Monitoring Sitecore Container environment Host OS and Docker

In part 1 of this series, I introduced Prometheus and lay some foundations for monitoring a Sitecore container environment using Prometheus. In this post, I will show you how to collect and monitor the Host OS and container metrics exposed by Docker.

Why should we care about Docker the Host OS Metrics?

To monitor your containerized Sitecore application effectively you need to understand the health of the underlying system your containers are running on. To achieve this, you have to monitor the system metrics like CPU, memory, network, and disk also docker is starting and stopping containers so you need to know the state of your docker resource.

How to collect Docker performance metrics

Docker supports Prometheus OOTB and provides performance metrics you can collect and monitor, however it is disabled by default.

1. Enabling Docker Metrics.

First things first lets enable the metrics. Open the daemon.json file and add the metrics-address setting:

“metrics-addr” : “127:0:0:1:9323”

Apply and restart docker. Now you should be able browse to the docker metrics and verify metrics are exposed.


2. Configure Docker Target

Update the Prometheus configuration file and add Docker as a new target.

- job_name: docker
honor_timestamps: true
scrape_interval: 30s
scrape_timeout: 20s
metrics_path: /metrics
scheme: http
- targets:

3. Verify Docker Target in Prometheus

Run docker-compose up -d and check the Prometheus targets and configuration and PromQL.

What metrics does docker expose?

Here is a list of metrics exposed by docker:

Metric Description Type
builder_builds_failed_total Number of failed image builds. counter
builder_builds_triggered_total Number of triggered image builds. counter
engine_daemon_container_actions_seconds The number of seconds it takes to process each container action. histogram
engine_daemon_container_states_containers The count of containers in various states. gauge
engine_daemon_engine_cpus_cpus The number of cpus that the host system of the engine has. gauge
engine_daemon_engine_info The information related to the engine and the OS it is running on. gauge
engine_daemon_engine_memory_bytes The number of bytes of memory that the host system of the engine has. gauge
engine_daemon_events_subscribers_total The number of current subscribers to events. gauge
engine_daemon_events_total The number of events logged. counter
engine_daemon_health_checks_failed_total The total number of failed health checks. counter
engine_daemon_health_checks_total The total number of health checks. counter
etcd_debugging_snap_save_marshalling_duration_seconds The marshalling cost distributions of save called by snapshot. histogram
etcd_debugging_snap_save_total_duration_seconds The total latency distributions of save called by snapshot. histogram
etcd_disk_wal_fsync_duration_seconds The latency distributions of fsync called by wal. histogram
etcd_snap_db_fsync_duration_seconds The latency distributions of fsyncing .snap.db file. histogram
etcd_snap_db_save_total_duration_seconds The total latency distributions of v3 snapshot save. histogram
go_gc_duration_seconds A summary of the GC invocation durations. summary
go_goroutines Number of goroutines that currently exist. gauge
go_memstats_alloc_bytes Number of bytes allocated and still in use. gauge
go_memstats_alloc_bytes_total Total number of bytes allocated, even if freed. counter
go_memstats_buck_hash_sys_bytes Number of bytes used by the profiling bucket hash table. gauge
go_memstats_frees_total Total number of frees. counter
go_memstats_gc_sys_bytes Number of bytes used for garbage collection system metadata. gauge
go_memstats_heap_alloc_bytes Number of heap bytes allocated and still in use. gauge
go_memstats_heap_idle_bytes Number of heap bytes waiting to be used. gauge
go_memstats_heap_inuse_bytes Number of heap bytes that are in use. gauge
go_memstats_heap_objects Number of allocated objects. gauge
go_memstats_heap_released_bytes_total Total number of heap bytes released to OS. counter
go_memstats_heap_sys_bytes Number of heap bytes obtained from system. gauge
go_memstats_last_gc_time_seconds Number of seconds since 1970 of last garbage collection. gauge
go_memstats_lookups_total Total number of pointer lookups. counter
go_memstats_mallocs_total Total number of mallocs. counter
go_memstats_mcache_inuse_bytes Number of bytes in use by mcache structures. gauge
go_memstats_mcache_sys_bytes Number of bytes used for mcache structures obtained from system. gauge
go_memstats_mspan_inuse_bytes Number of bytes in use by mspan structures. gauge
go_memstats_mspan_sys_bytes Number of bytes used for mspan structures obtained from system. gauge
go_memstats_next_gc_bytes Number of heap bytes when next garbage collection will take place. gauge
go_memstats_other_sys_bytes Number of bytes used for other system allocations. gauge
go_memstats_stack_inuse_bytes.  Number of bytes in use by the stack allocator. gauge
go_memstats_stack_sys_bytes Number of bytes obtained from system for stack allocator. gauge
go_memstats_sys_bytes Number of bytes obtained by system. Sum of all system allocations. gauge
http_request_duration_microseconds The HTTP request latencies in microseconds. summary
http_request_size_bytes The HTTP request sizes in bytes. summary
http_response_size_bytes The HTTP response sizes in bytes summary
logger_log_entries_size_greater_than_buffer_total Number of log entries which are larger than the log buffer counter
logger_log_read_operations_failed_total Number of log reads from container stdio that failed. counter
logger_log_write_operations_failed_total Number of log write operations that failed. counter
swarm_dispatcher_scheduling_delay_seconds Scheduling delay is the time a task takes to go from NEW to RUNNING state. histogram
swarm_manager_configs_total The number of configs in the cluster object store. gauge
swarm_manager_leader Indicates if this manager node is a leader. gauge
swarm_manager_networks_total The number of networks in the cluster object store gauge
swarm_manager_nodes The number of nodes. gauge
swarm_manager_secrets_total The number of secrets in the cluster object store. gauge
swarm_manager_services_total The number of services in the cluster object store. gauge
swarm_manager_tasks_total The number of tasks in the cluster object store. gauge
swarm_node_manager Whether this node is a manager or not. gauge
swarm_raft_snapshot_latency_seconds Raft snapshot create latency. histogram
swarm_raft_transaction_latency_seconds Raft transaction latency. histogram
swarm_store_batch_latency_seconds Raft store batch latency. histogram
swarm_store_lookup_latency_seconds Raft store read latency. histogram
swarm_store_memory_store_lock_duration_seconds Duration for which the raft memory store lock was held. histogram
swarm_store_read_tx_latency_seconds Raft store read tx latency. histogram
swarm_store_write_tx_latency_seconds Raft store write tx latency. histogram

Collect Host OS Performance Metrics

To be able to get our Host metrics into Prometheus we need a service that is capable of exposing them in the Prometheus format this is known as an Exporter. If I was running on Linux or a MAC I would use the popular Node Exporter. However, as I am on Windows I need to use WMI Exporter. WMI Exporter is capable of exposing Metrics like CPU Usage, Memory, Disk I/O as well as IIS, and SQL.

1. Install WMI Exporter

To install the WMI exporter, head over to the WMI releases page on GitHub or use chocolatey:

choco install prometheus-wmi-exporter.install

2. Verify Host OS Metrics

WMI runs as a webservice “WMI Exporter” Once installed I can now browse to http://localhost:9182/Metrics


3. Configure HostOS Target

Now I can update our Prometheus Config to include a job to target the HostOS

- job_name: hostos
honor_timestamps: true
scrape_interval: 30s
scrape_timeout: 20s
metrics_path: /metrics
scheme: http
- targets:

4. Verify HostOS Target in Prometheus

Run docker-compose up -d and check the Prometheus targets and configuration and PromQL.

I’ll can verify the metrics are being captured by Prometheus:

5. Grafana Dashboard for Host Metrics

While you could also create your own HostOS Grafana dashboard there are some excellent WMI Exporter dashboards available in the Grafana gallery. Simply search for WMI exporter, once you’ve located an existing dashboard you would like to use you can import it into your instance. In my case I have chosen the Windows Host Metrics Base

To import a dashboard from the Manage Dashboards screen click Import dashboard.


Enter your selected Grafana dashboard Id, alternatively you can paste the dashboard json, if you copied or saved it locally, and click load. Verify the dashboard details you are about to import. Here you can change the name of the dashboard, folder, identifier and data source you will need to select Prometheus.


Click Import and you should see the WMI Exporter dashboard display metrics about your local HostOS.


As you can see this dashboard provides extensive metrics about your HostOS.

The Overview panels provides a glimpse of the overall status of the Host:

  • Uptime
  • Processors
  • RAM
  • CPU Load
  • Memory Load
  • Disk usage
  • Network In/Out
  • Disk space

The CPU Panels displays load on the CPU the total thread consumed, which is great if you are experience issues cause by thread starvation you set an alert on these metrics, and the number of system exceptions dispatched.


Ability to monitor memory and set alerts based on high memory consumption is critical. The memory panel allows you to monitor virtual physical and memory available.


The network details panel provides insight into the network usage. Allowing you to check the number of packets sent versus the packets received.


Finally the Disk details panels provide information on the physical disk usage, activity and IO.


Additional Info

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