With the VMware Tanzu Greenplum streaming server's out-of-the-box Prometheus integration, you can obtain runtime metrics for a gpss
server instance when you enable Prometheus monitoring for the UNIX process.
The GPSS metrics available from Prometheus are:
Name | Description |
---|---|
gpss_jobs_total | The total number of jobs the gpss server instance is servicing. |
gpss_jobs_running | The number of jobs that are currently in the Running state. |
gpss_process_cpu_seconds_total | The total user and system CPU time (in seconds) for the GPSS server process. |
gpss_process_open_fds | The number of open file descriptors in the GPSS server instance process. |
gpss_process_max_fds | The maximum number of open file descriptors allowed for the GPSS server instance process. |
gpss_process_virtual_memory_bytes | The virtual memory size (in bytes) of the GPSS server instance process. |
gpss_process_virtual_memory_max_bytes | The maximum virtual memory size (in bytes) of the GPSS server instance process. |
gpss_process_resident_memory_bytes | The resident memory size (in bytes) of the GPSS server instance process. |
gpss_process_start_time_seconds | The start time of the GPSS server instance process since epoch (in seconds). |
GPSS uses the Prometheus stable HTTP API /api/v1
. Before you enable Prometheus integration with GPSS, ensure that:
Prometheus collects metrics from monitored processes by scraping HTTP endpoints exposed by the processes. Scraping pulls published statistics that allow you to aggregate and record time series data, or to generate alerts.
To enable Prometheus integration with GPSS, you must:
Identify the host name or IP Address and port number on which Prometheus will pull statistics from the GPSS server instance. Both GPSS and Prometheus require this configuration information.
Add a Monitor
property block to the gpss.json
GPSS server configuration file that identifies the address and port number from which GPSS will allow Prometheus to pull the server's statistics. For example:
Monitor: {
Prometheus: {
Listening: "0.0.0.0:5001"
}
}
The Listening
property value specified in this block allows any Prometheus server host to pull from port 5001.
Create a new, or update an existing, YAML-format Prometheus configuration file to include a GPSS scrape target. For example, to configure Prometheus metrics collection for the GPSS server instance running on the host named etlhost
that was configured with the Monitor
block above, copy/paste the following text into a file named prometheus_gpss_cfg.yml
:
global:
scrape_interval: 15s # By default, scrape targets every 15 seconds.
# A scrape configuration containing exactly one endpoint to scrape, GPPSS
scrape_configs:
# The job name is added as a label `job=<job_name>` to any timeseries
# scraped from this config.
- job_name: 'gpss'
static_configs:
- targets: ['etlhost:5001']
This configuration instructs Prometheus to pull metrics from port 5001
on etlhost
(the GPSS server instance) every fifteen seconds.
Start the Prometheus server, specifying the configuration file that you updated or created for GPSS:
$ prometheus --config.file=prometheus_gpss_cfg.yml &
Start the GPSS server:
$ gpss --config gpss.json &
When you run a Prometheus server, metrics for integrated services are available at the default port 9090
. To view metrics for all services integrated with Prometheus, navigate to http://<prometheus_host>:9090
in your web browser of choice.
To view the metrics for a specific GPSS server instance, navigate to Status->Targets, and select the GPSS Endpoint of interest.
The default Prometheus web user interface is rather low level. Once enabled, you can use the Prometheus expression browser to generate and run ad-hoc queries on GPSS time series data.
To view graphs of GPSS metrics, enable Grafana integration as described in Grafana Support for Prometheus in the Prometheus documentation.