DEVOPSdigest

OverOps launched the OverOps Platform, which arms DevOps teams with net new machine data to effectively evaluate the reliability of software they promote, and implement a culture of accountability within their organizations.

At its core, OverOps captures data from applications and services to provide code-aware insights to developers so they can detect and troubleshoot issues more effectively. Building on this foundation, OverOps Platform introduces new features such as software quality dashboards and an API that open this data up to fuel AIOps use cases.

For decades, development and operations teams have relied on noisy, shallow log files to detect and troubleshoot errors in software. OverOps improves this process by capturing net new machine data about every error and exception at the moment they occur, automating root cause analysis. OverOps' data includes structured details such as the value of all variables across the execution stack, the frequency and failure rate of each error, the classification of new and reintroduced errors, the associated release numbers for each event, and more.

This comprehensive data not only helps developers find and fix issues more quickly, but with the introduction of four key new features –– the OverOps API, Software re Health Dashboards, a Machine Learning Engine and OverOps Extensions –– OverOps Platform now also enables a number of AIOps-related usee cases for DevOps and Site Reliability Engineers (SRE), including:

- Continuous Reliability Using the RESTful API and Log File Linkage: The RESTful API included in OverOps Platform allows DevOps teams to investigate the overall quality of an application and determine when it is safe to promote code within a fast-paced continuous integration/continuous delivery (CI/CD) workflow. OverOps allows an organization to gain insight into new and reintroduced errors by type and for every release. Additionally, OverOps offers visibility into the uncaught and swallowed exceptions that are completely unavailable in log files. Finally, OverOps precedes the creation of a log file entry and augments them with links to the platform so developers are enabled with rich information about each error and can quickly remediate issues, completing the circle and providing a valuable feedback loop from operations to development.

- Create a Culture of Accountability with Software Health Dashboards: With the Software Health Dashboards that are introduced in OverOps Platform, development and operations teams can gain real-time insight into the overall quality and health of their applications and services. Powered by Grafana, the dashboards also help you understand types of errors, the team responsible for them and even the release or build they are associated with. This level of granularity into where, when, why and who is responsible for issues helps promote a culture of accountability across the software development lifecycle and ensures alignment and a shared goal for delivering reliable software.

Detect Anomalies with OverOps' Machine Learning Engine: OverOps Platform applies machine learning and anomaly detection techniques to its unique data set to detect elusive errors and help identify critical issues, new issues or reintroduced issues amongst billions of events. Existing AIOps solutions take a similar, machine learning-based approach, but are limited to the shallow information found in logs. With OverOps, the data beneath the algorithms enables you to analyze actual throughput in real-time, allowing for more exact analysis and helping teams focus on what's actually important.

All three of these DevOps use cases are dependent on the deep integration capabilities in OverOps Platform. With its API and support for metrics, OverOps expands the value of its unique data into critical DevOps tools such as Splunk, Elastic, Dynatrace and AppDynamics, among others. Further complementing this interoperability, OverOps Extensions provides an AWS Lambda-based framework (and on-premises code as an option) for organizations to create their own custom functions and workflows based on the valuable OverOps data. With open access to OverOps machine data and functional extensions, DevOps can enhance the entire software delivery supply chain to improve reliability of their applications and services, and avoid costly downtime.

"We initially created OverOps to help developers debug code and improve their productivity, but through our customers we discovered the unique value of looking at our data in aggregate, rather than in its individual form, to provide detailed insight into the overall quality of an application –– insight that is invaluable to DevOps and SRE. In response to this, we've opened up our product and our data to a complete platform that provides operations teams with critical insight to help them deliver on the promise of reliability," said Tal Weiss, CTO and co-founder of OverOps.

OverOps Platform is immediately available.