Blog › Authors › Kumar Saurabh
01.10.2013 | Posted by Kumar Saurabh, Co-Founder & VP of Engineering
Since I was a kid, I had a fascination for chess playing programs – until it got to a point that it became impossible for me to beat a good chess program. And years ago, not long after I gave up my personal fight with them – the last man standing lost to the best chess playing program. Clearly for chess, machine intelligence overtook human intelligence that day.
Another area where machine intelligence has evolved to a point where it’s better than human intelligence is the maps program. I used to have to carry a road atlas with me or risk spending a lot of time just finding my way back on track. It got better a little when you could take a print out, but if I missed an exit or wanted to go for a scenic detour – I again was on my own. Not any more, now I can simply plug in my phone, speak the next destination, and it guides me patiently to that destination – recalculating the route if i miss an exit, heck even warning me when the route is blocked with traffic. These are just couple of examples of how technology evolves to a point – where it would have seemed a sci-fi fantasy 10-15 years ago. And it fundamentally changes how we all go about our lives.
Machine Data Analytics seems like another area desperately in need of a similar evolution. Machine Data Analytics has to evolve into Machine Data Science – and it has to evolve to a point where we depend on it and use it just as I rely on maps and navigation on my cell phone. And Sumo Logic is at the forefront of making that change happen – and there are some fundamental shifts in computing technology – changes which bring that breakthrough within reach.
Cloud has become as mainstream as video streaming. And just like video streaming completely disrupted brick and mortar DVD rental businesses, Cloud has already and continues to bring along fundamentally disruptive technologies to life. So what does Cloud mean for Machine Data? It will be about generating sophisticated insights from the data generated by IT today. Machine data is already the one of the biggest sources of “Big Data” in enterprises. It will be about delivering smarter analytics at scale with the simplicity of a service. As the new year begins, I feel proud and satisfied with what we have accomplished in the last two and a half years. And super excited about the journey ahead – a future is waiting to be invented.
04.12.2012 | Posted by Kumar Saurabh, Co-Founder & VP of Engineering
How exciting can a discussion at 5PM on a Friday be? Very exciting, in fact, if you are talking to industry analyst Vanessa Alvarez (@vanessaalvarez1) from Forrester about Big Data.
Last Friday it turned out that we had tons to talk about together regarding recent developments in the Big Data space. Vanessa has a unique take on Big Data — she thinks “Analytics as a Service” is going to gain a lot of traction soon. And that line of thinking resonates with us a lot.
At Sumo Logic you’ll hear us using terms like Cloud, SaaS, elastic scalability… but the most exciting angle for us has always been the *aaS angle, the fact that our solution is a service. We believe that log analytics should be easy to use, and by lowering the effort it takes to perform log analytics, we can make this kind of technology much more widely accessible. A “Log Analytics as a Service” solution aims to do just that — shorten and democratize the path from data to insights.
So, the real question is not if you are Mac or PC — but rather are you a Mac or Linux guy — when it comes to log management. The choice is — do you really want to build and tweak and operate and maintain your log management system (the big data zoo in other words), or do you just need a solution that delivers log analytics in the most efficient way possible.
We still find a lot of prospects who think that they need to roll out their own log management system using a lot of new stacks (Hadoop, Cassandra, Solr, Hive…). We use similar technologies under the hood at Sumo, but we handle all the operational overhead that comes with this, and we certainly don’t shy away from fixing and optimizing pieces that don’t work, or don’t deliver the performance we need to deliver.
So, if you do not have extremely specialized requirements, is it worth rolling out your own log management systems? Is it worth all the operational overhead? Or would you rather use a service? Curious to hear your thoughts, please feel free to share your thoughts in comments, or shoot me an email at firstname.lastname@example.org
03.23.2012 | Posted by Kumar Saurabh, Co-Founder & VP of Engineering
As anybody who has worked with log data will tell you, one of the major problems is its sheer volume of this data—and the horsepower required to crunch it. And even if you can process it, you’re faced with a second problem: how to make sense of it all. And while there’s been progress on both fronts in the past ten years, the tools and techniques haven’t kept up with the explosion in data volume.
You can spend hours looking into logs, and still only understand a tiny fraction of it. It’s become such an overwhelming task that IT has generally given up on looking at logs proactively. And on the occasions when they do, it’s because something bad has happened, which means they’re in reactive mode, forced to dive CSI-style into the log forensics in the hope of finding the answer.
01.31.2012 | Posted by Kumar Saurabh, Co-Founder & VP of Engineering
On behalf of my co-founder Christian Beedgen and the entire Sumo Logic team, I’m proud to be able to launch the Sumo Logic service. It’s been an intense and productive two years, and we’re extremely proud of what we have accomplished.
Christian and I spent nearly a decade together at Arcsight, the security log management company purchased by HP two years ago. We were amazed, pained and disappointed by how much enterprise software asks of its users. We had seen first hand the song and dance during sales cycles, weeks and months of professional services before you can get value out of your investment, documents and brochures meant more to obfuscate and impress than to help, as well as the glacial speed of innovation. As we talked together, we realized we both had the same goal: to develop enterprise software that was easy to deploy, was powerful yet simple, and that delivered on the promise of actionable insights from IT data. To that end, Sumo Logic was founded.