Jun 182013

I made a major career decision two months ago to leave my day job and start Flux7 labs, a consulting and training firm. I made this decision because Flux7 Labs allows me to follow my passion of teaching (providing Big Data/NoSQL trainings) and solving challenges in latest technologies like Hadoop, Cassandra, Twitter Storm, etc. Please visit the LinkedIn profile to learn more.

One of the best parts is that I will have more time and incentive to write blog posts. For those of you who read my post on Linked Lists, I am finally doing a performance benchmark to generate data that proves my points. For those interested in Big Data, I am writing a qualitative and quantitate comparison of different Hadoop distributions out there. Exciting times ahead.


About Flux7 Labs

I have setup Flux7 Labs like a research lab in my home office (aka. garage) where my team and I partner with selected clients to work on innovative and new technologies. Our website (http://www.flux7.com) is WIP but you can visit our LinkedIn profile to learn more (followers and likes will be highly appreciated). The work is focused on measuring and improving performance of Big Data and Cloud Computing. We also teach the same topics as on-site/online corporate or independent trainings.

In the lab, we are working on some very exciting projects about measuring, simulating, and increasing performance of Hadoop, Cassandra, CouchDB,  etc using hardware+software techniques in the context of BioInformatics, Renewable energy, banking, and video analytics applications. Our clients/partners include Xockets Inc., Bioaxial Inc., Horan & Bird, Bank of America, Cloudant Inc, and Automaton Inc.

Some philosophy: I have learned a lot to share about this field in the last two years so expect more posts from me on Big Data performance. I am seeing a lot of things people do wrong in their Big Data deployments from an architecture standpoint. I believe this is because the field is new and not everyone thinks about scaling and performance upfront. What is intriguing is that many of the problems and their solutions seen in the Big Data space are the same as what we see in CPU architecture, just at a different scale. For example, challenges I faced at Intel while designing a coherence network for Intel Xeon Phi or during my thesis about the ACMP apply directly in the NoSQL domain without changes. 

Broadly, at Flux7 Labs, we accept projects related to:

  • Big Data (Hadoop, Twitter Storm, and related technologies like HDFS, HBase, Pig, Hive, etc)
  • Databases (CouchDB, MongoDB, Cassandra, MySQL)
  • Cloud Computing (AWS, OpenStack)
  • Video processing systems
  • Anything else thats challenging, innovative, and needs performance

We can handle optimization across all seven performance determinants: app software, OS, compiler, disk, network, CPU, and memory. Having worked in low-power throughout computing hardware for the last seven years, I have a specific knack for Xeon Phi and Microservers (Intel ATOM and ARM-based servers from Calxeda and other vendors) so any consulting/projects in that area are particularly interesting for me.

Any technical or sales/marketing feedback, tips, guidance, introductions, and references will be much appreciated.

Thank you for your time and sorry for putting you through the shameless marketing.

Side note: Shoot me an email if you are in a situation where you are having to decide between your job and venturing into a new career. I made a comparison spreadsheet that you may like. 

  2 Responses to “Meet Flux7 Labs (update + shameless marketing)”

  1. Best of luck .. Knowing you I am sure you would do great in this new venture. It would be interesting to see your excel sheet comparison

  2. 网站弄得挺不错,支持一下!!!!

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