If you're currently, or considering, using continuous delivery tactics like continuous integration or continuous deployment, you've likely heard of deployment tracking. Deployment tracking allows DevOps teams to release new versions of software with greater efficiency, accuracy, and velocity.
By employing deployment tracking, you can automate alerts to notify you of newly introduced errors so that you can catch and fix problems as soon as they occur and, more importantly, before they cause severe issues to your application and cause headaches for your customers.
Furthermore, application deployment tracking involves nearly all automated processes that speed up the identification and notification of issues, reduce the deployment lifecycle, and the propensity for human error.
By employing automated deployment tracking, agile teams can improve application development, environment modeling, and workflow orchestration by reducing human error. This ultimately frees up engineers to work on their most mission-critical tasks, and enables your team to release their applications more quickly and frequently. In this post, we’ll go in-depth on the benefits of deployment tracking and how automation improves the process.
DevOps teams use deployment tracking tools to get an overview of the different versions of software as they’re released, as well as to collect metrics about how their new release is performing.
When an error surfaces, software deployment tracking software will spot it immediately, determine what caused the error, and who triggered the offending deployment. All stakeholders are then notified so that they can take fast, aggressive action to troubleshoot the offending code and fix any discovered bugs.
Additionally, today’s modern deployment tracking tools, like Sleuth, can integrate with your other mission-critical tools to ensure a cohesive release process while keeping necessary parties informed on the health of your deployments, as well as track their impact over time.
Release automation is a large part of what makes software delivery so reliable and helpful. It makes deployments faster and more accurate because it removes error-prone manual processes and streamlines production tasks. With this error reduction, you can eliminate re-work, wait times, and the business impact of failures.
Automated deployment tracking also means that the software will record and broadcast what it does, which provides greater visibility to all the parties involved and allows them to quickly troubleshoot and resolve errors.
This further reduces the risk of production downtime for the end-users and, in turn, creates greater availability in your test environments for faster deployment cycles and shorter timelines.
Finally, deployment automation tools minimize cycle duration by executing tasks without the need for manual intervention. It increases the DevOps team's ability to release more frequently by providing a faster, responsive feedback loop.
Sleuth is an automated deployment tracking tool that helps improve the development process by giving teams the ability to focus on their mission-critical work, instead of putting out the fires of error-prone manual tasks.
With Sleuth, teams can stop waiting on human lag by automating most of their production tasks during the deployment process, as well as monitoring post-release metrics to ensure your deployments deliver positive impact over time. Most deployment tools call it a day and head home the second you deploy; Sleuth continues to deliver value even after your code hits production status by continuously evaluating your deployments with the assistance of the many integrations Sleuth employs, such as Datadog, Sentry, Rollbar, and many more.
Sleuth automates release management by merging with the production environment and providing real-time notifications to your entire software development team through its full-featured Slack integration. In addition to Slack, Sleuth also integrates with various mission-critical tools, such as GitHub, Bitbucket, and LaunchDarkly for change sources; Sentry, Rollbar, and Honeybadger for error tracking; Datadog and SignalFx for metrics tracking; Jira, Clubhouse, and Linear for issue tracking; and CircleCI to track builds, with more integrations always on the horizon.
With Sleuth, you can create greater efficiency in your deployment pipeline, improve your development environment with a faster software release process, and have visibility into the status of your deployment with instant notifications of new errors and bugs.
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