Google Bigtable

Présentation

Cloud Bigtable est le service de base de données NoSQL big data de Google. Cette base de données est utilisée par beaucoup de services Google, tels que le moteur de recherche, Analytics, Maps et Gmail.

Utilisez l’intégration Datadog/Google Cloud Platform pour recueillir des métriques de Google Bigtable.

Configuration

Installation

Si vous ne l’avez pas déjà fait, configurez d’abord l’intégration Google Cloud Platform. Aucune autre procédure d’installation n’est requise.

Collecte de logs

Les logs Google Bigtable sont recueillis avec Google Cloud Logging et envoyés à un Cloud Pub/Sub via un forwarder Push HTTP. Si vous ne l’avez pas déjà fait, configurez un Cloud Pub/Sub à l’aide d’un forwarder Push HTTP.

Une fois cette opération effectuée, exportez vos logs Google Bigtable depuis Google Cloud Logging vers le Pub/Sub :

  1. Accédez à la page Google Cloud Logging et filtrez les logs Google Bigtable.
  2. Cliquez sur Create Export et nommez le récepteur.
  3. Choisissez Cloud Pub/Sub comme destination et sélectionnez le Pub/Sub créé à cette fin. Remarque : le Pub/Sub peut se situer dans un autre projet.
  4. Cliquez sur Create et attendez que le message de confirmation s’affiche.

Données collectées

Métriques

gcp.bigtable.backup.bytes_used
(gauge)
Backup storage used.
Shown as byte
gcp.bigtable.client.application_blocking_latencies.avg
(count)
The average the total latency introduced by your application when Cloud Bigtable has available response data but your application has not consumed it.
Shown as millisecond
gcp.bigtable.client.application_blocking_latencies.samplecount
(count)
The sample count for the total latency introduced by your application when Cloud Bigtable has available response data but your application has not consumed it.
Shown as millisecond
gcp.bigtable.client.application_blocking_latencies.sumsqdev
(count)
The sum of squared deviation for the total latency introduced by your application when Cloud Bigtable has available response data but your application has not consumed it.
Shown as millisecond
gcp.bigtable.client.attempt_latencies.avg
(count)
The average client observed latency per RPC attempt.
Shown as millisecond
gcp.bigtable.client.attempt_latencies.samplecount
(count)
The sample count for client observed latency per RPC attempt.
Shown as millisecond
gcp.bigtable.client.attempt_latencies.sumsqdev
(count)
The sum of squared deviation for client observed latency per RPC attempt.
Shown as millisecond
gcp.bigtable.client.client_blocking_latencies.avg
(count)
The average the latency introduced by the client by blocking on sending more requests to the server when there are too many pending requests in bulk operations.
Shown as millisecond
gcp.bigtable.client.client_blocking_latencies.samplecount
(count)
The sample count for the latency introduced by the client by blocking on sending more requests to the server when there are too many pending requests in bulk operations.
Shown as millisecond
gcp.bigtable.client.client_blocking_latencies.sumsqdev
(count)
The sum of squared deviation for the latency introduced by the client by blocking on sending more requests to the server when there are too many pending requests in bulk operations.
Shown as millisecond
gcp.bigtable.client.connectivity_error_count
(count)
Number of requests that failed to reach the Google network. (Requests without google response headers).
gcp.bigtable.client.first_response_latencies.avg
(count)
The average latency from operation start until the response headers were received. The publishing of the measurement will be delayed until the attempt response has been received.
Shown as millisecond
gcp.bigtable.client.first_response_latencies.samplecount
(count)
The sample count for latency from operation start until the response headers were received. The publishing of the measurement will be delayed until the attempt response has been received.
Shown as millisecond
gcp.bigtable.client.first_response_latencies.sumsqdev
(count)
The sum of squared deviation for latency from operation start until the response headers were received. The publishing of the measurement will be delayed until the attempt response has been received.
Shown as millisecond
gcp.bigtable.client.operation_latencies.avg
(count)
The average distribution of the total end-to-end latency across all RPC attempts associated with a Bigtable operation.
Shown as millisecond
gcp.bigtable.client.operation_latencies.samplecount
(count)
The sample count for distribution of the total end-to-end latency across all RPC attempts associated with a Bigtable operation.
Shown as millisecond
gcp.bigtable.client.operation_latencies.sumsqdev
(count)
The sum of squared deviation for distribution of the total end-to-end latency across all RPC attempts associated with a Bigtable operation.
Shown as millisecond
gcp.bigtable.client.retry_count
(count)
The number of additional RPCs sent after the initial attempt.
gcp.bigtable.client.server_latencies.avg
(count)
The average the latency measured between the time when Google frontend receives an RPC and sending back the first byte of the response.
Shown as millisecond
gcp.bigtable.client.server_latencies.samplecount
(count)
The sample count for the latency measured between the time when Google frontend receives an RPC and sending back the first byte of the response.
Shown as millisecond
gcp.bigtable.client.server_latencies.sumsqdev
(count)
The sum of squared deviation for the latency measured between the time when Google frontend receives an RPC and sending back the first byte of the response.
Shown as millisecond
gcp.bigtable.cluster.autoscaling.max_node_count
(gauge)
Maximum number of nodes in an autoscaled cluster.
gcp.bigtable.cluster.autoscaling.min_node_count
(gauge)
Minimum number of nodes in an autoscaled cluster.
gcp.bigtable.cluster.autoscaling.recommended_node_count_for_cpu
(gauge)
Recommended number of nodes in an autoscaled cluster based on CPU usage.
gcp.bigtable.cluster.autoscaling.recommended_node_count_for_storage
(gauge)
Recommended number of nodes in an autoscaled cluster based on storage usage.
gcp.bigtable.cluster.cpu_load
(gauge)
CPU load of a cluster.
gcp.bigtable.cluster.cpu_load_by_app_profile_by_method_by_table
(gauge)
CPU load of a cluster split by app profile, method, and table.
gcp.bigtable.cluster.cpu_load_hottest_node
(gauge)
CPU load of the busiest node in a cluster.
gcp.bigtable.cluster.cpu_load_hottest_node_high_granularity
(gauge)
CPU load of the busiest node in a cluster sampled at a high granularity.
gcp.bigtable.cluster.disk_load
(gauge)
Utilization of HDD disks in a cluster.
gcp.bigtable.cluster.node_count
(gauge)
Number of nodes in a cluster.
Shown as node
gcp.bigtable.cluster.storage_utilization
(gauge)
Storage used as a fraction of total storage capacity.
gcp.bigtable.disk.bytes_used
(gauge)
Amount of compressed data for tables stored in a cluster.
Shown as byte
gcp.bigtable.disk.per_node_storage_capacity
(gauge)
Capacity of compressed data for tables that can be stored per node in the cluster.
Shown as byte
gcp.bigtable.disk.storage_capacity
(gauge)
Capacity of compressed data for tables that can be stored in a cluster.
Shown as byte
gcp.bigtable.replication.latency.avg
(gauge)
Distribution of replication request latencies for a table.
Shown as millisecond
gcp.bigtable.replication.latency.samplecount
(gauge)
Sample count for replication request latencies.
Shown as sample
gcp.bigtable.replication.latency.sumsqdev
(gauge)
Sum of squared deviation for replication request latencies.
Shown as second
gcp.bigtable.replication.max_delay
(gauge)
Upper bound for replication delay between clusters of a table.
Shown as second
gcp.bigtable.server.data_boost.eligibility_count
(count)
Current Bigtable requests that are eligible and ineligible for Data Boost.
gcp.bigtable.server.data_boost.ineligible_reasons
(gauge)
Reasons that current traffic is ineligible for Data Boost.
gcp.bigtable.server.data_boost.spu_usage
(gauge)
The Serverless-Processing-Units usage (in SPU-seconds) for Data Boost requests.
gcp.bigtable.server.error_count
(count)
Number of server requests for a table that failed with an error.
Shown as error
gcp.bigtable.server.latencies.avg
(gauge)
Distribution of replication request latencies for a table.
Shown as millisecond
gcp.bigtable.server.latencies.samplecount
(gauge)
Sample count for replication request latencies.
Shown as sample
gcp.bigtable.server.latencies.sumsqdev
(gauge)
Sum of squared deviation for replication request latencies.
Shown as second
gcp.bigtable.server.modified_rows_count
(count)
Number of rows modified by server requests for a table.
Shown as row
gcp.bigtable.server.multi_cluster_failovers_count
(count)
Number of failovers during multi-cluster requests.
gcp.bigtable.server.received_bytes_count
(count)
Number of uncompressed bytes of request data received by servers for a table.
Shown as byte
gcp.bigtable.server.request_count
(count)
Number of server requests for a table.
Shown as request
gcp.bigtable.server.request_max_per_minute_count
(count)
Maximum number of requests received in a five-second span per minute.
gcp.bigtable.server.returned_rows_count
(count)
Number of rows returned by server requests for a table.
Shown as row
gcp.bigtable.server.sent_bytes_count
(count)
Number of uncompressed bytes of response data sent by servers for a table.
Shown as byte
gcp.bigtable.table.bytes_used
(gauge)
Amount of compressed data stored in a table.
Shown as byte
gcp.bigtable.table.change_stream_log_used_bytes
(gauge)
Amount of disk storage used by the change stream logs.
Shown as byte

Événements

L’intégration Google Bigtable n’inclut aucun événement.

Checks de service

L’intégration Google Bigtable n’inclut aucun check de service.

Dépannage

Besoin d’aide ? Contactez l’assistance Datadog.