Merge "Fix documentation."

Copyright (C) 2015 The Android Open Source Project

Licensed under the Apache License, Version 2.0 (the "License");

you may not use this file except in compliance with the License.

You may obtain a copy of the License at

     http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software

distributed under the License is distributed on an "AS IS" BASIS,

WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

See the License for the specific language governing permissions and

limitations under the License.

================================================================================

The Chrome OS "metrics" package contains utilities for client-side user metric

collection.

When Chrome is installed, Chrome will take care of aggregating and uploading the

metrics to the UMA server.

When Chrome is not installed (embedded build) and the metrics_uploader USE flag

is set, metrics_daemon will aggregate and upload the metrics itself.

================================================================================

The Metrics Library: libmetrics

================================================================================

libmetrics is a small library that implements the basic C and C++ API for

metrics collection. All metrics collection is funneled through this library. The

easiest and recommended way for a client-side module to collect user metrics is

to link libmetrics and use its APIs to send metrics to Chrome for transport to

UMA. In order to use the library in a module, you need to do the following:

- Add a dependence (DEPEND and RDEPEND) on chromeos-base/metrics to the module's

  ebuild.

- Link the module with libmetrics (for example, by passing -lmetrics to the

  module's link command). Both libmetrics.so and libmetrics.a are built and

  installed under $SYSROOT/usr/lib/. Note that by default -lmetrics will link

  against libmetrics.so, which is preferred.

- To access the metrics library API in the module, include the

  <metrics/metrics_library.h> header file. The file is installed in

  $SYSROOT/usr/include/ when the metrics library is built and installed.

- The API is documented in metrics_library.h under src/platform/metrics/. Before

  using the API methods, a MetricsLibrary object needs to be constructed and

  initialized through its Init method.

  For more information on the C API see c_metrics_library.h.

- Samples are sent to Chrome only if the "/home/chronos/Consent To Send Stats"

  file exists or the metrics are declared enabled in the policy file (see the

  AreMetricsEnabled API method).

- On the target platform, shortly after the sample is sent, it should be visible

  in Chrome through "about:histograms".

================================================================================

Histogram Naming Convention

================================================================================

Use TrackerArea.MetricName. For example:

Platform.DailyUseTime

Network.TimeToDrop

================================================================================

Server Side

================================================================================

If the histogram data is visible in about:histograms, it will be sent by an

official Chrome build to UMA, assuming the user has opted into metrics

collection. To make the histogram visible on "chromedashboard", the histogram

description XML file needs to be updated (steps 2 and 3 after following the

"Details on how to add your own histograms" link under the Histograms tab).

Include the string "Chrome OS" in the histogram description so that it's easier

to distinguish Chrome OS specific metrics from general Chrome histograms.

The UMA server logs and keeps the collected field data even if the metric's name

is not added to the histogram XML. However, the dashboard histogram for that

metric will show field data as of the histogram XML update date; it will not

include data for older dates. If past data needs to be displayed, manual

server-side intervention is required. In other words, one should assume that

field data collection starts only after the histogram XML has been updated.

================================================================================

The Metrics Client: metrics_client

================================================================================

metrics_client is a simple shell command-line utility for sending histogram

samples and user actions. It's installed under /usr/bin on the target platform

and uses libmetrics to send the data to Chrome. The utility is useful for

generating metrics from shell scripts.

For usage information and command-line options, run "metrics_client" on the

target platform or look for "Usage:" in metrics_client.cc.

================================================================================

The Metrics Daemon: metrics_daemon

================================================================================

metrics_daemon is a daemon that runs in the background on the target platform

and is intended for passive or ongoing metrics collection, or metrics collection

requiring feedback from multiple modules. For example, it listens to D-Bus

signals related to the user session and screen saver states to determine if the

user is actively using the device or not and generates the corresponding

data. The metrics daemon uses libmetrics to send the data to Chrome.

The recommended way to generate metrics data from a module is to link and use

libmetrics directly. However, the module could instead send signals to or

communicate in some alternative way with the metrics daemon. Then the metrics

daemon needs to monitor for the relevant events and take appropriate action --

for example, aggregate data and send the histogram samples.

================================================================================

FAQ

================================================================================

Q. What should my histogram's |min| and |max| values be set at?

A. You should set the values to a range that covers the vast majority of samples

   that would appear in the field. Note that samples below the |min| will still

   be collected in the underflow bucket and samples above the |max| will end up

   in the overflow bucket. Also, the reported mean of the data will be correct

   regardless of the range.

Q. How many buckets should I use in my histogram?

A. You should allocate as many buckets as necessary to perform proper analysis

   on the collected data. Note, however, that the memory allocated in Chrome for

   each histogram is proportional to the number of buckets. Therefore, it is

   strongly recommended to keep this number low (e.g., 50 is normal, while 100

   is probably high).

Q. When should I use an enumeration (linear) histogram vs. a regular

   (exponential) histogram?

A. Enumeration histograms should really be used only for sampling enumerated

   events and, in some cases, percentages. Normally, you should use a regular

   histogram with exponential bucket layout that provides higher resolution at

   the low end of the range and lower resolution at the high end. Regular

   histograms are generally used for collecting performance data (e.g., timing,

   memory usage, power) as well as aggregated event counts.

Metricsd

========

The metricsd daemon is used to gather metrics from the platform and application,

aggregate them and upload them periodically to a server.

The metrics will then be available in their aggregated form to the developer

for analysis.

Three components are provided to interact with `metricsd`: `libmetrics`,

`metrics_collector` and `metrics_client`.

The Metrics Library: libmetrics

-------------------------------

`libmetrics` is a small library that implements the basic C++ API for

metrics collection. All metrics collection is funneled through this library. The

easiest and recommended way for a client-side module to collect user metrics is

to link `libmetrics` and use its APIs to send metrics to `metricsd` for transport to

UMA. In order to use the library in a module, you need to do the following:

- Add a dependency on the shared library in your Android.mk file:

  `LOCAL_SHARED_LIBRARIES += libmetrics`

- To access the metrics library API in the module, include the

  <metrics/metrics_library.h> header file.

- The API is documented in `metrics_library.h`. Before using the API methods, a

  MetricsLibrary object needs to be constructed and initialized through its

  Init method.

- Samples are uploaded only if the `/data/misc/metrics/enabled` file exists.

Server Side

-----------

You will be able to see all uploaded metrics on the metrics dashboard,

accessible via the developer console.

*** note

It usually takes a day for metrics to be available on the dashboard.

***

The Metrics Client: metrics_client

----------------------------------

`metrics_client` is a simple shell command-line utility for sending histogram

samples and querying `metricsd`. It's installed under `/system/bin` on the target

platform and uses `libmetrics`.

For usage information and command-line options, run `metrics_client` on the

target platform or look for "Usage:" in `metrics_client.cc`.

The Metrics Daemon: metricsd

----------------------------

`metricsd` is the daemon that listens for metrics logging calls (via Binder),

aggregates the metrics and uploads them periodically. This daemon should start as

early as possible so that depending daemons can log at any time.

`metricsd` is made of two threads that work as follows:

* The binder thread listens for one-way Binder calls, aggregates the metrics in

  memory (via `base::StatisticsRecorder`) and increments the crash counters when a

  crash is reported. This thread is kept as simple as possible to ensure the

  maximum throughput possible.

* The uploader thread takes care of backing up the metrics to disk periodically

  (to avoid losing metrics on crashes), collecting metadata about the client

  (version number, channel, etc..) and uploading the metrics periodically to the

  server.

The Metrics Collector: metrics_collector

----------------------------------------

metrics_collector is a daemon that runs in the background on the target platform,

gathers health information about the system and maintains long running counters

(ex: number of crashes per week).

The recommended way to generate metrics data from a module is to link and use

libmetrics directly. However, we may not want to add a dependency on libmetrics

to some modules (ex: kernel). In this case, we can add a collector to

metrics_collector that will, for example, take measurements and report them

periodically to metricsd (this is the case for the disk utilization histogram).

FAQ

---

### What should my histogram's |min| and |max| values be set at?

You should set the values to a range that covers the vast majority of samples

that would appear in the field. Note that samples below the |min| will still

be collected in the underflow bucket and samples above the |max| will end up

in the overflow bucket. Also, the reported mean of the data will be correct

regardless of the range.

### How many buckets should I use in my histogram?

You should allocate as many buckets as necessary to perform proper analysis

on the collected data. Note, however, that the memory allocated in metricsd

for each histogram is proportional to the number of buckets. Therefore, it is

strongly recommended to keep this number low (e.g., 50 is normal, while 100

is probably high).

### When should I use an enumeration (linear) histogram vs. a regular (exponential) histogram?

Enumeration histograms should really be used only for sampling enumerated

events and, in some cases, percentages. Normally, you should use a regular

histogram with exponential bucket layout that provides higher resolution at

the low end of the range and lower resolution at the high end. Regular

histograms are generally used for collecting performance data (e.g., timing,

memory usage, power) as well as aggregated event counts.

### How can I test that my histogram was reported correctly?

* Make sure no error messages appear in logcat when you log a sample.

* Run `metrics_client -d` to dump the currently aggregated metrics. Your

  histogram should appear in the list.

* Make sure that the aggregated metrics were uploaded to the server successfully

  (check for an OK message from `metricsd` in logcat).

* After a day, your histogram should be available on the dashboard.

class SystemProfileSetter;

// Service responsible for uploading the metrics periodically to the server.

// This service works as a simple 2-state state-machine.

// Service responsible for backing up the currently aggregated metrics to disk

// and uploading them periodically to the server.

//

// The two states are the presence or not of a staged log.

// A staged log is a compressed protobuffer containing both the aggregated

// metrics and event and information about the client. (product,

// model_manifest_id, etc...).

// A given metrics sample can be in one of three locations.

// * in-memory metrics: in memory aggregated metrics, waiting to be staged for

//   upload.

// * saved log: protobuf message, written to disk periodically and on shutdown

//   to make a backup of metrics data for uploading later.

// * staged log: protobuf message waiting to be uploaded.

//

// At regular intervals, the upload event will be triggered and the following

// will happen:

// * if a staged log is present:

//    The previous upload may have failed for various reason. We then retry to

//    upload the same log.

//    - if the upload is successful, we discard the log (therefore

//      transitioning back to no staged log)

//    - if the upload fails, we keep the log to try again later.

// The service works as follows:

// On startup, we create the in-memory metrics from the saved log if it exists.

//

// * if no staged logs are present:

//    Take a snapshot of the aggregated metrics, save it to disk and try to send

//    it:

//    - if the upload succeeds, we discard the staged log (transitioning back

//      to the no staged log state)

//    - if the upload fails, we continue and will retry to upload later.

// Periodically (every |disk_persistence_interval_| seconds), we take a snapshot

// of the in-memory metrics and save them to disk.

//

// Periodically (every |upload_interval| seconds), we:

// * take a snapshot of the in-memory metrics and create the staged log

// * save the staged log to disk to avoid losing it if metricsd or the system

//   crashes between two uploads.

// * delete the last saved log: all the metrics contained in it are also in the

//   newly created staged log.

//

// On shutdown (SIGINT or SIGTERM), we save the in-memory metrics to disk.

//

// Note: the in-memory metrics can be stored in |current_log_| or

// base::StatisticsRecorder.

class UploadService : public base::HistogramFlattener, public brillo::Daemon {

 public:

  UploadService(const std::string& server,