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Kubernetes is a popular open source platform for container orchestration — that is, for the management of applications built out of multiple, largely self-contained runtimes called containers. By making containerized applications dramatically easier to manage at scale, Kubernetes has become a key part of the container revolution.
Kubernetes has become the project to turn to if you need container orchestration at scale. The open source container orchestration system out of Google is well-regarded, well-supported, and evolving fast. Kubernetes is also sprawling, complex, and difficult to set up and configure.
Our journey was not your regular AWS migration as it involved moving our infrastructure from classic VMs to containers orchestrated by Kubernetes. Our journey was not your regular AWS migration as it involved moving our infrastructure from classic VMs to containers orchestrated by Kubernetes. Limited hardware choices.
This gives rise to the need for container orchestration —a tool that automates the deployment, management, scaling, networking, and availability of container-based applications. To read this article in full, please click here
Before AWS, engineering teams had to scale their own infrastructure. Before Kubernetes, DevOps teams were confined to assembling their own container orchestration and management solutions. Multi-tenant and secure, Frontegg supports multiple frameworks including React, Angular, Vue.js, Node.js, Django, Flask and ASP.NET.
As explained in the first part of this series, we clearly saw why Software-as-a-Service (SaaS) is the way to go when it comes to establishing self-serving applications that can be scaled up and developed fast(er). Scale up (or down) fast Better Latency – Access points all around the world for better performance.
Serverless platforms, such as AWS Lambda and Azure Functions, automatically scale resources based on demand, providing agility and cost optimization. Containers and Kubernetes: Containers have transformed application deployment and management, enabling lightweight and portable software packaging.
The aim was to ease data access across the company and allow data engineering functions to scale. We enabled logical replication AWS RDS instances, deployed Debezium and other Kafka connectors in our Kubernetes cluster which consume all real-time changes in Postgres tables, and stored them in relevant Kafka topics in our AWS MSK cluster.
Software as a Service (SaaS) has quickly become one of the primary models for offering software applications over the internet, and SaaS Development Frameworks provide developers with a methodical way of building and deploying these cloud apps efficiently while guaranteeing scale, reliability, and security of them.
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