A new documentation page about iterative build performance.

This document can be linked from the CLI warning when the analysis cache is discarded.

PiperOrigin-RevId: 529135476
Change-Id: I8b389e883c468e0d22b41a2652f6190480515bd7

site/en/_book.yaml

diff --git a/site/en/_book.yaml b/site/en/_book.yaml
index 3fa7c88..3ad3764 100644
--- a/site/en/_book.yaml
+++ b/site/en/_book.yaml
@@ -168,6 +168,8 @@
         path: /advanced/performance/json-trace-profile
       - title: Optimize memory
         path: /advanced/performance/memory
+      - title: Optimize build iteration speed
+        path: /advanced/performance/iteration-speed
     - name: Remote execution
       contents:
       - heading: Remote build execution (RBE)

site/en/advanced/performance/iteration-speed.md

diff --git a/site/en/advanced/performance/iteration-speed.md b/site/en/advanced/performance/iteration-speed.md
new file mode 100644
index 0000000..7a2a1fa
--- /dev/null
+++ b/site/en/advanced/performance/iteration-speed.md
@@ -0,0 +1,85 @@
+Project: /_project.yaml
+Book: /_book.yaml
+
+
+# Optimize Iteration Speed
+
+{% include "_buttons.html" %}
+
+This page describes how to optimize Bazel's build performance when running Bazel
+repeatedly.
+
+## Bazel's Runtime State
+
+A Bazel invocation involves several interacting parts.
+
+*   The `bazel` command line interface (CLI) is the user-facing front-end tool
+    and receives commands from the user.
+
+*   The CLI tool starts a [*Bazel server*](https://bazel.build/run/client-server)
+    for each distinct [output base](https://bazel.build/remote/output-directories).
+    The Bazel server is generally persistent, but will shut down after some idle
+    time so as to not waste resources.
+
+*   The Bazel server performs the loading and analysis steps for a given command
+    (`build`, `run`, `cquery`, etc.), in which it constructs the necessary parts
+    of the build graph in memory. The resulting data structures are retained in
+    the Bazel server as part of the *analysis cache*.
+
+*   The Bazel server can also perform the action execution, or it can send
+    actions off for remote execution if it is set up to do so. The results of
+    action executions are also cached, namely in the *action cache* (or
+    *execution cache*, which may be either local or remote, and it may be shared
+    among Bazel servers).
+
+*   The result of the Bazel invocation is made available in the output tree.
+
+## Running Bazel Iteratively
+
+In a typical developer workflow, it is common to build (or run) a piece of code
+repeatedly, often at a very high frequency (e.g. to resolve some compilation
+error or investigate a failing test). In this situation, it is important that
+repeated invocations of `bazel` have as little overhead as possible relative to
+the underlying, repeated action (e.g. invoking a compiler, or executing a test).
+
+With this in mind, we take another look at Bazel's runtime state:
+
+The analysis cache is a critical piece of data. A significant amount of time can
+be spent just on the loading and analysis phases of a cold run (i.e. a run just
+after the Bazel server was started or when the analysis cache was discarded).
+For a single, successful cold build (e.g. for a production release) this cost is
+bearable, but for repeatedly building the same target it is important that this
+cost be amortized and not repeated on each invocation.
+
+The analysis cache is rather volatile. First off, it is part of the in-process
+state of the Bazel server, so losing the server loses the cache. But the cache
+is also *invalidated* very easily: for example, many `bazel` command line flags
+cause the cache to be discarded. This is because many flags affect the build
+graph (e.g. because of
+[configurable attributes](https://bazel.build/configure/attributes)). Some flag
+changes can also cause the Bazel server to be restarted (e.g. changing
+[startup options](https://bazel.build/docs/user-manual#startup-options)).
+
+Bazel will print a warning if either the analysis cache was discarded or the
+server was restarted. Either of these should be avoided during iterative use:
+
+*   Be mindful of changing `bazel` flags in the middle of an iterative
+    workflow. For example, mixing a `bazel build -c opt` with a `bazel cquery`
+    causes each command to discard the analysis cache of the other. In general,
+    try to use a fixed set of flags for the duration of a particular workflow.
+
+*   Losing the Bazel server loses the analysis cache. The Bazel server has a
+    [configurable](https://bazel.build/docs/user-manual#max-idle-secs) idle
+    time, after which it shuts down. You can configure this time via your
+    bazelrc file to suit your needs. The server also restarted when startup
+    flags change, so, again, avoid changing those flags if possible.
+
+*   If you want to use multiple sets of flags from the same workspace, you can
+    use multiple, distinct output bases, switched with the `--output_base`
+    flag. Each output base gets its own Bazel server.
+
+A good execution cache is also valuable for build performance. An execution
+cache can be kept locally
+[on disk](https://bazel.build/remote/caching#disk-cache), or
+[remotely](https://bazel.build/remote/caching). The cache can be shared among
+Bazel servers, and indeed among developers.