Distributed tracing in Azure using Applications Insights [Pros and Cons]

Why distributed tracing for Azure Integrations is essential?

With distributed tracing, you can find answers to the following questions whenever there is a failure in the request flow “Which specific service is affected? To which request does that problem belong? And What is its origin?”.

Here are other significant advantages of attaining distributed tracing:

• Visualize the relationship between various services and understand how they are related to each other
• Get complete visibility into the data flow across services and track key user actions
• Faster diagnosis and troubleshooting of critical issues (Reduce MTTD & MTTR)
• Spend lesser time getting down to the root cause of failures
• Tracing clarifies where an error occurred, so you can assign it to the appropriate stakeholder for fixing it.

Let’s explore how Application Insights can be instrumented to attain distributed tracing in Azure.

Achieve distributed tracing using Azure Application Insights

Achieving distributing tracing with Application Insights involves three major stages: Instrumentation -> Data Collection -> Analysis & Visualization.

Setting up App Insights (Instrumentation)

Add the appropriate SDK, agent, or library to each service based on its supported language to enable distributed tracing in an Azure application. So, you can configure App Insights by either installing SDKs or leveraging its integration with OpenTelemetry/OpenCensus.

Check out the Microsoft documentation for step-by-step guidance.

Data Collection

Once the instrumentation is complete, Azure App Insights collects span data for each trace (represents the request flow).

Consider an order processing scenario involving Azure services like Logic Apps, Azure Functions, Service Bus, Storage Account, and more.

The SDK creates a trace and span when the application receives an order. It generates a unique Id for every order. As the request flows through the system, each service creates a new span for its work and correlates it using the generated id. On completing the order, SDK pushes the trace data to Application Insights.

Analysis and Visualization

After setting this up, you can quickly analyze and view the relationship between distributed services and how requests are routed. For instance, if the order is processed from Azure Functions to Blob Storage, Application Maps in App Insights help visualize the dependency and determine any hindrance while the request flows.

Pros

• App Insights is an in-built tool available in the Azure Portal
• It helps spot performance bottlenecks and failure hotspots
• It supports sending alerts via emails
• Drill deep into the end-to-end request flow details in case of failure

Cons

• It offers no complete view of the data flowing across your Azure/hybrid application.
• When there is a failure, you will have to dig into individual resources and their logs, which would take too long if that needed to be instantly resolved.
• Although App Insights assists you in mapping the dependency between Azure resources, achieving end-to-end tracking can be difficult.
• To set up App Insights, you should also be well-versed in monitoring each of those resources and be able to plug them together rightly.
• Access to all application resources is necessary for tracing, which might be a security concern when your Azure operations team is in charge of troubleshooting.
• There is no built-in support for different notification channels like teams, Slack, etc.

See how a technology-agnostic platform like Serverless360 BAM solves the above limitations and empowers you to attain end-to-end visibility.

Serverless360 BAM for advanced distributed tracing

Serverless360 is well known for managing and monitoring Azure resources from an application context. On top of this, they have an exclusive module called Serverless360 BAM with features to execute distribute tracing and eliminate failures faster than ever.

Here’s why we say Serverless360 is one of the top distributed tracing tools:

Get a centralized view: The platform provides a complete picture of your distributed Azure services and how the user requests traverse through them.

Locate failures: With all the tracking metrics available in one place, you can quickly identify failures and performance bottlenecks.

Recover from incidents faster: Serverless360 instantly notifies whenever a failure and helps track the root cause of any problems.

Here is the list of other unique features offered by Serverless360 BAM that guarantees to make tracking as seamless as possible.

Track the request flow across distributed Azure services

Serverless360 BAM can track the message flowing through various components in an Azure application. Your business users and the Azure operations teams can leverage this to get a familiar and convenient workflow representation, which depicts the underlying complexities from a non-technical perspective.

With this, you can eventually cut the dependencies on your technical team for remediating trivial and critical incidents.

Spot failures at a glance

The request flow will be tracked at every stage. As shown in the above image, the stages will be represented in different colors, allowing you to distinguish the service that needs immediate corrective actions.

And you don’t have to worry about the request flow failures because all the unsuccessful ones will be grouped into a separate tab, “Action required.” This way, you can avoid searching through multiple requests to identify the failures.

Reprocessing failed message transactions

Reprocess single or multiple transactions with just a few clicks. On top of this, you can even make necessary changes to the failed transactions and reprocess them again. This leaves no room for a business-critical transaction to be stuck in between, eventually ensuring business continuity.

In-built support for functional monitoring

Apart from end-to-end tracking, Serverless360 BAM monitors the request flows and stages from various aspects, including exception, query, and duration. You can attain the following with the in-built support for functional monitoring:

• Detect & get notified of any exceptions occurring within a specified duration.
• Monitor the request flows on queries like failures recorded last week.
• Get proactively alerted when a user request takes longer than expected to complete.

Plug-and-play dashboards to visualize KPI

Serverless360 BAM provides a valuable dashboard that helps make informed decisions by presenting all the tracked data in an easily consumable format. For instance, by looking at the charts in the dashboard, the user may quickly comprehend the number of failed requests and take appropriate actions.

Conclusion

Distributed tracing is one of the core pillars for troubleshooting critical failures in applications built on top of distributed Azure services. So, this blog highlights how tracing could be achieved using App Insights and the significant limitations users face. Explore how an enterprise-grade tool like Serverless360 BAM can be a better alternative for App Insights regarding distributed tracing.

Try out Serverless360 BAM’s 15-day free trial