SlideShare uma empresa Scribd logo
1 de 41
Baixar para ler offline
MODULARITY AND DOMAIN
DRIVEN DESIGN
a killer combination?
Tom De Wolf
Architect
tom.dewolf@aca-it.be
@tomdw
Stijn Van den Enden
CTO
stijn.vandenenden@aca-it.be
@stieno
www.aca-it.be
initial development maintenance phase
Software Design Customer Satisfaction
Separation of Concerns
Low coupling High Cohesion
B AB
A
• Change A impacts all
modules = costly
• Change B requires split
of module = costly
• Change A only impacts
other module if api change
• Change B limited to
module
Encapsulate Source of Change
Predictable Cost of Change
Constant change Business Driven
Aim for 1-on-1 mapping from business changes
onto software constructs
Source of Change = Business
Functional Modularisation
Vehicle
Option
Make
Warranty
Model
Transport
Location
Domain Driven Design
Without modularity
BusinessPartner
Address
Contact
consumer supplier
transports
owner
from to
Vehicle
Option
Make
Warranty
Owner
Model
Transported Item
Transport
Transport Supplier
Transport Consumer
Vehicle Context Transport Context
Domain Driven Design
Modularity with Bounded Contexts BusinessPartner
AddressContact
Business Partner Context
Location
from to
transport
vehicle
MODULAR DATABASE SCHEMA
• cross domain database structures not allowed
• queries cannot cross domain boundaries
NO foreign key
business partner
UUID MAKE MODEL OWNER_ID
djdfjfdkjdk221 Ford C-Max BE1234567
TRANSPORTED_ITEM_ID FROM CONSUMER_ID
djdfjfdkjdk221 454 BE1234567
LOCATION_ID ADDRESS
454 Sunstreet 23
foreign key
VAT_NUMBER NAME
BE1234567 Company A
BENEFITS …
• Domain modules can migrate independently
to next version!
• Database schema is internal to the domain
bundle, i.e. NOT part of the API!
• Persistence and/or database technology can
differ between modules in one system!
Mmodular database migration
cross domain transactions
Tx
Scross domain search and reporting
C
H
A
L
L
E
N
G
E
S
Mmodular database migration
M
Dev Machine 1
MIGRATION CHALLENGE
Dev Machine 2
Continuous
Integration
Test
environment
Acceptance
environment
Production
environment
Version	

1.0.0
Version	

1.0.1
Version	

1.0.2
Version	

?
Version	

?
Version	

?
environment x
Module 1 Module 2 Module 3
Version	

1.0.0
Version	

3.0.0
Version	

2.0.2
Manually track which scripts have run
on which environment for which module ?
M
LIQUIBASE
DATABASECHANGELOG table to track executed changesets for each environment
In versioned source code
XML based DSL for changeSets
www.liquibase.org
M
MODULAR LIQUIBASE
transportvehicle business partner
deployment 1
deployment 2
deployment 3
Migrate modules separately Migrate @deploy of module
migrate to initial version migrate to initial version migrate to initial version
no db changes, no migration migrate to version 2 migrate to version 2
migrate to version 3
M
THE EXTENDER PATTERN
bundle A
bundle B
bundle C
bundle D
extender bundle
Extension Pattern ?!
no match
/OSGI-INF/liquibase/db.changelog-master.xml
osgi-liquibase-extender
framework dependency
Liquibase
change sets domain A
change sets domain B
change sets domain C
• Only extender depends on
Liquibase framework
• Update of single bundle
triggers Liquibase update
• New Liquibase process 

for each matching bundle
Tcross domain transactionsx
JTA OR NOT?
• No persistence layer — direct jdbc/sql access — 1 datasource



• Multiple datasources
• Different types of persistence layers (JPA, NoSQL, …)
• JPA persistence layer in each domain bundle
• instead of one big persistence unit
• even on 1 datasource
T
1 transaction spanning multiple modular domains
JTA not needed
JTA required
x
MODULAR PERSISTENCE
T osgi-datasource
XA enabled
vehicle-domaintransport-domain
javax.transaction.TransactionManager
transaction provider
e.g. atomikos
javax.sql.DataSource
persistence
context
persistence
context
commit
x
Scross domain search
Scross domain search
SEARCH
the tale of the evil joins
NO
cross
module
search
A. Search encapsulated in a separate module leveraging
the functionality of other domain modules
search-
module
domainA
domainB
x
x
Repository
Repository
Stop
• requires specific implementation for every search	

• complexity increases with number of modules	

• inability to leverage power of the datastore
SearchAPI
domainA
B. Search is using a separate query model
search-
module
domainB
SearchAPI
EventProvider
Update	

Events
Update
$ curl -XPUT ‘localhost:9200/vehicle/external/1’ -d ‘{	
	“make”: “BMW”,	
	 “VIN”: “30203232012102”	
}’
index document_type
id
Index a document
$ curl -XPOST ‘localhost:9200/vehicle/external/1/
_update’ -d ‘{	
	“doc”: {“make”: “Alpina”}	
}’
Update a document
index document_type
id
$ curl -XPOST localhost:9200/vehicle/_search?pretty -d
‘{"query":{"match":{"make":"BMW"}}}'	
index
Querying an index
$ curl -XPOST localhost:9200/vehicle/_search?pretty -d
‘{"query":{"match":{"mark":"BMW"}}}'	
{	
"took" : 3,	
"timed_out" : false,	
"_shards" : {	
"total" : 5,	
"successful" : 5,	
"failed" : 0	
},	
"hits" : {	
"total" : 2,	
"max_score" : 0.30685282,	
"hits" : [ {	
"_index" : "vehicle",	
"_type" : "external",	
"_id" : "1",	
"_score" : 0.30685282, "_source" : {"make": "BMW", "VIN": "30203232012102"}	
}, {	
"_index" : "vehicle",	
"_type" : "external",	
"_id" : "2",	
"_score" : 0.30685282, "_source" : {"makes": "BMW", "VIN": "30203232012112"}	
} ]}}	
!
Querying an index
• Distributed (shards/replicas)	

• Advanced Quering (lucene/geo/
aggregation)	

• Facets (terms/ranges/histogram)	

• API (HTTP/Java/JavaTesting)	

• …
{
1Populate the index
1Populate the index
package be.vabfs.search.api;	
!
public interface SearchIndexService {	
	 	
	 void update(Object entityToUpdate);	
	 	
	 void delete(Object entityToRemove);	
!
	 void populate();	
!
	 void clear();	
!
}
search
SearchIndexService
domainB
Entity
EntityListener
@PrePersist
@PostUpdate
@PostRemove
1Populate the index
search
SearchIndexService
update(entity)
Synchronise onTransaction
Track updated entities
A
Map entities to searchData
B
Bulk update search index
C
1Populate the index
Map entities to searchData
B
package be.vabfs.search.api.data;	
!
import java.util.List;	
!
public interface SearchDataProvider {	
!
	 Class<? extends Object> getEntityClass();	
	 	
	 List<SearchData> index(Object entity);	
!
}
domainB
Entity
SearchData
1Populate the index
Map entities to searchData
B
SearchDataProvider
domainB
Entity
SearchData
1Populate the index
A
search
SearchIndexService
update(entity)
Synchronise onTransaction
Track updated entities
Bulk update search index
C
Map entities to searchData
B SearchDataProvider
domainB
A
2Enhancing Search
2Enhancing Search
2Enhancing Search
search
SearchService
package be.vabfs.search.api;	
!
import …	
!
public interface SearchService {	
	
…	
!
SearchResults query(String query, int start, int rows,	
	 	 	 	 	 	 	 	String sort, String sortOrder,	
	 	 	 	 	 	 	 	 	 String documentType);	
	 	
	 List<String> options(String field, 	
	 	 	 	 	 	 	 	 	 	 String... documentTypes);	
	 	
	 List<SearchCriterion> availableCriteria(	
	 	 	 	 	 	 	 	 	 	 String... criteriaCategories);	
	 	
}
2Enhancing Search
package be.vabfs.search.api.criteria;	
!
import java.util.List;	
!
public interface SearchCriteriaProvider {	
	 	
	 String getProviderCategory();	
	 	
	 List<SearchCriterion> getAvailableCriteria();	
}	
package be.vabfs.search.api.criteria;	
!
public interface SearchCriterion {	
!
	 String getName();	
	 String getKey();	
	 String getUnitName();	
	 SearchCriterionType getType();	
	 SearchCriterionQueryType getQueryType();	
	 String getDocumentType();	
!
}
"vehicle.mileage"
"mileage"
SearchCriterionType.NUMBER
SearchCriterionQueryType.RANGE_NUMBER
"SERVICE_ITEM"
"km"
2Enhancing Search
search
SearchService
domainB
SearchCriteriaProvider
domainB
LESSONS LEARNED
@deployment time migration = RISK
• have CI build continuously migrate current production
data
Refactor wrong modularisation requires unwanted migration
dependencies
• reset/flatten migration change sets to restore
modularisation
Migration
Cross domain search and reporting
Effort to integrate search is limited
• due to dynamic osgi service model
Advanced search functionality is possible
WHAT IS NEXT?
Multiple module versions active? Multiple schema versions
active?
• e.g. feature try-out to limited customer base
Downgrade to older module version?
• Previous schema with new data?
Hot deploy while users are firing requests?
• Migration still busy = failure
Migration
Cross domain search and reporting
Domain Specific Query Language
!
Exploiting elastic search capabilities beyond search, e.g.
reporting
M
Modular migration
Liquibase extender @ DeployT
Cross domain transactions
Distributed JTA transactionsx S
Cross domain search
Elasticsearch view
Functionally	

not limited by domain module boundaries to answer business questions
Non-functionally
future-proof platform with impact of change contained in loosely coupled domain modules
Tom De Wolf
Architect
tom.dewolf@aca-it.be
@tomdw
Stijn Van den Enden
CTO
stijn.vandenenden@aca-it.be
@stieno
www.aca-it.be

Mais conteúdo relacionado

Mais procurados

How to build an ETL pipeline with Apache Beam on Google Cloud Dataflow
How to build an ETL pipeline with Apache Beam on Google Cloud DataflowHow to build an ETL pipeline with Apache Beam on Google Cloud Dataflow
How to build an ETL pipeline with Apache Beam on Google Cloud DataflowLucas Arruda
 
Performance Analysis and Optimizations for Kafka Streams Applications
Performance Analysis and Optimizations for Kafka Streams ApplicationsPerformance Analysis and Optimizations for Kafka Streams Applications
Performance Analysis and Optimizations for Kafka Streams ApplicationsGuozhang Wang
 
Why Kubernetes as a container orchestrator is a right choice for running spar...
Why Kubernetes as a container orchestrator is a right choice for running spar...Why Kubernetes as a container orchestrator is a right choice for running spar...
Why Kubernetes as a container orchestrator is a right choice for running spar...DataWorks Summit
 
Solutions for bi-directional Integration between Oracle RDMBS & Apache Kafka
Solutions for bi-directional Integration between Oracle RDMBS & Apache KafkaSolutions for bi-directional Integration between Oracle RDMBS & Apache Kafka
Solutions for bi-directional Integration between Oracle RDMBS & Apache KafkaGuido Schmutz
 
Synchronize AD and OpenLDAP with LSC
Synchronize AD and OpenLDAP with LSCSynchronize AD and OpenLDAP with LSC
Synchronize AD and OpenLDAP with LSCLDAPCon
 
Running secured Spark job in Kubernetes compute cluster and integrating with ...
Running secured Spark job in Kubernetes compute cluster and integrating with ...Running secured Spark job in Kubernetes compute cluster and integrating with ...
Running secured Spark job in Kubernetes compute cluster and integrating with ...DataWorks Summit
 
A New Chapter of Data Processing with CDK
A New Chapter of Data Processing with CDKA New Chapter of Data Processing with CDK
A New Chapter of Data Processing with CDKShu-Jeng Hsieh
 
Enabling real interactive BI on Hadoop
Enabling real interactive BI on HadoopEnabling real interactive BI on Hadoop
Enabling real interactive BI on HadoopDataWorks Summit
 
Mondrian update (Pentaho community meetup 2012, Amsterdam)
Mondrian update (Pentaho community meetup 2012, Amsterdam)Mondrian update (Pentaho community meetup 2012, Amsterdam)
Mondrian update (Pentaho community meetup 2012, Amsterdam)Julian Hyde
 
Achieving a 50% Reduction in Cross-AZ Network Costs from Kafka (Uday Sagar Si...
Achieving a 50% Reduction in Cross-AZ Network Costs from Kafka (Uday Sagar Si...Achieving a 50% Reduction in Cross-AZ Network Costs from Kafka (Uday Sagar Si...
Achieving a 50% Reduction in Cross-AZ Network Costs from Kafka (Uday Sagar Si...confluent
 
QA Fest 2019. Дмитрий Собко. Testing Big Data solutions fast and furiously
QA Fest 2019. Дмитрий Собко. Testing Big Data solutions fast and furiouslyQA Fest 2019. Дмитрий Собко. Testing Big Data solutions fast and furiously
QA Fest 2019. Дмитрий Собко. Testing Big Data solutions fast and furiouslyQAFest
 
Build Your Kubernetes Operator with the Right Tool!
Build Your Kubernetes Operator with the Right Tool!Build Your Kubernetes Operator with the Right Tool!
Build Your Kubernetes Operator with the Right Tool!Rafał Leszko
 
Food Processing is Stream Processing (Stefan Freshe, Nordischer Maschinenbau...
Food Processing is Stream Processing (Stefan Freshe,  Nordischer Maschinenbau...Food Processing is Stream Processing (Stefan Freshe,  Nordischer Maschinenbau...
Food Processing is Stream Processing (Stefan Freshe, Nordischer Maschinenbau...confluent
 
An elastic batch-and stream-processing stack with Pravega and Apache Flink
An elastic batch-and stream-processing stack with Pravega and Apache FlinkAn elastic batch-and stream-processing stack with Pravega and Apache Flink
An elastic batch-and stream-processing stack with Pravega and Apache FlinkDataWorks Summit
 
The Future of Apache Ambari
The Future of Apache AmbariThe Future of Apache Ambari
The Future of Apache AmbariDataWorks Summit
 
Building large scale applications in yarn with apache twill
Building large scale applications in yarn with apache twillBuilding large scale applications in yarn with apache twill
Building large scale applications in yarn with apache twillHenry Saputra
 
Ultimate journey towards realtime data platform with 2.5M events per sec
Ultimate journey towards realtime data platform with 2.5M events per secUltimate journey towards realtime data platform with 2.5M events per sec
Ultimate journey towards realtime data platform with 2.5M events per secb0ris_1
 
How to Build an Apache Kafka® Connector
How to Build an Apache Kafka® ConnectorHow to Build an Apache Kafka® Connector
How to Build an Apache Kafka® Connectorconfluent
 
Dependency Injection in Apache Spark Applications
Dependency Injection in Apache Spark ApplicationsDependency Injection in Apache Spark Applications
Dependency Injection in Apache Spark ApplicationsDatabricks
 
Omid: scalable and highly available transaction processing for Apache Phoenix
Omid: scalable and highly available transaction processing for Apache PhoenixOmid: scalable and highly available transaction processing for Apache Phoenix
Omid: scalable and highly available transaction processing for Apache PhoenixDataWorks Summit
 

Mais procurados (20)

How to build an ETL pipeline with Apache Beam on Google Cloud Dataflow
How to build an ETL pipeline with Apache Beam on Google Cloud DataflowHow to build an ETL pipeline with Apache Beam on Google Cloud Dataflow
How to build an ETL pipeline with Apache Beam on Google Cloud Dataflow
 
Performance Analysis and Optimizations for Kafka Streams Applications
Performance Analysis and Optimizations for Kafka Streams ApplicationsPerformance Analysis and Optimizations for Kafka Streams Applications
Performance Analysis and Optimizations for Kafka Streams Applications
 
Why Kubernetes as a container orchestrator is a right choice for running spar...
Why Kubernetes as a container orchestrator is a right choice for running spar...Why Kubernetes as a container orchestrator is a right choice for running spar...
Why Kubernetes as a container orchestrator is a right choice for running spar...
 
Solutions for bi-directional Integration between Oracle RDMBS & Apache Kafka
Solutions for bi-directional Integration between Oracle RDMBS & Apache KafkaSolutions for bi-directional Integration between Oracle RDMBS & Apache Kafka
Solutions for bi-directional Integration between Oracle RDMBS & Apache Kafka
 
Synchronize AD and OpenLDAP with LSC
Synchronize AD and OpenLDAP with LSCSynchronize AD and OpenLDAP with LSC
Synchronize AD and OpenLDAP with LSC
 
Running secured Spark job in Kubernetes compute cluster and integrating with ...
Running secured Spark job in Kubernetes compute cluster and integrating with ...Running secured Spark job in Kubernetes compute cluster and integrating with ...
Running secured Spark job in Kubernetes compute cluster and integrating with ...
 
A New Chapter of Data Processing with CDK
A New Chapter of Data Processing with CDKA New Chapter of Data Processing with CDK
A New Chapter of Data Processing with CDK
 
Enabling real interactive BI on Hadoop
Enabling real interactive BI on HadoopEnabling real interactive BI on Hadoop
Enabling real interactive BI on Hadoop
 
Mondrian update (Pentaho community meetup 2012, Amsterdam)
Mondrian update (Pentaho community meetup 2012, Amsterdam)Mondrian update (Pentaho community meetup 2012, Amsterdam)
Mondrian update (Pentaho community meetup 2012, Amsterdam)
 
Achieving a 50% Reduction in Cross-AZ Network Costs from Kafka (Uday Sagar Si...
Achieving a 50% Reduction in Cross-AZ Network Costs from Kafka (Uday Sagar Si...Achieving a 50% Reduction in Cross-AZ Network Costs from Kafka (Uday Sagar Si...
Achieving a 50% Reduction in Cross-AZ Network Costs from Kafka (Uday Sagar Si...
 
QA Fest 2019. Дмитрий Собко. Testing Big Data solutions fast and furiously
QA Fest 2019. Дмитрий Собко. Testing Big Data solutions fast and furiouslyQA Fest 2019. Дмитрий Собко. Testing Big Data solutions fast and furiously
QA Fest 2019. Дмитрий Собко. Testing Big Data solutions fast and furiously
 
Build Your Kubernetes Operator with the Right Tool!
Build Your Kubernetes Operator with the Right Tool!Build Your Kubernetes Operator with the Right Tool!
Build Your Kubernetes Operator with the Right Tool!
 
Food Processing is Stream Processing (Stefan Freshe, Nordischer Maschinenbau...
Food Processing is Stream Processing (Stefan Freshe,  Nordischer Maschinenbau...Food Processing is Stream Processing (Stefan Freshe,  Nordischer Maschinenbau...
Food Processing is Stream Processing (Stefan Freshe, Nordischer Maschinenbau...
 
An elastic batch-and stream-processing stack with Pravega and Apache Flink
An elastic batch-and stream-processing stack with Pravega and Apache FlinkAn elastic batch-and stream-processing stack with Pravega and Apache Flink
An elastic batch-and stream-processing stack with Pravega and Apache Flink
 
The Future of Apache Ambari
The Future of Apache AmbariThe Future of Apache Ambari
The Future of Apache Ambari
 
Building large scale applications in yarn with apache twill
Building large scale applications in yarn with apache twillBuilding large scale applications in yarn with apache twill
Building large scale applications in yarn with apache twill
 
Ultimate journey towards realtime data platform with 2.5M events per sec
Ultimate journey towards realtime data platform with 2.5M events per secUltimate journey towards realtime data platform with 2.5M events per sec
Ultimate journey towards realtime data platform with 2.5M events per sec
 
How to Build an Apache Kafka® Connector
How to Build an Apache Kafka® ConnectorHow to Build an Apache Kafka® Connector
How to Build an Apache Kafka® Connector
 
Dependency Injection in Apache Spark Applications
Dependency Injection in Apache Spark ApplicationsDependency Injection in Apache Spark Applications
Dependency Injection in Apache Spark Applications
 
Omid: scalable and highly available transaction processing for Apache Phoenix
Omid: scalable and highly available transaction processing for Apache PhoenixOmid: scalable and highly available transaction processing for Apache Phoenix
Omid: scalable and highly available transaction processing for Apache Phoenix
 

Destaque

Roslyn: another introduction
Roslyn: another introductionRoslyn: another introduction
Roslyn: another introductionMiguel Fernández
 
Events & Microservices
Events & MicroservicesEvents & Microservices
Events & MicroservicesYamen Sader
 
Taming Complex Domains with Domain Driven Design
Taming Complex Domains with Domain Driven DesignTaming Complex Domains with Domain Driven Design
Taming Complex Domains with Domain Driven DesignAlberto Brandolini
 
Designing APIs and Microservices Using Domain-Driven Design
Designing APIs and Microservices Using Domain-Driven DesignDesigning APIs and Microservices Using Domain-Driven Design
Designing APIs and Microservices Using Domain-Driven DesignLaunchAny
 
A Practical Guide to Domain Driven Design: Presentation Slides
A Practical Guide to Domain Driven Design: Presentation SlidesA Practical Guide to Domain Driven Design: Presentation Slides
A Practical Guide to Domain Driven Design: Presentation Slidesthinkddd
 
Domain Driven Design using Laravel
Domain Driven Design using LaravelDomain Driven Design using Laravel
Domain Driven Design using Laravelwajrcs
 

Destaque (9)

Roslyn: another introduction
Roslyn: another introductionRoslyn: another introduction
Roslyn: another introduction
 
NuGet vs Maven
NuGet vs MavenNuGet vs Maven
NuGet vs Maven
 
Vertical Slicing
Vertical SlicingVertical Slicing
Vertical Slicing
 
Events & Microservices
Events & MicroservicesEvents & Microservices
Events & Microservices
 
Taming Complex Domains with Domain Driven Design
Taming Complex Domains with Domain Driven DesignTaming Complex Domains with Domain Driven Design
Taming Complex Domains with Domain Driven Design
 
Designing APIs and Microservices Using Domain-Driven Design
Designing APIs and Microservices Using Domain-Driven DesignDesigning APIs and Microservices Using Domain-Driven Design
Designing APIs and Microservices Using Domain-Driven Design
 
A Practical Guide to Domain Driven Design: Presentation Slides
A Practical Guide to Domain Driven Design: Presentation SlidesA Practical Guide to Domain Driven Design: Presentation Slides
A Practical Guide to Domain Driven Design: Presentation Slides
 
Domain Driven Design 101
Domain Driven Design 101Domain Driven Design 101
Domain Driven Design 101
 
Domain Driven Design using Laravel
Domain Driven Design using LaravelDomain Driven Design using Laravel
Domain Driven Design using Laravel
 

Semelhante a Modularity and Domain Driven Design - A killer combination - T De Wolf & S van Den Ende

Spring data presentation
Spring data presentationSpring data presentation
Spring data presentationOleksii Usyk
 
AWS Webcast - Build high-scale applications with Amazon DynamoDB
AWS Webcast - Build high-scale applications with Amazon DynamoDBAWS Webcast - Build high-scale applications with Amazon DynamoDB
AWS Webcast - Build high-scale applications with Amazon DynamoDBAmazon Web Services
 
Enterprise guide to building a Data Mesh
Enterprise guide to building a Data MeshEnterprise guide to building a Data Mesh
Enterprise guide to building a Data MeshSion Smith
 
Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...
Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...
Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...Julian Hyde
 
FiloDB: Reactive, Real-Time, In-Memory Time Series at Scale
FiloDB: Reactive, Real-Time, In-Memory Time Series at ScaleFiloDB: Reactive, Real-Time, In-Memory Time Series at Scale
FiloDB: Reactive, Real-Time, In-Memory Time Series at ScaleEvan Chan
 
The Evolution of a Relational Database Layer over HBase
The Evolution of a Relational Database Layer over HBaseThe Evolution of a Relational Database Layer over HBase
The Evolution of a Relational Database Layer over HBaseDataWorks Summit
 
What's New in .Net 4.5
What's New in .Net 4.5What's New in .Net 4.5
What's New in .Net 4.5Malam Team
 
dotNet Miami - June 21, 2012: Richie Rump: Entity Framework: Code First and M...
dotNet Miami - June 21, 2012: Richie Rump: Entity Framework: Code First and M...dotNet Miami - June 21, 2012: Richie Rump: Entity Framework: Code First and M...
dotNet Miami - June 21, 2012: Richie Rump: Entity Framework: Code First and M...dotNet Miami
 
Developing Kafka Streams Applications with Upgradability in Mind with Neil Bu...
Developing Kafka Streams Applications with Upgradability in Mind with Neil Bu...Developing Kafka Streams Applications with Upgradability in Mind with Neil Bu...
Developing Kafka Streams Applications with Upgradability in Mind with Neil Bu...HostedbyConfluent
 
Tackle Containerization Advisor (TCA) for Legacy Applications
Tackle Containerization Advisor (TCA) for Legacy ApplicationsTackle Containerization Advisor (TCA) for Legacy Applications
Tackle Containerization Advisor (TCA) for Legacy ApplicationsKonveyor Community
 
Deploying your Data Warehouse on AWS
Deploying your Data Warehouse on AWSDeploying your Data Warehouse on AWS
Deploying your Data Warehouse on AWSAmazon Web Services
 
Entity Framework: Code First and Magic Unicorns
Entity Framework: Code First and Magic UnicornsEntity Framework: Code First and Magic Unicorns
Entity Framework: Code First and Magic UnicornsRichie Rump
 
Migrating Very Large Site Collections (SPSDC)
Migrating Very Large Site Collections (SPSDC)Migrating Very Large Site Collections (SPSDC)
Migrating Very Large Site Collections (SPSDC)kiwiboris
 
Software Development: Beyond Training wheels
Software Development: Beyond Training wheelsSoftware Development: Beyond Training wheels
Software Development: Beyond Training wheelsNaveenkumar Muguda
 
Developing real-time data pipelines with Spring and Kafka
Developing real-time data pipelines with Spring and KafkaDeveloping real-time data pipelines with Spring and Kafka
Developing real-time data pipelines with Spring and Kafkamarius_bogoevici
 
Access Data from XPages with the Relational Controls
Access Data from XPages with the Relational ControlsAccess Data from XPages with the Relational Controls
Access Data from XPages with the Relational ControlsTeamstudio
 
Ladies Be Architects - Integration - Multi-Org, Security, JSON, Backup & Restore
Ladies Be Architects - Integration - Multi-Org, Security, JSON, Backup & RestoreLadies Be Architects - Integration - Multi-Org, Security, JSON, Backup & Restore
Ladies Be Architects - Integration - Multi-Org, Security, JSON, Backup & Restoregemziebeth
 
MongoDB .local Bengaluru 2019: Realm: The Secret Sauce for Better Mobile Apps
MongoDB .local Bengaluru 2019: Realm: The Secret Sauce for Better Mobile AppsMongoDB .local Bengaluru 2019: Realm: The Secret Sauce for Better Mobile Apps
MongoDB .local Bengaluru 2019: Realm: The Secret Sauce for Better Mobile AppsMongoDB
 
What is WebDAV - uploaded by Murali Krishna Nookella
What is WebDAV - uploaded by Murali Krishna NookellaWhat is WebDAV - uploaded by Murali Krishna Nookella
What is WebDAV - uploaded by Murali Krishna Nookellamuralikrishnanookella
 

Semelhante a Modularity and Domain Driven Design - A killer combination - T De Wolf & S van Den Ende (20)

Spring data presentation
Spring data presentationSpring data presentation
Spring data presentation
 
AWS Webcast - Build high-scale applications with Amazon DynamoDB
AWS Webcast - Build high-scale applications with Amazon DynamoDBAWS Webcast - Build high-scale applications with Amazon DynamoDB
AWS Webcast - Build high-scale applications with Amazon DynamoDB
 
Enterprise guide to building a Data Mesh
Enterprise guide to building a Data MeshEnterprise guide to building a Data Mesh
Enterprise guide to building a Data Mesh
 
Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...
Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...
Apache Calcite: A Foundational Framework for Optimized Query Processing Over ...
 
FiloDB: Reactive, Real-Time, In-Memory Time Series at Scale
FiloDB: Reactive, Real-Time, In-Memory Time Series at ScaleFiloDB: Reactive, Real-Time, In-Memory Time Series at Scale
FiloDB: Reactive, Real-Time, In-Memory Time Series at Scale
 
The Evolution of a Relational Database Layer over HBase
The Evolution of a Relational Database Layer over HBaseThe Evolution of a Relational Database Layer over HBase
The Evolution of a Relational Database Layer over HBase
 
What's New in .Net 4.5
What's New in .Net 4.5What's New in .Net 4.5
What's New in .Net 4.5
 
dotNet Miami - June 21, 2012: Richie Rump: Entity Framework: Code First and M...
dotNet Miami - June 21, 2012: Richie Rump: Entity Framework: Code First and M...dotNet Miami - June 21, 2012: Richie Rump: Entity Framework: Code First and M...
dotNet Miami - June 21, 2012: Richie Rump: Entity Framework: Code First and M...
 
Metaworks4 intro
Metaworks4 introMetaworks4 intro
Metaworks4 intro
 
Developing Kafka Streams Applications with Upgradability in Mind with Neil Bu...
Developing Kafka Streams Applications with Upgradability in Mind with Neil Bu...Developing Kafka Streams Applications with Upgradability in Mind with Neil Bu...
Developing Kafka Streams Applications with Upgradability in Mind with Neil Bu...
 
Tackle Containerization Advisor (TCA) for Legacy Applications
Tackle Containerization Advisor (TCA) for Legacy ApplicationsTackle Containerization Advisor (TCA) for Legacy Applications
Tackle Containerization Advisor (TCA) for Legacy Applications
 
Deploying your Data Warehouse on AWS
Deploying your Data Warehouse on AWSDeploying your Data Warehouse on AWS
Deploying your Data Warehouse on AWS
 
Entity Framework: Code First and Magic Unicorns
Entity Framework: Code First and Magic UnicornsEntity Framework: Code First and Magic Unicorns
Entity Framework: Code First and Magic Unicorns
 
Migrating Very Large Site Collections (SPSDC)
Migrating Very Large Site Collections (SPSDC)Migrating Very Large Site Collections (SPSDC)
Migrating Very Large Site Collections (SPSDC)
 
Software Development: Beyond Training wheels
Software Development: Beyond Training wheelsSoftware Development: Beyond Training wheels
Software Development: Beyond Training wheels
 
Developing real-time data pipelines with Spring and Kafka
Developing real-time data pipelines with Spring and KafkaDeveloping real-time data pipelines with Spring and Kafka
Developing real-time data pipelines with Spring and Kafka
 
Access Data from XPages with the Relational Controls
Access Data from XPages with the Relational ControlsAccess Data from XPages with the Relational Controls
Access Data from XPages with the Relational Controls
 
Ladies Be Architects - Integration - Multi-Org, Security, JSON, Backup & Restore
Ladies Be Architects - Integration - Multi-Org, Security, JSON, Backup & RestoreLadies Be Architects - Integration - Multi-Org, Security, JSON, Backup & Restore
Ladies Be Architects - Integration - Multi-Org, Security, JSON, Backup & Restore
 
MongoDB .local Bengaluru 2019: Realm: The Secret Sauce for Better Mobile Apps
MongoDB .local Bengaluru 2019: Realm: The Secret Sauce for Better Mobile AppsMongoDB .local Bengaluru 2019: Realm: The Secret Sauce for Better Mobile Apps
MongoDB .local Bengaluru 2019: Realm: The Secret Sauce for Better Mobile Apps
 
What is WebDAV - uploaded by Murali Krishna Nookella
What is WebDAV - uploaded by Murali Krishna NookellaWhat is WebDAV - uploaded by Murali Krishna Nookella
What is WebDAV - uploaded by Murali Krishna Nookella
 

Mais de mfrancis

Eclipse Modeling Framework and plain OSGi the easy way - Mark Hoffman (Data I...
Eclipse Modeling Framework and plain OSGi the easy way - Mark Hoffman (Data I...Eclipse Modeling Framework and plain OSGi the easy way - Mark Hoffman (Data I...
Eclipse Modeling Framework and plain OSGi the easy way - Mark Hoffman (Data I...mfrancis
 
OSGi and Java 9+ - BJ Hargrave (IBM)
OSGi and Java 9+ - BJ Hargrave (IBM)OSGi and Java 9+ - BJ Hargrave (IBM)
OSGi and Java 9+ - BJ Hargrave (IBM)mfrancis
 
Simplify Web UX Coding using OSGi Modularity Magic - Paul Fraser (A2Z Living)
Simplify Web UX Coding using OSGi Modularity Magic - Paul Fraser (A2Z Living)Simplify Web UX Coding using OSGi Modularity Magic - Paul Fraser (A2Z Living)
Simplify Web UX Coding using OSGi Modularity Magic - Paul Fraser (A2Z Living)mfrancis
 
OSGi for the data centre - Connecting OSGi to Kubernetes - Frank Lyaruu
OSGi for the data centre - Connecting OSGi to Kubernetes - Frank LyaruuOSGi for the data centre - Connecting OSGi to Kubernetes - Frank Lyaruu
OSGi for the data centre - Connecting OSGi to Kubernetes - Frank Lyaruumfrancis
 
Remote Management and Monitoring of Distributed OSGi Applications - Tim Verbe...
Remote Management and Monitoring of Distributed OSGi Applications - Tim Verbe...Remote Management and Monitoring of Distributed OSGi Applications - Tim Verbe...
Remote Management and Monitoring of Distributed OSGi Applications - Tim Verbe...mfrancis
 
OSGi with Docker - a powerful way to develop Java systems - Udo Hafermann (So...
OSGi with Docker - a powerful way to develop Java systems - Udo Hafermann (So...OSGi with Docker - a powerful way to develop Java systems - Udo Hafermann (So...
OSGi with Docker - a powerful way to develop Java systems - Udo Hafermann (So...mfrancis
 
A real world use case with OSGi R7 - Jurgen Albert (Data In Motion Consulting...
A real world use case with OSGi R7 - Jurgen Albert (Data In Motion Consulting...A real world use case with OSGi R7 - Jurgen Albert (Data In Motion Consulting...
A real world use case with OSGi R7 - Jurgen Albert (Data In Motion Consulting...mfrancis
 
OSGi Feature Model - Where Art Thou - David Bosschaert (Adobe)
OSGi Feature Model - Where Art Thou - David Bosschaert (Adobe)OSGi Feature Model - Where Art Thou - David Bosschaert (Adobe)
OSGi Feature Model - Where Art Thou - David Bosschaert (Adobe)mfrancis
 
Migrating from PDE to Bndtools in Practice - Amit Kumar Mondal (Deutsche Tele...
Migrating from PDE to Bndtools in Practice - Amit Kumar Mondal (Deutsche Tele...Migrating from PDE to Bndtools in Practice - Amit Kumar Mondal (Deutsche Tele...
Migrating from PDE to Bndtools in Practice - Amit Kumar Mondal (Deutsche Tele...mfrancis
 
OSGi CDI Integration Specification - Ray Augé (Liferay)
OSGi CDI Integration Specification - Ray Augé (Liferay)OSGi CDI Integration Specification - Ray Augé (Liferay)
OSGi CDI Integration Specification - Ray Augé (Liferay)mfrancis
 
How OSGi drives cross-sector energy management - Jörn Tümmler (SMA Solar Tech...
How OSGi drives cross-sector energy management - Jörn Tümmler (SMA Solar Tech...How OSGi drives cross-sector energy management - Jörn Tümmler (SMA Solar Tech...
How OSGi drives cross-sector energy management - Jörn Tümmler (SMA Solar Tech...mfrancis
 
Improved developer productivity thanks to Maven and OSGi - Lukasz Dywicki (Co...
Improved developer productivity thanks to Maven and OSGi - Lukasz Dywicki (Co...Improved developer productivity thanks to Maven and OSGi - Lukasz Dywicki (Co...
Improved developer productivity thanks to Maven and OSGi - Lukasz Dywicki (Co...mfrancis
 
It Was Twenty Years Ago Today - Building an OSGi based Smart Home System - Ch...
It Was Twenty Years Ago Today - Building an OSGi based Smart Home System - Ch...It Was Twenty Years Ago Today - Building an OSGi based Smart Home System - Ch...
It Was Twenty Years Ago Today - Building an OSGi based Smart Home System - Ch...mfrancis
 
Popular patterns revisited on OSGi - Christian Schneider (Adobe)
Popular patterns revisited on OSGi - Christian Schneider (Adobe)Popular patterns revisited on OSGi - Christian Schneider (Adobe)
Popular patterns revisited on OSGi - Christian Schneider (Adobe)mfrancis
 
Integrating SLF4J and the new OSGi LogService 1.4 - BJ Hargrave (IBM)
Integrating SLF4J and the new OSGi LogService 1.4 - BJ Hargrave (IBM)Integrating SLF4J and the new OSGi LogService 1.4 - BJ Hargrave (IBM)
Integrating SLF4J and the new OSGi LogService 1.4 - BJ Hargrave (IBM)mfrancis
 
OSG(a)i: because AI needs a runtime - Tim Verbelen (imec)
OSG(a)i: because AI needs a runtime - Tim Verbelen (imec)OSG(a)i: because AI needs a runtime - Tim Verbelen (imec)
OSG(a)i: because AI needs a runtime - Tim Verbelen (imec)mfrancis
 
Flying to Jupiter with OSGi - Tony Walsh (ESA) & Hristo Indzhov (Telespazio V...
Flying to Jupiter with OSGi - Tony Walsh (ESA) & Hristo Indzhov (Telespazio V...Flying to Jupiter with OSGi - Tony Walsh (ESA) & Hristo Indzhov (Telespazio V...
Flying to Jupiter with OSGi - Tony Walsh (ESA) & Hristo Indzhov (Telespazio V...mfrancis
 
MicroProfile, OSGi was meant for this - Ray Auge (Liferay)
MicroProfile, OSGi was meant for this - Ray Auge (Liferay)MicroProfile, OSGi was meant for this - Ray Auge (Liferay)
MicroProfile, OSGi was meant for this - Ray Auge (Liferay)mfrancis
 
Prototyping IoT systems with a hybrid OSGi & Node-RED platform - Bruce Jackso...
Prototyping IoT systems with a hybrid OSGi & Node-RED platform - Bruce Jackso...Prototyping IoT systems with a hybrid OSGi & Node-RED platform - Bruce Jackso...
Prototyping IoT systems with a hybrid OSGi & Node-RED platform - Bruce Jackso...mfrancis
 
How to connect your OSGi application - Dirk Fauth (Bosch)
How to connect your OSGi application - Dirk Fauth (Bosch)How to connect your OSGi application - Dirk Fauth (Bosch)
How to connect your OSGi application - Dirk Fauth (Bosch)mfrancis
 

Mais de mfrancis (20)

Eclipse Modeling Framework and plain OSGi the easy way - Mark Hoffman (Data I...
Eclipse Modeling Framework and plain OSGi the easy way - Mark Hoffman (Data I...Eclipse Modeling Framework and plain OSGi the easy way - Mark Hoffman (Data I...
Eclipse Modeling Framework and plain OSGi the easy way - Mark Hoffman (Data I...
 
OSGi and Java 9+ - BJ Hargrave (IBM)
OSGi and Java 9+ - BJ Hargrave (IBM)OSGi and Java 9+ - BJ Hargrave (IBM)
OSGi and Java 9+ - BJ Hargrave (IBM)
 
Simplify Web UX Coding using OSGi Modularity Magic - Paul Fraser (A2Z Living)
Simplify Web UX Coding using OSGi Modularity Magic - Paul Fraser (A2Z Living)Simplify Web UX Coding using OSGi Modularity Magic - Paul Fraser (A2Z Living)
Simplify Web UX Coding using OSGi Modularity Magic - Paul Fraser (A2Z Living)
 
OSGi for the data centre - Connecting OSGi to Kubernetes - Frank Lyaruu
OSGi for the data centre - Connecting OSGi to Kubernetes - Frank LyaruuOSGi for the data centre - Connecting OSGi to Kubernetes - Frank Lyaruu
OSGi for the data centre - Connecting OSGi to Kubernetes - Frank Lyaruu
 
Remote Management and Monitoring of Distributed OSGi Applications - Tim Verbe...
Remote Management and Monitoring of Distributed OSGi Applications - Tim Verbe...Remote Management and Monitoring of Distributed OSGi Applications - Tim Verbe...
Remote Management and Monitoring of Distributed OSGi Applications - Tim Verbe...
 
OSGi with Docker - a powerful way to develop Java systems - Udo Hafermann (So...
OSGi with Docker - a powerful way to develop Java systems - Udo Hafermann (So...OSGi with Docker - a powerful way to develop Java systems - Udo Hafermann (So...
OSGi with Docker - a powerful way to develop Java systems - Udo Hafermann (So...
 
A real world use case with OSGi R7 - Jurgen Albert (Data In Motion Consulting...
A real world use case with OSGi R7 - Jurgen Albert (Data In Motion Consulting...A real world use case with OSGi R7 - Jurgen Albert (Data In Motion Consulting...
A real world use case with OSGi R7 - Jurgen Albert (Data In Motion Consulting...
 
OSGi Feature Model - Where Art Thou - David Bosschaert (Adobe)
OSGi Feature Model - Where Art Thou - David Bosschaert (Adobe)OSGi Feature Model - Where Art Thou - David Bosschaert (Adobe)
OSGi Feature Model - Where Art Thou - David Bosschaert (Adobe)
 
Migrating from PDE to Bndtools in Practice - Amit Kumar Mondal (Deutsche Tele...
Migrating from PDE to Bndtools in Practice - Amit Kumar Mondal (Deutsche Tele...Migrating from PDE to Bndtools in Practice - Amit Kumar Mondal (Deutsche Tele...
Migrating from PDE to Bndtools in Practice - Amit Kumar Mondal (Deutsche Tele...
 
OSGi CDI Integration Specification - Ray Augé (Liferay)
OSGi CDI Integration Specification - Ray Augé (Liferay)OSGi CDI Integration Specification - Ray Augé (Liferay)
OSGi CDI Integration Specification - Ray Augé (Liferay)
 
How OSGi drives cross-sector energy management - Jörn Tümmler (SMA Solar Tech...
How OSGi drives cross-sector energy management - Jörn Tümmler (SMA Solar Tech...How OSGi drives cross-sector energy management - Jörn Tümmler (SMA Solar Tech...
How OSGi drives cross-sector energy management - Jörn Tümmler (SMA Solar Tech...
 
Improved developer productivity thanks to Maven and OSGi - Lukasz Dywicki (Co...
Improved developer productivity thanks to Maven and OSGi - Lukasz Dywicki (Co...Improved developer productivity thanks to Maven and OSGi - Lukasz Dywicki (Co...
Improved developer productivity thanks to Maven and OSGi - Lukasz Dywicki (Co...
 
It Was Twenty Years Ago Today - Building an OSGi based Smart Home System - Ch...
It Was Twenty Years Ago Today - Building an OSGi based Smart Home System - Ch...It Was Twenty Years Ago Today - Building an OSGi based Smart Home System - Ch...
It Was Twenty Years Ago Today - Building an OSGi based Smart Home System - Ch...
 
Popular patterns revisited on OSGi - Christian Schneider (Adobe)
Popular patterns revisited on OSGi - Christian Schneider (Adobe)Popular patterns revisited on OSGi - Christian Schneider (Adobe)
Popular patterns revisited on OSGi - Christian Schneider (Adobe)
 
Integrating SLF4J and the new OSGi LogService 1.4 - BJ Hargrave (IBM)
Integrating SLF4J and the new OSGi LogService 1.4 - BJ Hargrave (IBM)Integrating SLF4J and the new OSGi LogService 1.4 - BJ Hargrave (IBM)
Integrating SLF4J and the new OSGi LogService 1.4 - BJ Hargrave (IBM)
 
OSG(a)i: because AI needs a runtime - Tim Verbelen (imec)
OSG(a)i: because AI needs a runtime - Tim Verbelen (imec)OSG(a)i: because AI needs a runtime - Tim Verbelen (imec)
OSG(a)i: because AI needs a runtime - Tim Verbelen (imec)
 
Flying to Jupiter with OSGi - Tony Walsh (ESA) & Hristo Indzhov (Telespazio V...
Flying to Jupiter with OSGi - Tony Walsh (ESA) & Hristo Indzhov (Telespazio V...Flying to Jupiter with OSGi - Tony Walsh (ESA) & Hristo Indzhov (Telespazio V...
Flying to Jupiter with OSGi - Tony Walsh (ESA) & Hristo Indzhov (Telespazio V...
 
MicroProfile, OSGi was meant for this - Ray Auge (Liferay)
MicroProfile, OSGi was meant for this - Ray Auge (Liferay)MicroProfile, OSGi was meant for this - Ray Auge (Liferay)
MicroProfile, OSGi was meant for this - Ray Auge (Liferay)
 
Prototyping IoT systems with a hybrid OSGi & Node-RED platform - Bruce Jackso...
Prototyping IoT systems with a hybrid OSGi & Node-RED platform - Bruce Jackso...Prototyping IoT systems with a hybrid OSGi & Node-RED platform - Bruce Jackso...
Prototyping IoT systems with a hybrid OSGi & Node-RED platform - Bruce Jackso...
 
How to connect your OSGi application - Dirk Fauth (Bosch)
How to connect your OSGi application - Dirk Fauth (Bosch)How to connect your OSGi application - Dirk Fauth (Bosch)
How to connect your OSGi application - Dirk Fauth (Bosch)
 

Último

Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 
Developing An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of BrazilDeveloping An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of BrazilV3cube
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking MenDelhi Call girls
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEarley Information Science
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsTop 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsRoshan Dwivedi
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024The Digital Insurer
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesSinan KOZAK
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking MenDelhi Call girls
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Miguel Araújo
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slidespraypatel2
 

Último (20)

Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
Developing An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of BrazilDeveloping An App To Navigate The Roads of Brazil
Developing An App To Navigate The Roads of Brazil
 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live StreamsTop 5 Benefits OF Using Muvi Live Paywall For Live Streams
Top 5 Benefits OF Using Muvi Live Paywall For Live Streams
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen Frames
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 

Modularity and Domain Driven Design - A killer combination - T De Wolf & S van Den Ende

  • 1. MODULARITY AND DOMAIN DRIVEN DESIGN a killer combination? Tom De Wolf Architect tom.dewolf@aca-it.be @tomdw Stijn Van den Enden CTO stijn.vandenenden@aca-it.be @stieno www.aca-it.be
  • 2. initial development maintenance phase Software Design Customer Satisfaction Separation of Concerns Low coupling High Cohesion B AB A • Change A impacts all modules = costly • Change B requires split of module = costly • Change A only impacts other module if api change • Change B limited to module Encapsulate Source of Change Predictable Cost of Change Constant change Business Driven Aim for 1-on-1 mapping from business changes onto software constructs Source of Change = Business Functional Modularisation
  • 3. Vehicle Option Make Warranty Model Transport Location Domain Driven Design Without modularity BusinessPartner Address Contact consumer supplier transports owner from to
  • 4. Vehicle Option Make Warranty Owner Model Transported Item Transport Transport Supplier Transport Consumer Vehicle Context Transport Context Domain Driven Design Modularity with Bounded Contexts BusinessPartner AddressContact Business Partner Context Location from to
  • 5. transport vehicle MODULAR DATABASE SCHEMA • cross domain database structures not allowed • queries cannot cross domain boundaries NO foreign key business partner UUID MAKE MODEL OWNER_ID djdfjfdkjdk221 Ford C-Max BE1234567 TRANSPORTED_ITEM_ID FROM CONSUMER_ID djdfjfdkjdk221 454 BE1234567 LOCATION_ID ADDRESS 454 Sunstreet 23 foreign key VAT_NUMBER NAME BE1234567 Company A
  • 6. BENEFITS … • Domain modules can migrate independently to next version! • Database schema is internal to the domain bundle, i.e. NOT part of the API! • Persistence and/or database technology can differ between modules in one system!
  • 7. Mmodular database migration cross domain transactions Tx Scross domain search and reporting C H A L L E N G E S
  • 9. M Dev Machine 1 MIGRATION CHALLENGE Dev Machine 2 Continuous Integration Test environment Acceptance environment Production environment Version 1.0.0 Version 1.0.1 Version 1.0.2 Version ? Version ? Version ? environment x Module 1 Module 2 Module 3 Version 1.0.0 Version 3.0.0 Version 2.0.2 Manually track which scripts have run on which environment for which module ?
  • 10. M LIQUIBASE DATABASECHANGELOG table to track executed changesets for each environment In versioned source code XML based DSL for changeSets www.liquibase.org
  • 11. M MODULAR LIQUIBASE transportvehicle business partner deployment 1 deployment 2 deployment 3 Migrate modules separately Migrate @deploy of module migrate to initial version migrate to initial version migrate to initial version no db changes, no migration migrate to version 2 migrate to version 2 migrate to version 3
  • 12. M THE EXTENDER PATTERN bundle A bundle B bundle C bundle D extender bundle Extension Pattern ?! no match /OSGI-INF/liquibase/db.changelog-master.xml osgi-liquibase-extender framework dependency Liquibase change sets domain A change sets domain B change sets domain C • Only extender depends on Liquibase framework • Update of single bundle triggers Liquibase update • New Liquibase process 
 for each matching bundle
  • 14. JTA OR NOT? • No persistence layer — direct jdbc/sql access — 1 datasource
 
 • Multiple datasources • Different types of persistence layers (JPA, NoSQL, …) • JPA persistence layer in each domain bundle • instead of one big persistence unit • even on 1 datasource T 1 transaction spanning multiple modular domains JTA not needed JTA required x
  • 15. MODULAR PERSISTENCE T osgi-datasource XA enabled vehicle-domaintransport-domain javax.transaction.TransactionManager transaction provider e.g. atomikos javax.sql.DataSource persistence context persistence context commit x
  • 17. Scross domain search SEARCH the tale of the evil joins
  • 19. A. Search encapsulated in a separate module leveraging the functionality of other domain modules search- module domainA domainB x x Repository Repository Stop • requires specific implementation for every search • complexity increases with number of modules • inability to leverage power of the datastore SearchAPI
  • 20. domainA B. Search is using a separate query model search- module domainB SearchAPI EventProvider Update Events Update
  • 21.
  • 22. $ curl -XPUT ‘localhost:9200/vehicle/external/1’ -d ‘{ “make”: “BMW”, “VIN”: “30203232012102” }’ index document_type id Index a document
  • 23. $ curl -XPOST ‘localhost:9200/vehicle/external/1/ _update’ -d ‘{ “doc”: {“make”: “Alpina”} }’ Update a document index document_type id
  • 24. $ curl -XPOST localhost:9200/vehicle/_search?pretty -d ‘{"query":{"match":{"make":"BMW"}}}' index Querying an index
  • 25. $ curl -XPOST localhost:9200/vehicle/_search?pretty -d ‘{"query":{"match":{"mark":"BMW"}}}' { "took" : 3, "timed_out" : false, "_shards" : { "total" : 5, "successful" : 5, "failed" : 0 }, "hits" : { "total" : 2, "max_score" : 0.30685282, "hits" : [ { "_index" : "vehicle", "_type" : "external", "_id" : "1", "_score" : 0.30685282, "_source" : {"make": "BMW", "VIN": "30203232012102"} }, { "_index" : "vehicle", "_type" : "external", "_id" : "2", "_score" : 0.30685282, "_source" : {"makes": "BMW", "VIN": "30203232012112"} } ]}} ! Querying an index
  • 26. • Distributed (shards/replicas) • Advanced Quering (lucene/geo/ aggregation) • Facets (terms/ranges/histogram) • API (HTTP/Java/JavaTesting) • … {
  • 28. 1Populate the index package be.vabfs.search.api; ! public interface SearchIndexService { void update(Object entityToUpdate); void delete(Object entityToRemove); ! void populate(); ! void clear(); ! } search SearchIndexService domainB Entity EntityListener @PrePersist @PostUpdate @PostRemove
  • 29. 1Populate the index search SearchIndexService update(entity) Synchronise onTransaction Track updated entities A Map entities to searchData B Bulk update search index C
  • 30. 1Populate the index Map entities to searchData B package be.vabfs.search.api.data; ! import java.util.List; ! public interface SearchDataProvider { ! Class<? extends Object> getEntityClass(); List<SearchData> index(Object entity); ! } domainB Entity SearchData
  • 31. 1Populate the index Map entities to searchData B SearchDataProvider domainB Entity SearchData
  • 32. 1Populate the index A search SearchIndexService update(entity) Synchronise onTransaction Track updated entities Bulk update search index C Map entities to searchData B SearchDataProvider domainB A
  • 35. 2Enhancing Search search SearchService package be.vabfs.search.api; ! import … ! public interface SearchService { … ! SearchResults query(String query, int start, int rows, String sort, String sortOrder, String documentType); List<String> options(String field, String... documentTypes); List<SearchCriterion> availableCriteria( String... criteriaCategories); }
  • 36. 2Enhancing Search package be.vabfs.search.api.criteria; ! import java.util.List; ! public interface SearchCriteriaProvider { String getProviderCategory(); List<SearchCriterion> getAvailableCriteria(); } package be.vabfs.search.api.criteria; ! public interface SearchCriterion { ! String getName(); String getKey(); String getUnitName(); SearchCriterionType getType(); SearchCriterionQueryType getQueryType(); String getDocumentType(); ! } "vehicle.mileage" "mileage" SearchCriterionType.NUMBER SearchCriterionQueryType.RANGE_NUMBER "SERVICE_ITEM" "km"
  • 38. LESSONS LEARNED @deployment time migration = RISK • have CI build continuously migrate current production data Refactor wrong modularisation requires unwanted migration dependencies • reset/flatten migration change sets to restore modularisation Migration Cross domain search and reporting Effort to integrate search is limited • due to dynamic osgi service model Advanced search functionality is possible
  • 39. WHAT IS NEXT? Multiple module versions active? Multiple schema versions active? • e.g. feature try-out to limited customer base Downgrade to older module version? • Previous schema with new data? Hot deploy while users are firing requests? • Migration still busy = failure Migration Cross domain search and reporting Domain Specific Query Language ! Exploiting elastic search capabilities beyond search, e.g. reporting
  • 40. M Modular migration Liquibase extender @ DeployT Cross domain transactions Distributed JTA transactionsx S Cross domain search Elasticsearch view Functionally not limited by domain module boundaries to answer business questions Non-functionally future-proof platform with impact of change contained in loosely coupled domain modules
  • 41. Tom De Wolf Architect tom.dewolf@aca-it.be @tomdw Stijn Van den Enden CTO stijn.vandenenden@aca-it.be @stieno www.aca-it.be