Like most areas of IT, DevOps is going through its own reinvention through the intervention of Big Data. Let’s take a look.
Sramana Mitra: Vance, let’s introduce our audience to yourself as well as to Sumo Logic.
Vance Loiselle: Just a quick background on myself. I’ve been in IT for the last 20 years. I started in consulting at Accenture. I was a co-founder of a company in the data center automation space called BladeLogic. In the last decade, I saw first-hand a lot organizations trying to figure out how to automate a lot of the tasks and analysis that they have to do with their IT and applications investments.
I came to Sumo Logic about two years ago. We launched Sumo Logic, which helps address this big challenge of organizations needing to harvest lots of application infrastructure and mobile data to get better insights.
We focus on harvesting the space of big data – specifically on machine data. Any unstructured data that comes from devices – whether they are servers, networks, mobile devices, or the Internet of Things – have lots of data that gets spit out. People want to use that information in multiple ways. One way is to help companies improve the mean time to repair. If you’re an IT organization and you have an issue with your applications or infrastructure, the nirvana is to figure that problem out before that happens and proactively understand the issue. The only place that the answer really exists is in the unstructured or log data that exists in that infrastructure.
Similarly, you hear a lot from the press these days about security breaches and threats. A lot of the attack patterns and threats can be found just by looking at the machine or log data that’s in the firewalls, networks, and servers. We provide customers ways to better manage their applications and infrastructure by proactively analyzing that data, put a better security posture in place by being able to do forensics against the machine data, and at the end of the day, use that same data to do analytics of customers and product behaviors. For example, gaming companies leverage how users are using the games and what parts of the games are popular. We have companies like Gogo Inflight that use our product to understand how customers are using the service on the planes. That’s really the focus of Sumo Logic. It’s taking all of the machine data and being able to search, visualize, analyze and being able to use predictive analytics against it to uncover events that they may not have known about before.
Sramana Mitra: Let’s double click down. First, give us an overview of your target customers in terms of industry segment and size. Then, pick two or three of those and let’s do some use cases.
Vance Loiselle: The interesting thing in our space is that everybody has machine or unstructured data. Everybody has servers, networks, mobile devices, and applications. We tend to be very horizontal in nature. The first vertical we focused on is technology SaaS type of companies – companies that obviously have large technology footprint. The second vertical we focus on is media. They tend to have a lot of unstructured data about what’s going on in their environment and in their customer base. The last one is in e-commerce or retail. They have a lot of data and they can use it for analytics.