OpsClarity Visualizes Both Application and Infrastructure Monitoring
When organizations start to think about moving their applications into container-based architectures, the issue of how to monitor these services when working at scale has become a challenge. OpsClarity hopes to help ease this transition with a combination of operations analytics and monitoring that brings together application and infrastructure monitoring.
“The traditional paradigm of static monitoring infrastructure wouldn’t work given the complexity of today’s applications,” said OpsClarity CEO Dhruv Jain.
By focusing on both application and infrastructure monitoring, the OpsClarity Intelligent Operations Platform is able to synthesize insights and data from both these aspects of application development. OpsClarity’s SaaS service collects data from within a container’s internal architecture. The resulting output is similar to an application map that resembles architecture depiction on a whiteboard. The feature offers users a ‘street level’ view of an app’s architecture that updates continuously from the host level alongside information from other data sources.
Software teams need to not only have a solid infrastructure overview, but they must be able to see application types, dependencies, troubleshoot, and network services together.
“We believe data analytics is useless without visualization,” said Jain. With a focus on visualization of data, OpsClarity is able to focus on an entire system state. The anomaly detection and visualization tools offer a higher signal-to-noise ratio with the ability to troubleshoot common issues.
“Looking at marketing software 10 years ago — Every customer attribute was sliced and diced to create a pivot table. Now, machine-based learning has changed marketing. We’re automatically creating new clusters of similar users, getting answers as opposed to raw data. The same paradigm applies to operations,” said Jain.
Underneath the hood, OpsClarity is written primarily in Scala. It also makes use of machine learning libraries, graphing libraries, and large stream processing infrastructure. On the front end, OpsClarity uses Angular.js with Node.JS used server-side.
This framework allows for what Jain refers to as intuitive, hyper-interactive data visualization. Automation allows for OpsClarity users to get value instantly. Both data collection and configuration are automated processes, reducing steps that an ops manager would otherwise have to undertake to get the service up and running.
With the rise of microservices, presenting operations in a linear, static format is no longer suitable. Monitoring data must be interactive, rather than a presentation of columns of numbers left for the administrator to analyze. It is this distinction that will truly shape the next generation of monitoring software and services.