DYNAMAPPER AND PREPACKAGED INTEGRATIONS

Transcription

1 DYNAMAPPER AND PREPACKAGED INTEGRATIONS 1

2 THE NEED FOR INTEGRATION

3 3 CASE STUDY GLOBAL HEALTH CARE COMPANY SOURCE SYSTEMS NOT ADHERING TO INDUSTRY STANDARDS THE INITIAL PROBLEM Multiple source message structures and formats based on similar resources (functional objects) to be transformed into an industry standard (FHIR STU3) format. Multiple hospital facilities (source systems) transmitting patient s data to Research Panel (target system), with each facility having diverse functional objects as well as facility specific mappings.

4 4 CASE STUDY GLOBAL HEALTH CARE COMPANY NO STANDARD DATA FORMATTING ACROSS DIFFERENT PARTIES REQUIRED TO BE INTEGRATED THE ONGOING CHALLENGES Evolving source systems threatening the complexity of data transformations ecosystem Avoiding redundancy Keeping it Maintainable and Agile Faster Turn-Around Time

5 WE HAVE IDENTIFIED AN EFFICIENT SOLUTION TO THESE CHALLENGES DYNAMAPPER Accenture DynaMapper is an Architecture Solution to inject Agility, Superior Control, and Easier Maintainability in the most crucial piece of an Integration implementation i.e. Data Transformations Core Principle: Externalize the Data Mapping files FROM the Interface Package, TO a persistence layer e.g. Database Mule Flow Inbound Endpoint Data Mappings Outbound Endpoint Data Mappings *With DynaMapper *Traditional Approach Externalize

6 LET S ZOOM IN Property file main-execution-flow Inbound message Dynamically configured dwl Filename and original payload Transformed Output payload Flow logic DataWeave look-up Target system Caching dwl file contents Transformed output output payload Transformation dynamic-mapping-common-flow Source Systems dwls stored in Mongo.dwl Mongo DB 6

7 COMPLEXITIES OF TRADITIONAL MAPPING APPROACH Multiple flows: Redundant code in several similar flows with each flow having different set of mappings. Hard to maintain. Complex logic: Redundant logic to execute selected set of mappings (dwls).

8 DYNAMIC MAPPING APPROACH Dynamic dw() function DataWeave expressions defined within this function work just as those defined within a Transform Message element. The output is returned into the expression s result, wherever it may be. Simplified logic with no code redundancy.

9 LIQUID ARCHITECTURE PRINCIPLES One size GENERIC SOLUTION Can be applied across business domains and industries that use standard data formats for exchanging information. HIGHLY MAINTAINABLE Externalised data transformations enable ease of maintenance. REUSABLE Use of industry standards and externalisation allow to reuse transformations and data mappings. AGILE DEVELOPMENT New transformations can be easily added to the product, iterating the existing solution. ACCESS CONTROL Fine grained access control to maintain transformations. NON INTRUSIVE Modifications or additions to the transformations do not disturb the existing integrations. CENTRALISED Data transformations maintained in a single location. NO DOWNTIME No redeployment or refactoring when applying changes to existing applications.

10 INTRODUCING THE LEAN-MULE INTEGRATION XCHANGE AN INTEGRATION SOLUTION THAT PROVIDES INDUSTRY STANDARD PRE-PACKAGED INTEGRATIONS BASED ON MULE ANYPOINT PLATFORM CORE PRINCIPLES Micro-Services Architecture Lean Architecture Dev-Ops Cloud-Native Domain Driven Design Distributed and Dynamic Services Extensible, and Scalable Aligned to Lean Architecture best practices Reusable Services Low-Code Framework Built on DevOps best practices Supported by CI/CD Cloud native dockerized applications Built on AWS, compatible with cloud-only and hybrid architectures Supported by AWS CloudFormation 10

11 LeanMIX ENABLES THE STREAMLINING OF INTERFACE IMPLEMENTATION BY PROVIDING ARCHITECTURE BLUEPRINTS, AUTOMATION AND TOOLS Pre-Packaged Integrations MuleSoft AnyPoint Platform Experience APIs LeanMIX API-Led Connectivity Process APIs System APIs LeanMIX provides pre-built integrations for: Standard Integration Verticals and SaaS products such as Salesforce, SuccessFactors and ServiceNow. Standard Integration protocols, such as Web Service Consumers and File Processors. Standard Integration Patterns, such as Batch scopes, synchronous and asynchronous integrations.

12 DEMO 12

13 SCENARIO A TRANSFORMATIONS ARE DYNAMICALLY PICKED UP FROM THE REPOSITORY From API Console, Post HTTP request Deploy the project, and with input XML having one segment as expose the REST API payload. 4 Post HTTP request with XML having multiple segments as payload. 5 Verify dynamically mapped generated output of file in target folder. Transformed output file.

14 SCENARIO B - EASILY UPDATE TRANSFORMATIONS WITH NO INTRUSION TO EXISTING APPLICATION Refers Generates 1 dwl A File (Format A) 2 Substitute dwl file in Mongo 3 Refers Generates dwl B File (Format B) 14

15 Prateek Kakkar Accenture Technology Technology Arch Science Sr. Manager VISIT OUR LOUNGE TO FIND OUT MORE Kaustubh Patil Accenture Technology Technology Arch Science Manager Pankaj Bhardwaj Accenture Technology Technology Arch Science Manager