Amazon Bedrock AgentCore now runs a serverless agent that scans .NET repositories, produces architecture diagrams, and pushes the results through an AWS CodePipeline. Engineers get continuously refreshed visual documentation without manual effort, and the output is searchable via an Amazon Bedrock Knowledge Base.
Why Automated Architecture Documentation Matters
Manual diagramming is time‑consuming, quickly becomes stale, and creates knowledge silos that hinder onboarding and compliance. By embedding generation into the CI/CD flow, the documentation reflects the exact state of the code at each commit, reducing audit risk and keeping service‑dependency maps accurate for micro‑service environments.
Key Architectural Components
- Amazon Bedrock AgentCore – Executes the autonomous documentation agent in a serverless runtime, handling scaling and lifecycle without dedicated infrastructure.
- AWS CodePipeline – Triggers the agent on pushes to an AWS CodeCommit repository and orchestrates subsequent stages.
- AWS CodeBuild – Provides the build environment where the agent runs, dependencies are installed, and artifacts are prepared.
- Amazon S3 – Stores generated SVG and Mermaid source files, hosts the documentation site, and serves as the vector‑store backend for the Knowledge Base.
- Amazon Bedrock Knowledge Bases – Ingests diagram metadata and source files using the Amazon Titan Text Embeddings model, enabling semantic search and natural‑language queries over the architecture corpus.
Implementation Flow
- Developers commit .NET code to an AWS CodeCommit repository.
- CodePipeline detects the commit and starts a CodeBuild job.
- Within CodeBuild, the AgentCore‑hosted agent parses the code, extracts service definitions, and emits diagrams in SVG and Mermaid formats.
- The generated artifacts are uploaded to a dedicated S3 bucket.
- A post‑build step invokes the Bedrock Knowledge Base API to ingest the new files, indexing them with Titan Text Embeddings for semantic retrieval.
- Documentation is served directly from S3 or queried through the Knowledge Base for on‑demand insight.
Operational and Security Considerations
Because the agent runs in a managed, serverless environment, operational overhead is limited to pipeline configuration and S3 bucket policies. Practitioners should ensure that the bucket storing diagrams enforces least‑privilege access and versioning to protect against accidental overwrite. The Knowledge Base inherits the same S3 permissions, so controlling who can query or update the index is a separate access‑control decision.
Embedding generation relies on the Titan Text Embeddings model; any changes to the model or its parameters could affect search relevance, so monitoring ingestion logs is advisable. Additionally, the CI/CD integration means that any compromised commit could trigger diagram generation, so standard source‑code security practices (code signing, branch protection) remain essential.
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What This Means For Practitioners
Adopting this pattern replaces a manual, periodic documentation process with an automated, commit‑driven workflow. Teams should evaluate existing CI/CD pipelines for a suitable insertion point, provision an S3 bucket with appropriate security controls, and configure a Bedrock Knowledge Base to consume the generated artifacts. Once in place, the system delivers up‑to‑date architecture diagrams and searchable documentation with minimal ongoing effort, freeing engineers to focus on code rather than paperwork.
