AWS Code Pipeline — Technology Profile & Architecture

Core Information

#core_information

Name, description, vendor website, logo, technology type and tags.

Overview & Role

AWS CI/CD refers to the suite of services offered by Amazon Web Services (AWS) that enable continuous integration and continuous delivery practices. These services, including AWS CodePipeline, CodeBuild, CodeDeploy, and CodeCommit, help developers automate the software release process, from code commit to deployment, ensuring faster and more reliable software delivery.

Domain Classification & Tags

DevOps

Performance Profile

#performance_profile

Typical read and write throughput, payload size and processing latency.

Read Performance Profile

Throughput: Not directly applicable as AWS CI/CD is a set of services, not a data store with read throughput.

Payload Size: Not directly applicable.

Processing Latency: Not directly applicable.

Write Performance Profile

Throughput: Highly variable, depends on the specific AWS CI/CD services used (CodeCommit, CodeBuild, CodeDeploy, CodePipeline) and the complexity/size of the codebase, build artifacts, and deployment targets. For CodeBuild, typical build times can range from seconds for small projects to several minutes for large, complex builds. CodePipeline execution time is the sum of its stages.

Payload Size: Highly variable. For CodeCommit, repository size can range from MBs to GBs. For CodeBuild, source code size and generated artifacts can be MBs to GBs. For CodeDeploy, application revision size can be MBs to GBs.

Processing Latency: Highly variable. CodeCommit push latency is typically low (milliseconds to seconds) depending on network and repository size. CodeBuild start-up latency can be tens of seconds. CodeDeploy deployment latency depends on the application type and deployment strategy, ranging from seconds to minutes.

Architecture Diagram

#architecture_diagram

Reference diagram of the technology's internal architecture.

Component Architecture & Topology

open_in_new Standalone Tab

Features

#features

Catalogued product capabilities and what each one does.

Empirical data for features is currently being compiled in the global catalog.

Typical Use Cases

#typical_use_cases

Scenarios the technology is commonly chosen for.

Empirical data for typical use cases is currently being compiled in the global catalog.

Known Customers

#known_customers

Publicly referenced organisations using the technology.

Empirical data for known customers is currently being compiled in the global catalog.

Known Integrations

#known_integrations

Other products and services it is documented to work with.

Empirical data for known integrations is currently being compiled in the global catalog.

Connectors

#connectors

Directional data connections to other technologies, with direction and maturity.

Empirical data for connectors is currently being compiled in the global catalog.

Reference Architectures

#reference_architectures

Published architectures where the technology is used or mentioned.

No published reference architecture blueprints currently link to AWS Code Pipeline.

Security Features

#security_features

Built-in security and access-control capabilities.

Empirical data for security features is currently being compiled in the global catalog.

Known Issues

#known_issues

Documented limitations, defects and operational pitfalls.

Empirical data for known issues is currently being compiled in the global catalog.

Guidelines

#guidelines

Recommended practices for adopting and operating the technology.

Empirical data for guidelines is currently being compiled in the global catalog.

Standards & Compliance

#standards_and_compliance

Standards, certifications and control requirements it maps to.

Empirical data for standards & compliance is currently being compiled in the global catalog.

Sources

#sources

Documentation and research references behind the recorded information.

Empirical data for sources is currently being compiled in the global catalog.

Expert Validation

#expert_validation

Whether domain experts reviewed and confirmed the content.

Empirical data for expert validation is currently being compiled in the global catalog.