SAN FRANCISCO (PRWEB) August 01, 2018
OverOps today announced the launch of 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.
“The industry has retooled almost the entire software supply chain, yet organizations still rely on manual and shallow methods to investigate and measure errors found within code,” said Stephen Elliot, Program Vice President, Management Software and DevOps at IDC. “There is a need to rethink the way development and DevOps teams gather insight about code-level issues. By having more granular visibility into the quality of applications and services across all environments––including production––organizations can proactively prevent outages that could otherwise lead to brand degradation and loss of revenue.”
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. Unlike existing tools, 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 Health Dashboards, a Machine Learning Engine and OverOps Extensions––OverOps Platform now also enables a number of AIOps-related use cases for DevOps and Site Reliability Engineers (SRE), including:
- Continuous Reliability Using the RESTful API and Log File Linkage
Today, organizations rely on the limited information found in log files to gauge how safe it is to promote code. This manual process often results in bad code making it to production and downtime that leads to lost revenue and brand damage. The RESTful API included in OverOps Platform now 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
Today, many organizations have built natural walls between internal groups that encourage finger pointing and blame when software fails and systems go awry. Without visibility into how and why things break, it is difficult to combat this. 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
Organizations have become accustomed to sifting through thousands of log file entries to find where code breaks, but when this escalates to millions and billions of log entries, determining the signal in the noise is near impossible. OverOps Platform solves this challenge by applying 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.
"OverOps Platform reduces the need for time intensive, manual investigation of log files by providing deep machine data about each error and visibility into the overall quality of our applications. As a result, we’re not only able to troubleshoot quickly, but also to take a more proactive approach to evaluating service reliability and avoiding future errors,” said Ronan Ryan, Senior Director of Engineering, TripAdvisor.
“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. For information on pricing, visit https://www.overops.com/pricing.
- Read the blog post about OverOps Platform from co-founder Tal Weiss
- Join a webinar that will walk through new features in OverOps Platform
- Learn more about OverOps Platform
OverOps provides net new machine data from applications and services to help organizations effectively evaluate the reliability of their software and implement a culture of accountability. By combining static and dynamic code analysis, OverOps captures unique code-aware insight about every error and exception––both caught and uncaught––in any environment, including production. This deep visibility into the functional quality of applications and services not only helps developers more effectively troubleshoot, but also empowers DevOps to build metrics dashboards, implement continuous reliability and enhance the entire software delivery supply chain. As more organizations aim to innovate faster and deliver a seamless digital experience for their customers, OverOps helps avoid costly downtime that can lead to lost revenue and brand degradation. Backed by Lightspeed Venture Partners and Menlo Ventures, OverOps has over 200 enterprise customers such as Comcast, TripAdvisor and Intuit, and has offices in San Francisco, Atlanta and Tel Aviv.