CloudZero UCA Tools
Project description
CloudZero UCA Toolkit
Utilities for generating, transforming and transmitting unit cost analytics (UCA) data to the CloudZero API. Visit our UCA documentation to learn more about CloudZero and our enhanced unit cost analytics capabilities.
Features
- Transmit UCA data to CloudZero (using the CloudZero UCA API)
- Generate UCA data
prerequisites
- Tested on MacOS, should probably run on Linux in general
- Python 3.8 or newer
pip
or your favorite method of installing packages from PyPi. Have you considered pipx?
Installation
$ pipx install cloudzero-uca-tools
General Usage
CloudZero UCA tools exist to produce UCA events that can then be transmitted to the CloudZero API for analysis and processing. To use the CloudZero API, you should first obtain an API key from https://app.cloudzero.com/organization/api-keys
$ uca
Usage: uca [OPTIONS] COMMAND [ARGS]...
CloudZero Unit Cost Analytics Toolkit
Options:
--version Show the version and exit.
-c, --configuration TEXT UCA configuration file (JSON)
-o, --output TEXT Instead of sending events to the API, write
events to an output file (note: will overwrite file if it exists)
-dry, --dry-run Perform a dry run, read and transform the data but
do not send it to the API. Sample events will be output to the screen
-k, --api-key TEXT API Key to use
--help Show this message and exit.
Commands:
transmit
generate
Basic Configuration
The following is a minimal configuration file for transmitting data to the CloudZero API
(if you don't want to specify the API on the command line, otherwise no configuration file
is required for transmit
). If you wish to use generate
however a configuration file
is required.
{
"version": "1", # anything you want
"settings": {
"api_key": "<YOUR API KEY HERE>" # Also can be provided at runtime via the CLI. Get an API key at https://app.cloudzero.com/organization/api-keys
}
}
Each command also has its own set of command line options that will need to be provided as well
Transmit
UCA data transmission allows you easily send UCA data directly to the CloudZero API without having to write code. Prepare an input file with one or more correctly formatted JSON UCA records and quickly send it to the CloudZero telemetry API.
Help
$ uca transmit --help
Usage: uca transmit [OPTIONS]
Options:
-d, --data TEXT Source data, in text or gzip + text format, supports
file:// or s3:// paths [required]
-t, --transform TEXT Optional transformation script using jq
(https://stedolan.github.io/jq/). Used when the source
data needs modification or cleanup. See README.md for
usage instructions
--help Show this message and exit.
input data
Your input data can be either a text or gzip file, consisting of one JSON record per line.
For example:
{'timestamp': '2021-03-22 00:00:00+00:00', 'granularity': 'DAILY', 'cost-context': 'Cost-Per-Fake-Customer', 'id': 'StateEx', 'target': {}, 'telemetry-stream': 'test-data', 'value': '40.0000'}
{'timestamp': '2021-04-01 00:00:00+00:00', 'granularity': 'DAILY', 'cost-context': 'Cost-Per-Fake-Customer', 'id': 'Hooli', 'target': {}, 'telemetry-stream': 'test-data', 'value': '23.0000'}
Using an optional JQ transform
You can optionally provide a JQ script to transform the source data on the fly before transmission. This is helpful when you have minor or even major changes you want to make to the data quickly, and it would be more complicated or impossible to alter the input data (for example an existing system is producing UCA data in an older format).
Example JQ Script
The following script requires the id
field to be present (records missing this field will be skipped), followed
by setting the target field using a metadata and cost-context field, followed by setting the cost-context to a
constant value and then deleting the metadata and uca fields
select(.id != "")
| .target = {"tag:environment": [.metadata.environment], "feature": [.["cost-context"]] }
| .["cost-context"] = "cost-per-title"
| del(.metadata, .uca)
Example Input before JQ transform:
{
"uca": "v1.3",
"timestamp": "2021-05-25 13:00:00+0000",
"granularity": "HOURLY",
"context": "rosebud",
"id": "frank",
"target": {},
"telemetry-stream": "test-data",
"value": "1073641",
"metadata": {
"environment": "production"
}
}
Example Transformed Output after JQ transform:
{
"timestamp": "2021-05-25 13:00:00",
"granularity": "HOURLY",
"context": "Cost-Per-Customer",
"id": "frank",
"target": {
"tag:environment": ["production"],
"feature": ["rosebud"]
},
"telemetry-stream": "test-data",
"value": "1073641"
}
Generate
Generates UCA data from a source data set (in CSV format) or just based on rules you define. The time period for the data can be defined as part of the source data or generated based on a start and end range
Help
$ uca generate --help
Usage: uca generate [OPTIONS]
Options:
-s, --start TEXT start datetime <YYYY-MM-DD HH:MM:SS> (optional)
-e, --end TEXT End datetime <YYYY-MM-DD HH:MM:SS> (optional)
--today Generate events for the current day (optional)
-d, --data TEXT Input UCA data (CSV) [required]
--help Show this message and exit.
Examples
Generate UCA data between 2021-03-13 and 2021-04-07 using data/configuration.json and data/data.csv as input. Performs only a dry run and do not send the results to the CloudZero API
$ uca generate -s 2021-03-13 -e 2021-04-07 -c data/configuration.json -d data/data.csv --dry-run
Generate UCA data using data/configuration.json and data/data.csv (which must contain a timestamp column) as input. Performs only a dry run and do not send the results to the CloudZero API
$ uca generate -s 2021-03-13 -e 2021-04-07 -c data/configuration.json -d data/data.csv --dry-run
Configuration File
The generate
command requires a UCA template definition and specific settings that should be applied when generating data. You
can learn more about the UCA format and our UCA Telemetry API here.
{
"version": "1", # can be anything you want that helps you keep track of things
"template": {
"timestamp": "$timestamp", # Timestamp will be replaced automatically or from the input data source
"granularity": "DAILY", # Granularity can be HOURLY, DAILY or MONTHLY. See notes below for usage
"context": "Cost-Per-Fake-Customer", # You can have up to 5 telemetry streams per context
"id": "$unit_id", # Will be replaced using data from your data CSV
"target": {}, # Use {} to map to all spend or use a combination of tags and keywords to get more specific
"telemetry-stream": "test-data", # Unique name for this telemetry stream
"value": "$unit_value" # Will be replaced using generated data or data from your data CSV
},
"settings": {
"generate": {
"mode": "exact", # Can be exact, random, jitter or allocation
"jitter": 15, # if mode is jitter, this value defines the range
"allocation": 100000 # if mode is allocation, this value defines the total amount to be allocated
},
"api_key": "<YOUR API KEY HERE>" # Also can be provided at runtime via the CLI. Get an API key at https://app.cloudzero.com/organization/api-keys
}
}
A note on using MONTHLY granularity.
MONTHLY is a special granularity that when used instructs the UCA toolkit to expand the provided year and month to all possible days in the current month. For example if you have this input data:
unit_id,granularity,timestamp,unit_value
"SuperDogs, Inc",Monthly,2022-10-1,8
"CoolCats, LLC",Monthly,2022-10-1,229
This will expand to 61 events, 31 for "SuperDogs, Inc" and 31 for "CoolCats, LLC" (31 days in October)
Data CSV
The data CSV defines the input data you wish to feed into the template. This tool will produce matching UCA records for all rows in your data CSV for each hour or day as defined. The following example has 13 "customers" and can be used as input for all configuration modes.
unit_id,unit_value,unit_allocation
Sunbank,37,8.5574
SoftwareCorp,17,0.4091
"Parts, Inc.",140,10.9955
Transport Co.,25,6.3033
"WeShipit, Inc.",124,23.7549
CapitalTwo,90,1.5231
Bank of Sokovia,43,0.1198
Makers,9,1.0767
StateEx,40,3.5057
Flitter,15,22.9554
Pets2you,78,6.3358
Hooli,23,4.3294
Massive Dynamic,42,10.1339
Example output
Together this configuration and data will produce UCA events similar to the following:
{'timestamp': '2021-03-22 00:00:00+00:00', 'granularity': 'DAILY', 'context': 'Cost-Per-Fake-Customer', 'id': 'StateEx', 'target': {}, 'telemetry-stream': 'test-data', 'value': '40.0000'}
{'timestamp': '2021-04-01 00:00:00+00:00', 'granularity': 'DAILY', 'context': 'Cost-Per-Fake-Customer', 'id': 'Hooli', 'target': {}, 'telemetry-stream': 'test-data', 'value': '23.0000'}
{'timestamp': '2021-04-01 00:00:00+00:00', 'granularity': 'DAILY', 'context': 'Cost-Per-Fake-Customer', 'id': 'Sunbank', 'target': {}, 'telemetry-stream': 'test-data', 'value': '37.0000'}
{'timestamp': '2021-04-06 00:00:00+00:00', 'granularity': 'DAILY', 'context': 'Cost-Per-Fake-Customer', 'id': 'Transport Co.', 'target': {}, 'telemetry-stream': 'test-data', 'value': '25.0000'}
{'timestamp': '2021-03-19 00:00:00+00:00', 'granularity': 'DAILY', 'context': 'Cost-Per-Fake-Customer', 'id': 'StateEx', 'target': {}, 'telemetry-stream': 'test-data', 'value': '40.0000'}
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