--- title: "amazon-bedrock-samples vs agent-starter-pack" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aws-samples-amazon-bedrock-samples-vs-googlecloudplatform-agent-starter-pack" tools: ["aws-samples-amazon-bedrock-samples", "googlecloudplatform-agent-starter-pack"] --- # amazon-bedrock-samples vs agent-starter-pack *GraphCanon updated Jul 11, 2026* ## Verdict Pick amazon-bedrock-samples when amazon-bedrock-samples is primarily Jupyter Notebook; agent-starter-pack is Python; pick agent-starter-pack when agent-starter-pack is primarily Python; amazon-bedrock-samples is Jupyter Notebook. [amazon-bedrock-samples](https://aws.amazon.com/bedrock/) reports 1.5k GitHub stars, 701 forks, and 130 open issues, last pushed Jun 30, 2026. [agent-starter-pack](http://goo.gle/agents-cli) has 6.5k stars, 1.5k forks, and 48 open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [amazon-bedrock-samples's repository](https://github.com/aws-samples/amazon-bedrock-samples) and [agent-starter-pack's repository](https://github.com/GoogleCloudPlatform/agent-starter-pack). | | [amazon-bedrock-samples](/tools/aws-samples-amazon-bedrock-samples.md) | [agent-starter-pack](/tools/googlecloudplatform-agent-starter-pack.md) | | --- | --- | --- | | Tagline | This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models | Ship AI Agents to Google Cloud in minutes, not months. Production-ready templates with built-in CI/CD, evaluation, and observability. | | Stars | 1,470 | 6,514 | | Forks | 701 | 1,496 | | Open issues | 130 | 48 | | Language | Jupyter Notebook | Python | | Adopt for | - | agent-starter-pack is a specialized toolset for deploying AI agents on the Google Cloud Platform with built-in CI/CD, evaluation tools, and observability features. | | Persona | - | - | | Runtime | - | - | | License | MIT-0 | Apache-2.0 | | Categories | LLM Frameworks, Vector Databases | AI Agents, Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [amazon-bedrock-samples](/tools/aws-samples-amazon-bedrock-samples.md) | [agent-starter-pack](/tools/googlecloudplatform-agent-starter-pack.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 11d | 0d | | Open issues (now) | 130 | 48 | | Full report | [trust report](/tools/aws-samples-amazon-bedrock-samples/trust.md) | [trust report](/tools/googlecloudplatform-agent-starter-pack/trust.md) | ## Decision facts: agent-starter-pack - **Requirements:** Requires additional software installation: Google Cloud SDK, Terraform for deployment, Make for development tasks. - **Adopt for:** agent-starter-pack is a specialized toolset for deploying AI agents on the Google Cloud Platform with built-in CI/CD, evaluation tools, and observability features. ## Choose when ### Choose amazon-bedrock-samples if… - amazon-bedrock-samples is primarily Jupyter Notebook; agent-starter-pack is Python. - License: amazon-bedrock-samples is MIT-0, agent-starter-pack is Apache-2.0. - Tags unique to amazon-bedrock-samples: amazon-bedrock, amazon-titan, bedrock, embeddings. - Also covers Vector Databases. ### Choose agent-starter-pack if… - agent-starter-pack is primarily Python; amazon-bedrock-samples is Jupyter Notebook. - License: agent-starter-pack is Apache-2.0, amazon-bedrock-samples is MIT-0. - Requirements: Requires additional software installation: Google Cloud SDK, Terraform for deployment, Make for development tasks.. - Tags unique to agent-starter-pack: agents, gcp, gemini, genai-agents. - Also covers AI Agents, Inference & Serving. - When you require production-ready templates specifically adapted for deployment to Google Cloud. ## When NOT to use amazon-bedrock-samples - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## When NOT to use agent-starter-pack - If you are using another cloud provider (e.g., AWS, Azure) and do not plan on moving your operations to Google Cloud. - When your team lacks familiarity with Python 3.10+ or does not wish to install and manage dependencies such as the Google Cloud SDK locally. ## Common questions ### What is the difference between amazon-bedrock-samples and agent-starter-pack? amazon-bedrock-samples: This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models. agent-starter-pack: Ship AI Agents to Google Cloud in minutes, not months. Production-ready templates with built-in CI/CD, evaluation, and observability.. See the comparison table for live GitHub stats and shared categories. ### When should I choose amazon-bedrock-samples over agent-starter-pack? Choose amazon-bedrock-samples over agent-starter-pack when amazon-bedrock-samples is primarily Jupyter Notebook; agent-starter-pack is Python; License: amazon-bedrock-samples is MIT-0, agent-starter-pack is Apache-2.0; Tags unique to amazon-bedrock-samples: amazon-bedrock, amazon-titan, bedrock, embeddings; Also covers Vector Databases. ### When should I choose agent-starter-pack over amazon-bedrock-samples? Choose agent-starter-pack over amazon-bedrock-samples when agent-starter-pack is primarily Python; amazon-bedrock-samples is Jupyter Notebook; License: agent-starter-pack is Apache-2.0, amazon-bedrock-samples is MIT-0; Requirements: Requires additional software installation: Google Cloud SDK, Terraform for deployment, Make for development tasks.; Tags unique to agent-starter-pack: agents, gcp, gemini, genai-agents; Also covers AI Agents, Inference & Serving; When you require production-ready templates specifically adapted for deployment to Google Cloud. ### When should I avoid amazon-bedrock-samples? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### When should I avoid agent-starter-pack? If you are using another cloud provider (e.g., AWS, Azure) and do not plan on moving your operations to Google Cloud. When your team lacks familiarity with Python 3.10+ or does not wish to install and manage dependencies such as the Google Cloud SDK locally. ### Is amazon-bedrock-samples or agent-starter-pack more popular on GitHub? agent-starter-pack has more GitHub stars (6,514 vs 1,470). Stars measure visibility, not whether either tool fits your constraints. ### Are amazon-bedrock-samples and agent-starter-pack open source? Yes - both are open-source projects on GitHub (amazon-bedrock-samples: MIT-0, agent-starter-pack: Apache-2.0). ### Where can I find alternatives to amazon-bedrock-samples or agent-starter-pack? GraphCanon lists graph-backed alternatives at [amazon-bedrock-samples alternatives](/tools/aws-samples-amazon-bedrock-samples/alternatives) and [agent-starter-pack alternatives](/tools/googlecloudplatform-agent-starter-pack/alternatives) ([amazon-bedrock-samples markdown twin](/tools/aws-samples-amazon-bedrock-samples/alternatives.md), [agent-starter-pack markdown twin](/tools/googlecloudplatform-agent-starter-pack/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/aws-samples-amazon-bedrock-samples-vs-googlecloudplatform-agent-starter-pack.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, amazon-bedrock-samples or agent-starter-pack? amazon-bedrock-samples: Active. agent-starter-pack: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for amazon-bedrock-samples and agent-starter-pack? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [amazon-bedrock-samples trust report](/tools/aws-samples-amazon-bedrock-samples/trust); [agent-starter-pack trust report](/tools/googlecloudplatform-agent-starter-pack/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=aws-samples-amazon-bedrock-samples`](/api/graphcanon/graph?tool=aws-samples-amazon-bedrock-samples) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_