GKE on-prem includes multiple options for cluster logging and monitoring, including cloud-based managed services, open source tools, and validated compatibility with third-party commercial solutions. This page explains these options and provides some basic guidance on selecting the proper solution for your environment.
Options for GKE on-prem
You have several logging and monitoring options for your GKE on-prem clusters:
- Cloud Logging and Cloud Monitoring, enabled by in-cluster agents deployed with GKE on-prem.
- Prometheus and Grafana, disabled by default.
- Validated configurations with third-party solutions.
Cloud Logging and Cloud Monitoring
Google Cloud Observability is the built-in observability solution for Google Cloud. It offers a fully managed logging solution, metrics collection, monitoring, dashboarding, and alerting. Cloud Monitoring monitors GKE on-prem clusters in a similar way as cloud-based GKE clusters.
The in-cluster agents can be configured for the scope of monitoring and logging, as well as the level of metrics collected:
- Scope of logging and monitoring can be set to system components only (the default) or for system components and applications
- Level of metrics collected can be configured for an optimized set of metrics or for full metrics
See Configuring Stackdriver agents for Anthos clusters on VMware on this page for more information.
Logging and Monitoring provide an ideal solution for customers wanting a single, easy-to-configure, powerful cloud-based observability solution. We highly recommend Logging and Monitoring when running workloads only on GKE on-prem, or workloads on GKE and GKE on-prem. For applications with components running on GKE on-prem and traditional on-premises infrastructure, you might consider other solutions for an end-to-end view of those applications.
For details about architecture, configuration, and what data is replicated to your Google Cloud project by default for GKE on-prem, see the section How Logging and Monitoring for GKE on-prem works.
For more information about Logging, see the Cloud Logging documentation.
For more information about Monitoring, see the Cloud Monitoring documentation.
Prometheus and Grafana
Prometheus and Grafana are two popular open source monitoring products:
Prometheus collects application and system metrics.
Alertmanager handles sending alerts out with several different alerting mechanisms.
Grafana is a dashboarding tool.
Prometheus and Grafana can be enabled on each admin cluster and user cluster. Prometheus and Grafana is recommended for application teams with prior experience with those products, or for operational teams who prefer to retain application metrics within the cluster and for troubleshooting issues when network connectivity is lost.
Third-party solutions
Google has worked with several third-party logging and monitoring solution providers to help their products work well with GKE on-prem. These include Datadog, Elastic, and Splunk. Additional validated third parties will be added in the future.
The following solution guides are available for using third-party solutions with GKE on-prem:
How Logging and Monitoring for GKE on-prem works
Logging and metrics agents are installed and activated in each cluster when you create a new admin or user cluster.
The Stackdriver agents include several components on each cluster:
Stackdriver Operator (
stackdriver-operator-*). Manages the lifecycle for all other Stackdriver agents deployed onto the cluster.Stackdriver Custom Resource. A resource that is automatically created as part of the GKE on-prem installation process; users can change the custom resource to update values such as project ID, cluster name, and cluster location at any time.
Stackdriver Log Aggregator (
stackdriver-log-aggregator-*). A Fluentd StatefulSet that sends logs to the Cloud Logging API; if logs can't be sent, the Log Aggregator buffers the log entries, up to 200 GB, and tries to resend them for up to 24 hours. If the buffer gets full or if the Log Aggregator can't reach the Logging API for more than 24 hours, logs are dropped.Stackdriver Log Forwarder (
stackdriver-log-forwarder-*). A Fluentbit daemonset that forwards logs from each machine to the Stackdriver Log Aggregator.Stackdriver Metrics Collector (
stackdriver-prometheus-k8s-). A Prometheus and Stackdriver Prometheus Sidecar StatefulSet that sends Prometheus metrics to the Cloud Logging API.Stackdriver Metadata Collector (
stackdriver-metadata-agent-). A deployment that sends metadata for Kubernetes resources such as pods, deployments, or nodes to the Stackdriver Resource Metadata API; this data is used to enrich metric queries by enabling you to query by deployment name, node name, or even Kubernetes service name.
You can see all of the agents installed by Stackdriver by running the following command:
kubectl -n kube-system get pods | grep stackdriver
The output of this command is similar to the following:
stackdriver-log-aggregator-0 1/1 Running 0 4h31m stackdriver-log-aggregator-1 1/1 Running 0 4h28m stackdriver-log-forwarder-bpf8g 1/1 Running 0 4h31m stackdriver-log-forwarder-cht4m 1/1 Running 0 4h31m stackdriver-log-forwarder-fth5s 1/1 Running 0 4h31m stackdriver-log-forwarder-kw4j2 1/1 Running 0 4h29m stackdriver-metadata-agent-cluster-level... 1/1 Running 0 4h31m stackdriver-operator-76ddb64d57-4tcj9 1/1 Running 0 4h37m stackdriver-prometheus-k8s-0 2/2 Running 0 4h31m
Configuring Stackdriver agents for GKE on-prem
The Stackdriver agents installed with GKE on-prem collect data about system components, subject to your settings and configuration, for the purposes of maintaining and troubleshooting issues with your clusters.
System components only (default scope)
Upon installation, Stackdriver agents collect logs and metrics, including performance details (for example, CPU and memory utilization) and similar metadata, for Google-provided system components. These include all workloads in the admin cluster, and for user clusters, workloads in the kube-system, gke-system, gke-connect, istio-system, and config-management-system namespaces. The Stackdriver agents can be configured or disabled as described in the following sections.
The scope of logs and metrics collected can be expanded to include applications, as well. For instructions to enable application logging and monitoring, see Enabling Logging and Monitoring for user applications.
Optimized metrics (default metrics)
By default, the metrics agents running in the cluster collect and report an optimized set of container and kubelet metrics to Google Cloud's operations suite (formerly Stackdriver). Fewer resources are needed to collect this optimized set of metrics, which improves overall performance and scalability. This is especially important for container-level metrics, due to the large quantity of objects to monitor.
The following container metrics are excluded from the optimized metrics:
- container_cpu_cfs_periods_total
- container_cpu_cfs_throttled_periods_total
- container_cpu_load_average_10s
- container_cpu_system_seconds_total
- container_cpu_user_seconds_total
- container_fs_io_current
- container_fs_io_time_seconds_total
- container_fs_io_time_weighted_seconds_total
- container_fs_read_seconds_total
- container_fs_reads_bytes_total
- container_fs_reads_merged_total
- container_fs_reads_total
- container_fs_sector_reads_total
- container_fs_sector_writes_total
- container_fs_write_seconds_total
- container_fs_writes_bytes_total
- container_fs_writes_merged_total
- container_fs_writes_total
- container_last_seen
- container_memory_cache
- container_memory_failcnt
- container_memory_mapped_file
- container_memory_max_usage_bytes
- container_memory_swap
- container_network_receive_packets_dropped_total
- container_network_receive_packets_total
- container_network_transmit_packets_dropped_total
- container_network_transmit_packets_total
- container_start_time_seconds
- container_spec_cpu_period
- container_spec_cpu_quota
- container_spec_cpu_shares
- container_spec_memory_limit_bytes
- container_spec_memory_reservation_limit_bytes
- container_spec_memory_swap_limit_bytes
- container_start_time_seconds
- container_tasks_state
The complete set of metrics is documented in GKE Enterprise metrics.
The following kubelet metrics are excluded from the optimized metrics:
- kubelet_runtime_operations_duration_seconds
- kubelet_runtime_operations_errors
- kubelet_runtime_operations_duration_seconds
- kubelet_runtime_operations_latency_microseconds
- kubelet_runtime_operations_latency_microseconds_count
- kubelet_runtime_operations_latency_microseconds_sum
- rest_client_request_duration_seconds
- rest_client_request_latency_seconds
The complete set of metrics is documented in GKE Enterprise metrics.
To disable optimized metrics (not recommended), set the optimizedMetrics field
to false in your Stackdriver custom resource. For more information on changing
your Stackdriver custom resource, see
Configuring Stackdriver component resources.
All metrics, including those excluded by default, are
described in GKE Enterprise metrics.
Stackdriver disabled
Stackdriver agents can be disabled completely by deleting the Stackdriver custom resource. Before you disable Stackdriver, see the support page for details about how this affects Google Cloud Support's SLAs.
To disable Stackdriver for GKE on-prem:
kubectl -n kube-system delete stackdriver stackdriver
Stackdriver agents capture data stored locally, subject to your storage and retention configuration. The data is replicated to the Google Cloud project specified at installation by using a service account that is authorized to write data to that project. Stackdriver agents can be disabled at anytime, as described earlier. Data collected by Stackdriver agents can be managed and deleted like any other metric and log data, as described in the Cloud Monitoring documentation.
Configuration requirements for Logging and Monitoring
To use Logging and Monitoring with a cluster, you must configure the Google Cloud project where you want to view logs and metrics. This Google Cloud project is called your logging-monitoring project.
Enable the following APIs in your logging-monitoring project:
Grant following IAM roles to your logging-monitoring service account on your logging-monitoring project.
logging.logWritermonitoring.metricWriterstackdriver.resourceMetadata.writermonitoring.dashboardEditor
Pricing
There is no charge for GKE Enterprise system logs and metrics. Control plane logs, control plane metrics, and a curated subset of Kube state metrics are enabled by default for GKE clusters on Google Cloud that are registered at cluster creation time in a GKE Enterprise enabled project. Control plane logs incur Cloud Logging charges, while default-on metrics are included at no additional charge.
For the list of included GKE logs and metrics, see What logs are collected and Available metrics.
In a GKE on-prem cluster, GKE Enterprise system logs and metrics include the following:
- Logs and metrics from all components in an admin cluster
- Logs and metrics from components in these namespaces in a user cluster:
kube-system,gke-system,gke-connect,knative-serving,istio-system,monitoring-system,config-management-system,gatekeeper-system,cnrm-system
For more information, see Pricing for Google Cloud Observability.
To learn about credit for Cloud Logging metrics, contact sales for pricing.
How Prometheus and Grafana for GKE on-prem work
Each GKE on-prem cluster is created with Prometheus and Grafana disabled by default. You can follow the installation guide to enable them.
The Prometheus Server is set up in a highly-available configuration with two replicas running on two separate nodes. Resource requirements are adjusted to support clusters running up to five nodes, with each handling up to 30 Pods that serve custom metrics. Prometheus has a dedicated PersistentVolume with disk space preallocated to fit data for a retention period of four days plus an added safety buffer.
The admin control plane and each user cluster has a dedicated monitoring stack that you can configure independently. Each admin and user cluster includes a monitoring stack that delivers a full set of features: Prometheus Server for monitoring, Grafana for observability, and Prometheus Alertmanager for alerting.
All monitoring endpoints, transferred metric data, and monitoring APIs are secured with Istio components by using mTLS and RBAC rules. Access to monitoring data is restricted only to cluster administrators.
Metrics collected by Prometheus
Prometheus collects the following metrics and metadata from the admin control plane and user clusters:
- Resource usage, such as CPU utilization on Pods and nodes.
- Kubernetes control plane metrics.
- Metrics from add-ons and Kubernetes system components running on nodes, such as kubelet.
- Cluster state, such as health of Pods in a Deployment.
- Application metrics.
- Machine metrics, such as network, entropy, and inodes.
Multi-cluster monitoring
The Prometheus and Grafana instance installed on the admin cluster is specially configured to provide insight across the entire GKE on-prem instance, including the admin cluster and each user cluster. This enables you to:
- Use a Grafana dashboard to access metrics from all user clusters and admin clusters.
- View metrics from individual user clusters on Grafana dashboards; the metrics are available for direct queries in full resolution.
- Access user clusters' node-level and workload metrics for aggregated queries, dashboards and alerting (workload metrics are limited to workloads running in the kube-system namespace).
- Configure alerts for specific clusters.