Getting Started with BigPanda – Incident Analysis

Getting Started with BigPanda – Incident Analysis

By | 2018-04-17T18:52:34+00:00 October 15th, 2014|Blog|

Incident Analysis

Most of the ticketing or issue tracking systems that you’ve been stuck with require you to triage and link related tickets together manually. BigPanda is different. Every incident in BigPanda’s incident feed is created automatically. Each one is based on alerts generated in real time by your monitoring stack. Tools like Nagios, New Relic, Zabbix, Cloudwatch and more are all there – just about every monitoring tool you can imagine. If it makes alerts for IT, NOC, or DevOps teams, we’re working on an integration for it. BigPanda aggregates everything together into a single, intelligent incident dashboard.

Reduce the Noise

A single production incident often manifests itself in multiple alerts. A disk issue might first cause a disk IO alert. That, in turn, is likely to quickly trigger a series of CPU, memory, database and application alerts. Of course, in this case, you don’t want to manage a dozen or more separate issues. They’re all connected to the same root problem. For that reason, BigPanda automatically groups related alerts into consolidated, high-level incidents. BigPanda’s grouping algorithm leverages hostnames, clusters and applications in order to pull related alerts together. Additionally, the algorithm factors in the time between alerts in order to provide you with unique incident insight.

Drill into Alert Detail

Click on any incident in the feed to drill down into it. In the right panel, you will see each of the alerts that compose the incident.

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Clicking on any alert in the right panel will give you even more information about the alert. Full time and duration information as well as any of the tags provided by the source monitoring tool are all at your fingertips.

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Visualize the Incident Lifecycle

Next, click on the Incident Timeline button: lifecyclebutton at the top right of the Alert pane. Using BigPanda’s incident timeline visualization view you can see the cascading timeline of related alerts as they have occured over the life of the incident. Each dot on the timeline represents a status change in one of the incident’s alerts. With the BigPanda incident timeline, you can quickly understand how an incident has unfolded. This is light-years faster than sifting through a hundred seperate alert messages in your email inbox and trying to piece the fragments together manually.

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BigPanda speeds up the process of understanding incidents. Automatically-consolidated alerts in real-time as they unfold are combined with powerful alert lifecycle visibility. This makes BigPanda the best way for IT, NOC and DevOps teams to manage and resolve issues. Next, in part 4 of this series, we’ll discuss how to bring your whole team into the picture so that you’re collaborating together at maximum strength.

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About the Author:

Elik Eizenberg
Elik is CTO of BigPanda. His passions are yoga, wine & highly-scalable data processing systems. Previously he managed dev and ops teams at the Israeli Intelligence Service.