Data processing platforms architectures with SMACK: Spark, Mesos, Akka, Cassandra and Kafka

This post is a follow-up of the talk given at Big Data AW meetup in Stockholm and focused on different use cases and design approaches for building scalable data processing platforms with SMACK(Spark, Mesos, Akka, Cassandra, Kafka) stack. While stack is really concise and consists of only several components it is possible to implement different system designs which list not only purely batch or stream processing, but more complex Lambda and Kappa architectures as well.

Cassandra 2.1 Counters: Testing Consistency During Node Failures

For some cases such as the ones present in AdServing, the counters come really handy to accumulate totals for events coming into a system compared to batch aggregates. While distributed counters consistency is a well-known problem Cassandra counters in version 2.1 are claimed to be more accurate compared to the prior ones. This post describes the approach and the results of Cassandra counters consistency testing in different failure scenarios such as rolling restarts, abnormal termination of nodes, and network splits.

In the Wake of Scala Days 2015

Scala Days Amsterdam conference was full of interesting topics so in this post I’ll cover talks on the Scala platform, core concepts for making Scala code more idiomatic, monad transformers, consistency in distributed systems, distributed domain driven design, and a little more. This post came out of the post-conference presentation to my team, so the slides are also available here and contain all the links to related materials and presentations so you can discover more on your own.