IICS (via Collector method) - v3.0.0
This collector is for Informatica Intelligent Cloud Services (IICS)
About Collectors
Pre-requisites
Collector Server Minimum Requirements
IICS Requirements
IICS with access to both V2 and V3 APIs
Establish IICS Access
@Dean Nguyen need to populate this part with screenshots of the check boxes
Collector Limitations
Supports Data Integration Objects Only, specifically
Taskflows
Workflows
Mapping Tasks
Requires support of 20 requests per second if rate limiting to the API has been applied https://docs.informatica.com/integration-cloud/api-manager/current-version/api-manager-guide/api-specific-policies/api-specific-rate-limit-policy.html
We do not support gathering Metadata from Advance Filtering within Extended Objects
Supports only the following types of connections
CSVFile
Oracle
SqlServer2012
SqlsServer2016
Toolkit connections
Webservices
Toolkit CCI Connections
Snowflake
Step 1: Create the Source in K
Create a IICS source in K
Go to Settings, Select Sources and click Add Source
Select “Load from File” option
Give the source a Name - e.g. IICS Production
Add the Host name for the IICS Production
Click Finish Setup
Step 2: Getting Access to the Source Landing Directory
Step 3: Install the Collector
It is recommended to use a python environment such as pyenv or pipenv if you are not intending to install this package at the system level.
Some python packages also have dependencies on the OS level packages, so you may be required to install additional OS packages if the below fails to install.
You can download the Latest Core Library and whl via Platform Settings → Sources → Download Collectors
Run the following command to install the collector
pip install kada_collectors_extractors_<version>-none-any.whl
You will also need to install the common library kada_collectors_lib for this collector to function properly.
pip install kada_collectors_lib-<version>-none-any.whl
Step 4: Configure the Collector
The collector requires a set of parameters to connect to and extract metadata from IICS
FIELD | FIELD TYPE | DESCRIPTION | EXAMPLE |
---|---|---|---|
username | string | Username to log into IICS | “myuser” |
password | string | Password to log into IICS |
|
login_url | string | This is the base url for your IICS login service, see https://docs.informatica.com/integration-cloud/b2b-gateway/current-version/rest-api-reference/platform-rest-api-version-2-resources/login.html for more details | |
days_active | integer | Number of days which a task must have run to be considered active for lineage resolution | 60 |
timeout | integer | Timeout in seconds for IICS API responses, sometimes IICS server can be slow so tune this accordingly if needed | 20 |
output_path | string | Absolute path to the output location where files are to be written | “/tmp/output” |
mask | boolean | To enable masking or not | true |
compress | boolean | To gzip the output or not | true |
KADA provides an out of the box script that reads a configuration JSON file and runs the extractor. Below is the configuration file.
kada_iics_extractor_config.json
{
"username": "",
"password": "",
"login_url": "",
"timeout": 30,
"active_days": 60,
"mapping": {},
"output_path": "/tmp/output",
"mask": true,
"compress": true
}
Step 5: Run the Collector
The following code is an example of how to run the extractor. You may need to uplift this code to meet any code standards at your organisation.
This can be executed in any python environment where the whl has been installed.
This is the wrapper script: kada_iics_extractor.py
Advance options:
If you wish to maintain your own high water mark files else where you can use the above section’s script as a guide on how to call the extractor. The configuration file is simply the keyword arguments in JSON format.
If you are handling external arguments of the runner yourself, you’ll need to consider the following for the run method Collector Integration General Notes | Extractor run method
username: username to sign into server
password: password to sign into server
login_url: IICS login address
active_days: assessment window in days to consider tasks to be active for lineage resolution
timeout: timeout in seconds for API responses
output_path: full or relative path to where the outputs should go
mask: to mask files or not
compress: To gzip output files or not
Step 6: Check the Collector Outputs
K Extracts
A set of files (eg metadata, databaselog, linkages, events etc) will be generated. These files will appear in the output_path directory you set in the configuration details
High Water Mark File
A high water mark file is created in the same directory as the execution called iics_hwm.txt and produce files according to the configuration JSON. This file is only produced if you call the publish_hwm method.
If you want prefer file managed hwm, you can edit the location of the hwn by following these instructions Collector Integration General Notes
Step 8: Push the Extracts to K
Once the files have been validated, you can push the files to the K landing directory.
You can use Azure Storage Explorer if you want to initially do this manually. You can push the files using python as well (see Airflow example below)
Example: Using Airflow to orchestrate the Extract and Push to K