https://github.com/fogdong/kubevela-ai-demo

https://github.com/fogdong/kubevela-ai-demo

Last synced: about 2 months ago
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• Host: GitHub
• URL: https://github.com/fogdong/kubevela-ai-demo
• Owner: FogDong
• Created: 2022-01-18T02:39:14.000Z (about 3 years ago)
• Default Branch: main
• Last Pushed: 2022-01-25T12:57:42.000Z (almost 3 years ago)
• Last Synced: 2024-10-14T20:47:14.311Z (3 months ago)
• Language: Python
• Size: 1.77 MB
• Stars: 2
• Watchers: 2
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# AI 应用云原生最佳实践

这个案例包含了 [训练任务](train.py) 和 [推理服务](api.py) 两个应用。

对于 AI 应用开发者来说，操作流程如下：

- 写业务逻辑 code: train.py + api.py

- 配置下 [app.yaml](./app.yaml)

- 剩下的一键 `dagger up` 即可，包括

  - build & deploy orchestration

  - infrastructure resources rendering

## Quickstart

If you have not setup Dagger environment, run

```

dagger init

dagger new test -p plans/ml

```

Initialize parameters:

```

dagger input yaml parameters -f app.yaml

```

Run:

```

dagger up

dagger query resources

```

## Add a new capability

The [monitoring.cue](./plans/ml/monitoring.cue) is an example to add a new capability to an existing definition:

```go

package ml

// This will register the new capability and expose it to users

parameters: serveModel: monitoring: {

  groups: [...#monitorGroup]

}

#monitorGroup: {

  name: string

  rules: [...#monitorRule]

}

#monitorRule: {

  alert: string

  expr: string

  for: string

  annotations: [string]: string

}

```

Then you can use the capability in `app.yaml`:

```yaml

serveModel:

  ...

  monitoring:

    groups:

      - name: example

        rules:

          - alert: APIHighRequestLatency

            expr: api_http_request_latencies_second{quantile="0.5"} > 1

            for: 10m

            annotations:

              summary: "High request latency on {{ $labels.instance }}"

              description: "{{ $labels.instance }} has a median request latency above 1s (current value: {{ $value }}s)"

```