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.

Organizations are adopting cloud native and multi-cloud architectures to drive innovation, achieve faster time to market, improve yield, and deliver exceptional experiences to their customers. However, for all the business benefits of modernizing, the process does not come without challenges.

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.

We’re adopting Honeycomb with our teams, however, we’re trying to set up Availability Checks for our services like we’ve done with previous providers. How do we do that in Honeycomb?

Level 4, Proactive Observability With AIOps, is the most advanced level of observability. At this stage, artificial intelligence for IT operations (AIOps) is added to the mix. AIOps, in the context of monitoring and observability, is about applying AI and machine learning (ML) to sort through mountains of data looking for patterns.