Data is the lifeblood of any business. Data is used to make decisions, drive innovation, and serve customers. But data can also be expensive to store at scale in the cloud. That's where storage lifecycle configurations come in. An Amazon s3 lifecycle configuration is a set of rules that define
Software development has been and continues to be one of our society's most important building blocks. Software development has gifted us with the mobile phones we use to stay connected, the rockets we send to space and a host of other great innovations. As complex as these innovations become, the
Anyone who has used Kubernetes for an extended period of time will know that things don’t always go as smoothly as you’d like. In production, unexpected things happen, and Pods can crash or fail in some unforeseen way. When this happens, you need a reliable way to restart
Container technology streamlined how you’d build, test, and deploy software from local environments to the cloud or on-premise data centers. But with the benefit of building applications with container technology, there was the problem of manually starting and stopping each container while building multi-container applications. To solve this problem,
When building software, you start in a development environment (your local computer). You then move to another environment(s) (Staging, QA, etc.), and finally, the production environment where users can use the application. While moving through each of these environments, there may be some configuration options that will be different.
Whenever you work on open source projects, you usually maintain your copy (a fork) of the original codebase. To propose changes, you open up a Pull Request (PR). After you create a PR, there are chances that during its review process, commits will be made to the original codebase, which
A few months ago, while deploying an application in Amazon Elastic Kubernetes Service (EKS), my pods crashed with a standard_init_linux.go:228: exec user process caused: exec format error error. After a bit of research, I found out that the error tends to happen when the architecture an
When you deploy Kubernetes, you get a cluster. And the cluster you get upon deployment would consist of one or more worker machines (virtual or physical) called nodes for you to run your containerized applications in pods. For each worker node to run containerized applications, it must contain a container