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elasticmachine authored May 10, 2020
2 parents c509062 + 5e5ad19 commit 238bc64
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1 change: 0 additions & 1 deletion .eslintrc.js
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Expand Up @@ -112,7 +112,6 @@ module.exports = {
files: ['x-pack/plugins/lens/**/*.{js,ts,tsx}'],
rules: {
'react-hooks/exhaustive-deps': 'off',
'react-hooks/rules-of-hooks': 'off',
},
},
{
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2 changes: 1 addition & 1 deletion .i18nrc.json
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Expand Up @@ -34,7 +34,7 @@
"kibana_utils": "src/plugins/kibana_utils",
"navigation": "src/plugins/navigation",
"newsfeed": "src/plugins/newsfeed",
"regionMap": "src/legacy/core_plugins/region_map",
"regionMap": "src/plugins/region_map",
"savedObjects": "src/plugins/saved_objects",
"savedObjectsManagement": "src/plugins/saved_objects_management",
"server": "src/legacy/server",
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19 changes: 14 additions & 5 deletions docs/apm/machine-learning.asciidoc
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Expand Up @@ -6,22 +6,31 @@
<titleabbrev>Integrate with machine learning</titleabbrev>
++++

The Machine Learning integration will initiate a new job predefined to calculate anomaly scores on transaction response times.
The response time graph will show the expected bounds and add an annotation when the anomaly score is 75 or above.
Jobs can be created per transaction type, and based on the average response time.
Manage jobs in the *Machine Learning jobs management*.
The Machine Learning integration initiates a new job predefined to calculate anomaly scores on APM transaction durations.
Jobs can be created per transaction type, and are based on the service's average response time.

After a machine learning job is created, results are shown in two places:

The transaction duration graph will show the expected bounds and add an annotation when the anomaly score is 75 or above.

[role="screenshot"]
image::apm/images/apm-ml-integration.png[Example view of anomaly scores on response times in the APM app]

Service maps will display a color-coded anomaly indicator based on the detected anomaly score.

[role="screenshot"]
image::apm/images/apm-ml-integration.png[Example view of anomaly scores on response times in APM app in Kibana]
image::apm/images/apm-service-map-anomaly.png[Example view of anomaly scores on service maps in the APM app]

[float]
[[create-ml-integration]]
=== Create a new machine learning job

To enable machine learning anomaly detection, first choose a service to monitor.
Then, select **Integrations** > **Enable ML anomaly detection** and click **Create job**.

That's it! After a few minutes, the job will begin calculating results;
it might take additional time for results to appear on your graph.
Jobs can be managed in *Machine Learning jobs management*.

APM specific anomaly detection wizards are also available for certain Agents.
See the machine learning {ml-docs}/ootb-ml-jobs-apm.html[APM anomaly detection configurations] for more information.
24 changes: 23 additions & 1 deletion docs/apm/service-maps.asciidoc
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Expand Up @@ -9,7 +9,9 @@ Please use Chrome or Firefox if available.

A service map is a real-time visual representation of the instrumented services in your application's architecture.
It shows you how these services are connected, along with high-level metrics like average transaction duration,
requests per minute, and errors per minute, that allow you to quickly assess the status of your services.
requests per minute, and errors per minute.
If enabled, service maps also integrate with machine learning--for real time health indicators based on anomaly detection scores.
All of these features can help you to quickly and visually assess the status and health of your services.

We currently surface two types of service maps:

Expand Down Expand Up @@ -52,6 +54,26 @@ Additional filters are not currently available for service maps.
[role="screenshot"]
image::apm/images/service-maps-java.png[Example view of service maps with Java highlighted in the APM app in Kibana]

[float]
[[service-map-anomaly-detection]]
=== Anomaly detection with machine learning

Machine learning jobs can be created to calculate anomaly scores on APM transaction durations within the selected service.
When these jobs are active, service maps will display a color-coded anomaly indicator based on the detected anomaly score:

[horizontal]
image:apm/images/green-service.png[APM green service]:: Max anomaly score **<=25**. Service is healthy.
image:apm/images/yellow-service.png[APM yellow service]:: Max anomaly score **26-74**. Anomalous activity detected. Service may be degraded.
image:apm/images/red-service.png[APM red service]:: Max anomaly score **>=75**. Anomalous activity detected. Service is unhealthy.

[role="screenshot"]
image::apm/images/apm-service-map-anomaly.png[Example view of anomaly scores on service maps in the APM app]

If an anomaly has been detected, click *view anomalies* to view the anomaly detection metric viewier in the Machine learning app.
This time series analysis will display additional details on the severity and time of the detected anomalies.

To learn how to create a machine learning job, see <<machine-learning-integration,machine learning integration>>.

[float]
[[service-maps-legend]]
=== Legend
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Expand Up @@ -28,7 +28,6 @@ export declare class IndexPattern implements IIndexPattern
| [formatHit](./kibana-plugin-plugins-data-public.indexpattern.formathit.md) | | <code>any</code> | |
| [id](./kibana-plugin-plugins-data-public.indexpattern.id.md) | | <code>string</code> | |
| [metaFields](./kibana-plugin-plugins-data-public.indexpattern.metafields.md) | | <code>string[]</code> | |
| [routes](./kibana-plugin-plugins-data-public.indexpattern.routes.md) | | <code>{</code><br/><code> edit: string;</code><br/><code> addField: string;</code><br/><code> indexedFields: string;</code><br/><code> scriptedFields: string;</code><br/><code> sourceFilters: string;</code><br/><code> }</code> | |
| [timeFieldName](./kibana-plugin-plugins-data-public.indexpattern.timefieldname.md) | | <code>string &#124; undefined</code> | |
| [title](./kibana-plugin-plugins-data-public.indexpattern.title.md) | | <code>string</code> | |
| [type](./kibana-plugin-plugins-data-public.indexpattern.type.md) | | <code>string</code> | |
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This file was deleted.

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Expand Up @@ -18,7 +18,6 @@ indexPatterns: {
validate: typeof validateIndexPattern;
getFromSavedObject: typeof getFromSavedObject;
flattenHitWrapper: typeof flattenHitWrapper;
getRoutes: typeof getRoutes;
formatHitProvider: typeof formatHitProvider;
}
```
22 changes: 11 additions & 11 deletions docs/user/alerting/action-types/email.asciidoc
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Expand Up @@ -24,17 +24,17 @@ Password:: password for 'login' type authentication.

[source,text]
--
id: 'my-email'
name: preconfigured-email-action-type
actionTypeId: .email
config:
from: [email protected] <1.1>
host: validhostname <1.2>
port: 8080 <1.3>
secure: false <1.4>
secrets:
user: testuser <2.1>
password: passwordkeystorevalue <2.2>
my-email:
name: preconfigured-email-action-type
actionTypeId: .email
config:
from: [email protected] <1.1>
host: validhostname <1.2>
port: 8080 <1.3>
secure: false <1.4>
secrets:
user: testuser <2.1>
password: passwordkeystorevalue <2.2>
--

`config` defines the action type specific to the configuration and contains the following properties:
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14 changes: 7 additions & 7 deletions docs/user/alerting/action-types/index.asciidoc
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Expand Up @@ -21,13 +21,13 @@ Execution time field:: This field will be automatically set to the time the ale

[source,text]
--
id: 'my-index'
name: action-type-index
actionTypeId: .index
config:
index: .kibana <1>
refresh: true <2>
executionTimeField: somedate <3>
my-index:
name: action-type-index
actionTypeId: .index
config:
index: .kibana <1>
refresh: true <2>
executionTimeField: somedate <3>
--

`config` defines the action type specific to the configuration and contains the following properties:
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14 changes: 7 additions & 7 deletions docs/user/alerting/action-types/pagerduty.asciidoc
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Expand Up @@ -141,13 +141,13 @@ Integration Key:: A 32 character PagerDuty Integration Key for an integration

[source,text]
--
id: 'my-pagerduty'
name: preconfigured-pagerduty-action-type
actionTypeId: .pagerduty
config:
apiUrl: https://test.host <1.1>
secrets:
routingKey: testroutingkey <2.1>
my-pagerduty:
name: preconfigured-pagerduty-action-type
actionTypeId: .pagerduty
config:
apiUrl: https://test.host <1.1>
secrets:
routingKey: testroutingkey <2.1>
--

`config` defines the action type specific to the configuration and contains the following properties:
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6 changes: 3 additions & 3 deletions docs/user/alerting/action-types/server-log.asciidoc
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Expand Up @@ -18,9 +18,9 @@ Name:: The name of the connector. The name is used to identify a connector

[source,text]
--
id: 'my-server-log'
name: test
actionTypeId: .server-log
my-server-log:
name: test
actionTypeId: .server-log
--

[float]
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10 changes: 5 additions & 5 deletions docs/user/alerting/action-types/slack.asciidoc
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Expand Up @@ -19,11 +19,11 @@ Webhook URL:: The URL of the incoming webhook. See https://api.slack.com/messa

[source,text]
--
id: 'my-slack'
name: preconfigured-slack-action-type
actionTypeId: .slack
config:
webhookUrl: 'https://hooks.slack.com/services/abcd/efgh/ijklmnopqrstuvwxyz' <1>
my-slack:
name: preconfigured-slack-action-type
actionTypeId: .slack
config:
webhookUrl: 'https://hooks.slack.com/services/abcd/efgh/ijklmnopqrstuvwxyz' <1>
--

`config` defines the action type specific to the configuration and contains the following properties:
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22 changes: 11 additions & 11 deletions docs/user/alerting/action-types/webhook.asciidoc
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Expand Up @@ -23,17 +23,17 @@ Password:: An optional password. If set, HTTP basic authentication is used. Cur

[source,text]
--
id: 'my-webhook'
name: preconfigured-webhook-action-type
actionTypeId: .webhook
config:
url: https://test.host <1.1>
method: POST <1.2>
headers: <1.3>
testheader: testvalue
secrets:
user: testuser <2.1>
password: passwordkeystorevalue <2.2>
my-webhook:
name: preconfigured-webhook-action-type
actionTypeId: .webhook
config:
url: https://test.host <1.1>
method: POST <1.2>
headers: <1.3>
testheader: testvalue
secrets:
user: testuser <2.1>
password: passwordkeystorevalue <2.2>
--

`config` defines the action type specific to the configuration and contains the following properties:
Expand Down
8 changes: 4 additions & 4 deletions docs/user/alerting/pre-configured-connectors.asciidoc
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Expand Up @@ -25,12 +25,12 @@ The following example shows a valid configuration of two out-of-the box connecto

```js
xpack.actions.preconfigured:
- id: 'my-slack1' <1>
my-slack1: <1>
actionTypeId: .slack <2>
name: 'Slack #xyz' <3>
config: <4>
webhookUrl: 'https://hooks.slack.com/services/abcd/efgh/ijklmnopqrstuvwxyz'
- id: 'webhook-service'
webhook-service:
actionTypeId: .webhook
name: 'Email service'
config:
Expand All @@ -44,7 +44,7 @@ The following example shows a valid configuration of two out-of-the box connecto
password: changeme
```

<1> `id` is the action connector identifier.
<1> the key is the action connector identifier, eg `my-slack1` in this example.
<2> `actionTypeId` is the action type identifier.
<3> `name` is the name of the preconfigured connector.
<4> `config` is the action type specific to the configuration.
Expand All @@ -69,7 +69,7 @@ The following example shows a valid configuration of preconfigured action type w
```js
xpack.actions.enabledActionTypes: ['.slack', '.email', '.index'] <1>
xpack.actions.preconfigured: <2>
- id: 'my-server-log'
my-server-log:
actionTypeId: .server-log
name: 'Server log #xyz'
```
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14 changes: 14 additions & 0 deletions docs/visualize/tsvb.asciidoc
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Expand Up @@ -122,3 +122,17 @@ Edit the source for the Markdown visualization.
. To insert the mustache template variable into the editor, click the variable name.
+
The http://mustache.github.io/mustache.5.html[mustache syntax] uses the Handlebar.js processor, which is an extended version of the Mustache template language.

[float]
[[tsvb-style-markdown]]
==== Style Markdown text

Style your Markdown visualization using http://lesscss.org/features/[less syntax].

. Select *Markdown*.

. Select *Panel options*.

. Enter styling rules in *Custom CSS* section
+
Less in TSVB does not support custom plugins or inline JavaScript.
2 changes: 1 addition & 1 deletion package.json
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Expand Up @@ -210,7 +210,7 @@
"leaflet-responsive-popup": "0.6.4",
"leaflet-vega": "^0.8.6",
"leaflet.heat": "0.2.0",
"less": "^2.7.3",
"less": "npm:@elastic/less@2.7.3-kibana",
"less-loader": "5.0.0",
"lodash": "npm:@elastic/[email protected]",
"lodash.clonedeep": "^4.5.0",
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10 changes: 8 additions & 2 deletions packages/kbn-dev-utils/src/ci_stats_reporter/README.md
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Expand Up @@ -8,7 +8,7 @@ This class integrates with the `ciStats.trackBuild {}` Jenkins Pipeline function

To create an instance of the reporter, import the class and call `CiStatsReporter.fromEnv(log)` (passing it a tooling log).

#### `CiStatsReporter#metric(name: string, subName: string, value: number)`
#### `CiStatsReporter#metrics(metrics: Array<{ group: string, id: string, value: number }>)`

Use this method to record metrics in the Kibana CI Stats service.

Expand All @@ -19,5 +19,11 @@ import { CiStatsReporter, ToolingLog } from '@kbn/dev-utils';

const log = new ToolingLog(...);
const reporter = CiStatsReporter.fromEnv(log)
reporter.metric('Build speed', specificBuildName, timeToRunBuild)
reporter.metrics([
{
group: 'Build size',
id: specificBuildName,
value: sizeOfBuild
}
])
```
19 changes: 9 additions & 10 deletions packages/kbn-dev-utils/src/ci_stats_reporter/ci_stats_reporter.ts
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Expand Up @@ -84,32 +84,31 @@ export class CiStatsReporter {
return !!this.config;
}

async metric(name: string, subName: string, value: number) {
async metrics(metrics: Array<{ group: string; id: string; value: number }>) {
if (!this.config) {
return;
}

let attempt = 0;
const maxAttempts = 5;
const bodySummary = metrics
.map(({ group, id, value }) => `[${group}/${id}=${value}]`)
.join(' ');

while (true) {
attempt += 1;

try {
await Axios.request({
method: 'POST',
url: '/metric',
url: '/v1/metrics',
baseURL: this.config.apiUrl,
params: {
buildId: this.config.buildId,
},
headers: {
Authorization: `token ${this.config.apiToken}`,
},
data: {
name,
subName,
value,
buildId: this.config.buildId,
metrics,
},
});

Expand All @@ -125,14 +124,14 @@ export class CiStatsReporter {
this.log.warning(
`error recording metric [status=${error.response.status}] [resp=${inspect(
error.response.data
)}] [${name}/${subName}=${value}]`
)}] ${bodySummary}`
);
return;
}

if (attempt === maxAttempts) {
this.log.warning(
`failed to reach kibana-ci-stats service too many times, unable to record metric [${name}/${subName}=${value}]`
`failed to reach kibana-ci-stats service too many times, unable to record metric ${bodySummary}`
);
return;
}
Expand Down
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