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Representation of OpenTelemetry tracking and organizing telemetry data with the help of an observability tool
What is OpenTelemetry?

OpenTelemetry (link resides outside ibm.com), also known as OTel, is an open source observability framework with a collection of software development kits (SDKs), vendor-neutral or vendor-agnostic APIs and tools for instrumentation.

OpenTelemetry technology can generate, collect, export and instrument telemetry data to analyze your platform’s behavior and performance. Developers and SREs can use OpenTelemetry to reach business goals through its standardized process of collecting telemetry data and allowing for better understanding of system behaviors.

IT groups and DevOps professionals must use instrumentation to create an observable system in cloud-native applications. Instrumentation code used to be varied, making it difficult for companies to change backends. It was hard to switch tools because they would need to reinstrument their code and reconfigure new agents to send telemetry data to their new devices.

After seeing the need for a standardized system, Cloud Native Computing Foundation (CNCF) (link resides outside ibm.com) sponsored the OpenTelemetry project to create a standardized way to send, collect and transfer telemetry data to backend observability platforms. OpenTelemetry was born from combining the distributed tracing technology of OpenCensus (link resides outside ibm.com) and OpenTracing (link resides outside ibm.com) into one tool.

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What is Telemetry Data?

To gain a deeper understanding of OpenTelemetry, let’s deep dive into what telemetry data is and how your organization can use it. 

A key part of successful application performance is having observability through access to data.  IT professionals use telemetry data to determine the health and performance of your application. 

OpenTelemetry creates a standard for collecting and transferring telemetry data in cloud-native applications. These metrics can then be analyzed and monitored by your organization to improve your platforms. 

Telemetry data is composed primarily of outputs that are collected from logs, metrics and traces. These are often referred to as the three pillars of observability. 

  • Logs: Logs are a timestamp or record of events in your application. The important events identified using logs show errors or unpredictable behaviors within your system. This information signals to your internal teams that a problem has occurred so you can fix it before more users experience the error. 
  • Metrics: Metrics are typically where you’ll see the first sign of an issue occurring in your system. These give you numerical values or sets of measurements that show your resource utilization and application performance. The three main types of metrics are delta, gauge and cumulative. 

  • Traces: Traces evaluate how requests move through a server in distributed cloud environments. It looks at this by monitoring how an operation transfers from node to node. Traces can only provide limited visibility into application health because it is solely focused on application layers. To get a complete picture of what is going on in your system, it’s also essential to monitor your metrics and logs.

Collecting telemetry data is an important step in the OpenTelemetry and observability process. Next, we’ll discuss how OpenTelemetry is used in a dispersed cloud environment.

What is OpenTelemetry Used For?

OpenTelemetry’s primary goal is to collect and export telemetry data. OTel assists DevOps professionals in debugging and managing applications. Once they have this data, they can make informed coding decisions and adjust as their organization continues to change and grow. 

There are three primary ways by which OpenTelemetry is used in DevOps to solve application problems:

  • Prioritize Requests: OpenTelemetry has the unique ability to create a tier system for requests within your system. This is important because competing requests will be correctly prioritized. 

  • Track Resource Usage: Capture requests between microservers to attribute resource usage by groups. IT professionals can track this resource usage between shared systems.

  • Observability of Microservices: Monitor the health of your application by recording telemetry data from applications in distributed systems. Having this information will help your team optimize and run your application correctly. 

Each of these features helps organizations solve common errors when running applications across cloud-native systems. 

What are the benefits of OpenTelemetry?

There are many benefits to using OpenTelemetry for your open source projects. Each of these benefits will help improve observability and monitoring. These benefits explain why OTel is the future of application performance monitoring (APM).

  • Consistency: The main benefit of OpenTelemetry is the consistency of collecting OpenTelemetry data across different applications. A lack of a unified standard creates problems for Dev Ops professionals and SREs. OTel now saves you time, gives you more observability and collects telemetry data without changing your code. The broad adoption of this technology across organizations has made it easier to implement container deployment. This is similar to the mass embracement of Kubernetes as the standard for container orchestration. 

  • Simplified Observability: OTel simplifies observability because it can collect telemetry data without changing code or metadata. Now, developers don’t have to stick to specific backends or vendors. 

  • Flexibility: Developers can monitor performance metrics and usage from any web browser or device. The convenience of observing your application from any location makes it easier to track your analytics in real-time. 

Overall, OpenTelemetry's primary benefit is that it can help you achieve your optimal business goals. This software enables your organization to understand and fix issues that could negatively impact your customer experience. OpenTelemetry gives you the data needed to stop a problem in its tracks before your service is interrupted.

Learn more: Find out how developers and SREs can utilize IBM Instana and OpenTelemetry to reach business goals

How does OpenTelemetry work?

In a nutshell, OpenTelemetry works by combining an API, SDK, Collector and automatic instrumentation to pull data and send it to its target system. To make your system more agnostic, several steps need to be performed using these components.

An API will create traces by instrumenting your code and dictating which metrics need to be collected. Your SDK will then gather, translate and send that data to the next stage. The OpenTelemetry Collector processes the data, filters it and exports it to a supported backend. 

Components of OpenTelemetry

There are many moving pieces when it comes to making Otel’s data collection successful. Here is an in-depth explanation of the four major components of OpenTelemetry:

  • API: Application Performance Interface (API) enables different software components to communicate with each other. It defines data operations for logging, metrics and tracing data. Essentially, OpenTelemetry APIs decouple an application from the infrastructure, allowing developers to have the flexibility to switch servers that run your cloud. APIs are language-specific (Java, Ruby, JavaScript, Python, and many more).

  • SDK: DevOps professionals can use language SDKs to allow OTel APIs to generate telemetry data in the language of their choice. After they have generated this data, you can export the information to your desired backend. OpenTelemetry SDKs make it possible to connect the manual instrumentation of common libraries with the manual instrumentation of applications. SDKs are the bridge between APIs and collectors. It stands for software development kit.

  • Collector: The OpenTelemetry Collector is made up of exporters, processors, aggregates and receivers for telemetry data. It can support Prometheus, OpenTelemetry Protocol (OTLP), Jaeger, Zipkin and other proprietary tools. The collector can take telemetry data and send it to multiple observability backends. Lastly, it can assist your organization as a processing pipeline and with filtering your data before exporting. This helps with troubleshooting potential issues more quickly.

  • Automatic Instrumentation: It’s important to note that automatic instrumentation differs between varying programming languages. Auto-instrumentation takes numerous tedious manual coding out of the equation.   

Each of these components makes up the framework for why OpenTelemetry is a winning addition to monitoring your application. 

OpenTelemetry versus OpenTracing

OpenTracing is an open source project that assists developers in instrumenting code for distributed tracing through vendor-neutral APIs. This is beneficial because it doesn’t force you to stick with one particular vendor or product.

This project is available in nine different languages, including Ruby, Java and Python. DevOps and IT professionals can use distributed tracing to optimize and debug software architecture code. It is especially useful when dealing with microservices. 

The CNCF created OpenTelemetry by merging OpenTracing and OpenCensus into one platform. There have been over 10,000 contributions from 300 companies since the project was deployed. The encouragement of broad collaboration and additions has created access to a large set of instrumentation that is unmatched in the industry. 

If you are going to choose between the two open source platforms, it would be wise to go with OpenTelemetry since it has more capabilities. 

Is OpenTelemetry the future of instrumentation?

OpenTelemetry is changing the landscape of observability. Similar to Kubernetes becoming the standard for container orchestration, OpenTelemetry is becoming widely adopted for observability. The adoption and popularity of OpenTelemetry will continue to soar because of the OpenTelemetry benefits we stated above.  

The OpenTelemetry project teams continue to work on stabilizing the software’s core components and creating automated instrumentation. Once it is out of the beta stage, it’s projected to take over the observability framework in cloud-native ecosystems. 

Achieve your business goals with Instana and OpenTelemetry

The bottom line is that OpenTelemetry is not an observability backend but a tool that makes collecting and sending telemetry data more streamlined. Instana is the final piece of this equation as the observability tool. OpenTelemetry formats and SDKs can be a migration path for legacy systems and unsupported technologies. 

Our organization is committed to fully embracing OTel to help you achieve business goals through simplified data collection. We are working on giving end users the same visibility that they get with Instana’s AutoTrace through our integration with OpenTelemetry. Try our Sandbox for free today.

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