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.

As a fast-moving startup, you don’t have the luxury of spending days figuring out exactly what you need in a Kubernetes cluster. We’ve been there. To help out, we wrote a whole ebook on the blueprint we followed as we built and deployed our own web app in Kubernetes.

Docker is a platform that enables developers to run software in packaged environments called containers. These containers are operating system (OS)-level virtualized elements that share a common Linux server yet have their software, libraries, and configuration files bundled within them. These containers can communicate with each other and exchange information, making it easier to develop and host multiple applications through the CI/CD DevOps methodology.

Every day, application programming interfaces (APIs) are created to speed up the development of modern software applications—from globally-scaled public services to internal endpoints for your proprietary applications. For engineering leaders with teams that write and maintain APIs, however, it can be difficult to know how to prioritize API features, encourage adoption, and respond to feedback from developers. And as we at VMware Pivotal Labs well know, rapid iteration leads to product success.

The previous two posts in this series walked through both the architecture of the Tanzu Kubernetes Grid (TKG) Service for vSphere and how to use it to deploy Tanzu Kubernetes clusters. In this post, we’ll walk through how to take a cluster and scale it on demand. The examples shown are consistent with the same tag-demo-cluster-01 cluster spec used previously.

It comes as no surprise that the demand for Kubernetes is skyrocketing across the industry. According to the CNCF’s 2019 survey, 78% of respondents are using Kubernetes in production today. This growth is contributing to a surge of demand for talent: there are over 100 thousand cloud native job postings across Dice and Indeed alone. The talent pool of people that have worked with Kubernetes and the adjacent technologies is limited and demand is growing.