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Multi-Cluster Cassandra Deployment With Google Kubernetes Engine (Pt. 2)

This is the second in a series of posts examining patterns for using K8ssandra to create Cassandra clusters with different deployment topologies.

In the first article in this series, we looked at how you could create a Cassandra cluster with two datacenters in a single cloud region, using separate Kubernetes namespaces in order to isolate workloads. For example, you might want to create a secondary Cassandra datacenter to isolate a read-heavy analytics workload from the datacenter supporting your main application.

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Main Features and Benefits of Google Kubernetes Engine

In the modern technology world,  the technical domain is inclining towards cloud computing as it solves various problems such as accessibility and scalability. Most of the time, people use the same resources for running multiple software or programs on various operating systems, which creates inconsistencies. But this issue eradicates with Google Kubernetes Engine or GKE as it includes containers that make programs independent of OS and speeds up the app development process using solutions created with the cloud ecosystem.

GKE is the simplest way for deploying, scaling, and managing apps through Google infrastructure. In this blog, you will understand Kubernetes in detail, GKE’s salient features, and the advantages you can get by implementing it.

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Alexa and Kubernetes: Deploying the Alexa Skill on Google Kubernetes Engine (IX)

Now, we have everything prepared and ready to go to a Kubernetes Cluster in a cloud provider. It is a fact that creating a cluster in any cloud provider manually is a difficult task. Moreover, if we want to automate this deployment, we need something that helps us in this tedious task. In this article, we will see how to create a Kubernetes Cluster and all of its required objects, deploying our Alexa Skill with Terraform using Google Kubernetes Engine.

Pre-Requisites

Here, you have the technologies used in this project: