README.md

Pure1 API Integration Samples

This repository is a collection of scripts showcasing popular use cases for the Pure1 REST API. Currently, the use cases below are available:

• Custom reports
  • Targets use cases where there is a need to build highly customized, automated reports or multi-storage vendor reports
• 3rd-party monitoring
  • Targets use cases where there is a need to sync Pure1 metrics to a centralized monitoring tool (one-way sync from Pure1)

Custom reports integration

Overview

The goal of this integration is to showcase the capabilities of Python and the Pure Storage Unified Python Client to export average or max Pure1 metrics into a comma-separated values (CSV) file. The current script gathers general array fleet information (such as array name, array model, OS version), as well as a few performance metrics (such as used capacity)

Pre-requisites

• Be a member of a Pure1 organization
• Have the credentials of a Pure1 organization administrator account on hand
• Have Python 3.x installed on the machine where the script will run (Python 2.x might work but the script was only tested with Python 3.6.5)

Installation

1. Sign in to https://pure1.purestorage.com as an administrator and generate an API key (using the instructions available at https://blog.purestorage.com/pure1-rest-api-part-2, for instance)
2. Take note of your API Application Id, you will need it later on to call the pure1_wf.py script

Capacity Reports

2 scripts are provided to generate capacity reports:

• The pure1_report.py script generates a report of FlashArray appliances including a % comparison with the previous reporting interval (configurable in the REPORTING_INTERVAL_DAYS variable)
• • The pure1_fb_inventory.py script generates a report of FlashBlades appliances including the number of used vs. total blades in each appliance and a % comparison with the previous reporting interval (configurable in the REPORTING_INTERVAL_DAYS variable)

To run the script, simply call the following command line:

python3 pure1_report.py|pure1_fb_inventory.py <pure1_app_id> <pure1_rsa_private_key_file> -p <pure1_private_keyfile_password>

where the parameters should be:

• <pure1_app_id>: the Pure1 Application Id you registered in step #2 of the Installation section above
• <pure1_rsa_private_key_file>: the relative path to the RSA private key file used to register the Pure1 API application

Additionally, the script an optional parameter:

• -p (or --password) is only required if the private key file was encrypted with a password.

VMware Wavefront integration

Overview

The goal of this integration is to showcase the integration between Pure1 and Wavefront using the Pure Storage Unified Python Client and the Wavefront Python SDK. The sample pure1_wf.py Python script publishes all the array metrics (up to 2 hours from the current time) for all the arrays monitored in your Pure1 account to your Wavefront account.

Important note: this script is NOT supported by Pure Storage. However, you can connect to the Pure//Code() Slack Community or request an invitation to join if you don't have access to it yet.

Pre-requisites

• Be a member of a Pure1 organization
• Have the credentials of a Pure1 organization administrator account on hand
• Have a valid Wavefront account
• Have Python 3.x installed on the machine where the script will run (Python 2.x might work but the script was only tested with Python 3.6.5)

Installation

1. Sign in to https://pure1.purestorage.com as an administrator and generate an API key (using the instructions available at https://blog.purestorage.com/pure1-rest-api-part-2, for instance)
2. Take note of your API Application Id as well as your Wavefront account url (such as https://longboard.wavefront.com), you will need them later on to call the pure1_wf.py script
3. Connect to your Wavefront account or sign up for a trial account at https://www.wavefront.com/
4. Follow these instructions to generate a Wavefront API key
5. Install the Python pre-requisites by running the following command:
   pip3 install -r requirements.txt

Script Execution

To run the script, simply call the following command line:

python3 pure1_wf.py <wavefront_url> <wavefront_api_token> <pure1_app_id> <pure1_rsa_private_key_file> -p <pure1_private_keyfile_password> -i <query_interval> -r <resolution>

where the parameters should be:

• <wavefront_url>: the URL you use to access your Wavefront account (such as https://longboard.wavefront.com)
• <wavefront_api_token>: the API key you generated in step #1 of the Installation section above.
• <pure1_app_id>: the Pure1 Application Id you registered in step #2 of the Installation section above
• <pure1_rsa_private_key_file>: the relative path to the RSA private key file used to register the Pure1 API application

Additionally, the script accepts several optional parameters:

• -p (or --password) is only required if the private key file was encrypted with a password.
• -r (or --resolution) controls the resolution (in ms) of the metrics you are interesting in collecting. Specifically, the script will retrieve all the metrics for which the resolution is lower than the specified resolution. Defaults to 1 day (8,6400,000 milliseconds, i.e. all of the available metrics).
• -i (or --interval) controls the interval (in seconds) between each batched query. Defaults to 180s (3 minutes). For instance, with interval set to 180s, the script will retrieve metrics data for the last 3 minutes (2 hours prior) every 3 minutes (and pauses until 3 minutes have elapsed). If set to -1, the script will defer to the --start parameter to determine the start date and time (in the past) to start collecting data (in 30 minutes intervals, without pause)
• -s (or --start) controls the start date and time at which the script should start collecting data (up to 2 hours from now)

If everything was properly configured, you should see Pure1 metrics available in Wavefront Metrics page in the purestorage.metrics namespace.