Google Kubernetes Engine (GKE) is a managed Kubernetes service that makes it possible to run Kubernetes clusters without managing the underlying infrastructure. With GKE, DevOps teams can scale and deploy applications faster with Kubernetes, while spending less time on cluster maintenance and configuration. Obtaining enough insight into GKE is key to proactively preventing downtime and maximizing application performance.

There’s no denying it — Kubernetes has become the de-facto industry standard for container orchestration. In 2018, AWS, Oracle, Microsoft, VMware and Pivotal all joined the CNCF as part of jumping on the Kubernetes bandwagon. This adoption by enterprise giants is coupled by a meteoric rise in usage and popularity. Yet despite all of this, the simple truth is that Kubernetes is hard.

Netlify functions are a quick, easy and powerful tool, but like most serverless platforms, they can be even more difficult to debug and monitor than traditional server applications. It’s a hard environment to precisely recreate locally, there’s no machine you can SSH into in a pinch, and no built-in error notifications. Your code is going to break eventually, and you need the tools to fix it.

This is the first of a series of three articles focusing on Kubernetes security: the outside attack, the inside attack, and dealing with resource consumption or noisy neighbors.

Implementing security best practices for your cloud products might feel like you’re playing a game of chess against a chess grandmaster. You think you need to know the most complex strategies and plan ten moves in advance, but in reality, you’re playing against a 3rd-grade checkers player.

Get the complete picture of the health and performance of your business critical VMware environments. The NiCE VMware Management Pack delivers first-rate monitoring for your business critical, highly dynamical virtualized environments. Even overcoming the specter of global VMware service outages is now viable. Leverage your existing investment, reduce costs, save time and build efficiencies that will last beyond your expectations.

To connect every team in your organization, you need a 'wrapper' that ties the entire organization together, including the lines of business.

Quantifying the value of successful AIOps deployment requires tracking subsidiary metrics within the industry default of mean time to resolution (MTTR). This post breaks out the metrics that form MTTR and divides them into two categories: problem and solution.

Good news everyone! Or at least for all users of Raspberry Pi and the Raspbian operating system! We now provide official packages for Raspbian on ARM chips. You can find those packages on packages.icinga.com.

This month is a big month for PagerDuty—we turned 10 on February 18! I never imagined we’d reach this milestone, honestly. A lot of Dutonians have asked me recently: When you first started PagerDuty, did you ever imagine it would become what it is today?