使用 Java 函数的监控和日志记录策略有哪些？

监控和日志记录 java 函数的策略：监控：使用 cloud monitoring api：提供对性能和指标的可见性。发送自定义指标数据点和时间序列。日志记录：使用 stackdriver logging：记录事件，进行调试和故障排除。使用 cloud logging api：发送和接收日志条目。通过 stackdriver logging：直接记录，提供方便的日志语句和配置。

使用 Java 函数的监控和日志记录策略

简介

监控和日志记录对于维护稳定可靠的 Java 函数至关重要。本文讨论了在 Java 函数中实现这些策略的不同方法。

监控

• 使用 Cloud Monitoring API：该 API 提供了对函数性能和其他指标的深入可见性。

import com.google.cloud.functions.HttpFunction;
import com.google.cloud.functions.HttpRequest;
import com.google.cloud.functions.HttpResponse;
import com.google.cloud.monitoring.v3.MetricServiceClient;
import com.google.monitoring.v3.CustomMetric;
import com.google.monitoring.v3.ProjectName;
import com.google.monitoring.v3.TimeInterval;
import com.google.monitoring.v3.TimeSeries;
import com.google.protobuf.Struct;
import com.google.protobuf.Value;
import java.io.IOException;
import java.io.PrintWriter;
import java.util.Date;

public class Monitor implements HttpFunction {

  private static final String projectId = System.getenv("GOOGLE_CLOUD_PROJECT");
  private static final MetricServiceClient metricClient = MetricServiceClient.create();
  private static final ProjectName projectName = ProjectName.of(projectId);

  @Override
  public void service(HttpRequest request, HttpResponse response)
      throws IOException {
    var writer = new PrintWriter(response.getWriter());

    // 创建一个自定义指标
    var metric =
        CustomMetric.newBuilder()
            .setType("custom.googleapis.com/my_metric")
            .setMetricKind(CustomMetric.MetricKind.GAUGE)
            .setValueType(CustomMetric.ValueType.DOUBLE)
            .build();

    // 发送指标数据点
    var requestBuilder = TimeSeries.newBuilder()
        .setMetric(metric.getName())
        .setResource(projectName.toString())
        .addMetrics(
            CustomMetric.newBuilder()
                .setDoubleValue(Math.random() * 100)
                .build());

    var timestamp = new Date().getTime() / 1000.0;
    requestBuilder.setInterval(
        TimeInterval.newBuilder()
            .setStartTime(com.google.protobuf.Timestamp.newBuilder().setSeconds(timestamp).build())
            .setEndTime(com.google.protobuf.Timestamp.newBuilder().setSeconds(timestamp).build())
            .build());

    TimeSeries series = requestBuilder.build();

    metricClient.createTimeSeries(projectName, series);
    writer.printf("Metric sent at: %sn", new Date());
  }
}

• 使用 Stackdriver Logging：记录函数执行中的事件，提供对调试和故障排除的有价值见解。

import com.google.cloud.functions.HttpFunction;
import com.google.cloud.functions.HttpRequest;
import com.google.cloud.functions.HttpResponse;
import java.io.IOException;
import java.io.PrintWriter;
import java.util.logging.Logger;

public class Log implements HttpFunction {

  private static final Logger logger = Logger.getLogger(Log.class.getName());

  @Override
  public void service(HttpRequest request, HttpResponse response)
      throws IOException {
    var writer = new PrintWriter(response.getWriter());

    // 记录信息级别日志消息
    logger.info("Function executed successfully.");
    writer.printf("Logged at: %sn", new Date());
  }
}

日志记录

• 使用 Cloud Logging API：一个通用的日志记录服务，用于从 Java 函数发送和接收日志条目。

import com.google.api.gax.rpc.ApiException;
import com.google.cloud.functions.BackgroundFunction;
import com.google.cloud.functions.Context;
import com.google.cloud.logging.LogEntry;
import com.google.cloud.logging.Logging;
import com.google.cloud.logging.LoggingOptions;
import java.util.HashMap;
import java.util.Map;

public class CloudLog implements BackgroundFunction