Since the OpenTelemetry Tracing Specification reached 1.0.0 — guaranteeing long-term stability for the tracing portion of the OpenTelemetry clients, the community has been busy working to get the SDKs and APIs for popular programming language ready to be GA. Next in our ‘Getting Started with OpenTelemetry’ Series, we’ll walk you through instrumenting a Python application and install both the OpenTelemetry API and SDK.

Exemplars are a hot topic in observability recently, and for good reason. Similarly to how Prometheus disrupted the cost structure of storing metrics at scale beginning in 2012 and for real in 2015, and how Grafana Loki disrupted the cost structure of storing logs at scale in 2018, exemplars are doing the same to traces. To understand why, let’s look at both the history of observability in the cloud native ecosystem, and what optimizations exemplars enable.

The current landscape of what our customers are dealing with in monitoring and observability can be a bit of a mess. For one thing, there are varying expectations and implementations when it comes to observability data. For another, most customers have to lean on a hodgepodge of tools that might blend open source and proprietary, require extensive onboarding as team members have to learn which tools are used for what, and have a steep learning curve in general.

Recently we announced in our blog post, "The OpenTelemetry Tracing Specification Reaches 1.0.0!," that OpenTelemetry tracing specifications reached v1.0.0 — offering long-term stability guarantees for the tracing portion of the OpenTelemetry clients. Today we’re excited to share that the first of the language-specific APIs and SDKs have reached v1.0.0 starting with OpenTelemetry Java and OpenTelemetry .NET.

Last year, we released native tracing for AWS Lambda through Datadog APM to provide deep visibility into serverless functions and surface performance issues such as cold starts and errors, without any added latency. But Lambda functions are only one piece of the puzzle in a rapidly growing serverless ecosystem, which includes message queues, data streams, notification services, and more.

Logz.io has always prided itself as a company pushing the use of open source tech. As we have moved to expand our reach with metrics and traces over the past year and a half, we have doubled down on our own contributions to the community. With (distributed) traces in particular, we have been able to forge ahead. Our relationship with the teams at Jaeger and OpenTelemetry have really blossomed (and we are kind of proud to have supported the latter in the run-up to the OpenTelemetry v1.0 release).