Your First AWS CI/CD Pipeline: A CodePipeline Walkthrough for 2026

The Deploy Script Nobody Trusts

At a lot of companies, the deploy process before DevOps gets involved looks like this: someone SSHes into a production box, pulls the latest code, restarts a service, and watches the logs for a minute to make sure nothing broke. It works, until the one time it doesn't. A config file gets missed, or the person who normally handles it is on vacation and the backup forgets a step. That's the actual problem AWS's CI/CD services solve, not "innovation," just removing a fragile manual process that currently depends on one person's memory.

CodePipeline, CodeBuild, and CodeDeploy are AWS's answer, and building a first real pipeline with them is one of the more concrete, immediately useful things a DevOps engineer does in year one.

What Each Piece Actually Does

CodePipeline itself doesn't build or deploy anything. It's the orchestrator: it watches a source, usually CodeCommit, GitHub, or S3, and when something changes, it moves an artifact through a defined sequence of stages, waiting for each one to succeed before starting the next. CodeBuild is where compiling, testing, and packaging happens; it runs your buildspec.yml in a managed container and hands back an artifact. CodeDeploy takes that artifact and actually puts it on target infrastructure, whether that's EC2 instances, an ECS service, or a Lambda function.

The buildspec.yml file is worth understanding before writing one from scratch, since it's not just a script. It defines phases: install, where the container pulls in the right runtime version and dependencies; pre_build, where you log in to a container registry or install test-only packages; build, where the actual compile and test suite run; and post_build, where the finished artifact gets pushed somewhere CodeDeploy can find it. Skipping straight to a single build phase without a proper pre_build step is a common early mistake, and it usually surfaces the first time a dependency needs credentials to fetch.

The order matters. Teams that skip straight from build to deploy without a manual approval gate, or without CloudWatch alarms wired up to that deploy stage, usually add both back in right after the first bad release reaches customers. It's a lot cheaper to configure upfront than to retrofit after an incident review.

Rolling, Blue/Green, or Canary

CodeDeploy doesn't just push new code and hope. It supports a few genuinely different deployment strategies, and picking the wrong one for a given workload is a common early mistake.

For anything customer-facing, blue/green is the more defensible default, not rolling. It costs a bit more in idle infrastructure during the cutover window, but a broken deployment never touches live traffic in the first place, and rollback is just pointing the load balancer back at the old environment. Rolling deployments are fine for internal tools and batch jobs, where a few minutes of degraded instances doesn't matter to anyone outside the team.

Infrastructure as Code, Underneath All of It

None of this holds together without infrastructure defined as code rather than clicked together in the console. The course's own syllabus sequences CloudFormation and SAM before CDK and Terraform, and that ordering isn't arbitrary. Most teams still run CloudFormation under the hood even when CDK is what a developer actually writes, since CDK compiles down to CloudFormation templates anyway. Terraform earns its place for teams already multi-cloud, but for an AWS-only shop, there's rarely a strong reason to reach past CloudFormation and CDK just for variety.

Where This Actually Pays

That certification exam leans hard on exactly this material. SDLC automation, monitoring, incident response, and resilient architecture design are four of its six domains, not abstract theory questions. Someone who has actually wired a pipeline together, watched a bad deploy roll back, and debugged a failed CodeBuild stage walks into that exam with real reference points instead of memorized service names. The certification alone doesn't guarantee the higher end of that salary range, employers still weight real project experience heavily, but it's a credible signal that shortens a lot of first-round interview conversations.

Building One Yourself

Reading through pipeline stages isn't the same as watching one fail on a real AWS account and figuring out why. SkyTrainings' AWS DevOps course works through CodeCommit, CodeBuild, CodeDeploy, and CodePipeline as connected projects rather than isolated lecture topics, alongside the CloudFormation and container work above.

Explore the AWS DevOps course