Operations | Monitoring | ITSM | DevOps | Cloud

If your organization is frustrated with how long it takes to roll out new applications and updates, they are not alone. Speed-to-market is an obsession at many companies today (see call-out box below), so anything that restricts or slows it down is a problem.

“Cloud-first” has been a government imperative for many years, but the pandemic usurped this strategy, making “cloud-now” a priority. The results have been transformational. The cloud made wide-scale government telework possible, but it’s also given agencies the opportunity to test drive new cloud applications and experience the scalability and security benefits first-hand.

At Spike.sh , we are obsessed with making incident management more accessible to dev teams everywhere. With this goal in mind, we are always looking for ways to reduce the friction while setting up the Spike.sh platform. When we saw customers asking our advice for creating effective on-call schedules and escalations, we knew we had to do more than just good documentation - we needed a way to share best practices with our customers in the product itself.

This tutorial is a follow-up to TurboCharging your Android Gradle builds using build cache . The key focus of this post is the remote build cache, a build speed acceleration technology that can be implemented for both local and CI builds. This is a technology worth knowing about because: Gradle provides a build cache node available as a Docker image. You can host this image in a number of ways.

The software design is perhaps the most important aspect that directly influences the ability to scale up, workload performance, the availability of the software, and the longevity of the software itself. It is also important to understand that traditional monolithic designs are still usable and widely used to fulfil many everyday goals. However, now we have a different problem. With the rapid growth of digital services , virtualization services, and an increasing dependency on cloud-based services.

Even seemingly minor math bugs in software code can have outsize consequences.