適用於 Java 的 Micrometer 計量
適用於：
NoSQL
適用於 Azure Cosmos DB 的 Java SDK 使用 Micrometer 來實作用戶端計量，以在 Prometheus 這類熱門可檢視性系統中進行檢測。 本文包括將取自此範例的計量抓取至 Prometheus 的指示和程式碼片段。 SDK 所提供的完整計量清單記載於這裡。 如果您的用戶端部署在 Azure Kubernetes Service (AKS) 上，則您也可以搭配使用適用於 Prometheus 的 Azure 監視器受管理服務與自訂抓取，請參閱這裡的文件。
從 Prometheus 取用計量
您可以從這裡下載 Prometheus。 若要使用 Prometheus 在適用於 Azure Cosmos DB 的 Java SDK 中取用 Micrometer 計量，請先確定您已匯入登錄和用戶端所需的程式庫：
<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>
在您的應用程式中，將 Prometheus 登錄提供給遙測設定。請注意，您可以設定各種診斷閾值，這有助於限制取用您最感興趣的計量：
//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)
);
啟動本機 HttpServer 伺服器，以將計量登錄計量公開至 Prometheus：
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);
}
請確定您在建立 CosmosClient 時傳遞 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();
將應用程式用戶端的端點新增至 prometheus.yml 時，將網域名稱和連接埠新增至「目標」。 例如，如果 prometheus 正在與應用程式用戶端相同的伺服器上執行，則您可以將 localhost:8080 新增至 targets，如下所示：
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"]
現在，您可以從 Prometheus 取用計量：
