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advocate. “If you think of email, for example, it’s not just your Outlook or your inbox. It’s also the network that sends the email, the storage at the server that’s storing all the email.... ITSI works with that service view. So instead of, for example, just looking at server uptime or response rates or things like that, you’re actually seeing what end users see. You’re seeing the real service, the entirety of the service.”
For instance, Glass Tables let users monitor IT services via color-coded visualizations that show overall health plus specifics such as the number of users and number of open help-desk tickets. Deep Dives, an investigative tool that shows KPI search results over time, lets users visually correlate root causes of events in a graphi- cal dashboard.
In addition, the solution is ca- pable of machine learning, which means it can assess what baseline operations look like and predict problems so IT managers can stop
them before they start. Users can
also run correlation searches against learned indicators to pinpoint areas for concern.
“This was key to freeing up their cre- ativity by delivering strategic goals of driving greater automation, removing menial tasks and allowing their talent- ed crew to do more innovative work,” Mann said.
Every morning, the PNNL team starts with an operations meeting to study its infrastructure health dashboard, which offers an overview of all the servers, systems and network devices. It shows any outages that have occurred and lets the team see which problems are high priorities.
“It’s a great source for us to see quick- ly every morning if there are focuses and priorities that we need to attack the day with,” Anderson said.
The team also created an objective
life cycle replacement dashboard to let IT staff get a better understanding of an individual computer’s performance. It generated a scorecard for every com- puter using the data pulled into Splunk. Now, IT workers can replace computers when they stop performing rather than according to a set timetable, said Justin Brown, an IT engineer at PNNL.
Additionally, the team created dash-
“[The infrastructure health dashboard is]
a great source for us to see quickly every morning if there are focuses and priorities that we need to attack the day with.”
boards that show how many visitors a PNNL website had in the past 90 days and how frequently those users visited it. Now, when a site is going to be taken down, frequent users can be notified.
“It gives them a list of emails and everything else so they can quickly put together a personalized message that says, ‘Hey, Jim, I noticed you use our site a lot, and we’re going to be down tomorrow. Just wanted to let you know,’” Brown said. “It’s allowed us to be a lot more personal and taken a lot of the effort out of it as well.”
PNNL uses Splunk ITSI on site, but it’s available for cloud or hybrid envi- ronments, too.
When the lab started using Splunk a few years ago, it took several months to migrate and understand the data and figure out KPIs and dashboards. The IT staff prioritized data migration by look-
ing at the effects on customer service, Anderson said.
Ironing all that out before introduc- ing ITSI made for an easier migration, Brown said. “Now as new data comes in, we have a better handle” on it, he added.
The team is working on adding mo- bile alert capabilities that will use the infrastructure health dashboard to un-
derstand who needs alerts about systems and how best to commu- nicate them, said Arzu Gosney, monitoring and automation tech- nical lead at PNNL. We’re “really going with mobile...and notifying the right people at the right times for the right messages.”
Mann said PNNL’s need for a single view into its IT operations is common in the federal gov- ernment. “What we’re seeing in federal IT, and especially federal government IT, is adoption of new kinds of services,” Mann said, such as cloud computing, micro ser- vices, containerization, open data and APIs.
“We’re seeing a lot of fragmen- tation of IT across these different com- ponents and services and providers and technology, and that’s creating a lack of visibility,” he added.
Because each component of a system keeps an ongoing record of everything that happens — who’s logging on and off, what transactions are being made, whether users run a packet over a net- work — when a problem arises, IT man- agers have to comb through the data from each system.
“It’s a needle-in-the-haystack type of problem except you’ve got 20 different haystacks to look through,” Mann said. “Being able to look through all of those haystacks with one system lets [PNNL] find those outages faster. The really cool thing, though, in my mind, is that it lets them start to predict what’s going to happen. You can start to see trend lines. You can start to see into the future.” •
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