I recently read an article in the Wall Street Journal about the need for companies to take into account what their employees’ needs are when rolling out new technologies. Many new technology initiatives fail because employees aren’t involved in the process at some level — whether it’s helping design a solution to their problems or providing regular feedback to their leadership teams on what’s working and what they need to be successful.
If anyone asks: what is a patch? we have to abandon the semantic field of piracy and go to serious and technical things, so to speak.
You’ve probably seen mentions of Docker over the past few years. This guide explains the basics so you can get up and running with Docker for PHP in your local development environment.
In part one of this series, I recapped a good bit of the fireside chat with Kelsey Hightower, Caleb Hailey, and Sean Porter at Sensu Summit 2018. They discussed the evolution of monitoring tools and related DevOps technologies, and how to incorporate new tools into both modern and legacy infrastructure.
Staying in control of your users’ digital experience and their level of satisfaction is the most important thing you can do as a software-based business. Yet, that’s impossible to do without tools that enable you to visualize how customers interact with your app or website from their perspective. They give you the data you need to understand how your webapp or website is performing and avoid slow pages or screens that make your customers run in the direction of your competitors.
One of the questions we see fairly often from Python developers who are using InfluxDB is how to improve the write performance of programs which use the InfluxDB client library. Usually they’re trying to import or transfer large amounts of data and want to make sure it can be inserted into the database quickly enough for their business needs. In this post, we’ll go over the common pitfalls that people encounter, as well as some performance best practices.
A lot of enterprises are evolving their monolithic applications into microservices architectures. In this pattern, applications are composed of fine-grained services that communicate via APIs. Microservices promise, faster development, innovation, cloud scaling, better infrastructure optimization—and happier developers. No wonder this architecture gets so much attention.
For many years I have been using an application called OSSEC for monitoring my home network. The output of the application is primarily email alerts which are perfect for seeing events in near real-time. In this post, I’ll be showing you how to build a good high-level view of these alerts over time with Loki, Prometheus, and Grafana.