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Merge remote-tracking branch 'elastic' into tech-debt/rename_examples
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clintandrewhall committed Jul 31, 2020
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49 changes: 37 additions & 12 deletions docs/apm/machine-learning.asciidoc
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@@ -1,36 +1,61 @@
[role="xpack"]
[[machine-learning-integration]]
=== integration
=== Machine learning integration

++++
<titleabbrev>Integrate with machine learning</titleabbrev>
++++

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.
The Machine learning integration initiates a new job predefined to calculate anomaly scores on APM transaction durations.
With this integration, you can quickly pinpoint anomalous transactions and see the health of
any upstream and downstream services.

After a machine learning job is created, results are shown in two places:
Machine learning jobs are created per environment, and are based on a service's average response time.
Because jobs are created at the environment level,
you can add new services to your existing environments without the need for additional machine learning jobs.

The transaction duration graph will show the expected bounds and add an annotation when the anomaly score is 75 or above.
After a machine learning job is created, results are shown in two places:

* The transaction duration chart 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.

* Service maps will display a color-coded anomaly indicator based on the detected anomaly score.
+
[role="screenshot"]
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
=== Enable anomaly detection

To enable machine learning anomaly detection:

. From the Services overview, Traces overview, or Service Map tab,
select **Anomaly detection**.

. Click **Create ML Job**.

To enable machine learning anomaly detection, first choose a service to monitor.
Then, select **Integrations** > **Enable ML anomaly detection** and click **Create job**.
. Machine learning jobs are created at the environment level.
Select all of the service environments that you want to enable anomaly detection in.
Anomalies will surface for all services and transaction types within the selected environments.

. Click **Create Jobs**.

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*.
it might take additional time for results to appear on your service maps.
Existing 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.

[float]
[[warning-ml-integration]]
=== Anomaly detection warning

To make machine learning as easy as possible to set up,
the APM app will warn you when filtered to an environment without a machine learning job.

[role="screenshot"]
image::apm/images/apm-anomaly-alert.png[Example view of anomaly alert in the APM app]
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<!-- Do not edit this file. It is automatically generated by API Documenter. -->

[Home](./index.md) &gt; [kibana-plugin-core-server](./kibana-plugin-core-server.md) &gt; [KibanaRequestEvents](./kibana-plugin-core-server.kibanarequestevents.md) &gt; [completed$](./kibana-plugin-core-server.kibanarequestevents.completed_.md)

## KibanaRequestEvents.completed$ property

Observable that emits once if and when the request has been completely handled.

<b>Signature:</b>

```typescript
completed$: Observable<void>;
```

## Remarks

The request may be considered completed if: - A response has been sent to the client; or - The request was aborted.

Original file line number Diff line number Diff line change
Expand Up @@ -17,4 +17,5 @@ export interface KibanaRequestEvents
| Property | Type | Description |
| --- | --- | --- |
| [aborted$](./kibana-plugin-core-server.kibanarequestevents.aborted_.md) | <code>Observable&lt;void&gt;</code> | Observable that emits once if and when the request has been aborted. |
| [completed$](./kibana-plugin-core-server.kibanarequestevents.completed_.md) | <code>Observable&lt;void&gt;</code> | Observable that emits once if and when the request has been completely handled. |

91 changes: 91 additions & 0 deletions src/core/server/http/integration_tests/request.test.ts
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Expand Up @@ -23,6 +23,7 @@ import { HttpService } from '../http_service';
import { contextServiceMock } from '../../context/context_service.mock';
import { loggingSystemMock } from '../../logging/logging_system.mock';
import { createHttpServer } from '../test_utils';
import { schema } from '@kbn/config-schema';

let server: HttpService;

Expand Down Expand Up @@ -195,6 +196,96 @@ describe('KibanaRequest', () => {
expect(nextSpy).toHaveBeenCalledTimes(0);
expect(completeSpy).toHaveBeenCalledTimes(1);
});

it('does not complete before response has been sent', async () => {
const { server: innerServer, createRouter, registerOnPreAuth } = await server.setup(
setupDeps
);
const router = createRouter('/');

const nextSpy = jest.fn();
const completeSpy = jest.fn();

registerOnPreAuth((req, res, toolkit) => {
req.events.aborted$.subscribe({
next: nextSpy,
complete: completeSpy,
});
return toolkit.next();
});

router.post(
{ path: '/', validate: { body: schema.any() } },
async (context, request, res) => {
expect(completeSpy).not.toHaveBeenCalled();
return res.ok({ body: 'ok' });
}
);

await server.start();

await supertest(innerServer.listener).post('/').send({ data: 'test' }).expect(200);

expect(nextSpy).toHaveBeenCalledTimes(0);
expect(completeSpy).toHaveBeenCalledTimes(1);
});
});

describe('completed$', () => {
it('emits once and completes when response is sent', async () => {
const { server: innerServer, createRouter } = await server.setup(setupDeps);
const router = createRouter('/');

const nextSpy = jest.fn();
const completeSpy = jest.fn();

router.get({ path: '/', validate: false }, async (context, req, res) => {
req.events.completed$.subscribe({
next: nextSpy,
complete: completeSpy,
});

expect(nextSpy).not.toHaveBeenCalled();
expect(completeSpy).not.toHaveBeenCalled();
return res.ok({ body: 'ok' });
});

await server.start();

await supertest(innerServer.listener).get('/').expect(200);
expect(nextSpy).toHaveBeenCalledTimes(1);
expect(completeSpy).toHaveBeenCalledTimes(1);
});

it('emits once and completes when response is aborted', async (done) => {
expect.assertions(2);
const { server: innerServer, createRouter } = await server.setup(setupDeps);
const router = createRouter('/');

const nextSpy = jest.fn();

router.get({ path: '/', validate: false }, async (context, req, res) => {
req.events.completed$.subscribe({
next: nextSpy,
complete: () => {
expect(nextSpy).toHaveBeenCalledTimes(1);
done();
},
});

expect(nextSpy).not.toHaveBeenCalled();
await delay(30000);
return res.ok({ body: 'ok' });
});

await server.start();

const incomingRequest = supertest(innerServer.listener)
.get('/')
// end required to send request
.end();
setTimeout(() => incomingRequest.abort(), 50);
});
});
});
});
19 changes: 17 additions & 2 deletions src/core/server/http/router/request.ts
Original file line number Diff line number Diff line change
Expand Up @@ -64,6 +64,16 @@ export interface KibanaRequestEvents {
* Observable that emits once if and when the request has been aborted.
*/
aborted$: Observable<void>;

/**
* Observable that emits once if and when the request has been completely handled.
*
* @remarks
* The request may be considered completed if:
* - A response has been sent to the client; or
* - The request was aborted.
*/
completed$: Observable<void>;
}

/**
Expand Down Expand Up @@ -186,11 +196,16 @@ export class KibanaRequest<

private getEvents(request: Request): KibanaRequestEvents {
const finish$ = merge(
fromEvent(request.raw.req, 'end'), // all data consumed
fromEvent(request.raw.res, 'finish'), // Response has been sent
fromEvent(request.raw.req, 'close') // connection was closed
).pipe(shareReplay(1), first());

const aborted$ = fromEvent<void>(request.raw.req, 'aborted').pipe(first(), takeUntil(finish$));
const completed$ = merge<void, void>(finish$, aborted$).pipe(shareReplay(1), first());

return {
aborted$: fromEvent<void>(request.raw.req, 'aborted').pipe(first(), takeUntil(finish$)),
aborted$,
completed$,
} as const;
}

Expand Down
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