With the popularity of microservice architectures, or simply microservices, the demand to understand control flow and monitor distributed systems is becoming more and more of a necessity. This is where distributed tracing has shown to be extremely valuable to efficiently monitor systems, optimize applications, and effectively troubleshoot.
Distributed tracing is a way to observe requests as they proliferate in distributed cloud mediums. Distributed tracing works by marking interactions with identifiers that follow those interactions within networks, microservices, containers, and infrastructures.
These markers provide real-time access into user interactions throughout the front-end of an application all the way to the infrastructural backend. Distributed tracing enables IT teams to find relationships between events and identify any failures or errors in application performance.
Before the advent of complex service-oriented architecture, it was pretty easy to see what went on within monolithic applications. With today’s cloud-based environments and complex architectures, it is far more difficult to identify transactions through the various layers and tiers of an application, which can lead to difficulties in defining the source of latencies, delays, and other application-related issues.
Companies want and need more visibility into their applications and their environments. Distributed tracing allows businesses to quickly and seamlessly identify problems related to their microservice environments.
Let’s look at some of the benefits and drawbacks of distributed tracing and some relevant alternatives in observation and monitoring.
Benefits of distributed tracing:
Helps teams understand application performance issues quicker
Teams can effectively identify causes of issues and resolve those issues
Monitoring and observability allows teams to predict when microservices are susceptible to bottlenecks and other problems within your infrastructure
Improves the user experience and helps companies abide by defined SLA compliances
It helps teams collectively understand issues, which improves communication and collaboration
Increase competitive edge for companies by allowing to get new products and services to market much more quickly
Some common issues of distributed tracing include:
Requires you to generate trace data, which can be difficult early on
Different software might not be structured to accept the instrumentation code that is a prerequisite for emitting tracing data
Distributed tracing activities are often obsolete on arrival because of the challenges surrounding an existing codebase.
It is often difficult to parse through hundreds or thousands of services and decide which data is stored for analysis and which data to let go, as well as for how long you should store said data
Once data is retrieved, is difficult to efficiently translate raw data into concrete insights and actionable strategies
While you can use tracing and logging together, it’s important to know the differences and when it might be time to add distributed tracing to your monitoring process.
Logging is a method for tracking error reports and related data by using logs generated by an app. Logging is primarily focused on what happens within the application, and administrators can use logging to ensure that their applications are running smoothly. They can do this by collecting and storing data logs, tracking events, and utilizing that data to audit various processes within your network or application.
Distributed tracing practices, on the other hand, follow a single transaction throughout its endpoint journey. Distributed tracing relies on the flow context of data within an application, and can be a huge help in reducing the time it takes to detect and resolve any issues. Logging and distributed tracing can be used in unison, and distributed tracing is often only integrated when microservices are involved.
Distributed tracing offers real-time insights into your application and system’s health, and is a reliable source in tracking a request through the many components throughout separate systems. Distributed tracing will allow your IT, SRE teams, and DevOps teams to:
Accurately report on the status and health of microservices and applications to prevent failures
Alert you before errors or failures occur from automated scaling
Provide analytical reporting on end-user interactions, allowing you to stay on top of things like response times, user experience, errors, and other metrics relevant to DCX
Identify and alienate bottlenecks, resolve code-related problems, and help in the debugging process
Sumo logic’s transaction tracing provides cloud-native transactional intelligence for distributed business workflows by enriching and analyzing traces, logs, and metrics in real-time.
Sumo Logic provides a seamless end-to-end experience during the process of managing and responding to production incidents and reducing downtime by streamlining root cause analysis.
Click here to learn more about how Sumo Logic can help you monitor your systems and resolve issues efficiently today.
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