At Elastic, we believe in the power of open source and understand the importance of community. By putting the community first, we ensure that we create the best possible product for our users. With Elastic Security, two of our core objectives are to stop threats at scale and arm every analyst. Today, we’re opening up a new GitHub repository, elastic/detection-rules, to work alongside the security community, stopping threats at a greater scale.

Today’s modern deployment pipeline is arguably one of the most important aspects of an organization’s infrastructure. The ability to take source code and turn it into a production application that’s scalable, reliable and highly available has become an enormous undertaking due to the pervasiveness of modern application architectures, multi- or hybrid-cloud deployment strategies, container orchestration and the leftward movement of security into the pipeline.

This post is part of a series that examines some of the fundamentals of creating, utilizing, and managing Tanzu Kubernetes clusters with the Tanzu Kubernetes Grid (TKG) Service for vSphere. If you need a primer to understand the basic concepts, make sure you read vSphere 7 — Introduction to Tanzu Kubernetes Grid Clusters. And if you haven’t already, this would also be a good time to read An Elevated View of the Tanzu Kubernetes Grid Service Architecture, the first post in the series.

In our article on SLOs, we discussed the need for service level indicators to be relevant to the users’ experience. By consolidating a number of internal metrics into one indicator that reflects the typical use of the service, we can ensure that meeting our SLO means keeping users happy. A good way to think about this is by looking at the user’s experience or journey.

Many enterprises have already adopted Kubernetes or have a Kubernetes migration plan in place, making it clear that the platform is here to stay. While it provides a lot of benefits to its users, to take advantage of them, you need to thoroughly learn Kubernetes and how it works in production. Typically, the most difficult aspects of Kubernetes are learned through experience solving real-world problems.

Velocity, much like the pulse rate or oxygen level of an individual, is an important measure of health for your development team. A low velocity score for recent sprints limits your team's options for delivering value. Sustained failure to deliver to stakeholders can erode trust with those stakeholders quickly. But how do you know exactly what your velocity is and how you can improve it?

Today we’re announcing a new round of funding that brings an additional $27M to help us invest in growing and building Codefresh. When we started, we wanted to revolutionize the way people build and deploy software with continuous integration and delivery. I’m proud to say that we were the first platform to see the game-changing value of containers and Kubernetes.

Cloud cost management is essential for business success, especially in times of business and global volatility. However, gaining quick and clear visibility into all your containerized workloads so you can control and improve the way they are being used, has not been so simple to date. At Spot, we have been addressing these issues and recently introduced cost analysis and showback tools for Kubernetes within our Ocean solution.

In this article we are going to consider the two most common methods for Autoscaling in EKS cluster: The Horizontal Pod Autoscaler or HPA is a Kubernetes component that automatically scales your service based on metrics such as CPU utilization or others, as defined through the Kubernetes metric server. The HPA scales the pods in either a deployment or replica set, and is implemented as a Kubernetes API resource and a controller.

This article will focus on using fluentd and ElasticSearch (ES) to log for Kubernetes (k8s). This article contains useful information about microservices architecture, containers, and logging. Additionally, we have shared code and concise explanations on how to implement it, so that you can use it when you start logging in your own apps. ‍Useful Terminology.