Front-End Troubleshooting Using OpenTelemetry

As with back-end development, observability is becoming increasingly crucial in front-end development, especially when it comes to troubleshooting. For example, imagine a simple e-commerce application that includes a mobile app, web server, and database. If a user reports that the app is freezing while attempting to make a purchase, it can be challenging to determine the root cause of the problem. That's where OpenTelemetry comes in.

This article will dive into how front-end developers can leverage OpenTelemetry to improve observability and efficiently troubleshoot issues like this one.

Why Front-End Troubleshooting?

Similar to back-end development, troubleshooting is a crucial aspect of front-end development. For instance, consider a straightforward e-commerce application structure that includes a mobile app, a web server, and a database. Suppose a user reported that the app is freezing while attempting to purchase a dark-themed mechanical keyboard.

Without front-end tracing, we wouldn't have enough information about the problem since it could be caused by different factors such as the front-end or back-end, latency issues, etc. We can try collecting logs to get some insight, but it's challenging to correlate client-side and server-side logs. We might attempt to reproduce the issue from the mobile application, but it could be time-consuming and impossible if the client-side conditions aren't available.

However, if the issue isn't reproduced, we need more information to identify the specific problem. This is where front-end tracing comes in handy because, with the aid of front-end tracing, we can stop making assumptions and instead gain clarity on the location of the issue.

Front-End Troubleshooting With Distributed Tracing

Tracing data is organized in spans, which represent individual operations like an HTTP request or a database query. By displaying spans in a tree-like structure, developers can gain a comprehensive and real-time view of their system, including the specific issue they are examining. This allows them to investigate further and identify the cause of the problem, such as bottlenecks or latency issues. Tracing can be a valuable tool for pinpointing the root cause of an issue.

The example below displays three simple components: a front-end a back-end, and a database.

When there is an issue, the trace encompasses spans from both the front-end app and the back-end service. By reviewing the trace, it's possible to identify the data that was transmitted between the components, allowing developers to follow the path from the specific user click in the front-end to the DB query.

Rather than relying on guesswork to identify the issue, with tracing, you can have a visual representation of it. For example, you can determine whether the request was sent out from the device, whether the back-end responded, whether certain components were missing from the response and other factors that may have caused the app to become unresponsive.

Suppose we need to determine if a delay caused a problem. In Helios, there's a functionality that displays the span's duration. Here's what it looks like:

Now you can simply analyze the trace to pinpoint the bottleneck. In addition, each span in the trace is timestamped, allowing you to see exactly when each action took place and whether there were any delays in processing the request.

Helios comes with a span explorer that was created explicitly for this purpose. The explorer enables the sorting of spans based on their duration or timestamp:

The trace visualization provides information on the time taken by each operation, which can help identify areas that require optimization.

A default view available in Jaeger is also an effective method to explore all the bottlenecks by displaying a trace breakdown.

Adding Front-End Instrumentation to Your Traces in OpenTelemetery: Advanced Use Cases

It's advised to include front-end instrumentation in your traces to enhance the ability to analyze bottlenecks. While many SDKs provided by OpenTelemetry are designed for back-end services, it's worth noting that OpenTelemetry has also developed an SDK for JavaScript. Additionally, they plan to release more client libraries in the future. Below, we will look at how to integrate these libraries.

Aggregating Traces

Aggregating multiple traces from different requests into one large trace can be useful for analyzing a flow as a whole. For instance, imagine a purchasing process that involves three REST requests, such as validating the user, billing the user, and updating the database.

To see this flow as a single trace for all three requests, developers can create a custom span that encapsulates all three into one flow. This can be achieved using a code example like the one below.

const { createCustomSpan } = require('@heliosphere/web-sdk'); 
const purchaseFunction = () => {     validateUser(user.id);    chargeUser(user.cardToken);    updateDB(user.id); }; 
createCustomSpan("purchase", {'id': purchase.id}, purchaseFunction);

From now on, the trace will include all the spans generated under the validateUser, chargeUser, and updateDB categories. This will allow us to see the entire flow as a single trace rather than separate ones for each request.

Adding Span Events

Adding information about particular events can be beneficial when investigating and analyzing front-end bottlenecks. With OpenTelemetry, developers can utilize a feature called Span Event, which allows them to include a report about an event and associate it with a specific span.

A Span Event is a message on a span that describes a specific event with no duration and can be identified by a single time stamp. It can be seen as a basic log and appears in this format:

const activeSpan = opentelemetry.trace.getActiveSpan(); activeSpan.addEvent('User clicked Purchase button);

Span Events can gather various data, such as clicks, device events, networking events, and so on.

Adding Baggage

Baggage is a useful feature provided by OpenTelemetry that allows adding contextual information to traces. This information can be propagated across all spans in a trace and can be helpful in transferring user data, such as user identification, preferences, and Stripe tokens, among other things.

This feature can benefit front-end development since user data is a crucial element in this area. You can find more information about Baggage right here.

Deploying Front-End Instrumentation

Deploying the instrumentation added to your traces is straightforward, just like deploying any other OpenTelemetry SDK. Additionally, you can use Helios's SDK to visualize and gain more insights without setting up your own infrastructure.

To do this, simply visit the Helios website, register, and follow the steps to install the SDK and add the code snippet to your application. The deployment instructions for the Helios front-end SDK are shown below:

Where to Go From Here: Next Steps for Front-End Developers

Enabling front-end instrumentation is a simple process that unlocks a plethora of new troubleshooting capabilities for full-stack and front-end developers. It allows you to map out a transaction, starting from a UI click and to lead up to a specific database query or scheduled job, providing unique insights for bottleneck identification and issue analysis. Both OpenTelemetry and Helios support front-end instrumentation, making it even more accessible for developers. Begin utilizing these tools today to enhance your development workflow.