In our pursuit of Better IT, I bring you a post on how important data is to functional teams and groups. Last week we talked aboutnti-patterns in collaboration, covering things like data mine-ing and other organizational dysfunctions. In this post we will be talking about the role shared data, information, visualizations, and analytics play in helping ensure your teams can avoid all those missteps from last week.


Data! Data! Data!

These days we have data. Lots and lots of data. Even Big Data, data so important we capitalize it!. As much as I love my data, we can't solve problems with just raw data, even if we enjoy browsing through pages of JSON or log data. That's why we have products like NPM Network Performance Monitor Release Candidate , SAM Server & Applications Monitor Release Candidate and DPADatabase Performance Analyzer RC,  to help us collect and parse all that data.  Each of those products have specialized metrics they collect, meaning they apply to them and visualizations to help specialized SySadmins to leverage that data. These administrators probably don't think of themselves as data professionals, but they are. They choose which data to collect, which levels to be alerted on, and which to report upon. They are experts in this data and they have learned to love it all.

Shared Data about App and Infrastructure Resources

Within the SolarWinds product solutions, data about the infrastructure and application graph is collected and displayed on the Orion Platform. This means that cross-team admins share the same set of resources and components and the data about their metrics. Now we havePerfStack Livecast with features to do cross-team collaboration via data. We can see entities we want to analyze, then see all the other entities related them. This is what I call the Infrastructure and Application Graph, which I'll be writing about later. After choosing Entities, we can discover the metrics available for each of the entities and choose the ones that make the most sense to analyze based on the troubleshooting we are doing now.




Metrics Over Time


Another data feature that's critical to analyzing infrastructure issues is the ability to see data *over time." It's not enough to know how CPU is doing right now, we need to know what it was doing earlier today, yesterday, last week, and maybe even last month, on the same day of the month. By having a view into the status of resources over time, we can intelligently make sense of the data we are seeing today. End-of-month processing going on? Now we know why there might be slight spike in CPU pressure.


Visualizations and Analyses


The beauty of Perfstack is that by choosing these Entities and metrics we can easily build data visualizations of the metrics and overlay them to discover correlations and causes. We can then interact with the information we now have by working with the data or the visualizations. By overlaying the data, we can see how statuses of resources are impacting each other. This collaboration of data means we are performing "team troubleshooting" instead of silo-based "whodunits." We can find the issue, which until now might have been hiding in data in separate products.




So we've gone from data to information to analysis in just minutes. Another beautiful feature of PerfStack is that once we've built the analyses that show our troubleshooting results, we can copy the URL, send it off to team members, and they can see the exact same analysis -- complete with visualizations -- that we saw. If we've done similar troubleshooting before and saved projects, we might be doing this in seconds.

Save Project.png

This is often hours, if not days, faster than how we did troubleshooting in our previous silo-ed, data mine-ing approach to application and infrastructure support. We accomplished this by having quick and easy access to shared information that united differing views of our infrastructure and application graph.


Data -> Information -> Visualization -> Analysis -> Action


It all starts with the data, but we have to love the data into becoming actions. I'm excited about this data-driven workflow in keeping applications and infrastructure happy.