AWS bedrock-agentcore documentation change
Summary
Restructured documentation to remove detailed deployment steps and instead provide links to language-specific guides (Python, Node.js), supported runtimes, and troubleshooting. Removed all step-by-step instructions, code samples, and configuration details.
Security assessment
The changes are purely organizational, replacing implementation details with links to external pages. There is no evidence of security vulnerabilities being addressed, nor any new security documentation added. The modifications focus on improving documentation structure without altering security content.
Diff
diff --git a/bedrock-agentcore/latest/devguide/runtime-get-started-code-deploy.md b/bedrock-agentcore/latest/devguide/runtime-get-started-code-deploy.md index 10a2cb4ca..7d42b398d 100644 --- a//bedrock-agentcore/latest/devguide/runtime-get-started-code-deploy.md +++ b//bedrock-agentcore/latest/devguide/runtime-get-started-code-deploy.md @@ -7 +7 @@ -PrerequisitesStep 1: Set up project and install dependenciesStep 2: Create your agent projectStep 3: Test locallyStep 4: Enable observability for your agentStep 5: Deploy to AgentCore Runtime and invokeStep 6: Stop session, update, or cleanupDirect code deployment conceptsCommon Issues +Direct code deployment concepts @@ -11 +11 @@ PrerequisitesStep 1: Set up project and install dependenciesStep 2: Create your -Direct code deployment enables you to bring your Python-based agent to Amazon Bedrock AgentCore Runtime simply by packaging agent code and its dependencies in a .zip file archive. Your agent still needs to follow [AgentCore Runtime requirements](https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/runtime-service-contract.html) : have an entrypoint .py file that either uses the `@app.entrypoint` annotation from [Amazon Bedrock AgentCore Python SDK](https://github.com/aws/bedrock-agentcore-sdk-python) or implements `/invocations` POST and `/ping` GET server endpoints. +Direct code deployment enables you to bring your agent to Amazon Bedrock AgentCore Runtime simply by packaging agent code and its dependencies in a .zip file archive. Your agent still needs to follow [AgentCore Runtime requirements](https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/runtime-service-contract.html). @@ -13 +13 @@ Direct code deployment enables you to bring your Python-based agent to Amazon Be -To create your deployment package as .zip file archive, you can use [AgentCore CLI](https://github.com/aws/agentcore-cli) or follow the steps in the _Custom zip + boto3_ tab below, or any other .zip file utility such as [7zip](https://www.7-zip.org/download.html) . The examples shown in the following sections assume you’re using a command-line `zip` tool in a Linux or MacOS environment. To use the same commands in Windows, you can [install the Windows Subsystem for Linux](https://docs.microsoft.com/en-us/windows/wsl/install-win10) to get a Windows-integrated version of Ubuntu and Bash. +To create your deployment package as .zip file archive, you can use [AgentCore CLI](https://github.com/aws/agentcore-cli) or follow the steps in the language-specific guides below, or any other .zip file utility such as [7zip](https://www.7-zip.org/download.html) . The examples shown in the following sections assume you’re using a command-line `zip` tool in a Linux or MacOS environment. To use the same commands in Windows, you can [install the Windows Subsystem for Linux](https://docs.microsoft.com/en-us/windows/wsl/install-win10) to get a Windows-integrated version of Ubuntu and Bash. @@ -19,14 +18,0 @@ Note that AgentCore Runtime uses POSIX file permissions, so you may need to [set - * Prerequisites - - * Step 1: Set up project and install dependencies - - * Step 2: Create your agent project - - * Step 3: Test locally - - * Step 4: Enable observability for your agent - - * Step 5: Deploy to AgentCore Runtime and invoke - - * Step 6: Stop session, update, or cleanup - @@ -35,235 +21 @@ Note that AgentCore Runtime uses POSIX file permissions, so you may need to [set - * Common Issues - - - - -## Prerequisites - -Before you start, make sure you have: - - * **AWS Account** with credentials configured. To configure your AWS credentials, see [Configuration and credential file settings in the AWS CLI.](https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-files.html) - - * [Uv](https://docs.astral.sh/uv/getting-started/installation/) **installed** and [Python 3.10+](https://docs.astral.sh/uv/guides/install-python/) installed - - * **AWS Permissions** : To create and deploy an agent with the AgentCore CLI, you must have appropriate permissions. For information, see [Use the AgentCore CLI](https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/runtime-permissions.html#runtime-permissions-cli). - - * **Model access** : Anthropic Claude Sonnet 4.0 [enabled](https://docs.aws.amazon.com/bedrock/latest/userguide/model-access-modify.html) in the Amazon Bedrock console. For information about using a different model with the Strands Agents see the _Model Providers_ section in the [Strands Agents SDK](https://strandsagents.com/latest/documentation/docs/) documentation. - - - - -## Step 1: Set up project and install dependencies - -Initialize your project with the following commands: - - - uv init agentcore_runtime_direct_deploy --python 3.13 - cd agentcore_runtime_direct_deploy - -Add core packages: - - - uv add bedrock-agentcore strands-agents - -Install the AgentCore CLI (required for the steps that follow): - - - npm install -g @aws/agentcore - -Package descriptions: - - * **bedrock-agentcore** \- The Amazon Bedrock AgentCore SDK for building AI agents - - * **strands-agents** \- The [Strands Agents](https://strandsagents.com/latest/) SDK - - * **@aws/agentcore** \- The AgentCore CLI - - - - -Optionally, run `uv add aws-opentelemetry-distro` to enable [Amazon Bedrock AgentCore observability traces](https://docs.aws.amazon.com/xray/latest/devguide/xray-services-adot.html). - -Uv will automatically create a `pyproject.toml` file with dependencies, `uv.lock` file with dependency closure and `.venv` directory. - -## Step 2: Create your agent project - -Use the `agentcore create` command to set up a skeleton agent project with the framework of your choice: - - - agentcore create - -The command will prompt you to: - - * Choose a framework (choose Strands Agents for this tutorial) - - * Provide a project name - - * Choose a template (basic or production) - - * Choose model provider and other options - - - - -This command generates: - - * Agent code with your selected framework - - * A `pyproject.toml` file with necessary dependencies - - * An `agentcore/agentcore.json` configuration file - - * Infrastructure as Code (IaC) files if production template is selected - - - - -## Step 3: Test locally - -Make sure port 8080 is free before starting. See _Port 8080 in use (local only)_ in [Common issues and solutions](https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/runtime-get-started-cli.html#common-issues). - -Open a terminal window and start your agent with the following command: - - - agentcore dev --no-browser - -Test your agent by opening another terminal window and enter the following command: - - - curl -X POST http://localhost:8080/invocations \ - -H "Content-Type: application/json" \ - -d '{"prompt": "Hello!"}' - -**Success:** You should see a response like `{"result": "Hello! I’m here to help…"}` . In the terminal window that’s running the agent, enter `Ctrl+C` to stop the agent. - -## Step 4: Enable observability for your agent - -[Amazon Bedrock AgentCore Observability](https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/observability.html) helps you trace, debug, and monitor agents that you host in AgentCore Runtime. First enable CloudWatch Transaction Search by following the instructions at [Enabling Amazon Bedrock AgentCore runtime observability](https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/observability-configure.html#observability-configure-builtin) . To observe your agent, see [View observability data for your Amazon Bedrock AgentCore agents](https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/observability-view.html). - -## Step 5: Deploy to AgentCore Runtime and invoke - -Deploy your agent using one of the following methods: - -###### Example - -AgentCore CLI - - - 1. The following steps will be required to deploy an agent to AgentCore Runtime, refer to [Get started with the AgentCore CLI](https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/runtime-get-started-cli.html) , for detailed steps. If Uv is available, the AgentCore CLI will recommend direct code deployment. Otherwise it will default to container deployment type. - -Once you have your agent set up using `agentcore create` , use the `deploy` command to create a zip deployment package, upload it to the specified bucket, and deploy the agent. - - agentcore deploy - -Let’s prompt the agent to tell a joke! - - agentcore invoke "Tell me a joke" - -The first deployment takes time to install dependencies but subsequent updates to the agent optimizes this by re-using zipped dependencies - -**Configuration management** - -You can modify your agent configuration at any time using the `agentcore add` commands or by editing the `agentcore/agentcore.json` configuration file directly. - -The configuration file allows you to update deployment parameters such as your VPC configuration, execution roles, session timeouts, and OAuth authorizer settings. - - - - -Interactive - - - 1. Run `agentcore` to open the TUI, then select **deploy** . The deploy screen shows real-time progress as it validates your project, synthesizes CloudFormation, and provisions AWS resources: - - - -After deployment completes, use `agentcore invoke` to test your agent. - - - - -Custom zip + boto3 - - - 1. To download a wheel that’s compatible with AgentCore Runtime, you use the uv pip `--python-platform` option. AgentCore Runtime only supports **arm64** instruction set architecture, run the following command. Replace `--python 3.x` with the version of the Python runtime you are using. - - uv pip install \ - --python-platform aarch64-manylinux2014 \ - --python-version 3.13 \ - --target=deployment_package \ - --only-binary=:all: \ - -r pyproject.toml - -Create a .zip file with the installed libraries at the project root. - - cd deployment_package - zip -r ../deployment_package.zip. - -Add the `main.py` file and other files in your package to the root of the .zip file. - - cd .. - zip deployment_package.zip main.py