Operations | Monitoring | ITSM | DevOps | Cloud

DevOps monitoring didn’t simply become part of the collective engineering consciousness. It was built, brick by brick, by practices that have continued to grow and flourish with each new technological innovation. Have you ever been forced to sit back in your chair, your phone buzzing incessantly, SSH windows and half-written commands dashing across your screen, and admit that you’re completely stumped? Nothing is behaving as it should and your investigations have been utterly fruitless.

I am a Puppet beginner and I’m happy to make the code manager integration happen. I like to play around with my code and test my code changes on my agent nodes. However, the way I’m testing my code is a bit tedious: Save my code change, push into remote repo, run code deploy, and run Puppet on agents. Is there a simple way to quickly test my code? Yes! The answer is using Onceover.

In his HAProxyConf 2019 presentation, William Lallemand (Senior HAProxy Developer) shows how process management in HAProxy has evolved since the beginning of the project; With the advent of systemd, new techniques had to be developed so that users could reload HAProxy safely. The Master-Worker mode simplifies the management of HAProxy processes and introduces interesting features.

Enterprise applications typically sprawl and develop inter-dependencies producing complicated solutions. Ultimately the complexity makes change management complex, error prone, difficult to troubleshoot during service issues and ultimately start impacting the business in multiple ways. To provide the right context when taking up transformation initiatives or addressing service issues one should be equipped with dependency and impact insights. In this video, Rich Lane, a Sr.

Tanay is the Head of Developer Relations at n8n. He has published books on WebVR, virtual assistants on Raspberry Pi, and FirefoxOS. He has been listed in the about:credits of the Firefox web browser for his contributions to the different open source projects of the Mozilla Foundation. I’ve been involved in the DevOps world for a while and yet I finished reading The Phoenix Project only recently. The book piqued my interest in how teams execute their incident response playbooks.

Open-source software started around the millennium and is now one of the cornerstones of modern software development. Open-source projects make their source code available to anyone so that engineers across the world can inspect the code to find bugs or make changes to suit their needs. Today, there are more than 180,000 open-source projects available, according to Wikipedia. We at StackState are big believers in open-source software.

Choosing between blade servers or those intended to go installed in a rack is a small headache that is repeated daily in the complex minds of technicians around the world. What configuration to choose? What can best serve my installation? These are questions that are repeated while they pull out their silvery and silky hairs.

Application performance monitoring (APM) and logging both provide critical insight into your ecosystem. When paired together with context, they can provide vital clues on how to resolve problems with your applications. As the log data you analyze becomes more complex, navigating to the relevant pieces can be tricky using traditional tools. With Elastic Observability (powered by the Elastic Stack), correlating logs with APM is as simple as a few clicks in Kibana.

“If it’s not in Salesforce, it didn’t happen.” You’ve undoubtedly heard it, or perhaps you’ve said it yourself. And why not? Over the past 15 years, Salesforce has redefined the CRM industry, becoming the de facto solution for managing sales, customer service, marketing automation, and analytics functions with its cloud-only approach. As Salesforce’s solutions have expanded so has their user base.

It’s Friday at about quitting time, and my plans for the evening involved a great cocktail, hanging out with friends, and maybe continuing to binge The Office. Sadly, there was a problem. Our alerting system detected an enormous and immediate spike in errors. The error description was along the lines of “table ‘servers’ does not exist” and thousands of customers couldn’t use a large cloud provider’s services.