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A previous post covered how to deploy a Go Lambda function and trigger it in response to events sent to a topic in an MSK Serverless cluster.
This blog will take it a notch further.
Apache Cassandra is a distributed database that does a great job with geo-distributed workloads. K8ssandra, on the other hand, makes it possible to run it on Kubernetes, equipped with backups and dashboarding.
In line with the series of takeaways from DoK Day EU 2022, Matt Overstreet, Field CTO at the DataStax, shares the limits and further mechanisms of running 1000 Cassandra nodes on Kubernetes.
Containerization is becoming increasingly popular for the scalability, agility, portability, faster deliveries, and modernization it provides. But for all the benefits it offers, containerization is not a silver bullet. It poses an operational challenge when managing large clusters. This is where container orchestration steps in.
Container orchestration automates all tasks related to cluster deployment, management, and scaling. And Kubernetes is one such popular platform, with 96% of organizations using it or evaluating it as a preferred container orchestration solution.
In order to bridge the gap of delivering products quickly, all organizations are shifting the base architectural design patterns to distributed system architecture. It's kind of common practice to either bootstrap or transition the existing applications to containerized or server-less architectures.
Managing clustered applications can soon become an overhead when the organization scale and hence increases a dire need for a platform that can support automation of all the tasks related to management, deployment, scaling of these clusters.
In AWS, we have several ways to deploy Django (and not Django applications) with Docker. We can use ECS or EKS clusters. If we don't have one ECS or Kubernetes cluster up and running, maybe it can be complex. Today, I want to show how deploy a Django application in production mode within a EC2 host. Let's start.
The idea is create one EC2 instance (one simple Amazon Linux AMI AWS-supported image). This host doesn't initially have Docker installed. We need to install it. When we launch one instance, when we're configuring the instance, we can specify user data to configure an instance or run a configuration script during launch.
Kubernetes is a popular container orchestration platform that you can deploy on-premise or in the cloud. In this article, you will learn about Kubernetes upgrade options in Google Kubernetes Engine (GKE), Azure Kubernetes Service (AKS), and Amazon Elastic Container Service for Kubernetes (EKS).
A cluster is a unit that includes several Kubernetes pods. A pod is a set of containers, with facilities to allow containers to communicate and share data between them. A cluster consists of the following components:
Services Mesh is one of the “greatest new things” in our PaaS environments. No matter if you’re working with K8S, Docker Swarm, pure-cloud with EKS or AWS, you’ve heard and probably tried to know how you can use this new thing that has so many advantages because it provides a lot of options in handling communication between components without impacting the logic of the components. And if you’ve heard of Service Mesh, you’ve heard of Istio as well because it is the “flagship option” at the moment. Even though other options like Linkerd or AWS App Mesh are also great options, Istio is the most-used Service Mesh at the moment.
You've probably seen some examples about how to integrate Istio with your open source-based developments, but what happens if you have a lot of BWCE or BusinessWorks applications…can you use all this power, or are you going to be banned from this new world?
It is fairly safe to say that Kubernetes is now the go-to solution when it comes to deploying containerized apps. EKS simplifies the creation of a secure and capable K8s environment on the Amazon Web Services platform and makes deploying clusters there that much easier. We’ve covered EKS on several occasions previously here and here to read more. As discussed previously, EKS does have its limitations, but the service is very easy to use, even when you are not a server administrator.
However, EKS and similar services are not the only way you can set up a production-grade K8s environment. Kops, or Kubernetes Operations, has been around for a while, offering CLI tools that make creating and managing Kubernetes installations easy. Kops is designed for those who want complete control over their Kubernetes environment but without the usual headaches.
I have recently started working on a migration process to move our company deployments over to Kubernetes (from Fleet, if you were interested, which was, at the time of deployment, a pretty cutting-edge technology, but it is pretty low level, and you have to provide stuff like load balancing and DNS yourself).
A colleague of mine had already done the hard work in actually spinning up a Kubernetes cluster on AWS (using EKS) and generally most of the boilerplate around service deployment, so having had a general intro and deploying my first service (single microservice deployed as a Kubernetes “service” running inside a “pod”), which mostly just involved copy and pasting from my colleagues examples, my next goal was to deploy our monitoring setup. We currently use Prometheus and Grafana, and those still seem to be best in class monitoring systems, especially with Kubernetes.
Running Docker in production has quickly become the norm. Cloud hosting providers like AWS, GCE and Azure realized that this is what organizations need. Services like EKS and ECS from Amazon offer a completely managed environment for your Docker containers to run on. Through this article, we’ll take a closer look to one of them, Amazon ECS, which is Amazon Elastic Container Service. We are going to describe what AWS ECS is, its functions, and its importance in the current market.
“AWS ECS is a fully-managed, scalable and production-ready platform for running containers.”
If you don’t know what any of this means, then the rest of the article is going to help you with that. Suffice it to, say, "fully-managed" implies you don’t have to pay any third-party software vendor to run your containerized application. "Scalable" means you don’t have to worry, ahead of time, about resource utilization. AWS Cloud will make resources, like CPU, memory and storage, available to you, on demand.