OpenTelemetry is a popular open source project to instrument, generate, collect, and export telemetry data, including metrics, logs, and traces. OTel, however, does not provide a monitoring backend — and this is exactly where the Grafana stack comes in. Here at Grafana Labs, we’re fully committed to the OpenTelemetry project and community.

OpenTelemetry is rapidly becoming the most expansive project within the Cloud Native Computing Foundation (CNCF), boasting as many commits as Kubernetes and garnering widespread support from customers. Numerous companies are adopting OpenTelemetry and integrating it into their applications. Elastic® offers detailed guides on implementing OpenTelemetry for applications. However, like many applications, pinpointing and resolving issues can be time-consuming.

Profiling is emerging as a core pillar of observability, aptly dubbed the fourth pillar, with the OpenTelemetry (OTel) project leading this essential development. This blog post dives into the recent advancements in profiling within OTel and how Elastic® is actively contributing toward it. At Elastic, we’re big believers in and contributors to the OpenTelemetry project.

Standardized frameworks play a fundamental role in leveling the playing field and setting the standard within the tech industry, ensuring that everyone has access to the same tools and practices. These frameworks promote best practices and foster innovation and collaboration across different sectors. One example of such a framework is OpenTelemetry, a project that has rapidly gained traction and continued to flourish as an open-source initiative under the Cloud Native Computing Foundation (CNCF).

At observIQ, we are big believers and contributors to the OpenTelemetry project. In 2023, we noticed project awareness reached an all-time high as we attended trade shows like KubeCon and Monitorama. The project’s benefits of flexibility, performance, and vendor agnosticism have been making their rounds; we’ve seen a groundswell of customer interest.

In the fast-pace world of technology, keeping an eye on how well our applications are doing is crucial. Indeed, opentelemetry offers a comprehensive framework designed to capture the nuances of software applications. At the core of this framework lies the opentelemetry Collector, responsible for aggregating, processing, and exporting telemetry data. Why is this important?

Naming things, and specifically consistently naming things, is still one of the most useful pieces of work you can do in telemetry. It’s often overlooked as something that will just happen naturally and won’t cause too much of an issue—but it doesn’t happen naturally, it does cause issues, and you end up having to fix the data in pipelines or your backend tool.

According to Akamai, 83% of web traffic is through APIs. Microservices, servers, and clients constantly communicate to exchange information. Even the Google search you made to reach this article involved your browser client calling Google APIs. Given APIs govern the internet, businesses rely on them heavily. API health is directly proportional to business prosperity. This article covers everything about API monitoring, so your API infrastructure’s health is always in check ✅.

See the results of our 2024 survey of over 500 observability decision-makers to find out where the industry is headed As technology evolution continues at its rapid pace, so does observability. Observability is becoming critical to driving positive business outcomes, and we wanted to understand how users are evaluating trends and their impact over the coming years.

In this post, I describe how to send OpenTelemetry (OTel) data from an AWS Lambda instance to Honeycomb. I will be showing these steps using a Lambda written in Python and created and deployed using AWS Serverless Application Model (AWS SAM).