OverOps 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.
General Availability
OverOps Platform is immediately available. For information on
pricing, visit https://www.overops.com/pricing.