Your team is still deploying manually, or the pipeline is so fragile that releases feel risky. Environments drift between dev and production. Developers wait hours for builds. Every deploy is a Friday-afternoon anxiety event.
The right CI/CD setup lets you deploy multiple times per day with confidence, catching issues before production and giving developers autonomy to ship their own code. I help .NET and Node.js teams get there without a six-month "DevOps transformation" project.
What this looks like in practice
CI/CD that developers actually trust
Automated build, test, and deployment. Blue/green and canary deployments for zero-downtime releases. Automatic rollback on error rate spikes so you don't wait for humans to notice problems at 2am.
Infrastructure as code with CDK
Version-controlled infrastructure in C# or TypeScript. Eliminate environment drift, enable reproducible deployments across accounts, and let your whole team read the infrastructure definition.
Observability that answers questions
CloudWatch dashboards, centralized logging, X-Ray distributed tracing, and alerts on anomalies (not just thresholds). Know what's happening before users tell you.
Security baked into the pipeline
SAST, container scanning, IaC security checks, and secrets management. Catch vulnerabilities before they reach production, not in a quarterly audit.
How mature is your pipeline?
Uncheck the ones you've already addressed.
Patterns that consistently work
Trunk-based development
Short-lived feature branches merged frequently. Long-lived branches create merge hell and deployment bottlenecks.
Same artifact, promoted through environments
Build once, deploy to dev → staging → production. Never rebuild between environments.
Infrastructure and app in the same repo
CDK or CloudFormation deployed through the same pipeline as application code. One PR, one deploy.
Feature flags over feature branches
Deploy incomplete features behind flags. Decouple deployment from release. Ship code without shipping behavior.
CodePipeline vs GitHub Actions?
Both work. CodePipeline integrates tightly with AWS and keeps everything in your account (compliance teams like this). GitHub Actions has a larger ecosystem and is simpler if you're already on GitHub.
For most teams, I recommend GitHub Actions for build/test and CDK Pipelines for AWS deployments. Best of both worlds.
How an engagement works
Start with your current workflow
Not a theoretical ideal state. What's painful today? Where are the manual steps? What breaks when you try to deploy on a Tuesday?
Get one pipeline working well
Pick the most impactful service, build the full pipeline (build, test, deploy, rollback), prove it works. Teams that try to boil the ocean end up with half-finished automation nobody trusts.
Expand and standardize
Apply the patterns to other services. Reusable pipeline constructs, shared build configurations, consistent deployment strategies across the team.
Hand off with documentation
Your team can maintain and extend the pipelines after I'm gone. I'm not trying to create dependency.
Frequently Asked Questions
What's the difference between CloudFormation and CDK?
CloudFormation is AWS's native infrastructure-as-code service using YAML or JSON templates. CDK lets you define infrastructure using TypeScript, Python, C#, or other languages, then synthesizes to CloudFormation. CDK is more expressive for complex logic and reusable constructs, while CloudFormation templates are more portable. For .NET teams, CDK in C# often feels more natural.
How do I implement blue/green deployments on AWS?
For Lambda, use aliases with weighted traffic shifting. CodeDeploy can automate gradual rollouts with automatic rollback on errors. For ECS, use CodeDeploy with blue/green deployment configuration. For EC2/ASG, create a new Auto Scaling group, shift traffic at the load balancer, then terminate the old group. The key is having health checks that catch problems before full traffic shift.
How do I handle secrets in my CI/CD pipeline?
Never store secrets in your repository or pipeline configuration. Use AWS Secrets Manager or Parameter Store (SecureString) for runtime secrets, and reference them by ARN in your deployment. For build-time secrets, use your CI platform's secret management. Rotate secrets regularly and audit access via CloudTrail.
What should I monitor in my AWS environment?
Start with the basics: error rates, latency percentiles (p50, p95, p99), and resource utilization. For Lambda, track cold starts, duration, and concurrent executions. For APIs, monitor 4xx and 5xx rates by endpoint. Set up CloudWatch alarms for anomalies, not just thresholds. Use X-Ray for distributed tracing to find bottlenecks across services.