python - 尝试查询 Log Analytics 工作区表时出现 "Requested Path Does Not Exist"

Question

我正在做一个实验，其中使用 Azure Python SDK 创建一个资源组，其中包含:aks 集群、日志分析工作区和应用程序见解(基于工作区)。然后我运行另一个服务来为其创建可用性测试。第三步是使用 Flask 应用程序查询工作区日志中的“AppAvailabilityResults”表，该应用程序具有发出 GET 请求的路由。直到最后一步为止的所有内容都有效，并且我已经对其进行了调试，因此我知道凭据/LA 信息正在正确地通过我的代码，但是当我运行请求时，我收到此错误:

raise HttpResponseError(message=error.message, response=error.response, model=model)azure.core.exceptions.HttpResponseError: (PathNotFoundError) The requested path does not existCode: PathNotFoundErrorMessage: The requested path does not existINFO:werkzeug:127.0.0.1 - - [14/Sep/2023 14:34:02] "GET /checks HTTP/1.1" 500 -

代码如下:

# Check Log Analytics and return results
def query_availability_results():
    try:
        query_client = LogsQueryClient(credentials)

        query = """
        AppAvailabilityResults
        """

        # Use timespan in query
        response = query_client.query_workspace(workspace_id=LOG_ANALYTICS_WORKSPACE.id, query=query, timespan=timespan)
        result_tables = LogsQueryResult.tables(response)

        return result_tables

    except Exception as e:
        app.logger.error(f"Error querying Log Analytics: {str(e)}")
        return None

# API route to check uptime
@app.route("/checks")
def get_checks():
    app.logger.info("Received request for /checks")
    # Execute the query and handle errors
    availability_results = query_availability_results()

    if availability_results is None:
        return jsonify({"error": "Error querying Log Analytics"}), 500

    checks = []
    try:
        for row in availability_results[0]:
            check = {
                "timeGenerated": row.get("timeGenerated", ""),
                "name": row.get("name", ""),
                "duration": row.get("durationMs", ""),
                "success": row.get("success", ""),
                "location": row.get("location", ""),
            }
            checks.append(check)
    except Exception as e:
        app.logger.error(f"Error parsing Log Analytics results: {str(e)}")
        return jsonify({"error": "Error parsing Log Analytics results"}), 500

    return jsonify(checks)

有什么想法吗？提前致谢。

Answer 1

请求的路径不存在”通常表示您尝试对 Log Analytics 工作区执行的查询未在工作区中找到指定的表或数据源。

• 使用了以下代码 MSDOC在 flask 应用程序中并能够跟踪日志。

app = Flask(__name__)

# Configure logging to print logs to the console
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')

# Define the LOG_WORKSPACE_ID as a string
LOG_WORKSPACE_ID = " "

credential = DefaultAzureCredential()
client = LogsQueryClient(credential)

@app.route('/')
def query_and_print_logs():
    try:
        requests = [
            LogsBatchQuery(
                query="     ",
                timespan=timedelta(hours=1),
                workspace_id=LOG_WORKSPACE_ID
            ),
            LogsBatchQuery(
                query="  ",  # Replace with a valid log query
                timespan=timedelta(days=1),
                workspace_id=LOG_WORKSPACE_ID
            ),
            LogsBatchQuery(
                query= """let Weight = 92233720368547758;
                range x from 1 to 3 step 1
                | summarize percentilesw(x, Weight * 100, 50)""",
                workspace_id=LOG_WORKSPACE_ID,
                timespan=(datetime(2021, 6, 2, tzinfo=timezone.utc), datetime(2021, 6, 5, tzinfo=timezone.utc)), # (start, end)
                include_statistics=True
            ),
        ]
        results = client.query_batch(requests)

        for res in results:
            if res.status == LogsQueryStatus.FAILURE:
                # this will be a LogsQueryError
                logging.error(res.message)
            elif res.status == LogsQueryStatus.PARTIAL:
                ## this will be a LogsQueryPartialResult
                logging.warning(res.partial_error)
                for table in res.partial_data:
                    df = pd.DataFrame(table.rows, columns=table.columns)
                    logging.info(df)
            elif res.status == LogsQueryStatus.SUCCESS:
                ## this will be a LogsQueryResult
                table = res.tables[0]
                df = pd.DataFrame(table.rows, columns=table.columns)
                logging.info(df.to_string())

        return "Check console logs for output."

    except Exception as e:
        logging.error(str(e))
        return "An error occurred. Check console logs for details."

if __name__ == '__main__':
    app.run()

输出: