Streamlining IT operations with BigPanda and ServiceNow

Hello IT Ops teams using ServiceNow. 

Does the following sound familiar? 

You have a complex, hybrid and dynamic IT stack – with your cloud infrastructure changing by the minute and your container infrastructure changing by the second. Your monitoring and observability tools provide excellent visibility into your infrastructure, your applications and your services, but the dynamic environment in which they operate causes them to generate large volumes of heterogeneous machine data, with thousands of alerts a minute.  You are working hard to sift through these alerts, trying to detect, analyze, escalate and resolve outages affecting your applications and related services – relying on ServiceNow’s ITSM suite, including its CMDB and ticketing, to help you do so. 

You’re likely doing this in one of two ways: 

(a) by manually creating tickets – which, as we know, can be a laborious, inefficient and error-prone process, or

(b) by using ServiceNow’s built-in ITOM Event Management module (or other automatic ticket creation tools) to aggregate and correlate alerts into incidents, and then automatically create tickets. While this approach is obviously better, it just eliminates the manual effort associated with creating tickets, and you’re still faced with a large and unmanageable number of them.

Another major obstacle you face when using your ServiceNow deployment with your modern IT stack is its ability – or lack thereof – to match your incidents to the changes that caused them. That’s because ServiceNow’s change management module was originally built for the slow, planned and manual release cycles of the previous decade. Back then, If an incident or an outage was caused by a change being tracked in ServiceNow, it wasn’t hard to look at ServiceNow and identify the offending change. 

Today your teams are embracing continuous delivery, pushing code changes to production hundreds of times a day using tools like Jenkins, GitLab and Bamboo. This makes it difficult to track them inside ServiceNow change management, and to identify which of them caused an incident. And with changes causing the majority of incidents today (85% according to Gartner*), you find yourself in a tight spot more often than not. 

If all this sounds like what you and your IT Ops teams experience every day, you’re not alone.

 

This is where the BigPanda Event Correlation and Automation platform, powered by AIOps, can help.

BigPanda – integrated with your ServiceNow CMDB, ServiceNow Incident Management and ServiceNow Change Management modules – enhances and augments your deployment to provide you with three key benefits:

1) Ticket reduction and automation for high-volume monitoring data.

Leveraging a proprietary best-in-class machine learning engine, BigPanda correlates your thousands of monitoring alerts into high-level incidents, reducing alerts by up to 99%. BigPanda then automatically creates tickets within ServiceNow for each of these incidents, and in so reduces your ticket volume by the same 99%. On top of that, BigPanda’s bi-directional syncing keeps these tickets up-to-date as the incident evolves.

2) Service mapping for dynamic infrastructures.

BigPanda’s unique Real-time Topology Mesh ingests your incomplete ServiceNow CMDB data, and merges it with real-time topology data from your best-of-breed configuration management tools, cloud platforms, virtualization platforms and APM tools. This provides you with a full-stack, real-time topology model that helps you drive high-quality event correlation, even in highly dynamic environments.

3) Root cause analysis for continuously delivered applications.

BigPanda collects changes from ServiceNow’s change management module, as well as from your continuous delivery pipelines, change logs and audit feeds. It then uses its unique AI-driven Root Cause Changes capability to match your incidents to the changes that may have caused them, and surfaces these root cause changes affecting your continuously delivered apps. This helps your IT Ops teams and/or developers to easily and quickly identify and roll back these changes to resolve your outages.

Here’s a short video to summarize all this:

 

Does this sound like something your IT Ops teams, and your organization, could benefit from? We invite you to contact us and learn how some of the world’s largest enterprises are using ServiceNow and BigPanda together to prevent and resolve outages in their fast-paced IT stacks.

*”Causal Analysis Makes Availability and Performance Data Actionable”, Gartner report, 7 Oct 2015