The course is part of this learning path
The Google Cloud Operations suite (formerly Stackdriver) includes a wide variety of tools to help you monitor and debug your GCP-hosted applications. This course will give you hands-on demonstrations of how to use the Monitoring, Logging, Error Reporting, Debugger, and Trace components of the Cloud Operations suite. You can follow along with your own GCP account to try these examples yourself.
If you have any feedback relating to this course, feel free to reach out to us at firstname.lastname@example.org.
- Use the Cloud Operations suite to monitor, log, report on errors, trace, and debug
- System administrators
- People who are preparing to take the Google Associate Cloud Engineer certification exam
- Google Cloud Platform: Fundamentals course or experience with Google Cloud Platform
- The GitHub repository for this course is at https://github.com/cloudacademy/managing-gcp.
In the last lesson, we looked at how to debug errors in your application, but what do you do if your application is working properly but performing too slowly? That’s what Cloud Profiler and Cloud Trace are used for. In this lesson, I’m only going to talk about Cloud Trace.
The Trace List is probably where you will spend most of your time. It shows you all of the traces over a specific period of time in this cool graph. It is set to “1 hour” right now, but we can change that to give a longer view. Each one of these dots is a trace of an individual request to the application. If you click on one of the dots, it brings up two more panes underneath. The Waterfall View shows what happened during the request. The first bar shows the total end-to-end time, which was 215 milliseconds in this case. The bars underneath show the time it took to complete calls performed when handling the request. In this case, we have one bar for an HTTP GET request.
Of course, this timeline would be a lot more useful if we were running a more complex application with multiple calls so you could see which ones were taking the most time. Each of those calls would have a bar on this chart. The Hello World application is about the simplest application possible, so you’ll just have to use your imagination here.
Analysis reports show you the latency distribution for your application and also attempt to identify performance bottlenecks, which is a great feature. You have to have at least 100 traces before you can run a report, though.
If you’re running your applications in App Engine, then it’ll automatically capture and submit traces, but if you want to trace code that’s running outside of App Engine, then you’ll have to either add instrumentation code to your applications using the Trace SDK or submit traces through the API.
Before we go, you might want to delete your application, so it doesn’t incur charges. Go to App Engine and then go to Settings. Click “Disable application”. It will ask you to type the app’s ID before you can click “DISABLE”. This doesn’t delete the application, but it does stop it from serving requests. To start the application up again, you can just click “Enable application”.
If you want to permanently delete the application, then you’ll have to delete the project it’s associated with, which you can do in the “IAM & Admin” page. Be aware that if you delete a project, you will never be able to use that project ID again. That is, you won’t be able to create a new project with the same ID.
That’s it for this lesson.
Guy launched his first training website in 1995 and he's been helping people learn IT technologies ever since. He has been a sysadmin, instructor, sales engineer, IT manager, and entrepreneur. In his most recent venture, he founded and led a cloud-based training infrastructure company that provided virtual labs for some of the largest software vendors in the world. Guy’s passion is making complex technology easy to understand. His activities outside of work have included riding an elephant and skydiving (although not at the same time).