A highly visible, customer-facing application suffers a severe performance degradation. As the outage wears on, the potential business impact grows. IT springs into crisis mode, and teams of experts are assembled, pulled away from their other tasks. But it can take hours—in this case, 36—before the root cause is identified.
This scenario comes from an actual outage we experienced at HP more than a year ago. A critical application customers used to find up-to-date information about products they’d ordered went down. The HP IT Global Data Services team involved in investigating the incident took 36 hours to determine the root cause, and more than two weeks to clear the backlogged transactions. Since then, IT have been using an operations analytics solution. If they’d been using it when the application went down, they could have found the source of the problem in less than 30 minutes.
That’s a significant improvement, which is why we believe applying Big Data analytics to Operations data should be a priority for the enterprise. If CIOs are going to transform their IT organisations to adapt to today’s new digital business priorities, they will need to embrace analytics solutions to pinpoint critical problems.
Monitoring alone isn’t enough
As IT environments become more complex, it becomes harder to find the root cause of problems. Applications are constantly changing. Today, apps can move across the infrastructure to the cloud, they can automatically scale up and scale down. In addition, your infrastructure is constantly changing. And if you’re like most organisations, you’re dealing with multiple IT service providers.
When a problem occurs it’s impossible to gain the timely insight you need from traditional methods. You may be collecting data from various monitoring tools, but even with multiple tools, you don’t have the visibility you need.
You still need traditional monitoring, of course. But monitoring alone is not enough. To pinpoint the root cause of an incident in minutes, you need to apply analytics to all the data you’re collecting from your various monitoring tools as well as to the so-called “dark” data of your system log files. Only then can you see correlations that tell you where the problem is.
Three ways Operations Analytics saves time and money
Organisations see a number of benefits when they implement an Operations Analytics solution. Here are some of the most important:
Keys to success with Operations Analytics
When we’ve worked with organisations on implementing an Operations Analytics solution, we’re looking to help IT come up with what we call “Big Data maps” for their applications. Basically, we take everything that has to do with an application (your metrics data, your log files, your Venn data, your flow data, and so on) and instrument the solution so that you see all that data together. A Big Data map lets you see trends quickly. Over time, as trends develop, you’ll be able to predict problems instead of reacting to them after the fact.
To be successful with an Operations Analytics solution, take these three considerations into account:
Asking these questions can help you adapt an analytics solution to your organisation’s most pressing needs. The benefit is that you can then use the solution to improve monitoring, application development, troubleshooting, and more.