Operations | Monitoring | ITSM | DevOps | Cloud

Kubeflow v1.0 was released on March 2, 2020 Kubeflow and there was much rejoicing. The banner announcement, “Cloud-Native ML for Everyone,” while clearly hyperbole, is evidenced by the streamlined command-line interface (CLI), informative and intuitive dashboard and comprehensive cloud provider documentation. Compounded with a best-in-class product suite supporting each phase in the machine learning (ML) lifecycle, Kubeflow stands unrivaled in the arena of ML standardization.

Google, the original developer of Kubernetes, also provides the veteran managed Kubernetes service, Google Kubernetes Engine (GKE). GKE is easy to set up and use, but can get complex for large deployments or when you need to support enterprise requirements like security and compliance. Read on to learn how to take your first steps with GKE, get important tips for daily operations and learn how to simplify enterprise deployments with Rancher.

Most Kubernetes deployments live on the cloud. According to the CNCF, while 63 percent of companies use AWS for Kubernetes, 29 percent are deploying Kubernetes on Azure, and the number is rapidly growing. Microsoft Azure provides mature Kubernetes tools, primarily the Azure Kubernetes Service (AKS). In this post, we’ll show you how to run your first Kubernetes cluster on AKS, and how to manage enterprise Kubernetes deployments on AKS with Rancher.

Rancher is the enterprise computing platform to run Kubernetes on-premises, in the cloud and at the edge. It’s an excellent platform to get started with containers or for those who are struggling to scale up their Kubernetes operations in production. However, in a world increasingly dominated by public infrastructure providers like Google Cloud, it’s reasonable to ask how Rancher adds value to services like Google’s Kubernetes Engine (GKE).

Editor’s note: Rancher Labs’ William Jimenez provides an introduction to CIS Scan. Then Saiyam Pathak takes over with a hands-on demo. Cluster security is critical to any successful Kubernetes strategy. Recent research by AimPoint revealed that 44 percent of respondents had delayed application production due to security concerns around Kubernetes containers. Yet securing Kubernetes is a complex machine with many moving parts, integrations and knobs and levers.

Recently the leadership at Rancher Labs challenged all of us to think about ways we can contribute to the community during this current crisis. Coming up with ways to help in such an overwhelming situation is quite daunting. Since most needs are medical related, finding ways to apply software isn’t obvious. When I heard about Folding@home’s (FAH) efforts to reprioritize their computing resources toward COVID-19 research, I was immediately curious.

Containers are becoming the new computing standard for many businesses. New technology does not protect you from traditional security concerns. If your containers handle any sensitive data, including personally identifiable information (PII), credit cards or accounts, you’ll need to take a ‘defense in depth’ approach to container security. The CI/CD pipeline is vulnerable at every stage, from build to ship to runtime.

Delivering rapid innovation to your users is critical in the fast-moving world of technology. Kubernetes is an amazing engine to drive that innovation in the cloud, on-premise and at the edge. All that said, Kubernetes and the entire ecosystem itself changes quickly. Keeping Kubernetes up to date for security and new functionality is critical to any deployment.

Today I’m excited to announce Fleet, a new open source project from the team at Rancher focused on managing fleets of Kubernetes clusters. Ever since Rancher 1.0 shipped in 2016, Rancher has provided a central control plane for managing multiple clusters. As pioneers of Kubernetes multi-cluster management, we have seen firsthand how users have consistently increased the number of clusters under management.

We’ve heard from many of our customers and prospects that they love Rancher but just don’t have the staff and expertise to operate the platform. Figuring out the compute, storage and networking architecture can be a challenge. Performing upgrades, backups and troubleshooting can also be time consuming. Monitoring the environment and knowing when to scale up or down, horizontally or vertically, is yet another thing to worry about.