Open-source engineering management that unlocks developer potential

Middleware is an open-source tool designed to help engineering leaders measure and analyze the effectiveness of their teams using the DORA metrics. The DORA metrics are a set of four key values that provide insights into software delivery performance and operational efficiency.

They are:

• Deployment Frequency: The frequency of code deployments to production or an operational environment.
• Lead Time for Changes: The time it takes for a commit to make it into production.
• Mean Time to Restore: The time it takes to restore service after an incident or failure.
• Change Failure Rate: The percentage of deployments that result in failures or require remediation.

Table of Contents

• Middleware - Open Source
  • Features
  • Quick Start
    • Installing Middleware
    • Troubleshooting
  • Developer Setup
    • Using Gitpod
    • Using Docker
    • Manual Setup
  • Usage
  • How we Calculate DORA
  • Roadmap
  • Contributing guidelines
  • Security guidelines
  • License

• Integration with various CI/CD tools
• Automated collection and analysis of DORA metrics
• Visualization of key performance indicators
• Customizable reports and dashboards
• Integration with popular project management platforms

• Ensure that you have docker installed and running.

• Open the terminal and run the following command:

  docker volume create middleware_postgres_data
  docker volume create middleware_keys
  docker run --name middleware \
             -p 3333:3333 \
             -v middleware_postgres_data:/var/lib/postgresql/data \
             -v middleware_keys:/app/keys \
             -d middlewareeng/middleware:latest
  docker logs -f middleware

• Wait for sometime for the services to be up.

• The app shall be available on your host at https://localhost:3333.

1. In case you want to stop the container, run the following command:

   docker stop middleware

2. In order to fetch latest version from remote and then starting the system, use following command:

   docker pull middlewareeng/middleware:latest
   docker rm -f middleware || true
   docker run --name middleware \
              -p 3333:3333 \
              -v middleware_postgres_data:/var/lib/postgresql/data \
              -v middleware_keys:/app/keys \
              -d middlewareeng/middleware:latest
   docker logs -f middleware

3. If you see an error like: Conflict. The container name "/middleware" is already in use by container.
   Then run following command before running the container again:

   docker rm -f middleware

Gitpod enables development on remote machines and helps you get started with Middleware if your machine does not support running the project locally.

If you want to run the project locally you can setup using docker or setup everything manually.

1. Click the button below to open this project in Gitpod.

2. This will open a fully configured workspace in your browser with all the necessary dependencies already installed.

After initialization, you can access the server at port 3333 of the gitpod instance.

If you don't have docker installed, please install docker over here. Make sure docker is running.

1. Clone the Repository:

   git clone https://github.com/middlewarehq/middleware

2. Navigate to the Project Directory:

   cd middleware

3. Run dev.sh script in the project root 🪄
   ./dev.sh creates a .env file with required development environments and runs a CLI with does all the heavy lifting from tracking the container with docker compose watch to providing you with logs from different services.
   The usage is as follows:

   ./dev.sh

   You may update the env.example and set ENVIRONMENT=prod to run it in production setup.
   Further if any changes are required to be made to ports, you may update the docker-compose.yml file, accordingly.

4. Access the Application: Once the project is running, access the application through your web browser at https://localhost:3333. Further, other services can be accessed at:

   • The analytics server is available at https://localhost:9696.
   • The sync server can be accessed at https://localhost:9697.
   • The postgres database can be accessed at host: localhost, port: 5434, username: postgres, password: postgres, db name: mhq-oss.
   • The redis server can be accessed at host: localhost, port: 6385.

5. View the logs: Although the CLI tracks all logs, the logs of services running inside the container can be viewed in different terminals using the following commands:

   Frontend logs

   docker exec -it middleware-dev tail --lines 500 -f /var/log/web-server/web-server.log

   Backend api server logs

   docker exec -it middleware-dev tail --lines 500 -f /var/log/apiserver/apiserver.log

   Backend sync server logs

   docker exec -it middleware-dev tail --lines 500 -f /var/log/sync_server/sync_server.log

   Redis logs

   docker exec -it middleware-dev tail --lines 500 -f /var/log/redis/redis.log

   Postgres logs

   docker exec -it middleware-dev tail --lines 500 -f /var/log/postgres/postgres.log

To set up middleware locally, follow these steps:

1. Clone the Repository:

   git clone https://github.com/middlewarehq/middleware.git

2. Navigate to the Project Directory:

   cd middleware

3. Run Redis and Postgres Containers:

   If you don't have docker installed, please install docker over here

   Run the following commands to run Postgres and Redis using docker.

   cd database-docker && docker-compose up -d

   If you don't prefer Docker, you can choose to install Postgres and Redis manually.

   Once you are done with using or developing Middleware, you can choose to close these running container. (NOTE: Don't do this if you are following this document and trying to run Middleware.)

   cd database-docker/
   docker-compose down -v

4. Generate Encryption keys:

   Generate encryption keys for the project by running the following command in the project root directory:

   cd setup_utils && . ./generate_config_ini.sh && cd ..

5. Backend Server Setup

   • Install python version 3.11.6

     • For this you can install python from over here if you don't have it on your machine.

     • Install pyenev

       git clone https://github.com/pyenv/pyenv.git ~/.pyenv

     • Add pyenv to your shell's configuration file (.bashrc, .bash_profile, .zshrc, etc.):

       echo 'export PYENV_ROOT="$HOME/.pyenv"' >> ~/.bashrc
       echo 'export PATH="$PYENV_ROOT/bin:$PATH"' >> ~/.bashrc

     • Reload your shell:

       source ~/.bashrc
       

   • Move backend directory to create a virtual environment

     cd backend
     python -m venv venv

   • Activate virtual environment

     . venv/bin/activate

   • Install Dependencies

     pip install -r requirements.txt -r dev-requirements.txt

   • Create a .env.local file in the /backend directory and add the following environment variables, replacing the values with your own if needed:

     DB_HOST=localhost
     DB_NAME=mhq-oss
     DB_PASS=postgres
     DB_PORT=5434
     DB_USER=postgres
     REDIS_HOST=localhost
     REDIS_PORT=6385
     ANALYTICS_SERVER_PORT=9696
     SYNC_SERVER_PORT=9697
     DEFAULT_SYNC_DAYS=31
     

   • Start the backend servers

     • Change Directory to analytics_server

       cd analytics_server

     • For backend analytics server:

       flask --app app --debug run --port 9696

     • For backend sync server:

       flask --app sync_app --debug run --port 9697

       NOTE: Open this sync sever in a new terminal window after activating the virtual environment only after starting analytics server.

6. Web Server Setup

   • Install NodeJs 16.17 (LTS) either manually or using a tool like nvm or volta.

   • Install yarn package manager

     npm install --global yarn

   • Change Directory to web-server and install packages

     cd web-server
     yarn

   • Start the web-server

     yarn dev

7. Access the Application: Once the project is running, access the application through your web browser at https://localhost:3333.
   Additionally:

   • The analytics server is available at https://localhost:9696.
   • The sync server can be accessed at https://localhost:9697.

• Setup the project by following the steps mentioned above.
• Generate and Add your PAT token from code provider.
• Create a team and select repositories for the team.
• See Dora Metrics for your team.
• Update settings related to incident filters, excluded pull requests, prod branches etc to get more accurate data.

Middleware can display DORA Metrics using exclusively GitHub Data. The aim is to provide DORA metrics to anyone and everyone using their Git data, regardless of other integrations.

DORA metrics are derived from Pull Requests, Deployments, and Incidents.

For simplicity, we synchronize your Pull Request data and classify reverted Pull Requests as incidents and merged Pull Requests as Deployments.

Lead Time for Changes

• Lead time consists of First Commit to PR Open time, First Response Time, Rework Time, Merge Time, and Merge to Deploy Time.
• When calculating DORA using git-based data, PR merges are regarded as deployments, hence the merge to deploy time is considered as 0, while the rest of the time components remain the same.

Deployment Frequency

• This metric gauges how frequently code changes are deployed to production.
• When considering PR merges as deployments, this can also represent the daily/weekly/monthly frequency of PR merges.

Mean Time to Recover (MTTR)

• MTTR measures how swiftly a team can restore service after a failure occurs in production.
• The team's average incident resolution time is utilized to compute its MTTR.
• When treating Revert PRs as incidents, the resolution time for an incident is calculated from the merging of the original PR to the merging of the revert PR.

Change Failure Rate (CFR)

• CFR quantifies the percentage of changes that result in a service impairment or outage in production, aiding in the evaluation of deployment process stability and reliability.
• CFR is computed by linking incidents to deployments within an interval; each deployment may have several or no incidents.
• Deployments that can be linked to any incident are considered as causing a failure or outage.
• The fraction of deployments causing outages to the total deployments in an interval is used to determine the CFR.

Coming Soon!

To get started contributing to middleware check out our CONTRIBUTING.md.

We appreciate your contributions and look forward to working together to make Middleware even better!

To get started contributing to middleware check out our SECURITY.md.

We look forward to your part in keeping Middleware secure!

This project is licensed under the Apache 2.0 License - see the LICENSE.md file for details.