2022 Gartner® Magic Quadrant™ for APM and Observability Read the Report

Praveen Rangnath

Posts by Praveen Rangnath


Show Me the VPN Logs!!!

Show Me the Money!!! Show Me the VPN Logs!!! Move over Tesla automobile logs, it’s time for Yahoo VPN logs to get their moment in the sun! Just as soon as log data dropped out of the headlines they came right back, as Yahoo CEO Marissa Mayer announced a ban on telecommuting – with the decision reportedly driven by analysis of the company’s VPN log data. From the VPN data, it’s said that the Yahoo CEO determined too many remote workers were not pulling their weight, as evidenced by their lack of connecting to the VPN and accessing Yahoo’s IT systems. Certainly, VPN logs don’t tell the entire story around telecommuter productivity, but they are an important data point, and the information contained in those logs certainly was compelling for Ms. Mayer. There is of course a bigger picture to this, and it starts with the fact that this is not the first time VPN logs are in the news. (Not even the first time this year!). See this blog post from the Verizon RISK team, where they helped their client identify a developer who took global wage arbitrage to an extreme; he collected his six-figure paycheck in the USA and then outsourced his own job to a Chinese consulting firm, paying that firm a fraction of his salary to do his job for him! How did he do this? Simple: He FedEx’d his RSA token to China. How did he get caught? Simple: They found him sitting in his office while the VPN logs showed him in China. Busted. All thanks to the logs. At the highest level, what do the Tesla, Yahoo, and wage arbitrage stories tell us? Simply put, log data is immensely valuable, it’s increasingly becoming front and center, and it’s not going away anytime soon. We at Sumo Logic couldn’t be happier, as this is further public recognition of the value hidden in machine data (the biggest component of which is log data). We’ve said it many times, log data holds the absolute and authoritative record of all the events that occurred. That’s true for automobile logs, server logs, application logs, device logs, and yes Mr. Developer who outsourced his job to China… VPN logs.

March 7, 2013


A Few Good Logs

“I Want The Logs!” In the midst of this week’s back and forth between Tesla, the New York Times, and various other media outlets and bloggers, Greylock Data Scientist in Residence (and Sumo Logic Advisory Board Member) DJ Patil posted a tweet that caught my eye: “Love that everyone is using data to have a conversation. It’s about getting to the right answer.” DJ is 100% correct, and throughout this Tesla/NY Times debate, we at Sumo Logic are thrilled to see the public recognition of the importance of log data — as a source of the truth. Yes, log data needs to be properly analyzed and understood (as the debate makes evident), but what clearly emerged from the debate is the truism that that log data holds the absolute and authoritative record of all the events that occurred. It’s evident; just see how the discussion revolves entirely around understanding the logs. The Bigger Picture There is a bigger picture to this debate, which is that log data is generated everywhere, whether it be from the car you drive, the energy meter beside your home, the device you’re using to read this blog, the server delivering this content, the network delivering this content, the device I’m using to write this post… I could go on and on. And in the same way log files generated by a car hold the answer to whether it ran out of power or met range estimates, log files generated by applications, servers, network and virtualization infrastructure hold the answer to whether revenue generating applications are up and adequately performing, if customers are utilizing a newly developed feature, or if any part of an IT infrastructure is slow or experiencing downtime. It is important to remember — these are all business critical questions. And just like Tesla needed to analyze their logs to defend their business, every enterprise, large or small, needs to be able to easily analyze and visualize their log data to ensure the health of their business. Cars, Enterprises, and Terabytes Before moving on, let’s not forget, enterprises are not cars, and data generated from enterprises is different from data generated by cars, particularly along three dimensions: volume, variety, and velocity. You got it… the 3 Vs of Big Data. Cars do not (or at least do not yet!) generate up to terabytes of unstructured data per day. Enterprises with large distributed IT environments do. This is where Sumo Logic comes in. Sumo Logic is based on the recognition that enterprises need to be able to easily analyze and visualize the massive amounts of amounts of data generated by their infrastructure and business, and that current on-premise tools just can’t scale. Today, enterprises generate as much data in 10 minutes as they did in the entire year in 2003. It is therefore not surprising that legacy on-premise solutions just can’t keep up. Sumo Logic makes it possible for enterprises of all sizes to find the truth from their data. And we do so without adding any operational overhead for our customers; Sumo Logic is a 100% cloud-based service. Large enterprises like Netflix and Land O’Lakes use Sumo Logic. Fast growing enterprises like PagerDuty and Okta do as well. You want some answers? You have some logs? We can handle the logs. Contact us here, or try it out for yourself by signing up for Sumo Logic Free.

February 15, 2013


We hire Data Scientists... so our customers don't have to

At last week’s DataWeek conference in San Francisco, Stefan Zier, Manager of Sumo Logic’s cloud and infrastructure group, spoke on a panel titled “Analytics-as-a-Service”. During that session, the moderator, Karthik Kannan of VMware, asked if having Data Scientists on staff was a necessity or a luxury. Stefan gave a brilliant answer, stating that at Sumo Logic, we hire data scientists so our customers don’t have to. Read on to see why… At Sumo Logic, we have built a highly scalable cloud platform to enable organizations to instantly derive operational and business insights from their log and machine data. Log and machine data (for example application logs, Apache logs, VMware logs, server logs, IIS logs, Linux logs, network logs, etc.) are the largest components of Big Data, and one key challenge of Big Data is that it is too large for humans to know what questions to ask of it. Therein comes our Data Scientists, building machine-learning algorithms to instantly deliver insights to customers from terabytes of their log and machine data. In a nutshell, our Data Scientists are taking what is generally seen as their domain (the ability to extract insight from massive amounts of data), and putting it into the hands of all --- business and IT executives, business and data analysts, operations managers, developers, etc. As a result, executives can make critical IT and business decisions from the freshest set of data, operations managers can monitor their environment in real time, and developers and operations personnel can troubleshoot production applications 90% faster than they were able to previously. Curious to know more? Check out our website where you can read about our patent-pending LogReduceTM, and see a recent blog post by one of our co-founders and VP of Analytics. Or see for yourself by signing up for Sumo Logic Free, a fully-featured version of our enterprise solution allowing up to 3.5GB to total storage.