The OpenTelemetry Collector is a powerful tool for processing different types of telemetry data, such as metrics, traces, and logs, all in one place. This is important because traditional observability tools often require separate toolchains, which can be inconvenient and inflexible when changes are needed.

If you use the programming language C# there’s a chance that you’re already familiar with.NET (pronounced ‘dot net’), an open-source application platform supported by Microsoft. C# is the programming language for.NET but the platform can run programs written in multiple languages. Microsoft’s ambition with.NET is to offer developers one platform to solve any problem.

We hear it often—data volumes are growing at a 28% compound annual growth rate (CAGR) year over year, and organizations struggle to manage it all. With no additional money in their budgets, they can’t afford to store more and more data in their SIEM, which in most cases means being uncompliant or, worse, not having older data readily available in the case of a recently discovered breach. I’ve repeatedly heard that the data they have archived is practically inaccessible.

The OpenTelemetry project is changing how organizations approach observability. It aims to standardize monitoring across different systems. OpenTelemetry—commonly referred to as OTel—provides APIs, SDKs, exporters, and collectors. It is making data collection, analysis, and utilization more efficient, leading to better decision-making and technology adoption.

One challenge for the widespread adoption of telemetry pipelines for SRE teams within an organization is knowing where to start when building a pipeline. Faced with a wide assortment of sources, processors, and destinations, setting up a telemetry pipeline can seem like trying to build a Lego set without any instructions. The solution is to provide teams with pre-defined components that provide specific functionality, that they can then use to build pipelines that meet their own requirements.

Alerts that you receive from your observability tool are based on conditions that existed seconds to minutes in the past, because the alert is only triggered after the data has been indexed within the tool. This means that your ability to take timely action in response to the condition is significantly limited, and often your window of opportunity to react is past by the time you receive the alert.

It’s 10:00 p.m. on a Sunday when my 9th grader bursts into my room in tears. She says she doesn’t understand anything about algebra and is doomed to fail. I jump into supermom mode only to discover I don’t remember anything about high school math. So, I do what any supermom does in 2024 and head to ChatGPT for help. These generative AI chatbots are amazing. I quickly get a detailed explanation of how to solve all her problems.