If you’re just getting familiar with full-stack observability and Coralogix and you want to send us your metrics and traces using the new OpenTelemetry Community Demo Application,…
Monitoring distributed systems means collecting data from various sources, including servers, containers, and applications. In large organizations, this data distribution makes it harder to get a single view of the performance of their entire system.
OpenTelemetry helps you streamline your full-stack observability efforts by giving you a single, universal format for collecting and sending telemetry data. Thus, OpenTelemetry makes improving performance and troubleshooting issues easier for teams.
In this article, we will understand what is OpenTelemetry, the data pipeline, components of OpenTelemetry, and the benefits of OpenTelemetry.
OpenTelemetry (a.k.a. OTel) is an open-source observability framework under the Cloud Native Computing Foundation (CNCF). Otel helps developers, operations, DevOps, and IT teams instrument, generate, collect, and export telemetry data. With Otel, you can monitor application health, troubleshoot issues, and gain insights into the system’s overall performance.
In the context of OpenTelemetry, observability refers to the ability to collect, measure, and analyze data about an application and its infrastructure’s behavior and performance. OpenTelemetry provides tools, APIs, libraries, SDKs, and agents to add observability to your system.
With OpenTelemetry, you can instrument your application in a vendor-agnostic way and then analyze the telemetry data in your backend tool of choice, whether Prometheus, Jaeger, Zipkin, or others.
OpenTelemetry helps gather and process Telemetry data through stages or components, from collection to analysis and storage. These stages comprise the OpenTelemetry (OTel) pipeline, often called the telemetry data processing pipeline.
Here’s a high-level overview of how OpenTelemetry works:
The entire OpenTelemetry process can be implemented using the various components as follows:
OpenTelemetry has several vendor-neutral and open-source components, including:
These components work together to specify metrics to be measured, gather the relevant data, clean and organize the information, and export it in the appropriate format to a monitoring backend.
OpenTelemetry’s components are loosely coupled, so you can easily choose which OTel parts you want to integrate. Also, these components can be implemented with a wide range of programming languages, including Go, Java, and Python.
Let’s understand a bit about all these components:
Application programming interfaces (APIs) help instrument your code and coordinate data collection across your system. OpenTelemetry defines a set of language-agnostic APIs that define the structure and behavior of the telemetry data and operations. Also, for each supported programming language, there are language-specific OpenTelemetry implementations, so you can implement these APIs in the language of your choice.
Software development kits (SDKs) implement and support APIs via libraries that help gather, process, and export data. Unlike APIs, however, SDKs are language-specific.
The collector receives, processes, and exports telemetry data to your favorite observability tool, such as Coralogix. While not technically required, it is an extremely useful component of the OpenTelemetry architecture because it allows flexibility for receiving and sending the application telemetry to the backend(s).
The OpenTelemtry Collector consists of three components:
Since the collector is just a specification for collecting and sending telemetry, it still requires a backend to receive, store, and process the data.
OpenTelemetry defines a vendor and tool-agnostic protocol specification called OTLP (OpenTelemetry Protocol) for all kinds of telemetry data. OTLP can be used for transmitting telemetry data from the SDK to the Collector and from the Collector to the backend tool of choice. The OTLP specification defines the encoding, transport, and delivery mechanism for the data and is the future-proof choice.
Now that you have understood what is OpenTelemetry and how it works, let’s understand some benefits that you can get after using OpenTelemetry for your application.
OTel provides a future-proof standard for working with telemetry data in your cloud-native applications. You spend less debugging time and more time delivering business-centric features.
Some of the other benefits that you can see after implementing OpenTelemetry in your applications include:
Observability using OpenTelemetry provides a standardized and comprehensive approach to observability. You can trace requests, collect metrics, and analyze data to monitor system health effectively to gain deep insights into your application’s performance and behavior.
By adopting OpenTelemetry, you ensure that your full-stack observability practices remain up-to-date and aligned with industry standards. As the project evolves, you can benefit from new features and improvements without major rework.
OpenTelemetry enables distributed tracing, allowing you to trace requests as they traverse through different services and components of your application. This setup helps you visualize request flows, identify bottlenecks, and diagnose performance issues in complex, distributed systems.
By using OpenTelemetry, your organization doesn’t need to spend time developing an in-house solution or researching individual tools for your stack. You can even conserve engineering efforts, if you decide to switch to a different vendor or add tools to your system. Your team won’t need to develop new telemetry mechanisms after adding new tools.
OpenTelemetry provides a vendor-neutral, open-source standard for observability instrumentation. You can use the same instrumentation libraries and practices across different programming languages and frameworks.
With OpenTelemetry, you can collect telemetry data from different sources and send it to multiple platforms without significant configuration changes. OTel enables you to send Telemetry data to Coralogix or any backend of your choice, thus preventing vendor lock-in.
OpenTelemetry allows you to control the telemetry data you send to your platforms. You only capture the information you need, reducing unnecessary noise and excess costs. Additionally, filtering makes it easier to also add custom tags to metrics for streamlined organization and searching.
OpenTelemetry also allows exporters to integrate with various observability backends and platforms, including popular solutions like Prometheus, Jaeger, Zipkin, Elasticsearch, and more. So, you can choose any set of tools that fulfill your organizational needs.
Data plus context are key to supercharging observability using OpenTelemetry. Coralogix supports OpenTelemetry to get telemetry data (traces, logs, and metrics) from your app as requests travel through its many services and other infrastructure. You can easily use OpenTelemetry’s APIs, SDKs, and tools to collect and export observability data from your environment directly to Coralogix.
Coralogix currently supports OpenTelemetry metrics v0.19. Combine your telemetry data and Coralogix to supercharge your system’s observability!