Deployments
The Deployments page of a project is used to track the deployments of whatever app the project is monitoring. With deployment tracking, you can know when your code changed and what changed in it. By default, all errors are marked as resolved on deploy, meaning that when they occur again you will receive a new notification.
How Deployments Work in Honeybadger
On the deployment page, you can see all of your most recent deployments, by default sorted by timestamp, with the most recent at the top. At the top of the page, you can choose instead to sort by what environment a deploy was pushed to, as well as adjust the time range being displayed - with presets for month to date, the last seven days, and yesterday.
For each deployment in the list, we display the timestamp, the environment affected, the user who did it, and the revision link. When GitHub or GitLab is connected, you will also see a comparison link.
If your apps are hosted on Heroku, you will also see Heroku's own deploys in your deployment tab, with all the same information (excluding comparison links). For Heroku deploys, the user listed shows which part of Heroku had the deployment.
Connecting with GitHub and GitLab
When your project has been connected to a GitHub or GitLab account, the deploy list on the Deployments page in Honeybadger will include links to the comparison views so that you can see what exactly changed on each deploy.
Deploying with GitHub actions
If your CI/CD pipeline is hosted with GitHub Actions, you can use the Honeybadger Deploy Action to notify our API about deployments.
Deployments with Specific Languages
Honeybadger has specific features for tracking deployments for some of our supported languages and integrations.
Languages
Integrations
Searching with Deployments
With the Since Deploy token in the error search bar, you can filter for all the errors that have occurred since your latest deployment. New code often causes errors to pop up, and when combined with the other tokens in our powerful error search system, you can easily hone in on the errors caused by new code in the environments in which the code was deployed or users that the new code affected.
To learn more about search tokens - and how to combine them - check out the Error Search documentation page.