SSIS (Collector method) - v2.0.0

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About Collectors

Collectors are extractors that are developed and managed by you (A customer of K).

KADA provides python libraries that customers can use to quickly deploy a Collector.

Why you should use a Collector

There are several reasons why you may use a collector vs the direct connect extractor:

You are using the KADA SaaS offering and it cannot connect to your sources due to firewall restrictions
You want to push metadata to KADA rather than allow it pull data for Security reasons
You want to inspect the metadata before pushing it to K

Using a collector requires you to manage

Deploying and orchestrating the extract code
Managing a high water mark so the extract only pull the latest metadata
Storing and pushing the extracts to your K instance.

Pre-requisites

Python 3.6 - 3.10
MSDB database / SQLServer DB access
- We currently only support SSIS package deployments to the MSDB database and not project deployments which deploy to SSISDB database, please advise KADA if you use project deployments against SSISDB
- The collector will need access to the underlying SQLServer Database with permissions to read the following tables is the SSIS main databases:
  - MSDB.DBO.SYSSSISPACKAGES
  - <SSIS Logging Database>.DBO.SYSSSISLOG where <SSIS Logging Database> is the database configured for SSIS logging
Access to K landing directory

Step 1: Create the Source in K

Create a SSIS source in K

Go to Settings, Select Sources and click Add Source
Select “Load from file system” option

Give the source a Name - e.g. SSIS Production
Add the Host name for the SSIS Server
Click Finish Setup

Step 2: Getting Access to the Source Landing Directory

Collector Method

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 SSIS whl via Platform Settings → Sources → Download Collectors

Run the following command to install the collector

pip install kada_collectors_extractors_ssis-#.#.#-py3-none-any.whl

Step 4: Configure the Collector

The collector requires a set of parameters to connect to and extract metadata from SSIS.

FIELD	FIELD TYPE	DESCRIPTION	EXAMPLE

FIELD	FIELD TYPE	DESCRIPTION	EXAMPLE
server	string	SQLServer server	“10.1.18.19”
username	string	Username to log into the SQLServer account	“myuser”
password	string	Password to log into the SQLServer account
logging_database	string	Database where the SSIS Logging has been setup	“ssis_logging”
mapping	JSON	Mapping file of data source names against the onboarded host and database name in K	Assuming I have a “myDSN” data source name in powerbi, I’ll map it to host “myhost” and database “mydatabase” onboarded in K, snowflake type references are handled automatically `{ "myDSN": { "host": "myhost", "database": "mydatabase" } }`
driver	string	This is the ODBC driver, generally its ODBC Driver 17 for SQL Server, if you another driver installed please use that instead	“ODBC Driver 17 for SQL Server”
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

These parameters can be added directly into the run or you can use pass the parameters in via a JSON file. The following is an example you can use that is included in the example run code below.

kada_ssis_extractor_config.json

{
    "server": "",
    "username": "",
    "password": "",
    "logging_database": "ssis_logging",
    "mapping": {},
    "driver": "ODBC Driver 17 for SQL Server",
    "output_path": "/tmp/output",
    "mask": 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 code sample uses the kada_ssis_extractor_config.json for handling the configuration details

This code will produce and read a high water mark file from the same directory as the execution called ssis_hwm.txt and produce files according to the configuration JSON.

Advance options:

If you wish to maintain your own high water mark files elsewhere 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. Refer to this document for more information Collector Integration General Notes | Storing HWM in another location

If you are handling external arguments of the runner yourself, you’ll need to consider additional items for the run method. Refer to this document for more information Collector Integration General Notes | The run method

username: username to sign into sqlserver
password: password to sign into sqlserver
server: sqlserver host
driver: sqlserver driver name
logging_database: Logging Database name for SSIS
mapping: Dict of DNS to database and hostnames
output_path: full or relative path to where the outputs should go
mask: To mask the META/DATABASE_LOG 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 ssis_hwm.txt and produce files according to the configuration JSON. This file is only produced if you call the publish_hwm method.

Step 7: 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)

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