Instrumenting your kafka & storm pipeline

Jul 2015

13 Mon

14 Tue

15 Wed

16 Thu 08:30 AM – 06:35 PM IST

17 Fri 08:30 AM – 06:30 PM IST

18 Sat 09:00 AM – 06:30 PM IST

19 Sun

Make a submission

NIMHANS Convention center

Machine Learning, Distributed and Parallel Computing, and High-performance Computing are the themes for this year’s edition of Fifth Elephant.

The deadline for submitting a proposal is 15th June 2015

We are looking for talks and workshops from academics and practitioners who are in the business of making sense of data, big and small.

Track 1: Discovering Insights and Driving Decisions

This track is about general, novel, fundamental, and advanced techniques for making sense of data and driving decisions from data. This could encompass applications of the following ML paradigms:

Statistical Visualizations
Unsupervised Learning
Supervised Learning
Semi-Supervised Learning
Active Learning
Reinforcement Learning
Monte-carlo techniques and probabilistic programming
Deep Learning

Across various data modalities including multi-variate, text, speech, time series, images, video, transactions, etc.

Track 2: Speed at Scale

This track is about tools and processes for collecting, indexing, and processing vast amounts of data. The theme includes:

Distributed and Parallel Computing
Real Time Analytics and Stream Processing
MapReduce and Graph Computing frameworks
Kafka, Spark, Hadoop, MPI
Stories of parallelizing sequential programs
Cost/Security/Disaster Management of Data

HasGeek believes in open source as the binding force of our community. If you are describing a codebase for developers to work with, we’d like it to be available under a permissive open source license. If your software is commercially licensed or available under a combination of commercial and restrictive open source licenses (such as the various forms of the GPL), please consider picking up a sponsorship. We recognize that there are valid reasons for commercial licensing, but ask that you support us in return for giving you an audience. Your session will be marked on the schedule as a sponsored session.

Workshops

If you are interested in conducting a hands-on session on any of the topics falling under the themes of the two tracks described above, please submit a proposal under the workshops section. We also need you to tell us about your past experience in teaching and/or conducting workshops.

Hosted by

The Fifth Elephant

The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more

All submissions

Previous Next

This submission has been added to the schedule

Instrumenting your kafka & storm pipeline

Submitted May 11, 2015

Section: Full Talk Technical level: Intermediate

tips to design your stream processing setup.
what all can go wrong, how to instrument it.

Outline

introduction to a production setup that handles billions of events per week through our home-grown apache kafka client, process the stream with storm - and then aggregate into postgres. will also share pro’s and con’s of building our own kafka client as opposed to re-using one.

Speaker bio

Bosky (@bhaskerkode) leads a product engg team at Helpshift & works on erlang, clojure and golang.

building distributed systems since '06 across edtech, adtech & mobile in erlang, clojure & go.
=> http://in.linkedin.com/in/bhaskerkode & http://slideshare.net/bosky101

Built a kafka producer/micro-service used in production at helpshift, layer, and several other companies.
=> http://github.com/helpshift/ekaf
( Recommended by Apache kafka https://cwiki.apache.org/confluence/display/KAFKA/Clients )

Using storm in production for sentiment analysis, topic extraction, naive bayes classification, etc.
Eager to learn more about best practices in storm deployment/management. Incidentally another part that feeds into this system is in golang, uses the Shopify kafka producer.