Introduction
Data is at the core of any Operations regardless of the business model, it holds a huge stake in the decision making of day to day operations.
It can be engaging to extract, analyse and a draw a conclusive...
AWS cloud provides a number of services that make it possible to achieve this from kinesis data stream and its "complimentary" services like amazon firehose, amazon kinesis data analytics. AWS also has offers a solution for applications leveraging on Apache Kafka under the service amazon managed streaming for kafka.
In this article i will be looking at AWS Appflow it is managed by AWS it integrates well with other services like Amazon Redshift and Amazon simple storage service. It leverages its capability to intergrate with services out of AWS through API references. AWS provides a list of different platforms that integrate with AWS Appflow in the link below
https://docs.aws.amazon.com/appflow/latest/userguide/app-specific.html
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Content
**AWS AppFlow provides an easy and straight forward way to process data, enable data to be kept together in a synchronize, secure, organized and able to develop custom connectors.
AWS highlights various advantages and use cases in the link below.
https://docs.aws.amazon.com/appflow/latest/userguide/what-is-appflow.html
There are a number of Prerequisites when starting to use AWS Appflow. It leverages flow approach which can be achieved through the AWS console, AWS CLI, through APIs and also
cloudformation templates. AWS provides a step to step guide of the different approaches
https://docs.aws.amazon.com/appflow/latest/userguide/create-flow.html
After the implementation of the AppFlow it is necessary to manage the flow below is a link that provides a guide to go about it.
https://docs.aws.amazon.com/appflow/latest/userguide/flows-manage.html
The data goes through data cataloging this are metadata such as schema, format and data types. It is unified irregadles of the data belonging to different datasets.
AWS provides a briefed step on how cataloging is achieving Amazon S3 and AWS Glue data catalog, link below give's you a detailed approach
https://docs.aws.amazon.com/appflow/latest/userguide/flows-catalog.html.
There are a number of other steps that the service provides when the flow undergo partitioning and aggregation according to AWS this is used to optimize query performance for applications that access data, AWS provides a step to step guide on how to go about it in the link below.
https://docs.aws.amazon.com/appflow/latest/userguide/flows-partition.html
AWS AppFlow provides a system known as triggers that determines how a flow runs.It provides three types of flow triggers this are: on demand, on event and on schedule each suited for the application needs.
The on demand requires a manual run while the on event responses to events in software as a service application (SaaS) and an on schedule runs on a recurring schedule.
AWS Appflow also creates a private flow through a privatelink
to route data over AWS infrastructure without exposing it to public internet. This is used to provide access to SaaS applications.
AWS AppFlow offers notifications by intergrating with EventBridge to publish events related to the status of a flow aws highlights a number of step and common fields assosiated to this in the link
https://docs.aws.amazon.com/appflow/latest/userguide/flow-notifications.html
Conclusion
In any desired effect well calculated measures have to be put in place, in this case data is the ingredient that can be used to bring the desired effect, this is made possible by leveraging AWS Appflow with ease. I will see you next time, enjoy your AWS experience.
Authored by
Sospeter Gathungu, Aws community builder member
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