Author: Himanshu Gupta

integrating Cucumber with Akka-Http

Akka Cluster in use (Part 9): Effectively Resolving Split Brain Problem

Reading Time: 7 minutes We can deal with cluster failures manually, as mentioned in our blog post Manually Healing an Akka Cluster. However, it requires a DevOps engineer to be available 24 x 7. This process is very expensive and can be very frustrating (sometimes). Hence, we really need a way via which we can resolve cluster failures in an automated fashion. This is where a Split Brain Resolver Continue Reading

integrating Cucumber with Akka-Http

Akka Cluster in use (Part 8): What is a Split Brain?

Reading Time: 5 minutes In our previous blog post, Manually Healing an Akka Cluster, we have already seen that if we do not handle the failures in an Akka Cluster carefully, then it can lead to disastrous situations like Split Brain. Hence, in this blog post we will learn more about the consequences of the Split Brain problem. What is Split Brain? Split Brain is a destructive condition of Continue Reading

Akka Cluster in use (Part 7): Manually Healing an Akka Cluster

Reading Time: 4 minutes In our previous blog post, Understanding Failures in Akka Cluster, we came to know how an Akka Cluster reacts in case of a failure and what are the reasons behind the failures. Now, whenever a failure will occur in an Akka Cluster, we would need a way to heal the cluster, so that we can restore it back to its normal working condition. Hence, in Continue Reading

Akka Cluster in use (Part 6): Understanding Failures in Akka Cluster

Reading Time: 4 minutes Ideally we would never want our Akka Cluster(s) to fail. Instead we would like to keep them running in a perfect condition. But in real world failures are unavoidable and can be of many types. Like network failures, application failures, and many more. So let’s understand how an Akka Cluster reacts in case of a failure and what are the reasons behind the failures. Changes Continue Reading

Akka Cluster in use (Part 5): Let’s stay in touch via Gossip

Reading Time: 3 minutes In our previous blog post, Managing an Akka Cluster, we learnt how to manage an Akka Cluster via Akka Management. In this blog post, we are going to learn, how the Node(s) within an Akka Cluster communicate with each other via Gossip Let’s Gossip A very popular way to transmit a message is via Gossip 😛 . As it doesn’t need much effort and also Continue Reading

integrating Cucumber with Akka-Http

Akka Cluster in use (Part 4): Managing a Cluster

Reading Time: 3 minutes Hello friends, I hope you all are safe in the COVID-19 pandemic and learning new tools and tech while staying at home. In our last blog post on Akka Cluster, we saw an Akka Cluster in action and learnt about how the node(s) react to new nodes in the Cluster. Now when we know how to create & setup an Akka Cluster, let’s learn, how to Continue Reading

Akka Cluster in use (Part 3): Setup a Local Akka Cluster

Reading Time: 4 minutes Hello friends, I hope you all are safe in COVID-19 pandemic and learning new tools and tech while staying at home. In our last blog post on Akka Cluster, we learnt about the configurations we need in order to form an Akka Cluster. But we didn’t saw it in action. Hence in this blog post, we will see one in action. Step 1: Download the Continue Reading

Akka Cluster in use (Part 2): Forming a Cluster

Reading Time: 3 minutes Hello friends, in our last post on Akka Cluster, we understood the purpose of an Akka Cluster. Now, next step is to understand: How to Form an Akka Cluster? But before we start forming an Akka Cluster, let us understand that: How Actors can communicate with each other over a cluster of machines (JVMs)? Now we know that each Actor in Akka has an Address. Continue Reading

Akka Cluster in use (Part 1): What is Akka Cluster?

Reading Time: 3 minutes In computer architecture, Amdahl’s law is a formula which tells us that how many times faster a program can be executed if it is parallelized. For example, if a program needs 20 hours using a single processor core, and a particular part of the program which takes one hour to execute cannot be parallelized, while the remaining 19 hours of execution time can be parallelized, Continue Reading

Introduction to Logging in R using log4r

Reading Time: 3 minutes One of the most important aspect of an application is Logging. Since logs provide visibility into the behavior of a running app. Hence logs play a vital role in maintenance and enhancement of an application. However, most of us are already aware with the importance of logging. That’s why we add them in our applications. But one thing that we are not aware of is Continue Reading

A Beginner’s Guide to Writing Acceptance Testing for Lagom Microservices with Cucumber

Reading Time: 3 minutes In software development, acceptance criteria is a way via which a client communicates their expectations to engineering team. Also, it acts as a list of conditions upon completion of which a software/app is marked as complete. Since acceptance criteria is an important part of software development, it becomes important to determine that the acceptance criteria is met by the software or not. This sub-discipline of Continue Reading

Flinkathon: Guide to setting up a Local Flink Custer

Reading Time: 3 minutes In our previous blog post, Flinkathon: First Step towards Flink’s DataStream API, we created our first streaming application using Apache Flink. It was easy, clean, and concise. However, the real power of Apache Flink is seen on a cluster, where data is processed in a distributed manner, with the advantage of multi-core/multi-memory systems. So, in this blog post, we will see how to set up Continue Reading

Flinkathon: First Step towards Flink’s DataStream API

Reading Time: 3 minutes In our previous blog posts: Flinkathon: Why Flink is better for Stateful Streaming applications? Flinkathon: What makes Flink better than Kafka Streams? We saw why Apache Flink is a better choice for streaming applications. In this blog post, we will explore how easy it is to express a streaming application using Apache Flink’s DataStream API. DataStream API DataStream API is used to develop regular programs Continue Reading