Scala Futures in Detail – Part 2

In this blog post, we will build a deep understanding about how are scala futures implemented and how are other operations on scala futures implemented

Data at Rest / Data in Transit Encryption

Basics of What , Why and Hows of Data at Rest and Data in Transit Encryption

Effect of Threads on Application Throughput

In this blog post, we are going to understand how does the throughput of a service varies when we change the number of threads doing the tasks in a service

Best Practices for Creating Indexes in MySQL

MySQL is one of the most used databases in the current world. There has been a lot of research and thought gone into making the indexes in MySQL + InnoDB performant keeping the space complexity of these indexes in the same ballpark. In the context of this blog post, we will be going through the … Continue reading Best Practices for Creating Indexes in MySQL →

Could there be a data loss in DRAM while system is up ??

Recently I came across this interesting blog article. It really struck me that RAM sitting on our systems has to be refreshed again and again in a timely fashion to ensure that the contents stored by the memory cells are intact. According to Wikipedia, each bit in DRAM is stored as a presence or absence of electric … Continue reading Could there be a data loss in DRAM while system is up ?? →

Understanding Transactions with MySQL and Slick

How can Full GC cycles on one JVM could impact the latencies on other JVMS sharing the common MySQL RDS

Handling Large Amounts of Data with Parquet – Part 2

Know more about the knobs which parquet offers to tweak it with respect to your application so as to attain maximum benefits of parquet

Handling Large Amounts of Data with Parquet – Part 1

Know about the internal working of parquets and how does parquet achieve world class performance in terms of reads and writes

Exactly Once Semantics with Non-Idempotent Requests

Using PREPARE and COMMIT operations to make sure we achieve exactly once write or updates for non idempotent requests.

Building Replicated Distributed Systems with Kafka

In this blog, we are going to understand how can we easily build fault tolerant stateful services with kafka. Kafka provides us with concept of partitions which can be used for syncing writes among different replicas making sure that primary and replicas are in almost same state.