DevOps

[Webinar] Data-Driven DevOps: Introducing OverOps Platform

machine data

Get your hands on code-aware insights into the functional quality of your application to deliver more reliable software

For decades, development and operations teams have relied on noisy, shallow log files to detect and troubleshoot errors in software. That essentially means that we’re trying to solve application errors with only a tiny fraction of the data we actually need.

In order for DevOps teams to deliver reliable software, we need to rethink the way we gather insight about code-level issues. We need to be able to access more granular, code-aware data, that for the longest time has been inaccessible, and then be able to connect that data to a broader picture of application health. Until now, we were expected to solve 100% of issues, but with less than 50% of the data needed to solve them.

This pain is what led us to build OverOps Platform. It captures code-aware machine data at the time of every error and exception, including the variable values and source code cross the execution stack, the frequency and failure rate of each error, the classification of new and reintroduced errors, the associated release, and more.

Join us on August 22nd to learn how you can leverage this new machine data using key features in OverOps Platform:

  • Safely promote code within your CI/CD pipeline with Continuous Reliability using the RESTful API
  • Create a culture of code accountability with health dashboards and view folders
  • Stop sifting through millions of errors to find what’s important, and detect anomalies with OverOps’ Machine Learning Engine
  • Facilitate issue assignment and create new workflows using OverOps Extensions and AWS Lambda

Can’t make it on the 22nd? Sign up anyways, and we’ll send you the recording!

Tali Soroker

Tali studied theoretical mathematics at Northeastern University and loves to explore the intersection of numbers and the human condition. In her free time, she enjoys drawing and spending time with animals.
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