IFCB Prometheus Exporter

A Prometheus exporter for Imaging FlowCytobot (IFCB) data. This tool collects metrics from IFCB instruments and exposes them in a format compatible with Prometheus monitoring systems, enabling real-time observability and integration with Grafana dashboards.

Copyright 2025 Axiom Data Science, LLC

See LICENSE for details.

Installation

This project relies on conda for installation and managing of the project dependencies.

1. Download and install miniconda for your operating system https://docs.conda.io/en/latest/miniconda.html.

2. Clone this project with git.

3. Once conda is available build the environment for this project with:

   conda env create -f environment.yml
   

   The above command creates a new conda environment titled ifcb-prometheus-exporter with the necessary project dependencies.

   To update an existing environment with any changes to the dependencies use:

   conda env update -f environment.yml
   

4. An Additional environment file is present for testing and development environments. The additional developer dependencies can be installed with:

   conda env update -f test-environment.yml
   

5. To install the project to the new environment:

   conda activate ifcb-prometheus-exporter
   pip install -e .
   

Running Tests

To run the project's tests:

pytest -sv --integration

Usage Example

To run the exporter and expose metrics on port 8000, you must specify the base URL for the IFCB API using the --base-url argument:

python ifcb_prometheus_exporter/ifcb_prometheus_exporter.py --base-url https://ifcb.caloos.org/api

Then visit http://localhost:8000/metrics to view the metrics in Prometheus format. The exporter will use the provided base URL for data collection.

The following are a list of the base URLs that can be used with this exporter:

1. for Caloos: https://ifcb.caloos.org/api
2. for WHOI: https://ifcb-data.whoi.edu/api
3. for Salish Sea: https://salish-sea-ifcbdb.srv.axds.co/api
4. for HABON: https://habon-ifcb.whoi.edu/api

Additionally, the loop interval, port, lag threshold, and lookback period can be specified with arguments. The defaults are: interval=900 seconds, port=8000, lag-threshold-seconds=86400 (24 hours), lookback-seconds=1209600 (14 days).:

python ifcb_prometheus_exporter/ifcb_prometheus_exporter.py --base-url https://ifcb.caloos.org/api --interval 600 --port 9000 --lag-threshold-seconds 43200 --lookback-seconds 604800

Metrics Returned

The exporter provides the following metrics:

• ifcb_latest_bin_timestamp{dataset="<dataset_name>"}: Timestamp of the latest bin for the specified dataset (Unix timestamp), or 0 if none exist
• ifcb_is_dataset_up_to_date{dataset="<dataset_name>"}: Indicates if the dataset is lagging (0) or up-to-date (1)
• ifcb_latest_blobs_timestamp{dataset="<dataset_name>"}: Timestamp of the latest blobs for the specified dataset (Unix timestamp), or 0 if none exist
• ifcb_latest_blobs_lag_seconds{dataset="<dataset_name>"}: Lag time for the latest blobs for dataset (seconds), or -1 if none exist
• ifcb_latest_features_timestamp{dataset="<dataset_name>"}: Timestamp of the latest features for the specified dataset (Unix timestamp), or 0 if none exist
• ifcb_latest_features_lag_seconds{dataset="<dataset_name>"}: Lag time for the latest features for dataset (seconds), or -1 if none exist
• ifcb_latest_class_scores_timestamp{dataset="<dataset_name>"}: Timestamp of the latest class scores for the specified dataset (Unix timestamp), or 0 if none exist
• ifcb_latest_class_scores_lag_seconds{dataset="<dataset_name>"}: Lag time for the latest class scores for dataset (seconds), or -1 if none exist
• ifcb_size_value{dataset="<dataset_name>"}: Latest size value of the dataset in Bytes
• ifcb_size_timestamp{dataset="<dataset_name>"}: Timestamp of latest size value
• ifcb_temperature_value{dataset="<dataset_name>"}: Latest temperature in Degrees C
• ifcb_temperature_timestamp{dataset="<dataset_name>"}: Timestamp of latest temperature value
• ifcb_humidity_value{dataset="<dataset_name>"}: Latest humidity in Percentage
• ifcb_humidity_timestamp{dataset="<dataset_name>"}: Timestamp of latest humidity value
• ifcb_run_time_value{dataset="<dataset_name>"}: Latest run_time in Seconds
• ifcb_run_time_timestamp{dataset="<dataset_name>"}: Timestamp of latest run_time value
• ifcb_look_time_value{dataset="<dataset_name>"}: Latest look_time in Seconds
• ifcb_look_time_timestamp{dataset="<dataset_name>"}: Timestamp of latest look_time value
• ifcb_ml_analyzed_value{dataset="<dataset_name>"}: Latest ml_analyzed in Milliliters
• ifcb_ml_analyzed_timestamp{dataset="<dataset_name>"}: Timestamp of latest ml_analyzed value
• ifcb_concentration_value{dataset="<dataset_name>"}: Latest concentration in ROIs / ml
• ifcb_concentration_timestamp{dataset="<dataset_name>"}: Timestamp of latest concentration value
• ifcb_n_triggers_value{dataset="<dataset_name>"}: Latest n_triggers in Count
• ifcb_n_triggers_timestamp{dataset="<dataset_name>"}: Timestamp of latest n_triggers value
• ifcb_n_images_value{dataset="<dataset_name>"}: Latest n_images in Count
• ifcb_n_images_timestamp{dataset="<dataset_name>"}: Timestamp of latest n_images value

Prometheus Integration

Add the following to your Prometheus configuration to scrape metrics:

scrape_configs:
  - job_name: 'ifcb'
    static_configs:
      - targets: ['localhost:8000']

Troubleshooting

• If you see ModuleNotFoundError, make sure to update your environment with:

  conda env update -f environment.yml
  

• If metrics do not appear, check API connectivity and ensure the exporter is running.

Contributing

Pull requests and issues are welcome! Please see CONTRIBUTING.rst for guidelines.

License

This project is licensed under the terms described in LICENSE.

Building with Docker

To build the docker container:

docker build -t ifcb-prometheus-exporter .

Running with Docker

Credits

This package was created with Cookiecutter and the ``audreyr/cookiecutter-pypackage``_ project template.