Distributed tracing is a technique that addresses the challenges of logging information in microservices-based applications.
Monitoring applications with distributed tracing allows users to trace requests that display high latency across all distributed services. This visibility is needed to successfully troubleshoot applications and optimize application performance.
The rapid distribution of applications across a complex landscape of advanced technologies produces new challenges when it comes to monitoring modern IT environments and gaining a comprehensive understanding of individual service performance.
Without gaining a full view of a request from frontend to backend and across services, the process of diagnosing where a problem is occurring, why and what performance issues need to be resolved can eat up valuable time that could be spent on more innovative tasks.
Why do enterprises need distributed tracing?
The transition from a monolithic application to container-based microservices architecture is vital for an enterprise’s digital transformation, but it introduces operational complexity that can benefit from smarter application performance monitoring tools.
DevOps teams need to a gain a holistic, real-time view of application performance and requests as they move through the microservices that make up cloud-based applications. However, collecting and visualizing the record amounts of data generated from distributed systems in serverless environments and creating the instrumentation coding to system applications that is needed to trace this data and achieve end-to-end interoperability can be massively time and labor intensive.
Traditional performance monitoring tools are unable to cut through request noise and can slow down response time. Additionally, they lack the visibility required to get to a root-cause analysis or predict bottlenecks before they impact user experience. Therefore, end-to-end observability of all distributed systems is vital in order to quickly find and resolve performance issues.
Deploying an advanced software-tracing solution that embraces open-source tracing tools can enable full-stack enterprise observability and assure that the applications that power businesses drive positive results.
How does distributed tracing work to debug an application?
Tracing and debugging for an application with functions in a single service can be relatively simple. However, distributed software architecture requires more advanced request tracing communication processes from the multiple data sources and requests involved.
Distributed tracing works by assigning a unique trace ID to a single request. As user requests move through a distributed system, sets of spans are generated for every new operation that is needed on the journey. Numerous functions are performed on the request that generate different connected and/or nested spans — all of which have trace data encoded in them. This can include recorded annotation information like service names, date, time, duration, error messages or any metadata. This trace data, logs and signal information provide a metric that enables developers to not only debug current systems, but to optimize their code for future service improvement.
Benefits of implementing distributed tracing
- Reduce mean time to resolution (MTTR).
- Get immediate root-cause identification of every service impact.
- Improve end-user customer experience by minimizing and quickly troubleshooting issues.
- Effectively measure the overall health of a system.
- Improve collaborations and internal organization alignment for DevOps and SRE teams.
What is OpenTracing?
To take advantage of tracing and metrics, developers need to add instrumentation to an application’s code or instrumentation to an application’s framework. In other words, developers need the libraries integrated into code to deploy a software agent that can receive and process data.
OpenTracing allows developers to add this instrumentation to their application code using neutral-vendor APIs. OpenTelemetry — which is part of the Cloud Native Computing Foundation (CNCF) and originally started as an open-source project called OpenCensus — is a standard in the open-source observability community. GitHub docs are a way the open-source community shares codes, and this collaboration is essential. Systems in a distributed trace need to collaborate for the propagation of trace context for the passing of trace information to remain connected.
Distributed tracing and IBM
Instrumenting code and managing complex applications means you need advanced software solutions to deliver observability to detect issues, provide insight on performance and resources and take automated action to prevent future issues.
IBM Observability by Instana® APM is an application performance management (APM) platform that handles automated instrumentation for many popular runtime environments — such as Java, Node, and Python — without requiring multiple agents. The application-level metrics, tracing and logs are captured in production and analyzed for a synthesized view of your application and infrastructure estate, and there is also native support and seamless integration with OpenTelemetry applications.
Learn more about AIOps and what can be achieved through the combination of Instana’s next-generation APM and observability platform and IBM’s hybrid cloud and AI technologies.
Dive deeper into faster decision-making and see how your ITOps team can resolve incidents in real-time.