Today, Turbonomic is announcing support for AWS GovCloud and Azure Government Cloud and it is generally available to all Turbonomic customers. These clouds have been designed to address explicit regulatory and compliance requirements for U.S. government agencies and customers who have more sensitive workloads they want to deploy in the cloud.
We are pleased to share that Turbonomic, an IBM Company, was named to Inc. 5000’s list of fastest growing private companies for the sixth time! This list represents the most successful companies within the American economy – notable alumni include Microsoft, Intuit, LinkedIn, Zappos, and Patagonia. After receiving this honor in 2015, 2016, 2018, 2019, 2020, and now 2021, we are excited that Turbonomic’s track-record of customer and employee satisfaction, consistent revenue growth, and partnership momentum was culminated by IBM’s recent acquisition of Turbonomic.
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.