Imagine being one of the world’s largest banking institutions and experiencing a critical severity security incident that affects millions of customers and billions of dollars. Now imagine it takes 20 minutes from the first notification to log a response and track down all relevant information from a variety of global systems just to understand the context and nature of the incident.

The quality of database releases relies on thorough initial testing in development with teams needing access to fast, reliable data. While database testing is one of the most challenging aspects of development, processes which utilize database clones can overcome these issues. A database clone is a complete and fully functioning copy of a database that is identical to the original in terms of the metadata and the data.

JMX metrics give solid insights into the workings of your application. Integrating them with Levitate (our time series data warehosue) required us to jump some hoops with vmagent.

To celebrate a 3-year integration anniversary between Cloud 66 and Vultr we’re showcasing some of the changes and improvements that we have implemented in both of our platforms. To show how well our platforms work together, we’re taking a Rails 7 application sample and walking you through how to containerize and deploy that application on Vultr with Cloud 66.

SRE, DevOps and Platform Engineering are important concepts in today's world of software development. There are dedicated teams to manage these areas, each with a unique primary focus, set of responsibilities, tools and metrics used to gauge their performance requirements. This article explains SRE, DevOps, and Platform Engineering, including similarities and differences, and, most importantly, how these teams help streamline modern software development, delivery, and maintenance processes.

Separate “debug” and “release” builds are very common in embedded development. Typically the notion is improved debug capabilities (less aggressive compiler optimizations, more debugging information like logs) vs. highly optimized and hardened production release builds. I’m here to describe disadvantages to this practice, and why it might make sense to consolidate to a single build! Like Interrupt? Subscribe to get our latest posts straight to your mailbox.

We are pleased to announce that a tech preview version of Rancher Desktop with support for Docker Extensions has just been released!

Before we dive into the specifics of each alternative to Datadog, let's address the most critical point: scaling. Datadog is great for users who need to do a little bit of everything, but Datadog's biggest weakness is scaling. Datadog can do logs, APM, time series and more, but scaling time-series metrics, alerts, and servers will cause your monthly bill to escalate. The graph below shows what you pay at Datadog vs. MetricFire, a leading competitor.