Amazon and Salesforce are at the forefront of technological innovation in the cloud world, which is continually changing. Amazon AppFlow Salesforce, a fully managed integration tool that enables secure data flow between Software as a Service (Salesforce) and AWS, was only just announced. Users now have a quick and affordable option to transfer data thanks to this new service. It's a great solution for Salesforce customers that wish to adopt AWS right away and reap the rewards.
Now accessible programmatically, AWS AppFlow Salesforce is a fully managed integration tool that enables users to safely transmit data between AWS services and software-as-a-service (SaaS) applications. Developers can build up flows between source and destinations supported by Amazon AppFlow, define connector profiles, and programmatically execute flows thanks to the AWS AppFlow SDK and APIs. Developers can integrate Amazon AppFlow directly into their DevOps pipelines for data integrations by using the SDK and Amazon AppFlow APIs. Users of the Amazon AppFlow API will be assessed the same price parameters and rates as those of the Amazon AppFlow.
Software-as-a-Service (SaaS) apps like Salesforce, Marketo, Slack, and ServiceNow and AWS services like Amazon S3 and Amazon are all accessible through the fully managed integration tool Amazon AppFlow. Redshift is accessible with a few clicks.
With AppFlow, you may perform data flow on demand, in reaction to a business event, or almost at any scale and frequency you like. Without taking any additional steps, you may configure data transformation features like filtering and validation to produce rich, usable data as part of the flow itself. Data in motion is automatically encrypted by AppFlow. In order to lessen their exposure to security risks, customers can limit the transfer of data for SaaS apps that are linked with Amazon PrivateLink via the open Internet.
Amazon AppFlow enables you to do the following:
Without any coding knowledge, you can create data flows using Amazon AppFlow SDK in a matter of minutes. Without needing to rely on technical teams, you can choose your data sources and destinations, set up optional transformations, filters, and validations, and run your flow using a simple user interface.
You may set up a regular schedule to maintain data in sync or launch data flows on demand to perform bulk transfers using Amazon AppFlow. Moreover, it has the ability to execute flows in reaction to business events like the opening of a sales opportunity, updating the status of a support case, or finishing a registration form.
Salesforce, SAP, Google Analytics, and Facebook Ads are just a few of the software-as-a-service (SaaS) programs that are natively integrated with Amazon AppFlow, and more integrations are planned. You can transfer data from any supported SaaS service using a few options with Amazon AppFlow.
You can utilize a CSV file, bulk field mapping, individual field mapping, or Amazon AppFlow Salesforce to map source and destination fields. You may conduct data transformations like merging, masking, filtering, and validation with the aid of Amazon AppFlow. For instance, you can merge first and last names, verify that your data is in the correct numerical format, or hide credit card information.
When Amazon Simple Storage Service (S3) is selected as the destination, Amazon AppFlow divides your data according to the source object schema. The architecture of your data is improved by partitioning to facilitate effective querying by analytical engines like Amazon Athena and Amazon Redshift Spectrum. Depending on the destination fields you choose, data is arranged in a hierarchical partition structure.
Moreover, queries perform better when blocks of data can be read sequentially and when data scanning can be parallelized. You can combine records using Amazon AppFlow to create files that are tailored to the size you specify. Parallelism is enhanced and processing overhead is reduced as a result.
Your data's preparation and registration into the AWS Glue Data Catalog are automated by Amazon AppFlow in a few choices. Using AWS analytics and machine learning services like AWS Glue, Amazon Athena, and Amazon SageMaker Data Wrangler, you can share, find, and access data from the increasing library of more than 50 SaaS connectors from Amazon AppFlow.
You can create your own connectors using the Amazon AppFlow Connector Software Development Kit (SDK) to securely transport data between your unique endpoint, application, or other cloud service and the managed SaaS and AWS connectors in the Amazon AppFlow library. Using the same open-source SDK that internal AWS teams use, create and test integrations. Starting your custom connector right now is possible with Python and Java.
When compared to developing connections yourself or using alternative application integration services, Amazon AppFlow is more affordable. To utilize Amazon AppFlow, there are no setup fees or license costs; instead, you simply pay for the number of flows you execute and the amount of data handled.
Millions of Salesforce records, Marketo leads, or Zendesk tickets can be transferred more easily thanks to Amazon AppFlow's ability to process up to 100 GB of data per flow.
AWS By limiting the amount of data that is exposed to the internet, PrivateLink makes the security of data exchanged with cloud-based services simpler. Amazon AppFlow automatically builds and configures private endpoints for SaaS apps that have PrivateLink enabled, ensuring that your data is kept private by default.
You can use Amazon keys to encrypt data or provide your own custom keys to encrypt data. All data traveling through AppFlow is encrypted both in transit and at rest.
With Amazon AppFlow, you can enforce fine-grained permissions and maintain consistent access across your business without writing new policies by using your current AWS Identity and Access Management (IAM) policies. Application administrators may securely build and manage data flows without relying on technical teams with the help of carefully enforced IAM policies.
A highly available architecture was used in the development of Amazon AppFlow to guard against single points of failure. You don't need to configure AWS scaling, monitoring, auditing, or billing functionalities because Amazon AppFlow makes use of them.
Here are a few use cases that demonstrate how using Amazon AppFlow can be advantageous.
Build a flow that is activated each time a new record is created in Salesforce Cloud, calculates the potential sales, and then moves the updated record to an Amazon Redshift table.
Build a flow that moves discussion data from a Slack channel to Amazon Redshift, Snowflake, or Amazon S3 for archival and analysis on a regular basis.
Build a manually triggered flow in Zendesk that sends ticket data to Amazon Redshift, Snowflake, or Amazon S3 for archival and analysis for all tickets with the same case number.
Build a flow that will transfer data from Salesforce, Marketo, ServiceNow, and Zendesk to Amazon S3 on a weekly basis in an aggregate amount of up to 100GB per flow with minimal latency.
Integrating data from sales, customer service, and marketing will give you a 360-degree perspective of the customer journey.
A custom ML model created for Amazon SageMaker can be used to enrich data for various SaaS platforms, such as Salesforce, to help direct customers to the right sales support.
Create records in Salesforce from fresh Marketo leads by automating activities in one program based on data from another.
By using Amazon AppFlow, you may avoid spending a lot of time and money on highly qualified engineers to build and manage unique API connections for Amazon services to exchange data with SaaS apps. The majority of the interconnections that SaaS application administrators and business analysts require can be easily implemented without requiring IT to wait months for integration projects to be finished. Particularly, the advantages consist of:
Amazon AppFlow is even more appealing because of the pricing structure. Even though the market is filled with other solutions that are identical to AppFlow, none of them can match its cost-effectiveness. Customers just pay for the number of flows they execute and the volume of data they process; there are no up-front costs associated with using AppFlow. Every successful stream is paid for by you. A call to the source program to transfer data to the destination represents the start of a flow. Even if there is no new data on the source system to transfer, flow runs to check for fresh data nevertheless incur expenses.
The monthly processed data by volume for Amazon AppFlow aggregates all flows that are present in an AWS account and is charged per GB. Schema mapping, filtering, and field validation are a few examples of data processing. You only pay the charges associated with the data processing of the flows when using Amazon AppFlow; the AWS data transfer fees are not your responsibility.
The following services are compatible with Amazon AppFlow:
AWS CloudTrail, a service that offers a record of actions made by a person, role, or an AWS service in Amazon AppFlow, is connected with Amazon AppFlow. All API requests made to Amazon AppFlow are recorded as events by CloudTrail. Both code calls to the Amazon AppFlow API operations and calls from the Amazon AppFlow console are to be recorded. You can allow continuous delivery of CloudTrailevents, including events for Amazon AppFlow, to an Amazon S3 bucket by setting up a trail.
Even without configuring a trail, you can still access the CloudTrail console’s event history to see the most recent events. You may identify the request that was made to Amazon AppFlow, the IP address from which it was made, who made the request, when it was made, and other information using the data collected by CloudTrail.
For you to model and provision AWS and outside application resources in your cloud environment, AWS CloudFormation offers a common language. AWS CloudFormation enables you to model and provide all the resources required for your applications across all regions and accounts in an automated and secure manner using programming languages or a straightforward text file.
You now have a single source of truth for all of your AWS and outside resource needs. For secure, effective, and repeatable creation and configuration of Amazon AppFlow resources along with the rest of your AWS infrastructure, Amazon AppFlow supports AWS CloudFormation.
To receive events from Amazon AppFlow sources like Salesforce, Amazon AppFlow interfaces with Amazon EventBridge. You can now publish events that Amazon AppFlow has ingested to a partner event bus in Amazon EventBridge. Salesforce platform events and Change Data Capture events can be ingested by Amazon AppFlow.
To route events to AWS services like AWS Lambda, AWS Step Functions, Amazon Simple Queue Service, and others, rules in Amazon EventBridge can be set up to match patterns from events like those from Salesforce.
To further improve security and reduce the likelihood of internet-based attack vectors, you can use Amazon AppFlow’s private data transfer option to make sure that events don’t get exposed to the public internet while being transferred between AWS and Salesforce.
IAM is a service provided by Amazon that aids administrators in securely managing user access to AWS resources. You can manage who has access to Amazon AppFlow within your organization thanks to its integration with the IAM service.
How Do Consumers of Salesforce Fare Under Amazon AppFlow?
Utilizing the bidirectional capabilities and changing data-gathering capabilities of Amazon AppFlow, it enables third-party applications on AWS to update Salesforce and vice versa. You can quickly produce rich, automated data that spans several applications using AppFlow.
The default Salesforce data loader cannot successfully provide many more functions, but AppFlow can. Users of Salesforce can rapidly extract data and save it in Amazon S3 object by object. Users of Salesforce can now move data without rapidly acquiring a costly integration package thanks to Amazon AppFlow Salesforce.
Salesforce objects and fields can be quickly connected and mapped using AppFlow. As a result, you can schedule and run tasks through the AWS AppFlow UI without worrying about additional licenses. For instance, if you gather information about your customers' app and website usage and need to move it to S3. Salesforce is unable to carry out this task because a Salesforce database cannot be directly connected to a SQL database. You may effectively merge all of these data points into an S3 environment using AppFlow. And the advantages are considerably greater if your data lake already uses S3.
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