aws/chalice

Python Serverless Microframework for AWS

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Summary Information

Updated 21 minutes ago
Added to GitGenius on September 5th, 2026
Created on May 27th, 2016
Open Issues & Pull Requests: 493 (+0)
GitHub issues: Enabled
Number of forks: 1,012
Total Stargazers: 11,057 (+0)
Total Subscribers: 229 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 24.7 days
Mean response time: 131.0 days
90th percentile: 308.0 days
Tracked items: 40

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 97% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. Only 3% of issues opened in the past year have been closed. Three people close 60% of everything that gets resolved.

Charts & Analytics

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Issue Activity (beta)

Open issues: 34
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 1,383 days
Stale 30+ days: 33
Stale 90+ days: 32

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • feature-request (9)
  • documentation (1)
  • enhancement (1)
  • proposals (1)
  • response-requested (1)

Most active issues this week

No issue events were indexed in the last 7 days.

Detailed Description

Chalice is a Python microframework for building and deploying serverless applications on AWS Lambda.

Chalice addresses the complexity of writing serverless applications by providing a decorator-based API that abstracts away infrastructure details. Developers write Python functions decorated with route handlers, event triggers, and scheduled tasks, then run a single deploy command. The framework automatically generates IAM policies, manages Lambda function creation, and integrates with API Gateway, S3, SNS, SQS, and other AWS services. This approach eliminates boilerplate configuration and lets developers focus on application logic rather than cloud infrastructure setup.

Chalice suits teams building REST APIs, event-driven microservices, and scheduled tasks on AWS who want to minimize operational overhead. It works well for projects where rapid prototyping and deployment matter more than fine-grained infrastructure control. The tool is particularly valuable for developers already familiar with Python who want to avoid learning CloudFormation or Terraform. Those needing extensive customization of AWS resources or multi-cloud deployments may find the AWS-specific focus limiting.

The project maintains a substantial base of real-world adopters, as evidenced by the fact that nearly all open issues come from outside users rather than the core team. Responses to issues and pull requests typically arrive within one to two weeks. The issue tracker is dominated by feature requests, proposals, and enhancement discussions, reflecting an active community driving the project's evolution.