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Tips for Modern NOCs - Alleviating Incident Routing Bottlenecks

Critical and sev1 incidents are always a priority, but what about those dozens and often hundreds of lower priority ones that often sit in a queue waiting for a first response engineer to get to them? Do you find that no matter how much effort your team puts into minimizing the number of queued incidents, their number always seems to grow? If this sounds familiar – this blog is for you.

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Root Cause Changes: Real Examples of Modern Root Cause Analysis from our Beta Customers

Root Cause Analysis (RCA) is an all-encompassing process. It is usually very complicated and often requires many people with many different skills – all trying to tackle an incident to determine what happened, when, why, how and ultimately who (to blame). There is, however, secret sauce today that can help solve many issues before a “full-scale” RCA process is initiated – and that is Root Cause Changes (RCC).

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Meet Root Cause Changes from BigPanda - IT Ops, NOC and DevOps Teams' Best friend For Supporting Fast-Moving IT Stacks

TL;DR: Fast-moving IT stacks see frequent, long and painful outages. Thousands of changes – planned, unplanned and shadow changes – are one of the main reasons behind this. Until now, IT Ops, NOC & DevOps teams didn’t have an easy way to get a real-time answer to the “What Changed?” question – the answer that can help reduce the duration of outages and incidents in these fast-moving IT stacks. Now, with BigPanda Root Cause Changes, they do.

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Tips for modern NOCs - simplifying IT operations team reporting

The dreaded monthly operations and application meeting is edging near. You know which meeting we’re talking about: the one where all the Ops teams get together to talk about what they are seeing, about application enhancements and modifications, potential improvements, and often – about their frustrations!

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The Pragmatic Buyer's Guide to AIOps Platforms

It’s been said hundreds of times: in the digital era, customers tolerate no downtime. IT operations teams must keep systems running 24x7x365, as the price of downtime is steep. According to Gartner, in 2014, organizations lost $5,600 per minute of downtime, which worked out to well over $300,000 per hour. Today, it’s likely higher, as organizations increasingly rely on technology to power revenue-generating business services.