Operations | Monitoring | ITSM | DevOps | Cloud

For decades, IT operations teams have relied on monitoring for insight into the availability and performance of their systems. But the shift to more advanced IT technologies and practices is driving the need for more than monitoring – and so observability evolved. With infrastructures and applications that span multiple dynamic, distributed and modular IT environments, organizations need a deeper, more precise understanding of everything that happens within these systems.

This article is the final installment in a series that demystifies observability. The first three focused on the history of observability, dispelling myths around observability, and what observability is and what it can offer. In this last article of the series (Check out part 1), I want to offer a complete definition of observability.

Complex, distributed software systems are chatty things. Because there are many components interoperating amongst themselves and with things outside their bounds like users, those components and the systems themselves emit many information signals. It’s the goal of monitoring, logging, and observability (o11y) tools to help the systems’ “stewards,” those developers and operators tasked with maintaining and supporting them, make sense of those signals.

Cloud computing and containerization have brought many benefits to IT systems, like speed to market and on-demand scaling. But it has also increased operational complexity. Applications built on dynamic and distributed infrastructure are challenging to operate and maintain. A robust observability framework can help application owners stay on top of their software systems. In this article, we will introduce SigNoz - an open source observability platform.

Kubernetes is one of the most well-known open-source systems for automating and scaling containerized applications. Usually, you declare the state of the desired environment, and the system will work to keep that state stable. To make changes “on the fly,” you must engage with the Kubernetes API.

It's not like it used to be back in the day! Before CI/CD, we were building on-premises, service-oriented products following system style architecture and we were able to map out the build system and end-to-end process in a PowerPoint or Visio document. Although time-consuming and inefficient, it was relatively straightforward and the build pipeline was unlikely to change drastically. But that's no longer the case.

We recently sat down with Jude Bakeer, one of LogicMonitor’s Solutions Engineers, to talk about the future of IT and Observability. Part of Jude’s role requires her to talk to customers and enterprises every day. Over the years, she’s gathered unparalleled insights into key trends across these industries and segments – from ops teams to C-level executives.

It may seem like ancient history, but there was a time when telecommunications companies only had to worry about connecting customers over landlines. Today, their businesses depend on vast cellular networks to not only provide strong wireless phone coverage in countless locations, but also handle the demands of tablets, computers, and machine-to-machine communications.

In Part I in our series outlining best practices for scaling observability, we reviewed the data analysis capabilities that can help engineers troubleshoot faster during high pressure situations during a game launch. Nobody wants lag time or crashes in their game launch. Similarly, no one wants terminated sessions or for your gamer customers to log off and play a competitor’s game.