└──────┬─────────────┤YES
↓ ↓
┌────────────────────────────┐
│ UPDATE GITOPS │
│ ──────────────────── │
│ • Checkout gitops-repo │
│ • kustomize edit set image │
│ • git commit + push │
└─────────┬──────────────────┘

┌────────────────────────────┐
│ GIT UPDATED │
│ fastapi-agent/base/ │
│ kustomization.yaml: │
│ newTag: main-a1b2c3d │
└─────────┬──────────────────┘

┌────────────────────────────┐
│ ARGOCD WATCHES GIT │
│ ──────────────────── │
│ (every 3 seconds checks │
│ if cluster matches Git) │
└─────────┬──────────────────┘

┌────────────────────────────┐
│ CHANGE DETECTED! │
│ New image in kustomization │
└─────────┬──────────────────┘

┌────────────────────────────┐
│ ARGOCD SYNCS │
│ ──────────────────── │
│ kubectl apply -k ... │
│ pulls new image │
│ updates Deployment │
│ rolls pods │
└─────────┬──────────────────┘

┌────────────────────────────┐
│ HEALTH CHECKS │
│ ──────────────────── │
│ Pods start │
│ /ready endpoint → 200? │
│ /health endpoint → 200? │
└─────────┬──────────────────┘

┌────────────────────────────┐
│ DEPLOYMENT COMPLETE │
│ ──────────────────── │
│ Status: Synced + Healthy │
│ Agent responds to requests │
└────────────────────────────┘

TIMELINE: Code push → Deployment: ~8 minutes

Capstone Completion Checklist

Use this checklist to verify you've completed the entire capstone:

GitHub Actions Setup

  • .github/workflows/ci.yaml created with all three jobs
  • ✅ Tests run and enforce 80% coverage minimum
  • ✅ Multi-platform build configured (linux/amd64, linux/arm64)
  • ✅ Image pushed to GHCR with SHA tag
  • ✅ GitOps repository token configured in GitHub Secrets

GitOps Repository

  • ✅ Separate gitops-repo created (not code repo)
  • ✅ Directory structure: fastapi-agent/base/ and fastapi-agent/overlays/
  • kustomization.yaml configures image and namespace
  • deployment.yaml includes health checks and resource limits
  • service.yaml exposes agent on port 80
  • ✅ CI workflow updates image tag on every push

ArgoCD Configuration

  • ✅ ArgoCD Application created at argocd/applications/fastapi-agent.yaml
  • ✅ Application points to GitOps repo (https://github.com/org/gitops-repo)
  • ✅ Auto-sync enabled (prune + selfHeal)
  • ✅ Namespace created automatically (CreateNamespace=true)
  • ✅ Application syncs within 3 minutes of Git update

End-to-End Validation

  • ✅ Pushed code to main, triggered workflow automatically
  • ✅ Tests passed with coverage ≥ 80%
  • ✅ Image built and pushed to GHCR
  • ✅ GitOps repo updated with new image tag
  • ✅ ArgoCD synced (status: Synced + Healthy)
  • ✅ Agent pods running (2/2 Ready)
  • ✅ Agent endpoint responds (HTTP 200)
  • ✅ Health check passes (/health → 200)

Rollback Demonstration

  • ✅ Identified a problem commit
  • ✅ Ran git revert to revert the commit
  • ✅ Pushed revert, triggered workflow automatically
  • ✅ New image built with reverted code
  • ✅ ArgoCD synced old image to cluster
  • ✅ Agent pods restarted with previous version
  • ✅ Verified agent works again
  • ✅ Total rollback time < 10 minutes

Advanced Extensions (Optional)

  • ⭐ Add ApplicationSet for multi-environment deployment (dev/staging/prod)
  • ⭐ Configure Slack notifications (Lesson 12)
  • ⭐ Implement canary/blue-green with Argo Rollouts (Lesson 13)
  • ⭐ Add sealed secrets for database credentials (Lesson 14)
  • ⭐ Scale to multiple clusters with hub-spoke (Lesson 15)

Try With AI

You've built a complete, automated CI/CD pipeline. Now collaborate with Claude to troubleshoot and extend it.

Setup for This Section

You'll need:

  • Your FastAPI agent code in a GitHub repository
  • A working Kubernetes cluster (Minikube, GKE, EKS, etc.)
  • ArgoCD installed with admin access
  • Container registry access (GHCR, Docker Hub, etc.)
  • GitHub repository with Actions enabled

Scenario 1: Pipeline is Stuck

Your situation: You pushed code, GitHub Actions started, but the workflow is hanging on the build step.

Exploration prompt:

"I pushed code 15 minutes ago and GitHub Actions is still building. The log shows:

[+] Building 45.3s (12/25)
=> [internal] load build definition from Dockerfile
=> => transferring dockerfile: 36B
=> [internal] load .dockerignore
=> ...

It seems stuck. What are common reasons Docker builds hang in CI? How do I debug this?"

Ask Claude about:

  • Network issues (registry timeout, DNS problems)
  • Disk space in the runner
  • Memory constraints
  • Large dependency downloads without caching
  • How to add debugging output to your workflow

Refine your question:

  • Build output logging: docker buildx build --progress=plain
  • Timeout settings: timeout: 15m on the step
  • Debug environment variables: BUILDX_BUILDER_OUTPUT_VERBOSE=true

Scenario 2: ArgoCD Not Syncing

Your situation: The GitOps repo has the new image tag, but ArgoCD says "out of sync."

Exploration prompt:

"ArgoCD shows my app is 'OutOfSync' but the kustomization.yaml has the correct image tag:

images:
- name: fastapi-agent
newName: ghcr.io/org/repo/fastapi-agent
newTag: main-a1b2c3d

Why isn't it syncing? The app repo is set to auto-sync. What am I missing?"

Ask Claude about:

  • Is the app watching the right Git branch? (Check targetRevision)
  • Is the path correct? (Check path in Application spec)
  • Are there differing fields? (Use argocd app diff)
  • Is the Git token working? (Check SSH key or HTTPS token)
  • Run: argocd app sync --force to force reconciliation

Refine your question:

  • Diagnose with: argocd app diff fastapi-agent
  • Check Git access: argocd repo add ...
  • Enable debug logging: --loglevel debug

Scenario 3: Image Never Gets Updated

Your situation: CI completes successfully, image is pushed to GHCR, but kustomization.yaml never updates in the GitOps repo.

Exploration prompt:

"My workflow completed:

  • ✅ Tests passed
  • ✅ Image pushed: ghcr.io/org/repo/fastapi-agent:main-a1b2c3d
  • ❌ But GitOps repo kustomization.yaml still has the old tag: main-old

The update-gitops job logs show 'success' but the commit never appeared. What could be wrong?"

Ask Claude about:

  • Is secrets.GITOPS_REPO_TOKEN configured? (Authentication fails silently)
  • Does the token have write access to the GitOps repo?
  • Is the branch protection rule blocking commits?
  • Is the git config correct? (user.name, user.email)
  • How to check GitHub Actions logs for actual error

Refine your question:

  • Add explicit error handling: git push || { echo "Push failed"; exit 1; }
  • Verify token permissions: List allowed actions
  • Test locally: git clone with the token to verify it works
  • Add verbose logging: git config core.logallrefupdates true

Scenario 4: Rollback Didn't Work

Your situation: You reverted a commit and pushed, but ArgoCD is deploying the new image instead of the old one.

Exploration prompt:

"I ran:

git revert a1b2c3d
git push origin main

But ArgoCD is deploying image main-newSHA (the reverted commit) instead of main-oldSHA (the version before the reverted commit).

The kustomization.yaml shows the correct image tag. Why is it deploying the wrong one?"

Ask Claude about:

  • Image cache issues (pullPolicy should be Always, not IfNotPresent)
  • Pod using cached local image instead of pulling new one
  • ArgoCD showing correct image but deployment pulling cached version
  • Using kubectl describe pod -n agents to check actual image

Refine your question:

  • Force image pull: Change to imagePullPolicy: Always
  • Delete old pods: kubectl delete pods -n agents -l app=fastapi-agent
  • Verify image exists in registry: crane ls ghcr.io/org/repo/fastapi-agent
  • Check pull secret if registry is private

Scenario 5: Add Multi-Environment Deployment

Your situation: You want to deploy to dev and prod with different replicas and resources.

Exploration prompt:

"I have a working pipeline deploying to production. Now I need to deploy the same agent to a dev environment with:

  • 1 replica instead of 2
  • Smaller resource limits (128Mi RAM instead of 256Mi)
  • Same code, different configuration

Should I create another Application? Use ApplicationSets? How do I keep them in sync?"

Ask Claude about:

  • ApplicationSet with List generator (one entry per environment)
  • Overlays pattern (base + dev/prod patches)
  • Environment variables for different configs
  • Helm values overrides

Refine your question:

  • ApplicationSet YAML with List generator for dev, prod
  • Kustomize overlays: base/ + overlays/dev/ + overlays/prod/
  • How to parameterize replicas and resources
  • How CI deploys to both environments in sequence