Mushtaq Ahmed

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I was interviewed at ThoughtWorks for a position of Business Analyst in 2008. My resume mentioned that I eventually want to work on Scala projects as a developer. In spite of my bizarre intentions, I am grateful that TW made me the offer. Back then almost none in Pune office had heard of Scala. Today in 2013, almost 30 % of Pune office is working on Scala based projects. I became a full time developer in 2011, primarily to have fun coding Scala and also to support teams ramp up quickly on this new platform. I am very happy that directly or indirectly I influenced the technology choices on these projects. Looking forward to seeing even broader adoption of Scala by other TW offices in c...

zookeeper consul akka etcd service discovery crdt scala thoughtworks tmt telescope

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About

Mushtaq Ahmed

Presentations

Service discovery using crdt

Service discovery using crd ts fun-conf

Likes

Capabilities for Resources and Effects

Apache Spark's Built-in File Sources in Depth

Presbyopia/ Methods of Presbyopic Addition Determination (healthkura.com)

Making Data Timelier and More Reliable with Lakehouse Technology

Analysis of Zinc (ScalaSphere 2019)

Next generation actors with Akka

Networks and Types - the Future of Akka @ ScalaDays NYC 2018

Preparing for Scala 3

Building a Tagless Final DSL for WebGL

What Referential Transparency can do for you

Logging in Scala

What To Leave Implicit

N flavors of streaming

Apache Gearpump next-gen streaming engine

CQRS and Event Sourcing for Java Developers

Introduction to Kafka Streams

Deep dive into Apache Kafka consumption

Akka Streams in Action @ ScalaDays Berlin 2016

Data in Motion: Streaming Static Data Efficiently

Apache Spark 2.0: A Deep Dive Into Structured Streaming - by Tathagata Das

Structuring Apache Spark 2.0: SQL, DataFrames, Datasets And Streaming - by Michael Armbrust

Architectual Comparison of Apache Apex and Spark Streaming

Spark and Cassandra 2 Fast 2 Furious

Reducing Microservice Complexity with Kafka and Reactive Streams

Cassandra 3 new features 2016

20160317 lagom sf scala

Stateful Stream Processing at In-Memory Speed

Project Tungsten: Bringing Spark Closer to Bare Metal

HTTP/2 comes to Java

The Future of Real-Time in Spark