Cloud application optimization is beyond human scale.
It’s widely accepted that the standard for creating cloud native applications is Kubernetes, and while this software has solved key challenges, it has also introduced new complications. It didn’t take long before operators realized that monitoring a Kubernetes environment is one of the top obstacles that comes along with using this software. With the rise of Kubernetes came a new wave of monitoring tools to help overcome these challenges. Choosing the right monitoring toolkit for you and your team’s Kubernetes environment is a challenge in itself as each tool covers a different specialty, from logging to metrics to data collectors and much more.
Today, we're going to look at a real-world case study that demonstrates how to roll out smarter resourcing for cloud-based apps and the impact this has on solving key challenges like cultural change and embracing automation.
Taking every advantage of Kubernetes automation is critical for operating at scale. Kubernetes as a container orchestrator will ensure pods are scheduled, but if you're looking to use Kubernetes to build a platform that facilitates DevOps speed to market and application elasticity, there's a lot more automation work to be done.
With this blog, we'll give you a quick crash course on the essential Kubernetes automation features:
- Deployment Automation
- Scaling Automation
- Horizontal Pod Autoscaler (HPA)
- Cluster Scaling Automation
Ever felt like building a pipeline to help you with your application deployment process? It's not as difficult as you'd think and we are going to show you just how easy it is! In this blog, we will talk about how to set up a super quick code pipeline and get started with Red Hat OpenShift, so that you can be deploying faster than ever before!
This will be an end-to-end walkthrough of setting up a simple application with code hosted on Github that you can deploy into OpenShift yourself to give you a primer on the ease-of-administration when it comes to getting applications from idea to working prototype without a single SSH or FTP session required.
After announcing IBM’s intent to acquire Turbonomic on April 29th, we are excited to share that the acquisition has closed. There is an enormous opportunity ahead for customers, partners, and our employees as we join forces with IBM to build the future of AI-driven cross-cloud application operations.
It's no secret that the cloud has been a disruptive technology, and as it is still an emerging field of computing in relative terms of the age of some services, there are many misconceptions about what multi-cloud infrastructure really means. Whether you're considering going all-in on one provider or spreading your data across providers for higher availability, we'll cover some of the truths and myths behind this exciting new way to build out your IT infrastructure.
We hear this time and time again, but we’ll say it again here: Applications are the lifeblood of today’s business. The ecosystem of cloud native tools and solutions growing around Kubernetes management are all about building, running, and scaling modern container-based applications. And the Cloud Native Computing Foundation (CNCF) landscape is a testament to strength of the community as well as the growing complexity customers face.
It can also be overwhelming navigating this interactive map, let alone the tools themselves. So, with this blog we thought we’d provide a bit of a guide to what you’re looking at—and ultimately, what needs to be considered when you’re running mission-critical applications on Kubernetes. The categories we will be expanding on are...
Are you looking for a solution to automating application elasticity? Dynamically scaling your services to meet changing demand? Containers enable applications to be architected for elasticity: ready for business in seconds you can spin up services when you need them, spin them back when you don’t. Only pay for what you use. With these goals in mind, an increasing number of organizations are leveraging horizontal pod autoscaler (HPA), which is native to Kubernetes.