
Before you begin
- Labs create a Google Cloud project and resources for a fixed time
- Labs have a time limit and no pause feature. If you end the lab, you'll have to restart from the beginning.
- On the top left of your screen, click Start lab to begin
Create a cluster and deploy the sample application
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Create a cloud trace
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In this lab, you learn how to use Cloud Trace by sending an HTTP request to the sample application.
Learn how to use Trace by doing the following:
For each lab, you get a new Google Cloud project and set of resources for a fixed time at no cost.
Click the Start Lab button. If you need to pay for the lab, a pop-up opens for you to select your payment method. On the left is the Lab Details panel with the following:
Click Open Google Cloud console (or right-click and select Open Link in Incognito Window if you are running the Chrome browser).
The lab spins up resources, and then opens another tab that shows the Sign in page.
Tip: Arrange the tabs in separate windows, side-by-side.
If necessary, copy the Username below and paste it into the Sign in dialog.
You can also find the Username in the Lab Details panel.
Click Next.
Copy the Password below and paste it into the Welcome dialog.
You can also find the Password in the Lab Details panel.
Click Next.
Click through the subsequent pages:
After a few moments, the Google Cloud console opens in this tab.
In this task, you download a sample application from GitHub, enable the Google Kubernetes Engine API, create a GKE cluster, update cluster credentials, verify access, and deploy the application's three services.
To download and deploy the sample application, do the following:
After a few moments, a Cloud Shell session opens inside the Google Cloud console.
This command takes a few minutes to complete. After it completes successfully, your Google Cloud project contains the GKE cluster named cloud-trace-demo. You must have permission to create clusters that have external access in your Google Cloud project.
A sample output of this command is:
The script setup.sh configures three services of the application using a pre-built image. The workloads are named cloud-trace-demo-a, cloud-trace-demo-b, and cloud-trace-demo-c. The setup script waits for all resources to be provisioned, so the configuration might take several minutes to complete.
A sample output of this command is:
Click Check my progress to verify the objective.
In this task, you generate traces by sending curl
requests cloud-trace-demo-a and then view the trace data in Trace.
You can execute the curl command multiple times to generate multiple traces.
The output looks like the following:
Click Check my progress to verify the objective.
Trace shows distributed traces for analysis. It displays a heatmap of span durations over time, along with a table of individual spans, filterable by service name, span name, status, duration, and kind. The interface allows users to investigate performance issues and understand request flow within a distributed system.
The chart view displays the duration of spans over time using a heatmap. Each colored block represents a span, and its color intensity indicates its duration. This allows you to quickly identify slow spans or trends in latency.
In the chart view, click one of the darker span blocks.
In the Spans table, click any Span ID. A detailed breakdown of the specific trace is displayed. Each horizontal bar represents the duration of each span within the trace. The length of the bar corresponds to the span's duration.
This section of the trace provides a detailed view of a single request's journey through the system, breaking it down into individual operations (spans) and showing their timing and relationships. It helps pinpoint performance bottlenecks and understand the sequence of events.
Additional details about each span are shown in the details pane below.
In this lab, you performed the following tasks:
Good job.
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