Amazon AppFlow

Amazon AppFlow is a fully managed integration service that enables you to securely transfer data between Software-as-a-Service (SaaS) applications like Salesforce, SAP, Zendesk, Slack, and ServiceNow, and AWS services like Amazon S3 and Amazon Redshift, in just a few clicks. With AppFlow, you can run data flows at enterprise scale at the frequency you choose - on a schedule, in response to a business event, or on demand. You can configure data transformation capabilities like filtering and validation to generate rich, ready-to-use data as part of the flow itself, without additional steps. AppFlow automatically encrypts data in motion, and allows users to restrict data from flowing over the public Internet for SaaS applications that are integrated with AWS PrivateLink, reducing exposure to security threats.

Prerequisite Tasks

To use these operators, you must do a few things:

Generic Parameters

aws_conn_id

Reference to Amazon Web Services Connection ID. If this parameter is set to None then the default boto3 behaviour is used without a connection lookup. Otherwise use the credentials stored in the Connection. Default: aws_default

region_name

AWS Region Name. If this parameter is set to None or omitted then region_name from AWS Connection Extra Parameter will be used. Otherwise use the specified value instead of the connection value. Default: None

verify

Whether or not to verify SSL certificates.

  • False - Do not validate SSL certificates.

  • path/to/cert/bundle.pem - A filename of the CA cert bundle to use. You can specify this argument if you want to use a different CA cert bundle than the one used by botocore.

If this parameter is set to None or is omitted then verify from AWS Connection Extra Parameter will be used. Otherwise use the specified value instead of the connection value. Default: None

botocore_config

The provided dictionary is used to construct a botocore.config.Config. This configuration can be used to configure Avoid Throttling exceptions, timeouts, etc.

Example, for more detail about parameters please have a look botocore.config.Config
{
    "signature_version": "unsigned",
    "s3": {
        "us_east_1_regional_endpoint": True,
    },
    "retries": {
      "mode": "standard",
      "max_attempts": 10,
    },
    "connect_timeout": 300,
    "read_timeout": 300,
    "tcp_keepalive": True,
}

If this parameter is set to None or omitted then config_kwargs from AWS Connection Extra Parameter will be used. Otherwise use the specified value instead of the connection value. Default: None

Note

Specifying an empty dictionary, {}, will overwrite the connection configuration for botocore.config.Config

Operators

Run Flow

To run an AppFlow flow keeping as is, use: AppflowRunOperator.

tests/system/amazon/aws/example_appflow_run.py

run_flow = AppflowRunOperator(
    task_id="run_flow",
    flow_name=flow_name,
)

Note

Supported sources: Salesforce, Zendesk

Run Flow Full

To run an AppFlow flow removing all filters, use: AppflowRunFullOperator.

tests/system/amazon/aws/example_appflow.py

campaign_dump_full = AppflowRunFullOperator(
    task_id="campaign_dump_full",
    source=source_name,
    flow_name=flow_name,
)

Note

Supported sources: Salesforce, Zendesk

Run Flow Daily

To run an AppFlow flow filtering daily records, use: AppflowRunDailyOperator.

tests/system/amazon/aws/example_appflow.py

campaign_dump_daily = AppflowRunDailyOperator(
    task_id="campaign_dump_daily",
    source=source_name,
    flow_name=flow_name,
    source_field="LastModifiedDate",
    filter_date="{{ ds }}",
)

Note

Supported sources: Salesforce

Run Flow Before

To run an AppFlow flow filtering future records and selecting the past ones, use: AppflowRunBeforeOperator.

tests/system/amazon/aws/example_appflow.py

campaign_dump_before = AppflowRunBeforeOperator(
    task_id="campaign_dump_before",
    source=source_name,
    flow_name=flow_name,
    source_field="LastModifiedDate",
    filter_date="{{ ds }}",
)

Note

Supported sources: Salesforce

Run Flow After

To run an AppFlow flow filtering past records and selecting the future ones, use: AppflowRunAfterOperator.

tests/system/amazon/aws/example_appflow.py

campaign_dump_after = AppflowRunAfterOperator(
    task_id="campaign_dump_after",
    source=source_name,
    flow_name=flow_name,
    source_field="LastModifiedDate",
    filter_date="3000-01-01",  # Future date, so no records to dump
)

Note

Supported sources: Salesforce, Zendesk

Skipping Tasks For Empty Runs

To skip tasks when some AppFlow run return zero records, use: AppflowRecordsShortCircuitOperator.

tests/system/amazon/aws/example_appflow.py

campaign_dump_short_circuit = AppflowRecordsShortCircuitOperator(
    task_id="campaign_dump_short_circuit",
    flow_name=flow_name,
    appflow_run_task_id="campaign_dump_after",  # Should shortcircuit, no records expected
)

Note

Supported sources: Salesforce, Zendesk

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