Set up and monitor deployments

Set up a deployment

This guide covers the general setup of deployment environments. If you’re seeking platform-specific information, check out the deployment guides.

First, we'll define your environments in Bitbucket settings.

You can set:

their name
what type of environment they are
the order they show on your dashboard
any variables specific to that environment
and, if you have the premium plan, who can deploy to each one.

Then all you need to do is reference them in your bitbucket-pipelines.yml file to see them on your deployments dashboard.

Step 1: Define your environments

First we'll add the details of your environments.

When you enable pipelines, we create 3 basic environments for you by default, a test environment called 'Test', a staging environment called 'Staging', and a production environment called (you've guessed it!) 'Production'.

The environment types are used to logically order your environments, nothing more, so don't worry if the types don't quite match up to the function you use them for.

Go into your repository settings.
In the Pipelines section, choose Deployments
Click on any environment to:
- change its name
- set environment specific deployment variables.
  Deployment variables override both team and repository variables. Also variables with the same name can have different values for each deployment environment. For example, you could set a different $DEPLOYMENT_SECRET_KEY for each environment. If you then also restrict the environment, only your admins can use your secret keys.
- restrict the ability to deploy to admins, or to specific branches.

If you want to add more environments, decide which type of environment best describes it (test, staging, or production) and click add environment in that section.

You can also move environments within their type by clicking the left hand edge and dragging.

Step 2: Configure your deployment steps

Add the deployment keyword to the step or stage, followed by the name of the environment. The default Pipelines deployment environments are test, staging, or production.

For example:

pipelines:
  default:
    - step:
        name: Deploy to production
        deployment: production
        script:
          - python deployscript.py prod

Commit the changes to your bitbucket-pipelines.yml file to run your deployment pipeline. The deployment step or stage will now show up in the deployments dashboard.

When adding multiple deployment environments, Bitbucket Pipelines requires the deployments to be ordered as follows in the bitbucket-pipelines.yml file:

Test environments
Staging environments
Production environments

Pipelines don't require all three environment types, and steps and stages within each type can be in any order.

For example, if you have the following deployment environments configured on the Deployments settings page:

Test environments — testbed
Staging environments — staging1 and staging2
Production environments — production-east

When adding the associated steps or stages to your pipeline, ensure the Staging environments (staging1 and staging2) are grouped after any Test environments and before any Production environments.

Such as:

pipelines:
  default:
    - step:
        name: Build and push to S3
        script:
          - apt-get update
          - apt-get install -y python-dev
          - curl -O https://bootstrap.pypa.io/get-pip.py
          - python get-pip.py
          - pip install awscli
          - aws deploy push --application-name $APPLICATION_NAME --s3-location s3://$S3_BUCKET/test_app_$BITBUCKET_BUILD_NUMBER --ignore-hidden-files
    - step:
        name: Deploy to testing
        image: amazon/aws-cli:latest
        deployment: testbed # Test environment
        script:
          - python deploy.py test
    - step:
        name: Deploy to staging
        image: amazon/aws-cli:latest
        deployment: staging2 # Staging environment
        trigger: manual
        script:
          - python deploy.py staging
    - step:
        name: Deploy to QA staging
        image: amazon/aws-cli:latest
        deployment: staging1 # Staging environment
        trigger: manual
        script:
          - python deploy.py staging
    - step:
        name: Deploy to production
        image: amazon/aws-cli:latest
        deployment: production-east # Production environment
        trigger: manual
        script:
          - python deploy.py prod

Step 3: Track your deployments

Once your deployment step has run, you can track your deployments on the Deployments dashboard.

Understand the deployment dashboard

Use the deployments dashboard to get information about all your deployment environments at a glance. Also you can use deployment variables with permissions to make sure only the branches or people you want to deploy.

Deployment review and promotion

If you've made a deployment step manual, you will see a Promote button on the Deployments dashboard. Clicking on the Promote button launches the deployment preview screen where you can review the commits and the file changes that will be deployed. If it looks good, click Deploy and we'll trigger your manual deployment step.

Note: you can only have one in-progress deployment in each environment. Any later pipelines that deploy to the same environment will be automatically paused. You can manually resume the paused deployment step once the in-progress deployment completes.

Deployment information

There is a variety of information you can access from the environment card.

1. Deployment history

By clicking on the environment name you can see a history of all earlier deployments to an environment. You can click on any of these to get a deployment summary.

2. View pipeline

If you click on the pipeline number, it will take you to the summary for that run of the pipeline, where you can view logs and more.

3. Deployment summary

Access the deployment summary by clicking on the deployment on an environment card, or in the history list. The summary shows information about the deployment including:

The environment it was deployed to
The previous deployment in the environment
The status of the deployment
Who triggered the deployment (if the deployment was a manual step)
The date the deployment occurred
A full list of commits in the deployments
A file diff between the new deployment and the previous deployment in the environment
Any linked Jira issues you've mention in the commit message

If you use Jira to keep track of work, you can link Jira and Bitbucket, for added benefits.

Once they are linked, issues related to a deployment show up on the deployment summary and deployment preview screens, and your deployments will show up in relevant Jira issues. Just add the issue key, or keys, to your commit message and we'll do the rest.

Example

git commit -m "PT-323 Add created workers to container cluster"

In Bitbucket, this is shown as the following image.

In Jira, it is shown as:

If you rerun a successful deployment, Jira will continue to show the details of the first successful deployment, rather than any reruns.

Roll back deployments

Bitbucket Pipelines allow you to roll back a deployment step without running the entire pipeline. If your deployment failed, you can restore the last successful deployment in a couple of clicks.

Before you begin

For the Redeploy button to be enabled:

The initial deployment step in the pipeline must be completed successfully
The deployment permissions must allow the step to be redeployed (Premium plan only)
Artifacts can't be expired

Rolling back deployments

To roll back a deployment step:

Choose the deployment which you want to redeploy and click the Redeploy button.
In the Redeploy screen, review the changes and click Redeploy:

Alternatively, you can click Redeploy in the Deployments dashboard:

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