Membuat cluster Kafka

Membuat cluster Kafka

Mempelajari lebih lanjut

Untuk dokumentasi mendetail yang menyertakan contoh kode ini, lihat artikel berikut:

Contoh kode

Go

Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Go di Panduan memulai Managed Service untuk Apache Kafka menggunakan library klien. Untuk mengetahui informasi selengkapnya, lihat dokumentasi referensi API Go Managed Service untuk Apache Kafka.

Untuk melakukan autentikasi ke Managed Service untuk Apache Kafka, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

import (
	"context"
	"fmt"
	"io"

	"cloud.google.com/go/managedkafka/apiv1/managedkafkapb"
	"google.golang.org/api/option"

	managedkafka "cloud.google.com/go/managedkafka/apiv1"
)

func createCluster(w io.Writer, projectID, region, clusterID, subnet string, cpu, memoryBytes int64, opts ...option.ClientOption) error {
	// projectID := "my-project-id"
	// region := "us-central1"
	// clusterID := "my-cluster"
	// subnet := "projects/my-project-id/regions/us-central1/subnetworks/default"
	// cpu := 3
	// memoryBytes := 3221225472
	ctx := context.Background()
	client, err := managedkafka.NewClient(ctx, opts...)
	if err != nil {
		return fmt.Errorf("managedkafka.NewClient got err: %w", err)
	}
	defer client.Close()

	locationPath := fmt.Sprintf("projects/%s/locations/%s", projectID, region)
	clusterPath := fmt.Sprintf("%s/clusters/%s", locationPath, clusterID)

	// Memory must be between 1 GiB and 8 GiB per CPU.
	capacityConfig := &managedkafkapb.CapacityConfig{
		VcpuCount:   cpu,
		MemoryBytes: memoryBytes,
	}
	var networkConfig []*managedkafkapb.NetworkConfig
	networkConfig = append(networkConfig, &managedkafkapb.NetworkConfig{
		Subnet: subnet,
	})
	platformConfig := &managedkafkapb.Cluster_GcpConfig{
		GcpConfig: &managedkafkapb.GcpConfig{
			AccessConfig: &managedkafkapb.AccessConfig{
				NetworkConfigs: networkConfig,
			},
		},
	}
	rebalanceConfig := &managedkafkapb.RebalanceConfig{
		Mode: managedkafkapb.RebalanceConfig_AUTO_REBALANCE_ON_SCALE_UP,
	}
	cluster := &managedkafkapb.Cluster{
		Name:            clusterPath,
		CapacityConfig:  capacityConfig,
		PlatformConfig:  platformConfig,
		RebalanceConfig: rebalanceConfig,
	}

	req := &managedkafkapb.CreateClusterRequest{
		Parent:    locationPath,
		ClusterId: clusterID,
		Cluster:   cluster,
	}
	op, err := client.CreateCluster(ctx, req)
	if err != nil {
		return fmt.Errorf("client.CreateCluster got err: %w", err)
	}
	// The duration of this operation can vary considerably, typically taking 10-40 minutes.
	resp, err := op.Wait(ctx)
	if err != nil {
		return fmt.Errorf("op.Wait got err: %w", err)
	}
	fmt.Fprintf(w, "Created cluster: %s\n", resp.Name)
	return nil
}

Java

Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Java di Panduan memulai Managed Service untuk Apache Kafka menggunakan library klien. Untuk mengetahui informasi selengkapnya, lihat dokumentasi referensi API Java Managed Service untuk Apache Kafka.

Untuk melakukan autentikasi ke Managed Service untuk Apache Kafka, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.


import com.google.api.gax.longrunning.OperationFuture;
import com.google.api.gax.longrunning.OperationSnapshot;
import com.google.api.gax.longrunning.OperationTimedPollAlgorithm;
import com.google.api.gax.retrying.RetrySettings;
import com.google.api.gax.retrying.RetryingFuture;
import com.google.api.gax.retrying.TimedRetryAlgorithm;
import com.google.cloud.managedkafka.v1.AccessConfig;
import com.google.cloud.managedkafka.v1.CapacityConfig;
import com.google.cloud.managedkafka.v1.Cluster;
import com.google.cloud.managedkafka.v1.CreateClusterRequest;
import com.google.cloud.managedkafka.v1.GcpConfig;
import com.google.cloud.managedkafka.v1.LocationName;
import com.google.cloud.managedkafka.v1.ManagedKafkaClient;
import com.google.cloud.managedkafka.v1.ManagedKafkaSettings;
import com.google.cloud.managedkafka.v1.NetworkConfig;
import com.google.cloud.managedkafka.v1.OperationMetadata;
import com.google.cloud.managedkafka.v1.RebalanceConfig;
import java.time.Duration;
import java.util.concurrent.ExecutionException;

public class CreateCluster {

  public static void main(String[] args) throws Exception {
    // TODO(developer): Replace these variables before running the example.
    String projectId = "my-project-id";
    String region = "my-region"; // e.g. us-east1
    String clusterId = "my-cluster";
    String subnet = "my-subnet"; // e.g. projects/my-project/regions/my-region/subnetworks/my-subnet
    int cpu = 3;
    long memoryBytes = 3221225472L; // 3 GiB
    createCluster(projectId, region, clusterId, subnet, cpu, memoryBytes);
  }

  public static void createCluster(
      String projectId, String region, String clusterId, String subnet, int cpu, long memoryBytes)
      throws Exception {
    CapacityConfig capacityConfig =
        CapacityConfig.newBuilder().setVcpuCount(cpu).setMemoryBytes(memoryBytes).build();
    NetworkConfig networkConfig = NetworkConfig.newBuilder().setSubnet(subnet).build();
    GcpConfig gcpConfig =
        GcpConfig.newBuilder()
            .setAccessConfig(AccessConfig.newBuilder().addNetworkConfigs(networkConfig).build())
            .build();
    RebalanceConfig rebalanceConfig =
        RebalanceConfig.newBuilder()
            .setMode(RebalanceConfig.Mode.AUTO_REBALANCE_ON_SCALE_UP)
            .build();
    Cluster cluster =
        Cluster.newBuilder()
            .setCapacityConfig(capacityConfig)
            .setGcpConfig(gcpConfig)
            .setRebalanceConfig(rebalanceConfig)
            .build();

    // Create the settings to configure the timeout for polling operations
    ManagedKafkaSettings.Builder settingsBuilder = ManagedKafkaSettings.newBuilder();
    TimedRetryAlgorithm timedRetryAlgorithm = OperationTimedPollAlgorithm.create(
        RetrySettings.newBuilder()
            .setTotalTimeoutDuration(Duration.ofHours(1L))
            .build());
    settingsBuilder.createClusterOperationSettings()
        .setPollingAlgorithm(timedRetryAlgorithm);

    try (ManagedKafkaClient managedKafkaClient = ManagedKafkaClient.create(
        settingsBuilder.build())) {

      CreateClusterRequest request =
          CreateClusterRequest.newBuilder()
              .setParent(LocationName.of(projectId, region).toString())
              .setClusterId(clusterId)
              .setCluster(cluster)
              .build();

      // The duration of this operation can vary considerably, typically taking between 10-40
      // minutes.
      OperationFuture<Cluster, OperationMetadata> future =
          managedKafkaClient.createClusterOperationCallable().futureCall(request);

      // Get the initial LRO and print details.
      OperationSnapshot operation = future.getInitialFuture().get();
      System.out.printf("Cluster creation started. Operation name: %s\nDone: %s\nMetadata: %s\n",
          operation.getName(),
          operation.isDone(),
          future.getMetadata().get().toString());

      while (!future.isDone()) {
        // The pollingFuture gives us the most recent status of the operation
        RetryingFuture<OperationSnapshot> pollingFuture = future.getPollingFuture();
        OperationSnapshot currentOp = pollingFuture.getAttemptResult().get();
        System.out.printf("Polling Operation:\nName: %s\n Done: %s\n",
            currentOp.getName(),
            currentOp.isDone());
      }

      // NOTE: future.get() blocks completion until the operation is complete (isDone =  True)
      Cluster response = future.get();
      System.out.printf("Created cluster: %s\n", response.getName());
    } catch (ExecutionException e) {
      System.err.printf("managedKafkaClient.createCluster got err: %s", e.getMessage());
    }
  }
}

Python

Sebelum mencoba contoh ini, ikuti petunjuk penyiapan Python di Panduan memulai Managed Service untuk Apache Kafka menggunakan library klien. Untuk mengetahui informasi selengkapnya, lihat dokumentasi referensi API Python Managed Service untuk Apache Kafka.

Untuk melakukan autentikasi ke Managed Service untuk Apache Kafka, siapkan Kredensial Default Aplikasi. Untuk mengetahui informasi selengkapnya, lihat Menyiapkan autentikasi untuk lingkungan pengembangan lokal.

from google.api_core.exceptions import GoogleAPICallError
from google.cloud import managedkafka_v1

# TODO(developer)
# project_id = "my-project-id"
# region = "us-central1"
# cluster_id = "my-cluster"
# subnet = "projects/my-project-id/regions/us-central1/subnetworks/default"
# cpu = 3
# memory_bytes = 3221225472

client = managedkafka_v1.ManagedKafkaClient()

cluster = managedkafka_v1.Cluster()
cluster.name = client.cluster_path(project_id, region, cluster_id)
cluster.capacity_config.vcpu_count = cpu
cluster.capacity_config.memory_bytes = memory_bytes
cluster.gcp_config.access_config.network_configs = [
    managedkafka_v1.NetworkConfig(subnet=subnet)
]
cluster.rebalance_config.mode = (
    managedkafka_v1.RebalanceConfig.Mode.AUTO_REBALANCE_ON_SCALE_UP
)

request = managedkafka_v1.CreateClusterRequest(
    parent=client.common_location_path(project_id, region),
    cluster_id=cluster_id,
    cluster=cluster,
)

try:
    operation = client.create_cluster(request=request)
    print(f"Waiting for operation {operation.operation.name} to complete...")
    # The duration of this operation can vary considerably, typically taking 10-40 minutes.
    # We can set a timeout of 3000s (50 minutes).
    response = operation.result(timeout=3000)
    print("Created cluster:", response)
except GoogleAPICallError as e:
    print(f"The operation failed with error: {e.message}")

Terraform

Untuk mempelajari cara menerapkan atau menghapus konfigurasi Terraform, lihat Perintah dasar Terraform. Untuk mengetahui informasi selengkapnya, lihat dokumentasi referensi penyedia Terraform.

resource "google_managed_kafka_cluster" "default" {
  project    = data.google_project.default.project_id # Replace this with your project ID in quotes
  cluster_id = "my-cluster-id"
  location   = "us-central1"
  capacity_config {
    vcpu_count   = 3
    memory_bytes = 3221225472
  }
  gcp_config {
    access_config {
      network_configs {
        subnet = google_compute_subnetwork.default.id
      }
    }
  }
}

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