Reading Time: 3 minutes Now that we have a basic understanding of Akka Cluster Sharding in my previous blog. Let’s have a look at how we are going to implement this and what are the things that we need to keep in our mind while doing that. To shard a specific type of actor we use the cluster sharding akka extension, and we call it as start, we can Continue Reading
Reading Time: 3 minutes When we think of sharding or partitioning it’s typically related to databases. Databases uses sharding to improve resilience and elasticity. The Akka Toolkit provides Cluster Sharding as a way to introduce sharding in your application. Instead of distributing database records across a cluster, we’re distributing actors across nodes in the cluster, and it enables running at most one instance of a given actor at any Continue Reading
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
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
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
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
Reading Time: 4 minutes This article talks about the Lightbend’s Cloudstate which is used for serverless computing.
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
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
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
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
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
