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Add baseline doc and point to SkyPredictor project (#13040)
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docs/en/api/metrics-query-expression.md

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```
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**Notice**:
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- This feature is required to enable the `baseline module` and deploy a baseline service. And the baseline service should implement the protocol of the [baseline.proto](../../../oap-server/ai-pipeline/src/main/proto/baseline.proto).
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- This feature is required to enable the [Metrics Baseline Calculation](../setup/ai-pipeline/metrics-baseline-integration.md) and deploy a remote service.
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Otherwise, the result will be empty.
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- The baseline operation requires the relative metrics declared through baseline service.
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Otherwise, the result will be empty, which means there is no baseline or predicated value.

docs/en/setup/ai-pipeline/introduction.md

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**Warning, this module is still in the ALPHA stage. This is not stable.**
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Pattern Recognition, Machine Learning(ML) and Artificial Intelligence(AI) are common technology to identify patterns in data.
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This module provides a way to integrate these technologies in a standardized way about shipping the data from OAP kernel
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to 3rd party.
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From the industry practice, Pattern Recognition, Machine Learning(ML) and Artificial Intelligence(AI) are always overestimated,
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Pattern Recognition, Machine Learning(ML) and Artificial Intelligence(AI) are common technology to identify patterns in data.
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From the industry practice, these three are always overestimated for the marketing interests,
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they are good at many things but have to run in a clear context.
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Hence, SkyWalking OAP AI pipeline features are designed for very specific solutions and scenarios with at
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least one recommended (remote) implementations for the integration。
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The ai-pipeline module is activated by default.
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The ai-pipeline module is activated by default for the latest release. Make sure you have these configurations when upgrade
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from a previous version.
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```yaml
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ai-pipeline:
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selector: ${SW_AI_PIPELINE:default}
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default:
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# HTTP Restful URI recognition service address configurations
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uriRecognitionServerAddr: ${SW_AI_PIPELINE_URI_RECOGNITION_SERVER_ADDR:}
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uriRecognitionServerPort: ${SW_AI_PIPELINE_URI_RECOGNITION_SERVER_PORT:17128}
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# Metrics Baseline Calculation service address configurations
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baselineServerAddr: ${SW_API_PIPELINE_BASELINE_SERVICE_HOST:}
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baselineServerPort: ${SW_API_PIPELINE_BASELINE_SERVICE_PORT:18080}
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```
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## Supported Scenarios
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We supported the following AI features:
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* [**HTTP Restful URI recognition**](./http-restful-uri-pattern.md).
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* [**Metrics Baseline Calculation and Alerting**](./metrics-baseline-integration.md).
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# Metrics Baseline Calculation and Alerting
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Metrics baseline calculation and alerting is a feature that calculates the baseline of metrics data and feed for the
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alarm engine as additional metrics to setup rules for alerting.
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[Alarm docs](../backend/backend-alarm.md#use-the-baseline-predicted-value-to-trigger-the-alarm) has more details about
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how to use the baseline, and further about MQE usages of the baseline values.
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SkyAPM community provides a default implementation [SkyAPM/SkyPredictor](https://github.com/SkyAPM/SkyPredictor).
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It has complete support for the baseline calculation by following SkyWalking's metrics data model through GraphQL, and
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feed baseline data back to the OAP server through the following gRPC service per SkyWalking requirement..
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```protobuf
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service AlarmBaselineService {
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// Query the supported metrics names.
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rpc querySupportedMetricsNames(google.protobuf.Empty) returns (AlarmBaselineMetricsNames);
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// Query the predicted metrics of the given service.
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rpc queryPredictedMetrics(AlarmBaselineRequest) returns (AlarmBaselineResponse);
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}
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```
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You could find the protocol definition
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in [AlarmBaseline.proto](../../../../oap-server/ai-pipeline/src/main/proto/baseline.proto).

docs/en/setup/backend/backend-alarm.md

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message: Service {name} response time is higher than the baseline predicted value in 3 minutes of last 10 minutes.
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```
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Note, the baseline predicted value is calculated based on the historical data of the same time window in the past, which
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is through [AI powered baseline calculation](../ai-pipeline/metrics-baseline-integration.md).
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## Hooks
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Hooks are a way to send alarm messages to the outside world. SkyWalking supports multiple hooks of the same type, each hook can support different configurations.
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For example, you can configure two Slack hooks, one named `default` and set `is-default: true` means this hook will apply on all `Alarm Rules` **without config** `hooks`.

docs/menu.yml

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path: "/en/setup/ai-pipeline/introduction"
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- name: "HTTP Restful URI recognition"
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path: "/en/setup/ai-pipeline/http-restful-uri-pattern"
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- name: "Metrics Baseline Calculation and Alerting"
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path: "/en/setup/ai-pipeline/metrics-baseline-integration"
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- name: "UI Setup"
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catalog:
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- name: "Native UI"

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