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Debug missing images in your service

15 min

lab

This procedure is part of a lab that teaches you how to monitor your Kubernetes cluster with Pixie.

Each procedure in the lab builds upon the last, so make sure you've completed the last procedure, Instrument your cluster, before starting this one.

Until now, you've been working with application services that don't have bugs (we hope). You've been able to access TinyHat.me and render Bob Ross with one or more silly hats without a hitch. But it's time to deploy some new code to your cluster.

Change to the scenario-1 directory and set up your environment:

bash
$
cd ../scenario-1
$
./setup.sh
Please wait while we update your lab environment.
deployment.apps/fetch-service configured
deployment.apps/simulator configured
Done!

Important

If you're a windows user, run the PowerShell setup script:

bash
$
.\setup.ps1

Uh oh! You look on social media and see some confused customers:

A Twitter thread showing some users can't access a hat

What's wrong with TinyHat.me? Use Pixie to find out.

Reproduce the issue

You've been notified by your users that they can't see a particular hat on TinyHat.me. Before you start debugging your code, reproduce the issue for yourself.

Step 1 of 5

Look up your frontend's external IP address:

bash
$
kubectl get services
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
add-service ClusterIP 10.109.114.34 <none> 80/TCP 20m
admin-service ClusterIP 10.110.29.145 <none> 80/TCP 20m
fetch-service ClusterIP 10.104.224.242 <none> 80/TCP 20m
frontend-service LoadBalancer 10.102.82.89 10.102.82.89 80:32161/TCP 20m
gateway-service LoadBalancer 10.101.237.225 10.101.237.225 80:32469/TCP 20m
kubernetes ClusterIP 10.96.0.1 <none> 443/TCP 20m
manipulation-service ClusterIP 10.107.23.237 <none> 80/TCP 20m
moderate-service ClusterIP 10.105.207.153 <none> 80/TCP 20m
mysql ClusterIP 10.97.194.23 <none> 3306/TCP 20m
upload-service ClusterIP 10.108.113.235 <none> 80/TCP 20m
Step 2 of 5

Paste the IP in your browser:

TinyHat.me

This looks the same as it did before, except that there's a new hat style, called PIXIE.

Step 3 of 5

Select a number of hats, the PIXIE style, and Hat me:

TinyHat.me

Oops! Where did Bob go? Instead of rendering Bob Ross with your hat selection, the frontend served no image at all.

Tip

The number of hats you choose to display has no effect on the result.

Step 4 of 5

Observe a network request in your browser's developer tools:

The error response from your service

Here, the response from the image request says, "This hat style does not exist! If you want this style - try submitting it."

You know that the PIXIE hat style most certainly does exist because you chose it from the selector. But for some reason, the application can't render the image.

Step 5 of 5

For good measure, try to render a different hat style:

Your site successfully renders Bob Ross with cat ears

It worked! Your users were right. There's something wrong with your application.

Solve the mystery with Pixie

The bad news is that you've confirmed there's an error in your application. The good news is that you recently instrumented your cluster with Pixie! Go to New Relic and sign into your account, if you haven't already.

Step 1 of 14

From the New Relic homepage, go to Kubernetes:

New Relic site with an arrow pointing to Kubernetes

Step 2 of 14

Choose your tiny-hat cluster:

Arrow pointing to the tiny-hat cluster

Step 3 of 14

Then click Live Debugging with Pixie:

Arrow pointing to the live-debugger

This is Pixie's live, code-level debugger:

Pixie's live debugger

You use it to drill down and learn more about the services in your cluster.

Important

When you go to the live debugger, you may see an error saying your cluster is disconnected. This is normal, as it takes a little while for New Relic to start seeing your Pixie data. Wait a few more minutes and refresh the debugger.

Step 4 of 14

Notice the script dropdown menu at the top of the debugger:

Pixie's script selector

Pixie's live debugger renders data based on open source scripts written in PxL, Pixie's proprietary query language. The default script is px/cluster, which shows cluster-level information including:

  • A service map
  • Nodes
  • Namespaces
  • Services
  • Pods
Step 5 of 14

Scroll down to see the error rates for your services:

A box showing high error rates for your services

Yikes! You have three services returning a high percentage of errors:

  • fetch-service
  • frontend-service
  • gateway-service

You know that the website lives at frontend-service. You can reasonably rule this out as the culprit because you know it renders other hats just fine. That leaves two potential problem services:

  • gateway-service
  • fetch-service
Step 6 of 14

To decide which service to look at first, scroll up to NAMESPACES and choose default:

Choose the default namespace

Your app services live in the default namespace. This helps you filter the service map to show more useful nodes.

Step 7 of 14

Scroll up to the service map:

Pixie service map highlighting the erroring services

Here, you see that the frontend-service requests data from gateway-service. In turn, gateway-service requests data from fetch-service. So, following that order of operations, focus first on the gateway-service.

Tip

You can click and drag the nodes in the service map to make it more readable.

Step 8 of 14

Double click the gateway-service in your service map to learn more about it:

Pixie's service view

Notice that Pixie's live debugger has seamlessly replaced namespace data with service data by changing the script:

A box showing the service script is selected

You're now using the px/service script filtered down to default/gateway-service. In this service, you see a graph with the errors, but not much about where those errors are coming from.

Step 9 of 14

Click the script selector to switch to the px/service_stats script. Filter the svc to default/gateway-service:

Gateway service stats

This gives a better picture of the errors in your service.

Step 10 of 14

Scroll down to the Incoming Traffic and Outgoing Traffic tables:

Gateway service traffic

The gateway service is returning the same amount of errors on inbound requests as it's receiving from outbound requests to the fetch service. This is a good indicator that you need to look at what's happening upstream.

Step 11 of 14

Switch to the px/http_data_filtered script, targeting default/fetch-service and requests with a 400 response status code:

400 responses in the fetch service

Step 12 of 14

Click on a row to learn more about a request to the fetch service that resulted in an error:

400 response details

Here, you see that the request path looks like /fetch?style=PIXIE&number=1. This looks right, because the hat style you chose is called PIXIE. So if the fetch service is still returning 400s, something wrong is happening when it tries to find the hat.

Step 13 of 14

Switch to the px/mysql_data script and add a source filter for default/fetch-service:

Fetch queries

Many of these queries returned no results.

Step 14 of 14

Click on one with no results, and look at the req_body to see the query:

Fetch PIXIE query

SELECT * FROM main.images WHERE BINARY description='pixie' AND approve='true'

There's the problem! The BINARY type cast effectively makes the WHERE condition case sensitive. Since the hat's style is called PIXIE, this condition fails to find it. Now that you know, you can fix this query in your fetch service.

Summary

To recap, you observed an error in your application and used Pixie in New Relic to:

  1. Understand your services' relationships
  2. Review the error percentages for each of your services
  3. Look at individual response bodies
  4. Find a semantic error in a query within one of those services

And you didn't even need to individually install agents in any of your services. Pixie was able to deliver all the information you needed!

lab

This lesson is part of a lab that teaches you how to monitor your Kubernetes cluster with Pixie. Next, try to figure out why some APIs have high latency.

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