Explore traces

Distributed tracing in Axiom allows you to observe how requests propagate through your distributed systems. This could involve a user request going through several microservices, and resources until the requested information is retrieved and returned. By tracing these requests, you're able to understand the interactions between these microservices, pinpoint issues, understand latency, and trace the life of the request through your app's architecture.

Traces and spans

A trace is a representation of a single operation or transaction as it moves through a system. A trace is made up of multiple spans.

A span represents a logical unit of work in the system with a start and end time. For example, an HTTP request handling process might be a span. Each span includes metadata like unique identifiers (trace_id and span_id), start and end times, parent-child relationships with other spans, and optional events, logs, or other details to help describe the span's operation.

Trace schema overview

This guide explains how you can use Axiom to analyze and interrogate your trace data from simple overviews to complex queries.

Browse traces with the OpenTelemetry app

The Axiom OpenTelemetry app automatically detects any OpenTelemetry trace data flowing into your datasets and publishes an OpenTelemetry Traces dashboard to help you browse your trace data.

Navigate the app

• Use the Filter Bar at the top of the app to narrow the charts to a specific service or operation.
• Use the Search Input to find a trace ID in the selected time period.
• Use the Slowest Operations chart to identify performance issues across services and traces.
• Use the Top Errors list to quickly identify the worst-offending causes of errors.
• Use the Results table to get an overview and navigate between services, operations, and traces.

View a trace

Click a trace ID in the results table to show the waterfall view. This view allows you to see that span in the context of the entire trace from start to finish.

Customize the app

To customize the app, use the fork button to create an editable duplicate for you and your team.

Query traces

In Axiom, trace events are just like any other events inside datasets. This means they're directly queryable in the UI. While this is can be a powerful experience, it's important to note some important details to consider before querying:

• Directly aggregating upon the duration field produces aggregate values across every span in the dataset. This is usually not the desired outcome when you want to inspect a service's performance or robustness.

• For request, rate, and duration aggregations, it's best to only include the root span using isnull(parent_span_id).

Waterfall view of traces

To see how spans in a trace are related to each other, explore the trace in a waterfall view. In this view, each span in the trace is correlated with its parent and child spans.

To explore spans within a trace using the OpenTelemetry Traces app, follow these steps:

1. Click the Dashboards tab.
2. Click OpenTelemetry Traces.
3. In the Slowest Operations chart, click the service that contains the trace.
4. In the list of trace IDs, click the trace you want to explore.
5. Explore how spans within the trace are related to each other in the waterfall view. To reveal additional options such as collapsing and expanding child spans, right-click on a span.

To try out this example, go to the Axiom Playground.

To access the waterfall view from Explore, follow these steps:

1. Ensure the dataset you work with has trace data.

2. Click the Explore tab.

3. Run a query that returns the _time and trace_id fields. For example, the following query returns the number of spans in each trace:

   ['otel-demo-traces']
   | summarize count() by trace_id

4. In the list of trace IDs, click the trace you want to explore. To reveal additional options such as copying the trace ID, right-click on a trace.

5. Explore how spans within the trace are related to each other in the waterfall view. To reveal additional options such as collapsing and expanding child spans, right-click on a span.

To try out this example, go to the Axiom Playground.

Span duration histogram

When you select a span in the waterfall view, Axiom displays a histogram to the right. This chart displays the durations of spans that have the same span name and service name as the span you selected. By default, the histogram shows a one-hour window around the selected span.

The span duration histogram can be useful in the following cases, among others:

• You look at a span and you're not familiar with the typical behavior of the service that created it. You want to know if you look at something normal in terms of duration or an outlier. The histogram helps you determine if you look at an outlier and might drill down further.
• You've found an outlier. You want to investigate and look at other outliers. The histogram shows you what the baseline is and what is not normal in terms of duration. You want to filter for the outliers and see what they have in common.
• You want to see if there was a recent change in the typical duration for the selected span type.

To narrow the time range of the histogram, click and select an area in the histogram.

Example queries

Below are a collection of queries that can help get you started with traces inside Axiom. Queries are all executable on the Axiom Play sandbox.

Number of requests, average response

['otel-demo-traces']
| where isnull(parent_span_id)
| summarize count(),
            avg(duration),
            percentiles_array(duration, 95, 99, 99.9)
  by bin_auto(_time)

Top five slowest services by operation

['otel-demo-traces']
| summarize count(), avg(duration) by name
| sort by avg_duration desc
| limit 5

Top five errors per service and operation

['otel-demo-traces']
| summarize topk(['status.message'], 5) by ['service.name'], name
| limit 5

Semantic Conventions

OpenTelemetry defines Semantic Conventions which specify standard attribute names and values for different kinds of operations and data. Attributes that follow semantic conventions will be available as nested fields under the attributes field, such as attributes.http.method, attributes.db.system, etc.

For example, if a span represents an HTTP request, it may include the following attributes:

• attributes.http.method: The HTTP request method, e.g., "GET", "POST", etc.
• attributes.http.url: The full HTTP request URL.
• attributes.http.status_code: The HTTP response status code.

Similarly, resource attributes that follow semantic conventions will be available under the resource field, such as resource.host.name, resource.host.id, resource.host.os, etc.

Custom attributes that do not match any semantic conventions will be nested under the attributes.custom map field.

Querying custom attributes

Trace spans often include many custom attributes under the attributes.custom field. These custom attributes are stored as nested key-value pairs.

To access nested custom attributes, you can use Axiom Processing Language (APL) for example:

['otel-demo-traces'] 
| where ['attributes.custom']['app.synthetic_request'] == true

If you frequently need to query the same nested attribute, consider creating a virtual field for it:

1. Go to "Datasets" and click the f(x) button
2. Define the new virtual field, for example:

['otel-demo-traces']
| extend useragent = ['attributes.custom']['User-Agent']

3. You can then query the virtual field like any other field in the UI or APL.

To create a typed virtual field, you can specify the type, e.g.:

| extend deployment_id = tostring(['attributes.custom']['deployment_id'])