When Azure AD is configured to record Sign-In activity, Kusto KQL can be used to gain valuable insights. This blog walks through common needs and shows how to visualize them in SquaredUp. Ruben Zimmermann is an Infrastructure Architect at a large manufacturing company who likes Azure, KQL, PowerShell and, still, SCOM.
Since we launched the new SquaredUp last Fall, our focus has been making it easier than it’s ever been to connect to any data source, build beautiful dashboards, and share them with anyone. Today we’re excited to announce a fully redesigned dashboarding experience that does just that. The new dashboarding experience remains backed by data mesh technology, which means your data stays where it lives – it’s simply stitched together and available on-tap from the source.
So you want to spin up a Postgres database on your local machine, but you don't fancy having to install and manage everything manually? Running Postgres inside Docker is a great way to simplify the situation. It lets you: In this article I will explain how to do this step by step.
Prometheus is an open source and free to use metrics collection and storage solution. It's used extensively in the industry for monitoring many different technologies. In this article I will show you how to get Prometheus up and running as a binary, a container running in Docker, and inside Kubernetes.
In software observability, we often talk about three signal types - metrics, logs, and distributed traces. More recently I've been hearing about profiles as another signal type. In this article I will explain the different observability signals and when to use them in a clear and concise way.
Automatic instrumentation is great, but to get the most out of your monitoring you often need to instrument your code. In this article I am going to explain how to instrument a Node.js express app with custom metrics using the Prometheus prom-client package. Although this article specifically addresses Node.js and express, my hope is that the general concepts are applicable to other languages too.
Observability has become a bit of a buzzword in the industry for the last few years. Exactly what "observability" means depends on who you ask, but most people would agree its about both: There's plenty of content out there telling you how to implement observability, or what good looks like. But what about bad observability? What are some anti-patterns to watch out for?
You’re part of a data-driven engineering team. You have a rich, complex, and dynamic set of tools but you’re struggling to discover and share insights from all that data. So, you're looking for a platform that will help unify it all. Naturally, you want to compare Grafana vs. Power BI - the big names. Plus, there's a new player on the block - SquaredUp.
In November/December 2022 I attended AWS re:Invent in Las Vegas. It was certainly an experience for this small town kid from New Zealand, and one that I took a lot away from. While I was at the conference, I took the time to walk around and take notes. In this article I will share the trends that I observed which I think will have an impact on SRE work in 2023 and beyond, including: ...and others.
A new year has started and I've been pondering my hopes and dreams for the year to come. In the world of SRE, observability is the most prominent pillar of my work. So, I decided to drill into the topic of observability and what I'd like to see happen in the industry in 2023. Rather than focusing on any tool, technology, or methodology, I'lll be exploring concepts that can be broadly applied in any organization.
