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What are Data Agnostic Services?

In application software development, a Data Agnostic Service is defined as:

A service interface where the data content of a record is passed using an agnostic mechanism (such as untyped XML or JSON)

  • The service interface can pass any type of data
  • The service implementation can process any type of data

What is data agnostic Services architecture?

  • DAS Architecture is the next evolution of:
    • Micro Service Architecture
    • Domain Driven Design
    • Agile DevOps
  • All data agnostic services are grouped into loosely coupled service areas with ONE well-defined concern:
  • As data moves between services, you should:
    • Enforce security and privacy rules BEFORE data crosses any service boundary
    • Apply layered “defense in depth” monitoring and auditing
  • All services have direct access to the latest version of a record in “Data at Rest”
  • Service implementations should be data driven and not hard coded
    • “Plug and play” components that can be configured during deployment
    • Generic data driven logic where possible to process any type of record
    • Custom coded only when the business logic can’t be data driven efficiently
    • Easily upgraded or replaced to create a sustainable solution
  • As well as being data agnostic, a true DAS Architecture should also:
    • Be platform and technology agnostic
    • Utilize the latest Agile, Development, Security and Operations (DevSecOps) processes

Why go beyond micro-service architecture?

  • The DAS Architecture eliminates the need:
    • For defining artificial service boundaries
      • Such as Customer, Order, Invoice, etc.
    • For coarse-grained services, eventual consistency, or caching
    • For even creating separate services for: Customer, Order, Invoice etc.
  • Any type of data can be:
    • Stored in a single Data at Rest service
    • Securely shared with users through a single Data Presentation service
  • Any workflow operation can:
    • Securely access the latest version of any required data
    • Write the results of the operation back to common storage
    • Can be deployed as its own completely independent service
  • The DAS Architecture is inherently more secure and sustainable because:
    • There is only one implementation of the core services for storing and presenting data
    • All workflow operation services are completely independent