RDC REST API (Sample code)
Please follow the README file Update README_rdc_rest_api.txt Update RDC_REST_API.py Error handling updates Updates for error handling Updates Updates for rdc_field_watch/rdc_field_unwatch and delete query Updates for rdc_field_watch/rdc_field_unwatch and delete query SWDEV-479738 [RDC] - Rest API Delete python_binding/RDC_REST_API.py new rdc_rest_api.py file for SWDEV-479738 [RDC] - Rest API
Этот коммит содержится в:
AL Musaffar, Yazen
коммит произвёл
Galantsev, Dmitrii
Galantsev, Dmitrii
родитель
e847f74f78
Коммит
cf566ebd31
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# RDC REST API
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## Overview
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This REST API provides functionalities to:
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- Discover available GPUs on a node.
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- Configure and manage GPU monitoring queries.
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- Retrieve GPU metrics based on configured queries.
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The API is built using Flask and interacts with the RDC library to monitor GPU usage and performance metrics.
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## Installation
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### Prerequisites
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- Python 3.x
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- Flask
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- RDC Library (`librdc_bootstrap.so` must be available and accessible)
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### Install Dependencies
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```sh
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pip install flask
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```
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## Running the API
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1. Ensure `librdc_bootstrap.so` is in the library path:
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```sh
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export LD_LIBRARY_PATH=/path/to/librdc_bootstrap.so:$LD_LIBRARY_PATH
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```
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2. Run the API:
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```sh
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python rdc_rest_api.py
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```
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The API will start and listen on `http://0.0.0.0:50052`.
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## API Endpoints
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### 1. Discover GPUs
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**GET** `/rdc/discovery`
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#### Response:
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```json
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{
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"0": "GPU Name",
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"1": "GPU Name"
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}
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```
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### 2. Create Query Criteria
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**POST** `/rdc/query_criteria`
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#### Request Body:
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```json
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{
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"gpu_index": [0,1],
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"metrics": ["RDC_FI_GPU_CLOCK", "RDC_FI_GPU_TEMP"]
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}
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```
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#### Response:
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```json
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{
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"query_id": "G-1-F-2"
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}
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```
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### 3. Get Query Criteria
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**GET** `/rdc/query_criteria/<query_id>`
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#### Response:
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```json
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{
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"gpu_index": [0,1],
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"metrics": ["RDC_FI_GPU_CLOCK", "RDC_FI_GPU_TEMP"],
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"query_id": "G-1-F-2"
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}
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```
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### 4. Delete Query Criteria
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**DELETE** `/rdc/query_criteria/<query_id>`
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#### Response:
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```json
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{
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"message": "Deleted successfully"
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}
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```
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### 5. Retrieve GPU Metrics
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**GET** `/rdc/gpu_metrics/<query_id>`
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#### Response:
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```json
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[
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{
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"gpu_index": 0,
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"RDC_FI_GPU_CLOCK": 1450,
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"RDC_FI_GPU_TEMP": 32
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},
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{
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"gpu_index": 1,
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"RDC_FI_GPU_CLOCK": 736,
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"RDC_FI_GPU_TEMP": 35
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}
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]
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```
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## Notes
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- Ensure `librdc_bootstrap.so` is properly linked.
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- The API should be run on a system with RDC installed and GPUs accessible.
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from flask import Flask, request, jsonify
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from RdcReader import RdcReader
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from RdcUtil import RdcUtil
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from rdc_bootstrap import *
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# Initialize Flask app
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app = Flask(__name__)
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# Initialize RDC Reader and Utilities for handling GPU queries
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rdc_reader = RdcReader(ip_port=None)
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rdc_util = RdcUtil()
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# Dictionary to store query criteria with query_id
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gpu_queries = {}
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# Endpoint to discover available GPUs
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@app.route('/rdc/discovery', methods=['GET'])
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def discover_gpus():
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"""Retrieve a list of available GPUs and their names."""
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try:
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gpu_indexes = rdc_util.get_all_gpu_indexes(rdc_reader.rdc_handle)
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gpus = {}
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for gpu in gpu_indexes:
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device_attr = rdc_device_attributes_t()
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rdc.rdc_device_get_attributes(rdc_reader.rdc_handle, gpu, device_attr)
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gpus[gpu] = device_attr.device_name.decode('utf-8') # Decode GPU name from bytes
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return jsonify(gpus)
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except Exception as e:
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return jsonify({"error": str(e)}), 500
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# Endpoint to create a new query criteria
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@app.route('/rdc/query_criteria', methods=['POST'])
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def create_query_criteria():
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"""Define a new query criteria specifying GPU indices and metrics to monitor."""
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try:
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data = request.json
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if not data or "metrics" not in data:
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return jsonify({"error": "Invalid request payload"}), 400
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gpu_indexes = data.get("gpu_index", rdc_util.get_all_gpu_indexes(rdc_reader.rdc_handle))
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metrics = data.get("metrics", [])
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# Create rdc group and fieldgroup
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gpu_group_id, _ = rdc_util.create_gpu_group(rdc_reader.rdc_handle, b"query_gpu_group", gpu_indexes)
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field_group_id, _ = rdc_util.create_field_group(rdc_reader.rdc_handle, b"query_field_group", [rdc.get_field_id_from_name(m.encode('utf-8')).value for m in metrics])
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# Call rdc_field_watch to start fetching metrics into cache
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result = rdc.rdc_field_watch(rdc_reader.rdc_handle, gpu_group_id, field_group_id, 1000000, 3600.0, 1000)
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if rdc_status_t(result) != rdc_status_t.RDC_ST_OK:
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return jsonify({"error": "Failed to watch fields"}), 500
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query_id = f"G-{gpu_group_id.value}-F-{field_group_id.value}"
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gpu_queries[query_id] = {"gpu_index": gpu_indexes, "metrics": metrics, "query_id": query_id}
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return jsonify({"query_id": query_id})
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except Exception as e:
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return jsonify({"error": str(e)}), 500
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# Endpoint to get all query criteria
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@app.route('/rdc/query_criteria', methods=['GET'])
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def get_all_query_criteria():
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"""Retrieve all stored query criteria for all GPUs."""
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try:
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query_id = request.args.get("query_id")
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if query_id:
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return jsonify(gpu_queries.get(query_id, {}))
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return jsonify(list(gpu_queries.values()))
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except Exception as e:
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return jsonify({"error": str(e)}), 500
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# Endpoint to retrieve a specific query criteria
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@app.route('/rdc/query_criteria/<query_id>', methods=['GET'])
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def get_query_criteria(query_id):
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"""Retrieve query criteria based on a given query ID."""
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try:
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if query_id in gpu_queries:
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return jsonify(gpu_queries[query_id])
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return jsonify({"error": "Query ID not found"}), 404
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except Exception as e:
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return jsonify({"error": str(e)}), 500
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# Endpoint to delete a specific query criteria
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@app.route('/rdc/query_criteria/<query_id>', methods=['DELETE'])
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def delete_query_criteria(query_id):
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"""Delete a query criteria using its query ID."""
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try:
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if query_id in gpu_queries:
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gpu_group_id = rdc_reader.field_group_id
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field_group_id = rdc_reader.field_group_id
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# Call rdc_field_unwatch to stop fetching metrics
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result = rdc.rdc_field_unwatch(rdc_reader.rdc_handle, gpu_group_id, field_group_id)
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if rdc_status_t(result) != rdc_status_t.RDC_ST_OK:
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return jsonify({"error": "Failed to unwatch fields"}), 500
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# Delete GPU and field groups
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rdc.rdc_group_gpu_destroy(rdc_reader.rdc_handle, gpu_group_id)
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rdc.rdc_group_field_destroy(rdc_reader.rdc_handle, field_group_id)
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# Remove the query from storage
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del gpu_queries[query_id]
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return jsonify({"message": "Deleted successfully"})
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return jsonify({"error": "Query ID not found"}), 404
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except Exception as e:
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return jsonify({"error": str(e)}), 500
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# Endpoint to fetch GPU metrics for a specific query ID
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@app.route('/rdc/gpu_metrics/<query_id>', methods=['GET'])
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def get_gpu_metrics(query_id):
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"""Retrieve GPU metrics based on the query ID."""
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try:
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if query_id not in gpu_queries:
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return jsonify({"error": "Query ID not found"}), 404
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query = gpu_queries[query_id]
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gpu_metrics = [] # List to store GPU metric results
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for gpu in query["gpu_index"]:
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gpu_data = {"gpu_index": gpu} # Store GPU index in the response
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for metric in query["metrics"]:
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field_id = rdc.get_field_id_from_name(metric.encode('utf-8')).value
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value = rdc_field_value()
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result = rdc.rdc_field_get_latest_value(rdc_reader.rdc_handle, gpu, field_id, value)
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if rdc_status_t(result) == rdc_status_t.RDC_ST_OK:
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gpu_data[metric] = value.value.l_int # Store metric value
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gpu_metrics.append(gpu_data) # Append GPU data to results
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return jsonify(gpu_metrics)
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except Exception as e:
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return jsonify({"error": str(e)}), 500
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# Main entry point to start the Flask server
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if __name__ == '__main__':
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# Runs the API server, making it accessible on all network interfaces
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app.run(host='0.0.0.0', port=50052)
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