In our series of blog posts based on Automated Containerization, here is another quick read on why Enterprises should invest in containerization of applications instead of Lift-and-Shift approach. Legacy applications can be slow and expensive to maintain. If you use the Lift-and-Shift approach to migrate applications to cloud is relatively inexpensive, but ongoing operating costs can be exactly the opposite. The contention is that applications perform and evolve relative to their environments.

I’m excited to announce that Rancher has signed a definitive agreement to be acquired by SUSE. Rancher is the most widely used enterprise Kubernetes platform. SUSE is the largest independent open source software company and a leader in enterprise Linux. By combining Rancher and SUSE, we not only gain massive engineering resources to further strengthen our market-leading product, we are also able to preserve our unique 100% open source business model.

Rancher and SAP have been working on a dedicated verification of SAP Data Intelligence 3 (SAP DI) on Rancher Kubernetes Engine (RKE) cluster and Longhorn storage platform. This blog will guide you on how to properly install SAP DI on an RKE cluster.

In our latest two-part series blog, Gigi Sayfan, author of “Mastering Kubernetes”, discusses managing complex infrastructure on AWS with an eye towards SLOs (service level objectives). Though there are many ways to discuss the management of infrastructure, in this two-part series, he covers SLOs for AWS, Observability on AWS, Quotas Limits, and Optimizing cost on AWS and in the second part, he uses the lens of Kubernetes to compare and contrast compute infrastructure on AWS with Kubernetes.

This post is the second in our Kubernetes observability tutorial series, where we explore how you can monitor all aspects of your applications running in Kubernetes, including: We’ll cover using Elastic Observability to ingest and analyze container metrics in Kibana using the Metrics app and out-of-the-box dashboards.

Secrets, by definition, should be kept secret, whichever tool you’re using. While there are plenty of best practices for keeping your Kubernetes secrets actually secret, there are some loopholes that can compromise their security, and might be taken advantage of by malicious entities. This post will cover prevalent best practices for securing your secrets on Kubernetes along with some new approaches for secrets management.

The Splunk Security Research Team has been working on Kubernetes security analytic stories mainly focused on AWS and GCP cloud platforms. The turn has come now for some Azure Kubernetes security monitoring analytic stories. As outlined in my "Approaching Kubernetes Security — Detecting Kubernetes Scan with Splunk" blog post, when looking at Kubernetes security, there are certain items within a cluster that must be monitored.

We’re excited to announce a new KubeAcademy course—Building Images. Designed for developers, devops engineers, and architects, this intermediate-level course covers different approaches for building images. Completing it will give you the skills and understanding needed to easily start building images and maintain them over time.

If you’re looking to deploy your services to Kubernetes, Helm works great. However, once you start deploying to multiple environments, developing code as a team, or automating in a CI/CD pipeline, you start to run into limitations with Helm. Codefresh Pipelines using Helmfile has the power and flexibility to address these issues and many others. It’s also one of the best ways to organize your Helm code and values.

This blog series is part of the joint collaboration between Canonical and Manceps. Visit our AI consulting and delivery services page to know more. Kubeflow Pipelines are a great way to build portable, scalable machine learning workflows. It is a part of the Kubeflow project that aims to reduce the complexity and time involved with training and deploying machine learning models at scale. For more on Kubeflow, read our Kubernetes for data science: meet Kubeflow post.