Operations | Monitoring | ITSM | DevOps | Cloud

Testing in production is one of the most effective—and risky—ways of testing. The ability to use real-world conditions ensures reliability of tests, as no bugs can appear as a result of misconfigurations of the environment. However, using the same environment as your users also has an obvious downside: any bugs discovered by testing will immediately affect users.

Augmented Reality for Industry Repair When augmented reality emerged onto the scene, most people anticipated that it would primarily change consumer industries, like gaming. This idea was seemingly confirmed with the explosive popularity of Pokémon Go, the 2016 AR game that saw gamers capture virtual pokemon out in the real world, using only their phone. But some of the most powerful applications of augmented reality are in industry.

I/O wait is a plaguing issue in Linux. Speaking in layman terms, I/O wait is the time taken by the processor (here, CPU) to complete an input service request. Ideally, our CPU doesn't seem to do any work when it is processing one input request at a time, thus the duration between your input and the output provided by the system can be treated as the I/O wait time.

As a site reliability engineer (SRE), you juggle a lot of moving targets. You keep tabs on your operational environment’s health and maximize service levels, all while trying to scale your business and exceed client expectations. To hold it all together, you’ve likely implemented a hybrid cloud strategy to keep a watchful eye over everything: your on-premises infrastructure, containers, and numerous cloud deployments.

The DevOps industry has been experiencing rapid growth over the past few years. However, with this growth comes a shortage of skilled DevOps engineers who can efficiently implement and maintain the practices. Organizations are facing the challenge of finding and retaining qualified professionals, but there is a solution. Utilizing the right tools and technologies can empower organizations to overcome the DevOps talent shortage.

Managing your own time series database is painful. We’ve moved from servers to services, and yet, monitoring metrics data is primitive. Our managed time series database powers mission-critical workloads for monitoring, at a fraction of the cost.

In a previous post, I explained how we made our Ubuntu image 15 times smaller by chiselling a specific slice of Ubuntu for.NET developers. In this blog, I will provide step-by-step instructions on customising your chiselled Ubuntu base images for any use case. I don’t believe in a perfect container base image anymore.