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chaostoolkit-prometheus

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Prometheus Extension for the Chaos Toolkit

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# Prometheus extension for the Chaos Toolkit

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[Prometheus][prometheus] support for the [Chaos Toolkit][chaostoolkit].

[prometheus]: https://prometheus.io/
[chaostoolkit]: http://chaostoolkit.org/

## Install

To be used from your experiment, this package must be installed in the Python
environment where [chaostoolkit][] already lives.

[chaostoolkit]: https://github.com/chaostoolkit/chaostoolkit

```
$ pip install chaostoolkit-prometheus
```

## Usage

To use this package, you must create have access to a Prometheus instance via
HTTP and be allowed to connect to it.

By default, the Prometheus instance at `http://localhost:9090` will be queried.
To override, you need to set up the instance details using the `prometheus_base_url`
configuration property:

```json
"configuration": {
  "prometheus_base_url": "http://my.prometheus.server/"
}
```

This package only exports probes to query for some aspects of your system as
monitored by Prometheus.

Here is an example of querying Prometheus at a given moment

```json
{
    "type": "probe",
    "name": "fetch-cpu-just-2mn-ago",
    "provider": {
        "type": "python",
        "module": "chaosprometheus.probes",
        "func": "query",
        "arguments": {
            "query": "process_cpu_seconds_total{job='websvc'}",
            "when": "2 minutes ago"
        }
    }
}
```

You can also ask for an interval as follows:

```json
{
    "type": "probe",
    "name": "fetch-cpu-over-interval",
    "provider": {
        "type": "python",
        "module": "chaosprometheus.probes",
        "func": "query_interval",
        "arguments": {
            "query": "process_cpu_seconds_total{job='websvc'}",
            "start": "2 minutes ago",
            "end": "now",
            "step": 5
        }
    }
}
```

In both cases, the probe returns the [JSON payload as-is][api] from Prometheus
or raises an exception when an error is met.

[api]: https://prometheus.io/docs/querying/api/

The result is not further process and should be found in the generated report
of the experiment run.

You can also send metrics to a pushgateway service via a control:

```json
{
    "controls": [
        {
            "name": "prometheus",
            "provider": {
                "type": "python",
                "module": "chaosprometheus.metrics",
                "arguments": {
                    "pushgateway_url": "http://someip:9091",
                    "job": "chaostoolkit"
                }
            }
        }
    ]
}
```

You can also set three more arguments:

* `grouping_key`: A mapping of strings to uniquely aggregate multiple runs
  in the Prometheus backend
* `trace_id`: This must be a string which will identify this run uniquely in
  your metrics. If none is a provided, a random string is generated.
* `experiment_ref`: Sometimes it's useful to identify a particular experiment,
  not just its run, throughout many runs. This is the string to do that. If
  none is provided, a hash of the experiment is performed and used. The hash
  is not stable across changes of the experiment of course.
  
These are particularly useful when you couple this extension with others like
Loki where you want to cross-reference between logs and metrics.

## Contribute

If you wish to contribute more functions to this package, you are more than
welcome to do so. Please, fork this project, make your changes following the
usual [PEP 8][pep8] code style, sprinkling with tests and submit a PR for
review.

[pep8]: https://pycodestyle.readthedocs.io/en/latest/

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