In this reviewed article I present how to connect to AWS CodeCatalyst from AWS Builder ID, taking advantage of the free tier and the initial features that allow you to get projects up and running quickly.
What is AWS CodeCatalyst: AWS CodeCatalyst is a managed service that unifies planning, development, continuous integration CI, continuous delivery CD, and deployment on a single platform designed for teams looking to accelerate the software lifecycle in the cloud.
What is AWS Builder ID: AWS Builder ID is the unified identity for developers and learners within the AWS ecosystem that allows access to tools like CodeCatalyst without relying on the AWS administrative account.
First steps to connect: When entering CodeCatalyst, you can sign in with Builder ID or via SSO. If it is your first time, you will be asked to create a space by providing a name, region, and the destination account where resources will be deployed. You also need to provide a billing account even when using the free tier.
Space configuration: Within the space, linked accounts and team members are managed. From here, permissions, roles, and the necessary approvals are managed so that CodeCatalyst can act on the destination account.
Creating projects from Blueprints: CodeCatalyst offers the option to create projects from predefined Blueprints. When selecting a Blueprint, the involved services, architecture, and required permissions are displayed. You can choose the project name, the repository where the code will be stored, and the account where the solution will be deployed, which makes it easy to integrate external repositories if the team prefers not to host the code exclusively within CodeCatalyst.
Additional requirements: It is common for the destination account to require approving access and adding a role from the account so that deployment actions can run correctly. You also need to confirm the billing account before finalizing the project creation.
Deployment and pipeline: Blueprints include CI CD pipelines that can be run with a simple Run. These pipelines build, test, and deploy the application using IaC when configured, for example with AWS CDK, Terraform, or other compatible tools.
Testing and validation: After running the pipeline, you can validate the API operation, check DynamoDB tables, and review logs and metrics to ensure the application responds correctly in the deployed environment.
History and evolution: AWS introduced CodeCatalyst in preview in December 2022 and reached general availability in April 2023. Since then, it has expanded integrations with external repositories, support for Graviton workflows, and improvements in privacy and Blueprint management.
Recent updates: In later iterations, a universal image for build environments was released, and improvements were introduced in data privacy, role management, and cleanup of obsolete Blueprints, making it easier to manage in organizations with stricter security requirements.
Technical conclusions: CodeCatalyst makes it easy to centralize the development lifecycle in AWS, speeds up the creation of reproducible environments through Blueprints and CI CD, and allows integrating external repositories and IaC tools. It is a good option for teams looking for an integrated DevOps experience without managing all the pieces separately.
About Q2BSTUDIO: At Q2BSTUDIO we are a software development company specialized in custom applications and custom software. We offer comprehensive services in artificial intelligence, cybersecurity, aws and azure cloud services, business intelligence services, AI for businesses, AI agents, and power bi. We help companies design scalable solutions that combine DevOps, automation, and security to accelerate value delivery.
How Q2BSTUDIO can help with CodeCatalyst: We can support integrating CodeCatalyst into existing workflows, designing custom Blueprints, implementing CI CD pipelines with CDK or Terraform, and ensuring access management and billing are correctly configured. We also accompany projects in artificial intelligence and business intelligence to leverage data through Power BI and AI agents adapted to the business.
Practical recommendations: Before going into production, make sure to review roles and permissions in the destination account, configure alerts and monitoring, and set cost limits. Take advantage of the possibility of using external repositories if your team already has GitHub or GitLab, and explore Blueprints as a starting point to accelerate deliveries.
Important keywords: custom applications, custom software, artificial intelligence, cybersecurity, aws and azure cloud services, business intelligence services, AI for businesses, AI agents, power bi.
Thank you for reading this summary about testing AWS CodeCatalyst from AWS Builder ID. If you want support implementing projects, optimizing pipelines, or developing AI and business intelligence solutions, at Q2BSTUDIO we are ready to collaborate.
