From legacy systems to microservices and back | Andera Gioia, Quantyca
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The document discusses legacy modernization strategies, emphasizing the need for improved integration architectures to bridge legacy systems with frontend applications. It outlines various integration architectures, such as integration rationalization and data offloading, which aim to improve time-to-market, reduce costs, and enhance resilience. The author, Andrea Gioia, encourages a data-centric approach and highlights the Digital Integration Hub as a decoupling mechanism for managing legacy systems effectively.
From legacy systems to microservices and back | Andera Gioia, Quantyca
- 1. KAFKA Summit EMEA 2021 Andrea Gioia CTO at Quantyca Co-Founder at Blindata From legacy systems to microservices and back
- 2. What is legacy modernization Current integration architecture between frontend applications and backend legacy systems does not scale anymore The legacy systems cannot be replaced overnight A better integration architecture is needed in order to modernize them in place. ...and why it matters System of Engagement System of Insight System of Records Legacy Systems Application Layer Integration Layer Point to point “Spaghetti” integration
- 3. Who am I? Not an easy question to answer but keeping it simple... Andrea Gioia andrea.gioia@quantyca.it Quantyca is a privately owned technological consulting firm specialized in data and metadata management based in Italy quantyca.it Blindata is a SAAS platform that leverages Data Governance and Compliance to empower your Data Management projects. blindata.io CTO CO-FOUNDER
- 4. Integration architecture #1 All new functionalities are implemented directly by extending the legacy system or by buying complementary products offered by the same vendor of the legacy system. Integration layer if present is limited to an API Gateway to decouple legacy backend from frontend applications Legacy systems take it all System of Engagement Frontend System of Insight Frontend System of Records Legacy Systems Application Layer Integration Layer API Gateway SoE & SoI Backend SoE & SoI Backend SoE & SoI Backend SoE & SoI Backend SoE & SoI Backend TIME-TO-MARKET AND BUSINESS AGILITY IMPROVEMENT COSTS AND RISKS REDUCTION RESILIENCE AND PERFORMANCE IMPROVEMENT
- 5. Integration architecture #2 Integration rationalization through composite services System of engagement System Of Insight System of Records Legacy Systems Application Layer Integration Platform API Gateway Request Based Integration Layer Application Services Process Services Sourcing Services Composite Services Integrations are rationalized through different layers of reusable and composable services. Sourcing services wrap legacy systems, process service orchestrate business process and application services provide a backend for frontend applications TIME-TO-MARKET AND BUSINESS AGILITY IMPROVEMENT COSTS AND RISKS REDUCTION RESILIENCE AND PERFORMANCE IMPROVEMENT
- 6. Integration architecture #2 Integration rationalization through data virtualization System of engagement System Of Insight System of Records Legacy Systems Application Layer Integration Platform API Gateway Request Based Integration Layer Application Layer Business Layer Physical Layer Virtual DWH TIME-TO-MARKET AND BUSINESS AGILITY IMPROVEMENT COSTS AND RISKS REDUCTION RESILIENCE AND PERFORMANCE IMPROVEMENT Integrations are rationalized through different layers of views served by a data virtualization application. Physical layer wraps legacy systems, business layer exposes the business model and application layer provide projections designed to facilitate consumption.
- 7. Integration architecture #2 Integration rationalization System of engagement System Of Insight System of Records Legacy Systems Application Layer Hybrid Integration Platform API Gateway Request Based Integration Layer Virtual DWH Composite Services TIME-TO-MARKET AND BUSINESS AGILITY IMPROVEMENT COSTS AND RISKS REDUCTION RESILIENCE AND PERFORMANCE IMPROVEMENT Composite services and data virtualization can be used in the same architecture. The former is preferred to back system of engagement the latter to back system of insight. Both solutions simplify integrations but don’t reduce the workload on the backend systems
- 8. Integration architecture #3 Data offloading System of engagement System Of Insight System of Records Legacy Systems Application Layer Hybrid Integration Platform API Gateway Event-BasedIntegration Layer High-Performance Data Store Microservices Metadata Management TIME-TO-MARKET AND BUSINESS AGILITY IMPROVEMENT COSTS AND RISKS REDUCTION RESILIENCE AND PERFORMANCE IMPROVEMENT Data offloaded from legacy systems are aggregated into low- latency, high performance datastore accessible via APIs, events or batch. The data store synchronizes with the beck ends via event- driven integration patterns.
- 9. Digital Integration Hub Key building blocks Event store High performanc e data store Connectors Legacy Systems Applications Services Where the data is stored Keeps the legacy systems and the high performance data store in sync offloading all modifications to relevant data in real time Transform technical events coming from connectors to domain and business events that can be consumed downstream by high performance data store or other consumers (event driven integration) Stores domain specific data exposing a single consolidated view of entities ~ Supports fast ingestion to reduce eventual consistency window ~ Can support analytical queries Connect to high performance data store for read queries Execute write on the legacy systems by means of command events pushed on the event store (command query responsibility segregation) Where the data is used
- 10. Legacy System Streaming Platform Connectors Data acquisition patterns
- 11. Legacy System Streaming Platform Technical Events (Speed & Fidelity) Domain Events (Trusted Views) Business Events (Ease of consumption) Event Store Event driven integration
- 12. Legacy System Streaming Platform Technical Events (Speed & Fidelity) Domain Events (Trusted Views) High Performance Data Store Business Events (Ease of consumption) High-performance data store Some options
- 13. Legacy System Streaming Platform Technical Events (Speed & Fidelity) Domain Events (Trusted Views) High Performance Data Store Business Events (Ease of consumption) Commands Micro/Mini Services READ WRITE Microservices From legacy systems to services and back
- 14. The legacy modernization journey Offloading, Isolation and Refactoring Legacy System Digital Integration Hub Applications 1 Legacy Offloading Legacy System Digital Integration Hub Applications Anti Corruption Layer Bubble Context 2 Legacy Isolation Digital Integration Hub Applications Anti Corruption Layer Bubble Context 3 Legacy Refactoring
- 15. Takeaways Digital integration hub can be seen as a way of decoupling systems using data as anti corruption layer. Data offloaded into the integration platform become a first-class citizen of the new data centric architecture. Benefits ○ Responsive user experience ○ Offload legacy systems from expansive workloads generated by front-end services ○ Support legacy refactoring ○ Align services to business domain ○ Enable real time analytics ○ Foster a data centric approach to integration Challenges ○ Adapting the conceptual architecture to your specific context ○ Assembling different technology components, possibly from different vendors ○ Operating a complex distributed and loosely coupled architecture ○ Supporting bidirectional synchronization ○ Designing the domain data models for the business entities ○ Developing services that can tolerate eventual consistency ○ Managing organizational politics related to data ownership
- 16. Questions? Feel free to ask andrea.gioia@quantyca.it
Editor's Notes
- #3: Digital transformation continuously push toward the development of new touchpoints in a omnichannel logic (System of engagement) analytical and AI based services (System of insight) These new applications are usually integrated with back-office legacy systems with a point-to-point logic. This way of integrating the new with the legacy does not scale up in the long term. Because the legacy cannot be simply thrown away a better integration architecture is needed in order to modernize them in place.
- #15: CQRS Micro vs Mini Services e data mesh The journey Takeaways