Developer Tools
AWS CodeDeploy
AWS CodeDeploy automates application revisions to EC2 or on-premises instances, Lambda functions, and Amazon ECS services using in-place or blue/green deployment strategies, lifecycle hooks, health evaluation, alarms, and rollback.
Explore pricing models, common use cases, infrastructure support, and the AWS services that commonly work with AWS CodeDeploy.
AWS CodeDeploy pricing and cost programs
Pricing model: No charge for deployments to AWS compute; on-premises usage
- On-Demand
- Service-specific
- Reserved Instances or reserved capacity
- Not applicable
- Savings Plans
- Not applicable
- Spot
- Not applicable
Billing dimensions: On-premises instance deployments · Underlying compute · Related pipeline services
Programs and modes: EC2 and Auto Scaling deployments · Lambda deployments · ECS deployments · On-premises deployments
Deployments to supported AWS compute have no additional CodeDeploy fee; on-premises deployments are billed.
Free Tier: Not applicable — verify current offers
Pricing reviewed 2026-07-25. Reviewed against the linked official AWS pricing page. Recheck regional rates and program terms before purchase.
Official AWS sources reviewed 2026-07-21.
Why implement AWS CodeDeploy?
- Coordinates repeatable deployments across fleets and serverless or container traffic-shifting targets without custom deployment controllers.
- Supports EC2 in-place and blue/green deployments plus Lambda and ECS canary, linear, or all-at-once traffic shifting.
- Integrates lifecycle hooks, load balancers, Auto Scaling, CloudWatch alarms, notifications, deployment history, and automatic rollback.
How to implement AWS CodeDeploy
- Choose compute platform and failure-tolerant strategy, package an immutable revision and AppSpec with idempotent hooks, define service and instance roles, target groups or instance tags, alarms, and stop conditions.
- Create deployment groups per environment, test hooks and permissions on a canary, preserve capacity during blue/green replacement, and shift traffic only after functional and health checks pass.
- Observe hook logs, target health, alarms, deployment events, and business metrics; stop or roll back on regression, remembering that rollback deploys a previous revision and does not reverse arbitrary script side effects.
AWS CodeDeploy best practices
- Make every lifecycle script idempotent and forward-compatible, externalize durable state, and test upgrades, repeated hooks, partial failure, instance replacement, and rollback.
- Use immutable versioned bundles, least-privilege roles, encrypted sources, signed or attested artifacts, and restrict who can update deployment groups or ignore alarm failures.
- Prefer canary or linear traffic shifting for risky changes, monitor application-level success metrics, and size blue/green capacity and termination waits to preserve availability and control cost.
AWS CodeDeploy use cases and server impact
- EC2 application fleet releases
- Lambda alias traffic shifting
- ECS blue/green service deployments
Replaces deployment coordinators and custom traffic-shifting scripts, while artifact quality, lifecycle hooks, capacity, application health signals, data migrations, and rollback safety remain yours.
Official implementation resources
Commonly paired AWS services
- AWS CodePipeline — CI/CD pipelines
- AWS CodeBuild — Build & test code
- Amazon Elastic Compute Cloud — Resizable virtual servers
- Amazon EC2 Auto Scaling — Scale EC2 capacity automatically
- Amazon Elastic Container Service — Container orchestration
- AWS Lambda — Run code without servers
- Elastic Load Balancing — Load balancing
- Amazon CloudWatch — Metrics & logs