Monitoring with Grafana
Prometheus and Grafana can be used for displaying metrics to assist with troubleshooting production systems.
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Prometheus and Grafana can be used for displaying metrics to assist with troubleshooting production systems.
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metrics endpointFor monitoring, the REST API of a Konduit Serving instance exposes a /metrics endpoint that returns metrics in the Prometheus format.
By default, metrics returned by the metrics endpoint include
average CPU load;
memory use;
I/O wait time;
GPU bandwidth device to device, bandwidth device to host, current load for device, current available memory for each GPU; and
CPU current load for device, current available memory.
The metrics above are implemented by the . The metrics endpoint also returns Micrometer JVM and system metrics via the ClassLoaderMetrics, JvmMemoryMetrics, JvmGcMetrics, ProcessorMetrics and JvmThreadMetrics binders. See the for descriptions of these classes. Error, warning, info, debug and trace counts are monitored using Micrometer's .
Prometheus is a widely used time series database for tracking system metrics used for debugging production systems. This includes common metrics used to troubleshoot problems with production applications such as:
Out of memory
Latency
For machine learning, we may include other metrics to help debug things such as:
Compute time for a neural net
ETL creation (number of times it takes to convert raw data to a minibatch or NumPy ndarray)
Prometheus works by pulling data from the specified sources. A Prometheus instance is configured by a YAML file such as:
The main component to configure is targets. targets is where you specify the source to pull data from. A Konduit Serving instance exposes metrics to be picked up by Prometheus from http://<hostname>:<port>/metrics.
Grafana allows you to declare a dashboard as a JSON file. An imported Grafana dashboard will show some pre-configured metrics. You can always extend/add more metrics in the Grafana GUI and re-export the configuration.
In this folder, run the following in a command line
In this example, we use Prometheus to monitor the Konduit Serving instance.
Copy the prometheus.yml file in this directory to the location of your Prometheus binary. Then, run:
Omit the ./ if you're running Prometheus on cmd.exe. The ./ suffix is required on PowerShell.
By default, Prometheus runs on port 9090.
In this example, we use Grafana, which provides a dashboard to visualize data from the Prometheus instance.
In your browser, openlocalhost:3000. Login with the username admin and password admin.
On the bar on the left, mouse over on the + button, then click on Import.
On the next page, enter a name for your dashboard (such as Pipeline Metrics). Click the Import button:
Your Grafana dashboard will render on the next page. This dashboard contains metrics for system load and memory as well as timings for performing inference and ETL.
Use the predict-numpy command:
Remember to stop the Konduit Serving instance with
This YAML file contains a global configuration and a section. See for details.
is a dashboard system for pulling data from different sources and displaying it in real time. It can be used to visualize output from Prometheus.
Konduit Serving: Follow the to build a Konduit Serving JAR file and install the konduit Python module.
Prometheus: Download a for your OS architecture and unzip to a location on your local drive.
Grafana: Install Grafana from Grafana's page. See the for platform-specific instructions.
The following instructions assume that you're in the of the repository.
This creates a local Konduit Serving instance using the YAML configuration file at port 1337.
See the Grafana installation instructions for your platform (, , , ) for instructions to start a Grafana service or, optionally, have Grafana initialize on startup. If you use the Windows installer to install Grafana, will run Grafana automatically at startup, and there is no need to initialize the Grafana server instance.
Next, add a Prometheus data source. Click on Add Data Source > Prometheus, then insert the HTTP URL in the following page.
Copy and paste the JSON in into the import page as follows, then click the Load button:
Grafana support for Prometheus:
