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适用于 Java 的 Micrometer 指标
适用范围：
NoSQL
适用于 Azure Cosmos DB 的 Java SDK 使用 Micrometer 工具在常用的可观测性系统（如 Prometheus）中实现客户端指标。 本文包含用于将指标抓取到 Prometheus 中的说明和代码片段，取自此示例。 此处介绍了由 SDK 提供的指标的完整列表。 如果客户端部署在 Azure Kubernetes 服务 (AKS) 上，还可以将适用于 Prometheus 的 Azure Monitor 托管服务与自定义抓取配合使用，请参阅此处的文档。
使用来自 Prometheus 的指标
可以从此处下载 prometheus。 若要在适用于 Azure Cosmos DB 的 Java SDK 中通过 Prometheus 使用 Micrometer 指标，请首先确保已导入注册表和客户端所需的库：
<dependency>
<groupId>io.micrometer</groupId>
<artifactId>micrometer-registry-prometheus</artifactId>
<version>1.6.6</version>
</dependency>
<dependency>
<groupId>io.prometheus</groupId>
<artifactId>simpleclient_httpserver</artifactId>
<version>0.5.0</version>
</dependency>
在应用程序中，向遥测配置提供 prometheus 注册表。请注意，可以设置各种诊断阈值，这有助于将使用的指标限制为最感兴趣的指标：
//prometheus meter registry
PrometheusMeterRegistry prometheusRegistry = new PrometheusMeterRegistry(PrometheusConfig.DEFAULT);
//provide the prometheus registry to the telemetry config
CosmosClientTelemetryConfig telemetryConfig = new CosmosClientTelemetryConfig()
.diagnosticsThresholds(
new CosmosDiagnosticsThresholds()
// Any requests that violate (are lower than) any of the below thresholds that are set
// will not appear in "request-level" metrics (those with "rntbd" or "gw" in their name).
// The "operation-level" metrics (those with "ops" in their name) will still be collected.
// Use this to reduce noise in the amount of metrics collected.
.setRequestChargeThreshold(10)
.setNonPointOperationLatencyThreshold(Duration.ofDays(10))
.setPointOperationLatencyThreshold(Duration.ofDays(10))
)
// Uncomment below to apply sampling to help further tune client-side resource consumption related to metrics.
// The sampling rate can be modified after Azure Cosmos DB Client initialization – so the sampling rate can be
// modified without any restarts being necessary.
//.sampleDiagnostics(0.25)
.clientCorrelationId("samplePrometheusMetrics001")
.metricsOptions(new CosmosMicrometerMetricsOptions().meterRegistry(prometheusRegistry)
//.configureDefaultTagNames(CosmosMetricTagName.PARTITION_KEY_RANGE_ID)
.applyDiagnosticThresholdsForTransportLevelMeters(true)
);
启动本地 HttpServer 服务器，以向 Prometheus 公开计量注册表指标：
try {
HttpServer server = HttpServer.create(new InetSocketAddress(8080), 0);
server.createContext("/metrics", httpExchange -> {
String response = prometheusRegistry.scrape();
int i = 1;
httpExchange.sendResponseHeaders(200, response.getBytes().length);
try (OutputStream os = httpExchange.getResponseBody()) {
os.write(response.getBytes());
}
});
new Thread(server::start).start();
} catch (IOException e) {
throw new RuntimeException(e);
}
确保在创建 CosmosClient 时传递 clientTelemetryConfig：
// Create async client
client = new CosmosClientBuilder()
.endpoint(AccountSettings.HOST)
.key(AccountSettings.MASTER_KEY)
.clientTelemetryConfig(telemetryConfig)
.consistencyLevel(ConsistencyLevel.SESSION) //make sure we can read our own writes
.contentResponseOnWriteEnabled(true)
.buildAsyncClient();
将应用程序客户端的终结点添加到 prometheus.yml 时，在“targets”中添加域名和端口。 例如，如果 prometheus 与应用客户端运行在同一服务器上，则可以按如下所示添加 localhost:8080 到 targets：
scrape_configs:
# The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.
- job_name: "prometheus"
# metrics_path defaults to '/metrics'
# scheme defaults to 'http'.
static_configs:
- targets: ["localhost:9090", "localhost:8080"]
现在，可以使用来自 Prometheus 的指标：
