Operations | Monitoring | ITSM | DevOps | Cloud

Deployment is an essential stage of any software development project. With the fast-paced modern agile software development needs, deployment frequency increases rapidly. Although it looks very appealing to often release due to its positive impact on customer satisfaction and improved customer engagement, it is risky at the same time. What if the deployment goes wrong on production?

Welcome to the second post in a series of “How to Scale your AWS Infrastructure”. In the first post, we talked about horizontal scaling, autoscaling, CI/CD, infrastructure automation, containerization, etc. In this post, we will continue the discussion around databases, loose coupling, caching, CDN, etc. Let’s start the discussion with database scaling.

When designing a solution, you should keep future needs in mind. If the number of users increases dramatically in a short period of time, the solution should be scalable enough to handle the new growth. Making systems scalable on cloud is relatively easier as compared to scaling on-premises infrastructure. AWS has provided excellent tools/services to enable your applications for as much scalability as you want.

Let’s face it. Gaining a competitive advantage in the target market is expensive. Even if you have a good idea and its execution plan in mind, operations related to management, storage, networking, service provisioning, security, and application management will cost you a fortune. To say the least, a cutting-edge IT infrastructure, a reliable team, and a strategy for rapid product releases or expansion/scaling is a must for your product’s success.

Do you need to manage hundreds of Kubernetes clusters, or are you just curious to know why you could potentially need more than two clusters, or do you want to see the magic behind it? You are in the right place because you’re about to learn everything there is to know about it.

Kubernetes has become the most widely adopted and popular container orchestrator and, with the help of CNCF and the surrounding community, its reach is increasing every day. The orchestrator currently boasts 140k+ members on its Slack and continues to grow in popularity.

Containerization packages a software component and its environment, dependencies, and configuration into an isolated unit called a container. That makes it possible to deploy an application consistently across different computing environments, whether on-premises or on the cloud. The concept of containerization is more than a decade old.

So you have a Kubernetes cluster, and you are tempted to isolate your production from staging? If you are still unsure, don’t know where to start, or have doubts about the cost, this article should help you shine a light through all of your interrogations.