Operations | Monitoring | ITSM | DevOps | Cloud

In today’s post, we’ll dive into how we, at AppSignal, solved a daunting engineering challenge. Giving you a look into the kitchen, this post will show you how we tested a new database in production without having to worry about errors/downtime. Alright, let’s get cooking!

As part of my job as a Senior Solutions Engineer here at Grafana Labs, I tend to pretty easily find ways out of technical troubles. However, I was recently having some Wi-Fi issues at home and needed to do some troubleshooting. My experience changed my whole opinion on logs, and I wanted to share my story in hopes that I could open up some other people’s eyes as well. (I originally posted a version of this story on my personal blog in January.) First, some background info.

Running and troubleshooting production services requires deep visibility into your applications and infrastructure. Virtual machines running on Google Compute Engine (GCE) provide some system logs and metrics without any configuration required, but capturing application and advanced system data has required the installation of both a metrics agent and a logging agent.

It can be really exciting when your development team is growing fast! But then you soon realize that managing all the developer tools to constantly create new projects or add users is becoming a full-time job. Well, not anymore. At least, not for Rollbar. We’re releasing our HashiCorp Terraform Verified Provider for Rollbar today, built in partnership with HashiCorp.

On one of our monthly check-in calls, the Director of Infrastructure and Operations at one of our largest customers, was telling me how the one big problem he was still trying to solve is optimizing their OPEX or at least make it more predictable. He cited a popular Content Delivery Network (CDN) that they spend millions with as an example. The company had launched a new service and he spoke about how the CDN cost had quadrupled.

There are more than eight hundred pages of documentation for Pandora FMS. The science – and art, I think – of monitoring is very extensive. The needs of a large company are different from those of a medium or small organization. But even two large companies are not the same and their needs may be totally different.

Our product & dev team has been cranking out so many small, medium and big updates the last ~2 months, we thought we'd do a comprehensive sum up. Grab some coffee ☕️ and strap yourself in: the list is quite long!

The current landscape of what our customers are dealing with in monitoring and observability can be a bit of a mess. For one thing, there are varying expectations and implementations when it comes to observability data. For another, most customers have to lean on a hodgepodge of tools that might blend open source and proprietary, require extensive onboarding as team members have to learn which tools are used for what, and have a steep learning curve in general.