diff --git a/site/docs/skylark/performance.md b/site/docs/skylark/performance.md
index c367d8b..ec22bee 100644
--- a/site/docs/skylark/performance.md
+++ b/site/docs/skylark/performance.md
@@ -343,77 +343,6 @@
     0.96 ms    0.02%   runfiles for //tools/aquery_differ aquery_differ
 ```
 
-You can use the following options to display more detailed information:
-
-- `--dump=text`: Print all recorded tasks in the order they occurred.
-- `--dump=raw`: Use this for automated analysis with scripts.
-- `--html`: Writes a file called `<profile-file>.html` in the directory of the
-  profile file. Open it in you browser to see a Gantt type chart that displays
-  time on the horizontal axis and threads of execution along the vertical axis.
-- `--html_details`: Renders a more detailed execution chart. Beware that this
-  increases file size and browser load considerably.
-
-### JSON profile
-
-When you add the flag `--experimental_generate_json_trace_profile` to your Bazel
-invocations, Bazel will write a JSON profile in [Chrome Trace
-Format](https://docs.google.com/document/d/1CvAClvFfyA5R-PhYUmn5OOQtYMH4h6I0nSsKchNAySU/preview).
-
-We suggest to use the flag together with the following flags:
-- `--experimental_json_trace_compression`: The profile will be compressed with
-  gzip.
-- `--experimental_profile_cpu_usage`: Bazel will measure and include local CPU
-  usage in the JSON profile.
-
-Example usage:
-```
-$ bazel build --experimental_generate_json_trace_profile --experimental_profile_cpu_usage //third_party/zlib/...
-INFO: Writing tracer profile to '/home/johndoe/.cache/bazel/_bazel_johndoe/f01bc937da326f5bb0feb15c854c110c/command.profile'
-INFO: Invocation ID: 34995931-ef6f-4838-9ab1-9a0bc39a8712
-INFO: Analysed 3 targets (7 packages loaded, 316 targets configured).
-INFO: Found 3 targets...
-INFO: Elapsed time: 1.223s, Critical Path: 0.27s
-INFO: 17 processes: 17 linux-sandbox.
-INFO: Build completed successfully, 20 total actions
-```
-
-The resulting profile file
-(`/home/johndoe/.cache/bazel/_bazel_johndoe/f01bc937da326f5bb0feb15c854c110c/command.profile`
-in this case; can be configured by the `--profile=<path>` flag) can then be
-loaded and viewed in Chrome. For this, open `chrome://tracing` in a new tab,
-click `Load` and pick the profile file.
-
-Example profile:
-<img src="profile.png" alt="Example Profile" />
-
-The top row ('cpu counters') shows the local CPU usage, which is high in this
-build during the analysis phase and then gets lower during execution.
-The second row ('Critical Path') refers to the critical path of the build, that
-is even with infinite parallelism the build would not be faster than the actions
-in this path.
-The third row ('grpc-command-1') displays everything that's happening on
-Bazel's main thread, giving a high level overview of what Bazel is doing.
-The remaining rows show what the worker threads are doing.
-
-You can interact with the profile, for example zoom in, inspect particular tasks,
-filter for task descriptions and select multiple tasks to get an overview. Press
-`?` to get an overview of what you can do.
-
-When analyzing these kind of profiles look for the following:
-- Slow analysis phase (RunAnalysisPhase), especially on incremental builds. This
-  can be a sign of a poor rule implementation, for example one that flattens
-  nested sets.
-- Individual slow actions, especially those on the critical path. It might be
-  possible to split large actions into multiple smaller actions or reduce the
-  dependencies to speed them up.
-- Bottlenecks, that is a small number of threads is busy while all others are
-  idleing waiting for the result. Optimizing this will most likely require
-  touching the rule implementations to introduce more parallelism.
-
-Note that we filter out fast tasks and certain task types completely to keep the
-profile files small enough to render fast in the Chrome Trace Viewer.
-
-
 ## Memory profiling
 
 Bazel comes with a built-in memory profiler that can help you check your rule's