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Elastic Beanstalk

AWS LabsOfficialPublished by AWS Labs

  • Skill
  • Tool integration
  • Cloud and DevOps
  • Apache-2.0
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From the author

Deploy to AWS Elastic Beanstalk, in either Beanstalk Standard mode (EC2) or Beanstalk Cluster mode (managed EKS). Triggers on: elastic beanstalk, EB, beanstalk standard, beanstalk cluster, managed EC2 platform, web app with managed patching, worker on EC2, Heroku alternative, don't want to manage servers or container orchestration, migrate from Heroku, managed operational lifecycle, containerised app without operating Kubernetes, several services sharing a managed cluster, managed EKS without kubectl. Covers web and worker applications on EC2, and containerised single- and multi-service applications on managed EKS.
— the description by AWS Labs

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

Elastic Beanstalk is an application management service that handles the operational lifecycle of your code or container images, including deployment, scaling, patching, and health monitoring. It offers two distinct modes: Standard, which runs applications on Amazon EC2 instances, and Cluster, which runs containerized applications on a managed Amazon EKS Auto Mode cluster. The service is designed for users who want to avoid managing underlying infrastructure while maintaining a standard application programming model.

What it does

  • Deploys web and worker applications using either EC2 (Standard) or managed EKS (Cluster) infrastructure.
  • Automates operational tasks like scaling, patching, health monitoring, and deployment rollbacks.
  • Supports configuration via AWS CLI, CDK, or Terraform for infrastructure-as-code workflows.
  • Provides managed HTTPS termination and load balancing for web environments.
  • Integrates with AWS Secrets Manager for secure environment variable injection.
  • Enables custom lifecycle hooks and environment configuration via platform-specific settings.

When to use it

  • When you need a managed application platform and want to avoid manual server or container orchestration.
  • When migrating applications from platforms like Heroku, Render, or Railway to AWS.
  • When you require a managed operational lifecycle for web frameworks, APIs, or background workers.
  • When you need to run containerized applications on Kubernetes without managing the cluster yourself.
  • When you prefer a standard application programming model over the constraints of serverless functions.

Advantages

  • Reduces ongoing maintenance overhead by offloading operational responsibility to AWS.
  • Supports both traditional EC2-based deployments and modern containerized EKS workflows.
  • Maintains standard application programming models (e.g., long-running processes, local state).
  • Provides flexible deployment policies including rolling and immutable updates for zero-downtime.
  • Offers consistent infrastructure-as-code support across different deployment modes.

Usage examples

“Deploy my Python web application to Elastic Beanstalk.”
The agent will analyze the codebase, select the appropriate Standard mode platform, configure the environment, and execute the deployment workflow.
“I need to migrate my containerized multi-service app from Heroku to AWS without managing Kubernetes.”
The agent will verify the application contract for Cluster mode and set up a managed EKS environment to host the services.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/awslabs/elastic-beanstalk/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip elastic-beanstalk.zip -d .agents/skills

Documentation by AWS Labs

Elastic Beanstalk

Deploy applications to production on AWS with full lifecycle management. Elastic Beanstalk is an application management service: the user provides application code or a container image, AWS manages everything underneath (deployment, scaling, patching, monitoring, health response).

There are two modes, and the choice determines every setting that follows. Standard runs the application on Amazon EC2; Cluster runs a container on a managed Amazon EKS Auto Mode cluster. See Choose the Mode.

When to Use

Elastic Beanstalk is the right choice when:

  • User explicitly asks for Elastic Beanstalk, EB, or a managed application platform

  • User says "don't want to manage servers", "managed patching", or "Heroku-like"

  • User is migrating from Heroku, Render, or Railway

  • User wants AWS to manage ongoing operational lifecycle (patching, scaling, health monitoring, rollback, deployments) after initial setup

  • App is a web framework, API, or background worker on a standard runtime and the user signals low infrastructure involvement

Elastic Beanstalk is NOT the right choice when:

  • User explicitly wants serverless/Lambda — this imposes a different programming model (event-driven functions, stateless, cold starts, 15-min max execution) rather than just eliminating server management

  • User wants fine-grained container orchestration control (use ECS)

  • User already has Kubernetes expertise and wants direct K8s access (use EKS)

  • App is a static site or SPA (use Amplify Hosting for the frontend; deploy the backend API separately if present)

  • User already has ECS task definitions or Fargate configuration

Key Distinction

ECS and EKS are infrastructure management services: the user defines and operates the deployment infrastructure (task definitions, services, clusters, scaling policies) and owns ongoing operational decisions. Elastic Beanstalk is an application management service: the user provides source code or a Docker image, and AWS provisions and operates the production environment on an ongoing basis. The result is the same reliability, but with lower ongoing maintenance cost because operational responsibility stays with the provider.

Both models support IaC (CDK, CloudFormation, Terraform). The distinction is not about tooling — it is about who manages the lifecycle after deployment.

Lambda/serverless is a different axis entirely. "Don't want to manage servers" does not mean "wants serverless" — Elastic Beanstalk also eliminates server management while preserving the standard application programming model (long-running processes, persistent connections, threads, and — in Standard mode only — local state; Cluster mode replicas have ephemeral local storage). Serverless imposes a specific programming model: stateless functions, cold starts, event-driven invocation, and a 15-minute execution ceiling. Route to Lambda only when the user explicitly asks for serverless or the workload is natively event-driven (e.g., S3 triggers, API Gateway request/response with no session state).

Choose the Mode

Decide before generating anything. The modes share an API and nothing else: a Standard mode namespace passed to a Cluster mode environment is rejected, not ignored.

Cluster mode has an entry requirement, and it is checked first. Route to Cluster only when every service can run as identical, interchangeable replicas and all durable state — uploads, sessions, caches, working files — already lives outside the container. Replica local storage is ephemeral and is lost on every restart, and there is no persistent volume option. An application that fails this goes to Standard mode, or gets changed first; a multi-service signal does not override it. See the application contract.

Then the signals:

SignalMode
Source on a standard runtime; Windows or .NET FrameworkStandard
Worker consuming an SQS queueStandard
Writes uploads, sessions, or working files to local diskStandard
One small application, cost is the priorityStandard
Several services needing private service-to-service trafficCluster
Kubernetes underneath without operating KubernetesCluster
Managed OpenTelemetry, or faster deploys and scalingCluster

A container image alone does not settle it, because Standard mode has a Docker platform too — ask. Prefer Cluster mode when the application is containerised, multi-service, and meets the contract above, since environments sharing subnets share one cluster and reach each other privately. Prefer Standard for a single container where a cluster is not yet justified. Do not propose migrating a working Standard environment unless asked: there is no in-place conversion, only new environments and a CNAME swap.

If the mode is Cluster, follow cluster mode and stop here. Everything below is Beanstalk Standard.

Workflow (Standard)

This skill is invoked after the deploy skill selects Elastic Beanstalk as the deployment target. The deploy skill handles codebase analysis and cost estimation. This skill handles EB-specific configuration:

  1. Map to platform - Select the EB platform branch (see platforms)

  2. Configure - Environment type (web server or worker), instance size, scaling

  3. Generate - AWS CLI commands, CDK, or Terraform (see IaC section below)

  4. Deploy - Execute with user confirmation

Defaults

SettingDevProduction
Environment type (web)Load-balanced (min=1, max=1)Load-balanced, Multi-AZ
Environment type (worker)Auto Scaling group (min=1, max=1)Auto Scaling group (min=2, max=4)
Instancet3.smallt3.medium or larger
DeploymentsAll-at-onceRolling with additional batch
Health reportingEnhancedEnhanced
Managed updatesEnabled (weekly)Enabled (maintenance window)
HTTPS (web only)ACM certificate + ALBACM certificate + ALB

Default to dev unless user says "production" or "prod".

Always use load-balanced environments for web server types. This ensures instances stay in private subnets behind an ALB, HTTPS terminates via ACM automatically, and scaling up later is a config change rather than an environment type migration. Dev deployments with min=max=1 cause brief downtime on deploy (single instance, all-at-once). If zero-downtime dev is needed, use min=1 max=2 with rolling.

Worker environments do not have load balancers — they receive work from SQS and are scaled via Auto Scaling group settings.

Environment Types

Signal in CodebaseEnvironment Type
HTTP listener, web framework, API routesWeb server
Queue-based consumer, SQS processing, no HTTP servingWorker
HTTP serving + queue-based background processingWeb server + separate Worker environment

Worker environments receive work via an SQS queue managed by Elastic Beanstalk. EB's SQS daemon sends HTTP POST requests to the application at a configurable path (default: POST /). The application must expose this HTTP endpoint to process each message — no SQS SDK integration required.

Worker environments also support periodic tasks via cron.yaml for scheduled jobs (alternative to EventBridge + Lambda when the user is already using EB).

If the app uses in-process background threads or async tasks (not queue-based), a single web server environment is sufficient — do not create a separate Worker.

IaC Generation

Default: AWS CLI — no extra tooling to install. The agent orchestrates the multi-step workflow:

  1. aws elasticbeanstalk create-storage-location → returns the S3 bucket (idempotent — returns existing bucket if already created)

  2. aws elasticbeanstalk create-application

  3. Zip source bundle, upload to the bucket from step 1

  4. aws elasticbeanstalk create-application-version

  5. aws elasticbeanstalk create-environment with --option-settings (web: --tier Name=WebServer,Type=Standard, worker: --tier Name=Worker,Type=SQS/HTTP)

  6. aws elasticbeanstalk wait environment-updated

  7. Subsequent deploys: new version + update-environment

Resolve the --solution-stack-name by running aws elasticbeanstalk list-available-solution-stacks and filtering for the detected platform (e.g., ".NET" + "Amazon Linux 2023"). Alternatively, use --platform-arn from aws elasticbeanstalk list-platform-versions.

Use .ebextensions/ and platform hooks for customization.

See AWS CLI EB reference for full command documentation.

Override: CDK (TypeScript) when the user has an existing CDK project, wants repeatable IaC, or explicitly requests it:

  • CfnApplication, CfnEnvironment, CfnConfigurationTemplate

Override: Terraform when the user's repo already has Terraform:

  • aws_elastic_beanstalk_application, aws_elastic_beanstalk_environment

CDK and Terraform templates are scannable by cfn-nag/checkov pre-deploy.

Security

Apply these automatically:

  • Web server instances in private subnets behind ALB

  • Worker instances in private subnets with NAT Gateway for outbound

  • HTTPS via ACM certificate on ALB (web server environments)

  • IAM instance profile with least-privilege permissions — scan source code for AWS SDK client usage to determine required actions (e.g., AmazonBedrockRuntimeClient → bedrock:InvokeModel, AmazonS3Client → s3:GetObject/s3:PutObject on specific buckets)

  • Enhanced health reporting enabled

  • Managed platform updates enabled

  • Security groups: ALB accepts 443, instances accept only from ALB

See the deploy skill's security defaults for encryption, VPC placement, and IAM patterns.

Cost

Elastic Beanstalk has no service fee. Cost = underlying AWS resources. Query the awspricing MCP server for region-accurate estimates. Approximate us-east-1 pricing:

ConfigurationEstimated Monthly Cost
Dev web (1x t3.small + ALB)~$35-40
Dev worker (1x t3.small, no ALB)~$15-20
Production web (4x t3.medium + ALB, Multi-AZ)~$150-200

Add RDS/Aurora costs separately if database is included.

References

Files

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Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an MCP server

Security

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Attribution and licence

Published by
AWS Labs
Publisher
AWS Labs (Official)
Source
awslabs/agent-plugins · plugins/deploy-on-aws/skills/elastic-beanstalk · commit fbefb37
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • NOTICE (added by AutoGineer from NOTICE)
  • ATTRIBUTION.md (written by AutoGineer)
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