A mini-profiler for the Google App Engine Java runtime
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Google App Engine Mini Profiler for Java


This is a "mini profiler" for the Google App Engine Java runtime.

It's heavily inspired by

It's released under the MIT license.


  • Live profiling of any request in production:

    • Provides a basic Java profiler used to explicitly profile sections of your code.
    • Captures Appstats data if the AppstatsFilter is running.
  • Capture of profiles for requests that redirected to the current request as well as any XMLHttpRequests that happen after the page loads as they happen.

  • Granular control over when profiling happens and who can see the results:

    • Limit to a subset of URLs,
    • Limit to app administrators,
    • Limit to certain app users (by email),
    • Any combination of the above.
  • Simple configuration:

    • A single .jar file (and a dependency on the Jackson JSON library).
    • A new <servlet> and <filter> in your web.xml file.
    • An include in the <head> of your page template.


A demo app (with profiling enabled for anyone) is at http://gae-java-mini-profiler.appspot.com/.

Example Screenshot

Getting Started


  • appengine-api-1.0-sdk (you should already have this in your project)
  • appengine-api-labs (you should already have this in your project)
  • servlet-api (you should already have this in your project)
  • jackson-core-asl
  • jackson-mapper-asl


Clone the source from here and build it using maven.

Then copy the gae-mini-profiler-1.0.0.jar file (and the two Jackson jars) to your WEB-INF/lib folder.


Add the ca.jimr.gae.profiler.MiniProfilerServlet and ca.jimr.gae.profiler.MiniProfilerFilter to your web.xml.


Note: The MiniProfilerFilter MUST be before the AppstatsFilter if you want to have Appstats show up.

There are a bunch of initParameter params you can set to configure the profiler:

Servlet Parameters

maxStackFramesThe maximum number of stack frames to show in the Appstats stack traces. The default is to show all of them.
htmlIdPrefixPrefix to use for HTML ids generated by the profiler. This MUST match the htmlIdPrefix in the filter definition. The default is "mp".
resourceCacheHoursNumber of hours to cache the static resources generated by the profiler in the browser. The default is not to cache at all (0 hours).

Filter Parameters

servletURLThe base URL that the servlet is mapped to. This MUST match the URL in the <servlet-mapping> specified for the MiniProfilerServlet. The default is /gae_mini_profile/.
restrictToAdminsWhether to restrict profiling to app admins. The default is false.
restrictToEmailsComma-delimited list of emails of app users to restrict profiling to. The default is no restriction.
restrictToURLsComma-delimited list of regular expressions of URL patterns that profiling should be done on. This can be used to further limit the scope of the filter mapping specified in the web.xml. The default is no restriction.
dataExpiryHow many seconds to keep profile data around in Memcache. The default is 30 seconds.
htmlIdPrefixPrefix to use for HTML ids generated by the profiler. This MUST match the htmlIdPrefix in the servlet definition. The default is "mp".

At the bottom of the <head> in your page (usually in whatever global template you are using), you must output the contents of the mini_profile_includes request attribute. This attribute will be null if the profiler did not run for this request. E.g.

  <!-- Other Stuff would go here -->

If you are already including jQuery and/or jQuery Templates on your page, this include needs to happen after them. If jQuery or jQuery Templates are not already included on the page, they will be.

Start up your app!

And that's it. When you run your application, depending on what restrictions you have set, you will see profiling stats showing up in the left-hand corner of the page.

Instrumenting your code

Odds are you will want more than just the elapsed time for the entire request.

You can use the MiniProfiler class to record execution times for sections of your code.

The main method to call is MiniProfiler.step( String stepName ). This will start a new profiling step, and return an object that you can later call the close() method on to finish the step. These steps can be nested to create a tree-structure.

If the profiler is inactive, the steps won't do anything.

Step step1 = MiniProfiler.step("Big things happening");
  Step step2 = MiniProfiler.step("Sub-Step 1");
    // Do some work
  Step step3 = MiniProfiler.step("Sub-Step 2");
    // Do some work

This will show up in the profiler UI as something like (different numbers obviously):

Name                        Duration (ms)   Self (ms)   Offset (ms)
Request                     100.00          10.00       0 
  Big things happening      90.00           15.00       10.00
    Sub-Step 1              35.00           35.00       15.00
    Sub-Step 2              40.00           40.00       50.00