1. A client application makes a loan quote request to a LoanBroker service, which creates a LoanQuoteRequest message.
2. The message is sent to various services via JMS to retrieve a credit profile, get lender recommendations, and request quotes from banks.
3. The responses from the banks are returned to the LoanBroker, which selects the lowest quote and returns it to the client.
This document describes the implementation of a loan broker application using Mule ESB. It involves components like a loan broker service, credit agency service, lender service, and bank services. The loan broker receives a request, gets the customer's credit profile, selects lenders, sends requests to banks, and returns the best loan quote to the customer. Key aspects of the design in Mule include using JMS as the message bus, transforming messages between formats, and routing messages between components asynchronously.
The document discusses implementing an example loan broker application using Mule ESB. It provides an overview of the key components involved - a Loan Broker service, Credit Agency service, Lender service, Banking Gateway and individual Bank services. It describes the message flow and how each component is implemented as a Mule endpoint, service or router. It discusses how Mule handles message routing, transformation and correlation to orchestrate the end-to-end request and response processing across the different systems and services.
This document provides an overview of implementing a loan broker application using Mule as an enterprise service bus. The application allows customers to request loan quotes from multiple banks and returns the best offer. Key aspects summarized:
1. The loan broker service receives customer requests and sends messages to coordinate getting a credit check and requesting quotes from banks. Messages are routed via a JMS message bus.
2. Gateways handle marshalling requests between the message bus and external services like a credit agency EJB application and bank web services.
3. Banks return quotes by responding to a reply-to address, and responses are aggregated to select the lowest rate before returning to the client.
4. Mule components
This document provides an overview and example of implementing an enterprise service bus (ESB) using Mule. It discusses the key components involved - a LoanBroker service, CreditAgency gateway, Lender gateway, Banking gateway, and Banks. It describes the message flow and components when a customer requests loan quotes. The LoanBroker uses Mule to route the request to the CreditAgency, Lender service, and Banking gateway. Responses from Banks are aggregated and the best quote selected and returned to the customer. The implementation leverages various Mule features like transports, routing, transformations, and components.
1) The document describes a real-world loan broker application that uses Mule to integrate various systems and services. It involves a loan broker service receiving requests and coordinating responses from a credit agency, lender service, and banks.
2) Key components include a loan broker endpoint, credit agency gateway, lender gateway, and banking gateway. Messaging is handled through JMS, with services exposed via transports like HTTP, JMS, EJB, and SOAP.
3) The implementation uses Mule components, transports, and message routing to handle the request flow, transforming data between formats and systems as needed.
Mule is used to implement an ESB that aggregates loan quotes from multiple banks. It uses Mule transports like JMS, HTTP, VM, and SOAP to connect various components. These include a LoanBroker service, CreditAgency, LenderService, and multiple Bank components. Messages are routed between components, transforming data and aggregating responses to return the best loan quote to the client.
1) The document describes a real-world loan broker application that uses Mule to integrate various systems and services. It involves a loan broker service receiving requests and coordinating responses from a credit agency, lender service, and banks.
2) Key components include a loan broker endpoint, credit agency gateway, lender gateway, and banking gateway. The loan broker coordinates the flow, transforming and routing messages between the systems.
3) Mule handles the integration using various transports like JMS, HTTP, VM, and SOAP. Components are defined that handle the message flow and data transformation between the different systems and formats.
The document provides an overview of implementing an enterprise service bus (ESB) using Mule. It discusses Mule and Java Business Integration (JBI), describes a real-world loan broker application, and details the implementation of the loan broker application using Mule. The loan broker application orchestrates requests to a credit agency, lenders, and banks and aggregates the responses to return the best loan quote to the customer. The document outlines the components, transports, event flows, and Mule configurations used to implement the loan broker application.
This document describes the implementation of a loan broker application using Mule ESB. It involves components like a loan broker service, credit agency service, lender service, and bank services. The loan broker receives a request, gets the customer's credit profile, selects lenders, sends requests to banks, and returns the best loan quote to the customer. Key aspects of the design in Mule include using JMS as the message bus, transforming messages between formats, and routing messages between components asynchronously.
The document discusses implementing an example loan broker application using Mule ESB. It provides an overview of the key components involved - a Loan Broker service, Credit Agency service, Lender service, Banking Gateway and individual Bank services. It describes the message flow and how each component is implemented as a Mule endpoint, service or router. It discusses how Mule handles message routing, transformation and correlation to orchestrate the end-to-end request and response processing across the different systems and services.
This document provides an overview of implementing a loan broker application using Mule as an enterprise service bus. The application allows customers to request loan quotes from multiple banks and returns the best offer. Key aspects summarized:
1. The loan broker service receives customer requests and sends messages to coordinate getting a credit check and requesting quotes from banks. Messages are routed via a JMS message bus.
2. Gateways handle marshalling requests between the message bus and external services like a credit agency EJB application and bank web services.
3. Banks return quotes by responding to a reply-to address, and responses are aggregated to select the lowest rate before returning to the client.
4. Mule components
This document provides an overview and example of implementing an enterprise service bus (ESB) using Mule. It discusses the key components involved - a LoanBroker service, CreditAgency gateway, Lender gateway, Banking gateway, and Banks. It describes the message flow and components when a customer requests loan quotes. The LoanBroker uses Mule to route the request to the CreditAgency, Lender service, and Banking gateway. Responses from Banks are aggregated and the best quote selected and returned to the customer. The implementation leverages various Mule features like transports, routing, transformations, and components.
1) The document describes a real-world loan broker application that uses Mule to integrate various systems and services. It involves a loan broker service receiving requests and coordinating responses from a credit agency, lender service, and banks.
2) Key components include a loan broker endpoint, credit agency gateway, lender gateway, and banking gateway. Messaging is handled through JMS, with services exposed via transports like HTTP, JMS, EJB, and SOAP.
3) The implementation uses Mule components, transports, and message routing to handle the request flow, transforming data between formats and systems as needed.
Mule is used to implement an ESB that aggregates loan quotes from multiple banks. It uses Mule transports like JMS, HTTP, VM, and SOAP to connect various components. These include a LoanBroker service, CreditAgency, LenderService, and multiple Bank components. Messages are routed between components, transforming data and aggregating responses to return the best loan quote to the client.
1) The document describes a real-world loan broker application that uses Mule to integrate various systems and services. It involves a loan broker service receiving requests and coordinating responses from a credit agency, lender service, and banks.
2) Key components include a loan broker endpoint, credit agency gateway, lender gateway, and banking gateway. The loan broker coordinates the flow, transforming and routing messages between the systems.
3) Mule handles the integration using various transports like JMS, HTTP, VM, and SOAP. Components are defined that handle the message flow and data transformation between the different systems and formats.
The document provides an overview of implementing an enterprise service bus (ESB) using Mule. It discusses Mule and Java Business Integration (JBI), describes a real-world loan broker application, and details the implementation of the loan broker application using Mule. The loan broker application orchestrates requests to a credit agency, lenders, and banks and aggregates the responses to return the best loan quote to the customer. The document outlines the components, transports, event flows, and Mule configurations used to implement the loan broker application.
Integrating with LinkedIn using Mule ESB LinkedIn ConnectorRupesh Sinha
This document discusses how to integrate with LinkedIn using Mule ESB and the LinkedIn Connector. It provides an overview of LinkedIn and describes configuring a LinkedIn developer app for authentication. It then shows how to configure the LinkedIn Connector in Mule and provides examples of Mule flows for LinkedIn authentication and retrieving a user's profile.
This document discusses implementing an application in Mule ESB that acts as a loan broker. It provides an overview of key aspects of the implementation including:
- The systems and components involved like the loan broker service, credit agency, lenders, and banks.
- The design considerations around transports, message formats, and event flows.
- How the implementation is done using Mule including configuration of components, gateways, routing, and response aggregation.
Web services allow programs to communicate over the web through standard protocols like HTTP and SOAP. They evolved from earlier technologies like RPC and CORBA to address issues of interoperability, firewall traversal, and complexity. Key components of web services include XML for data exchange, SOAP for communication, WSDL for describing services, and UDDI for discovering them. A web service follows a publish, find, bind model where providers publish services to a registry, clients find services, and then bind and invoke them.
Mule is a lightweight Java-based ESB (enterprise service bus) that allows for integration of applications regardless of technology. The document discusses getting started with Mule including understanding concepts, setting up the IDE and studio, configuring components, and deploying. It also outlines key Mule concepts like layers of the architecture, common components used for transformations, filters, routers and cloud connectors.
This document summarizes various database connectors available through Anypoint Platform from MuleSoft. It lists connectors for Oracle Database, MySQL, JDBC, PostgreSQL, DB2 and Cassandra database. The connectors allow applications to connect and perform CRUD operations on databases. They enable integration of databases with applications, systems and services.
The document summarizes the structure of Mule messages, which contain a header and payload. The header includes properties and variables that provide metadata about the message. Properties have inbound and outbound scopes, while variables have flow, session, and record scopes. The document describes how to set, copy, and remove properties and variables using message processors. It also explains how to set and enrich the message payload.
Anypoint Enterprise Security provides features that enforce secure access to information in Mule applications, including a SecureToken Service, Credentials Vault, message encryption and digital signature processors, filtering, and CRC32 processing. These security features help businesses securely provide access to protected resources while preventing breaches. The security suite builds on capabilities in Mule ESB like authentication, authorization, and integration with identity management systems. It also supports technologies like encryption, digital signatures, filtering, CRC checks, and compliance with the FIPS 140-2 security standard.
Mule ESB is a lightweight, open-source integration framework that allows for quick and easy connection of applications to enable data exchange regardless of technology. It uses a service-oriented architecture and can integrate applications using transports like JMS, web services, HTTP, and more. Mule ESB is highly scalable and manages interactions between applications transparently whether they are on the same machine or across the internet. It is vendor-neutral so developers are not locked into a single vendor implementation.
The document discusses various components in Mule ESB including the File, Database, and REST components. The File component allows exchanging files with the file system and can be used as an inbound or outbound endpoint. The Database component connects to JDBC databases and performs SQL operations. The REST component allows Mule to act as a RESTful service consumer or provider. DataWeave is introduced as a data transformation language replacing the DataMapper.
The document discusses Mule Enterprise Service Bus (ESB). Mule ESB is a lightweight Java-based integration platform that allows developers to connect applications together quickly and easily, enabling them to exchange data across various technologies and protocols. It acts as a transit system to carry data between applications within or across organizations. Key capabilities include support for multiple access points and protocols, simplified programming model, and ease of configuration and extensibility.
The document discusses Mule ESB, an open source lightweight Java-based enterprise service bus and integration platform. It provides an overview of key Mule ESB concepts like flows, subflows, private flows, message sources, message processors, connectors, endpoints, and transformers. The document also outlines some advantages of Mule ESB like its lightweight and scalable nature, ability to integrate different applications and technologies, and support for various transport protocols and data formats.
Anypoint MQ is a cloud messaging service that enables asynchronous messaging between applications. It supports pub-sub messaging, large payloads up to 10 MB, persistent storage, disaster recovery, dead letter queues, and integration with Mule applications. Anypoint MQ provides a management console for client management, statistics, and reporting. It also includes operations for message queues, exchanges, and clients.
The document describes implementing a loan broker application using Mule ESB. It involves receiving loan requests from clients over HTTP, enriching the request with credit profile data from a credit agency system, selecting potential lenders using a lender service, requesting loan quotes from bank systems, and returning the best quote to the client. Key aspects covered include the system components, message flow, design considerations using Mule transports and components, and how the application is implemented within Mule including message transformation and routing.
The Mule Healthcare Toolkit allows integration with healthcare systems by providing tools to create, read, and transform HL7 messages within Mule. It supports HL7 versions 2.1 through 2.6 and allows transformation between HL7 ER7, XML, and HAPI message object formats. The toolkit also enables sending and receiving HL7 messages over various protocols like MLLP and HTTP and provides features for HL7 message validation and accessing message contents using Mule Expression Language.
Mule ESB is a lightweight Java-based integration framework that allows for integration between applications regardless of technology. It acts as an enterprise service bus (ESB) to provide messaging and integration capabilities. The document discusses setting up Mule Studio, configuring Mule components, and deploying integrations. It also provides overviews of key Mule concepts like layers of the ESB architecture, common components like transformers and filters, and tasks for deployment.
The document summarizes using Mule, an open-source integration framework, to implement an enterprise service bus (ESB) for a loan broker application. The loan broker application receives customer loan requests, obtains the customer's credit profile from a credit agency, requests loan quotes from multiple banks, aggregates the quotes, and returns the best offer to the customer. The implementation uses Mule components, transports and routing to connect the various services involved, including transforming messages between different data formats and protocols.
This document provides an overview of Mule ESB, including what it is, its architecture and components, configuration and deployment, and how it can be used for enterprise integration projects. Mule ESB is a lightweight integration platform that allows for connecting applications together through various transports while offering features for web services, message routing, transformation and transaction management. It supports loose coupling of services, orchestration of integrations, and encourages best practices like enterprise integration patterns. The document discusses the benefits of Mule ESB such as decoupling business logic, location transparency, protocol conversion, and scalability.
The Mule Healthcare Toolkit allows for easy integration with healthcare systems by providing tools to create, read, and transform HL7 messages within Mule. It supports common HL7 versions and message types, and allows sending and receiving HL7 messages over various protocols like MLLP and HTTP. Key features include HL7 message validation and ability to access and modify message contents using Mule Expression Language.
Mule is an open-source lightweight Java-based enterprise service bus and integration platform that can broker interactions between different systems and applications. It uses a scalable and distributable object broker architecture to handle integrations across legacy systems, in-house applications, and modern protocols. Mule provides tools for design, development, testing, deployment and management of integration applications and flows.
The document discusses how to call stored procedures from a Mule application using Mule's database component. It explains how to create a stored procedure in a database like MS SQL, then call it from a Mule flow by configuring the database connector and invoking the stored procedure using SQL. Testing the application by hitting a URL in the browser confirms that the stored procedure runs successfully from Mule.
The document discusses API layers and Anypoint Platform for APIs. It describes how API layers provide a common interface for interacting with applications and gives examples where API layers are used to connect to legacy systems or publish partner APIs. It then introduces Anypoint Platform for building, managing, and securing APIs using components like the API Gateway, API Manager, API contract manager, and API policy manager. Finally, it provides a link for more information on APIs.
Integrating with LinkedIn using Mule ESB LinkedIn ConnectorRupesh Sinha
This document discusses how to integrate with LinkedIn using Mule ESB and the LinkedIn Connector. It provides an overview of LinkedIn and describes configuring a LinkedIn developer app for authentication. It then shows how to configure the LinkedIn Connector in Mule and provides examples of Mule flows for LinkedIn authentication and retrieving a user's profile.
This document discusses implementing an application in Mule ESB that acts as a loan broker. It provides an overview of key aspects of the implementation including:
- The systems and components involved like the loan broker service, credit agency, lenders, and banks.
- The design considerations around transports, message formats, and event flows.
- How the implementation is done using Mule including configuration of components, gateways, routing, and response aggregation.
Web services allow programs to communicate over the web through standard protocols like HTTP and SOAP. They evolved from earlier technologies like RPC and CORBA to address issues of interoperability, firewall traversal, and complexity. Key components of web services include XML for data exchange, SOAP for communication, WSDL for describing services, and UDDI for discovering them. A web service follows a publish, find, bind model where providers publish services to a registry, clients find services, and then bind and invoke them.
Mule is a lightweight Java-based ESB (enterprise service bus) that allows for integration of applications regardless of technology. The document discusses getting started with Mule including understanding concepts, setting up the IDE and studio, configuring components, and deploying. It also outlines key Mule concepts like layers of the architecture, common components used for transformations, filters, routers and cloud connectors.
This document summarizes various database connectors available through Anypoint Platform from MuleSoft. It lists connectors for Oracle Database, MySQL, JDBC, PostgreSQL, DB2 and Cassandra database. The connectors allow applications to connect and perform CRUD operations on databases. They enable integration of databases with applications, systems and services.
The document summarizes the structure of Mule messages, which contain a header and payload. The header includes properties and variables that provide metadata about the message. Properties have inbound and outbound scopes, while variables have flow, session, and record scopes. The document describes how to set, copy, and remove properties and variables using message processors. It also explains how to set and enrich the message payload.
Anypoint Enterprise Security provides features that enforce secure access to information in Mule applications, including a SecureToken Service, Credentials Vault, message encryption and digital signature processors, filtering, and CRC32 processing. These security features help businesses securely provide access to protected resources while preventing breaches. The security suite builds on capabilities in Mule ESB like authentication, authorization, and integration with identity management systems. It also supports technologies like encryption, digital signatures, filtering, CRC checks, and compliance with the FIPS 140-2 security standard.
Mule ESB is a lightweight, open-source integration framework that allows for quick and easy connection of applications to enable data exchange regardless of technology. It uses a service-oriented architecture and can integrate applications using transports like JMS, web services, HTTP, and more. Mule ESB is highly scalable and manages interactions between applications transparently whether they are on the same machine or across the internet. It is vendor-neutral so developers are not locked into a single vendor implementation.
The document discusses various components in Mule ESB including the File, Database, and REST components. The File component allows exchanging files with the file system and can be used as an inbound or outbound endpoint. The Database component connects to JDBC databases and performs SQL operations. The REST component allows Mule to act as a RESTful service consumer or provider. DataWeave is introduced as a data transformation language replacing the DataMapper.
The document discusses Mule Enterprise Service Bus (ESB). Mule ESB is a lightweight Java-based integration platform that allows developers to connect applications together quickly and easily, enabling them to exchange data across various technologies and protocols. It acts as a transit system to carry data between applications within or across organizations. Key capabilities include support for multiple access points and protocols, simplified programming model, and ease of configuration and extensibility.
The document discusses Mule ESB, an open source lightweight Java-based enterprise service bus and integration platform. It provides an overview of key Mule ESB concepts like flows, subflows, private flows, message sources, message processors, connectors, endpoints, and transformers. The document also outlines some advantages of Mule ESB like its lightweight and scalable nature, ability to integrate different applications and technologies, and support for various transport protocols and data formats.
Anypoint MQ is a cloud messaging service that enables asynchronous messaging between applications. It supports pub-sub messaging, large payloads up to 10 MB, persistent storage, disaster recovery, dead letter queues, and integration with Mule applications. Anypoint MQ provides a management console for client management, statistics, and reporting. It also includes operations for message queues, exchanges, and clients.
The document describes implementing a loan broker application using Mule ESB. It involves receiving loan requests from clients over HTTP, enriching the request with credit profile data from a credit agency system, selecting potential lenders using a lender service, requesting loan quotes from bank systems, and returning the best quote to the client. Key aspects covered include the system components, message flow, design considerations using Mule transports and components, and how the application is implemented within Mule including message transformation and routing.
The Mule Healthcare Toolkit allows integration with healthcare systems by providing tools to create, read, and transform HL7 messages within Mule. It supports HL7 versions 2.1 through 2.6 and allows transformation between HL7 ER7, XML, and HAPI message object formats. The toolkit also enables sending and receiving HL7 messages over various protocols like MLLP and HTTP and provides features for HL7 message validation and accessing message contents using Mule Expression Language.
Mule ESB is a lightweight Java-based integration framework that allows for integration between applications regardless of technology. It acts as an enterprise service bus (ESB) to provide messaging and integration capabilities. The document discusses setting up Mule Studio, configuring Mule components, and deploying integrations. It also provides overviews of key Mule concepts like layers of the ESB architecture, common components like transformers and filters, and tasks for deployment.
The document summarizes using Mule, an open-source integration framework, to implement an enterprise service bus (ESB) for a loan broker application. The loan broker application receives customer loan requests, obtains the customer's credit profile from a credit agency, requests loan quotes from multiple banks, aggregates the quotes, and returns the best offer to the customer. The implementation uses Mule components, transports and routing to connect the various services involved, including transforming messages between different data formats and protocols.
This document provides an overview of Mule ESB, including what it is, its architecture and components, configuration and deployment, and how it can be used for enterprise integration projects. Mule ESB is a lightweight integration platform that allows for connecting applications together through various transports while offering features for web services, message routing, transformation and transaction management. It supports loose coupling of services, orchestration of integrations, and encourages best practices like enterprise integration patterns. The document discusses the benefits of Mule ESB such as decoupling business logic, location transparency, protocol conversion, and scalability.
The Mule Healthcare Toolkit allows for easy integration with healthcare systems by providing tools to create, read, and transform HL7 messages within Mule. It supports common HL7 versions and message types, and allows sending and receiving HL7 messages over various protocols like MLLP and HTTP. Key features include HL7 message validation and ability to access and modify message contents using Mule Expression Language.
Mule is an open-source lightweight Java-based enterprise service bus and integration platform that can broker interactions between different systems and applications. It uses a scalable and distributable object broker architecture to handle integrations across legacy systems, in-house applications, and modern protocols. Mule provides tools for design, development, testing, deployment and management of integration applications and flows.
The document discusses how to call stored procedures from a Mule application using Mule's database component. It explains how to create a stored procedure in a database like MS SQL, then call it from a Mule flow by configuring the database connector and invoking the stored procedure using SQL. Testing the application by hitting a URL in the browser confirms that the stored procedure runs successfully from Mule.
The document discusses API layers and Anypoint Platform for APIs. It describes how API layers provide a common interface for interacting with applications and gives examples where API layers are used to connect to legacy systems or publish partner APIs. It then introduces Anypoint Platform for building, managing, and securing APIs using components like the API Gateway, API Manager, API contract manager, and API policy manager. Finally, it provides a link for more information on APIs.
Mule is an open-source ESB that uses a staged event-driven architecture. It decomposes applications into stages connected by queues to improve performance. Mule also leverages Java NIO for efficient I/O operations using buffers, character encoding, regular expressions, and non-blocking channels. A Mule flow contains various components like endpoints, routers, transformers to receive, process and dispatch messages. Exception strategies define how errors are handled.
Mule is the runtime engine of Anypoint Platform that combines data and application integration across legacy systems, SaaS applications, and APIs. It can deploy anywhere as an on-premises integration engine, hybrid iPaaS, or API gateway. Mule integrates events in real-time using its staged-event driven architecture and can also move millions of records between applications or data sources in batch. It provides universal connectivity through pre-built connectors or building custom connectors.
This tutorial explains how to use the Dropbox connector in Mulesoft to authorize a Dropbox account, get account details, create a folder, and logout. The Dropbox connector must be configured with an app key and secret from the Dropbox developer dashboard. A flow is then created to call Dropbox operations like authorize, get account details, create a folder, and unauthorize.
This document discusses using Drools, a business rules management system, with Mule to execute business rules in applications. It provides an example of creating a simple Mule application that uses a .drl file to define rules to determine a warehouse destination based on a randomly generated weight variable. The application is deployed to a Mule standalone server and the rules are executed by the Drools component to set the destination variable according to the rules.
Mule is an open-source enterprise service backbone (ESB) that allows users to move data between different endpoints and applications in a flexible way. It uses a universal message object and XML configuration to define message processing pipelines. These pipelines can include operations like validation, transformation, splitting and merging of XML files. Mule also provides routing functionality and handles exceptions that occur during message processing.
This document describes using DataWeave in Mule ESB to transform XML input into a Java object. It includes an XML input file, Mule flow configuration with a DataWeave transform, and a User Java class. The DataWeave transform defines a 'user' object type and maps the XML elements to fields on the User class, setting the payload to a User instance.
CloudHub is a platform as a service (PaaS) that provides a fully-managed, multi-tenanted, globally available, secure and highly available cloud platform for integration and APIs through Anypoint Platform. With CloudHub, users do not need to maintain hardware or manage cloud infrastructure as it provides automatic software updates and maintenance. CloudHub also offers true multi-tenancy and elastic scalability to increase cloud capacity during high demand periods.
Mule is an open-source enterprise service backbone (ESB) that can move data between different endpoints and applications in a flexible way. It uses a universal message object and XML configuration to define event flows through various routing, transformation, and processing stages. Core concepts include routing with filters and splitters, exception handling strategies, and defining business logic in reusable Java components that operate on standardized message objects.
This document discusses a simple yet amazing trick for transforming XML to XML in Mule. It demonstrates how to take an XML payload and transform it to a new XML structure without writing any complex transformation logic. The full post with more details on this XML transformation technique in Mule can be found at a specific URL.
This document provides an overview of integrating MuleSoft with Dropbox using the Mule Dropbox connector. It describes setting up a Dropbox developer account and creating an app to get API keys. Steps are outlined for installing the Dropbox connector in Anypoint Studio and creating a Mule flow to perform authorization and create a folder in Dropbox. The flow uses the Dropbox connector endpoints to authorize and make API calls to create a folder, with the folder name passed as a query parameter. Running the application triggers the flow, which authorizes with Dropbox and creates the new folder, demonstrating successful integration between Mule and Dropbox.
Scatter-gather in Mule sends a request message concurrently to multiple targets. It then collects the responses from all routes and aggregates them into a single message. To implement scatter-gather, the flow references two sub-flows that run concurrently. At the end, the payloads from both sub-flows are merged by the scatter-gather processor. Testing the flow via a URL will output logs showing that the sub-flows completed concurrently and the payloads were merged.
This short document promotes creating presentations using Haiku Deck, a tool for making slideshows. It encourages the reader to get started making their own Haiku Deck presentation and sharing it on SlideShare. In a single sentence, it pitches presentation creation software.
The CloudHub Console provides a point-and-click interface for managing integration applications running on CloudHub. It allows users to create and deploy new applications, add on-premises servers to run applications, monitor application logs and message statistics, and more. The dashboard homepage displays applications and their status. Users can click on an application to access the management dashboard where additional options are available for monitoring and controlling the selected application.
The document discusses implementing an enterprise service bus (ESB) using Mule to automate the process of a customer obtaining multiple loan quotes. It describes the key components involved - a Loan Broker service, Credit Agency, Lender service, and multiple Banking services. It then provides details on how to design and implement this application using Mule, including defining the message format, configuring the various endpoints and transports, and how messages flow through the system to retrieve a credit profile, get loan quotes from banks, and return the best quote to the customer.
Mule ESB allows authentication of requests via various transport-specific and generic authentication methods. It also controls authorization at the method level on service components. Security is pluggable via the Mule security API, allowing custom implementations. Spring Security 3.0 and Acegi provide authentication and authorization providers like LDAP, JAAS, and CAS. WS-Security enforces integrity, confidentiality and end-to-end security in SOAP messages using XML signatures and security tokens. Mule also supports encryption strategies, PGP security, and Jaas security.
The Mule agent is a plugin extension that exposes the Mule API, allowing external systems to monitor and control Mule ESB servers by calling APIs or having Mule publish data. It has features like controlling applications and services, publishing metrics, and supports REST and WebSockets. It is installed in the plugins directory and configured via a single file.
MuleSoft's Stripe connector allows developers to integrate their MuleSoft applications with the Stripe API to perform payment-related functions like accepting payments, creating invoices and customers. The document provides steps for setting up a Stripe developer account, configuring the Stripe API key, and using the Stripe connector in a Mule flow to create a customer and coupon in Stripe. Sample Mule flows are demonstrated to showcase how to trigger customer and coupon creation via HTTP requests.
The document discusses software integration challenges and how an Enterprise Service Bus (ESB) addresses them. It describes integration patterns like peer-to-peer and client-server architectures. The Service Oriented Architecture (SOA) approach defines discrete services that can be combined to meet business needs. An ESB provides intelligent routing, reliable messaging, and data transformation to connect different applications. Mule is an open source ESB that provides a lightweight platform for easy integration across various technologies using different connectors. Examples demonstrate how Mule can be used to create a loan broker application that integrates systems.
This document provides an overview of implementing a loan broker application using Mule Enterprise Service Bus. The application allows customers to request loan quotes from multiple banks simultaneously and receive the best quote. Key aspects summarized:
1. The loan broker service receives customer requests and sends them to various internal and external services like a credit agency and multiple banks via a JMS message bus.
2. Responses from the services are aggregated by the loan broker which selects the lowest loan quote to return to the customer.
3. The implementation leverages Mule components, transports, transformers and routing to integrate the different systems and process requests asynchronously over JMS, HTTP, EJB and SOAP.
The document discusses developing a loan broker application in Mule. It provides an overview of enterprise service buses (ESBs) and introduces Mule. It then describes a real-world loan broker application that involves multiple systems - a loan broker service, credit agency service, lender service, banking gateways, and banks. It discusses design considerations and event flows for the application. It outlines how the application would be implemented using various Mule components, transports, and features like routing and fault tolerance.
This document provides an overview and implementation details of using Mule to build an enterprise service bus (ESB) for a loan broker application. It describes the key components involved - a loan broker service, credit agency service, lender service, banks, and various gateways. It outlines the message and event flows as the loan broker service receives a request, checks the customer's credit, requests quotes from selected banks, and returns the best quote to the customer. It then discusses using Mule transports, components and transformations to implement this loan broker application and integrate the different systems and services.
The document describes implementing an enterprise service bus (ESB) using Mule to integrate different systems involved in processing a loan quote request. It discusses the components, including a Loan Broker service, Credit Agency service, Lender service, and Banking systems. The event flow is described, starting with a client request to the Loan Broker which triggers credit checks and requests loan quotes from various banks before returning the best offer to the client. Key aspects of the Mule implementation are outlined, including using messages, endpoints, and transformations to integrate the components over various transports.
Mule is used to implement an ESB that aggregates loan quotes from multiple banks. It uses Mule transports like JMS, HTTP, VM, and SOAP to connect various components. These include a LoanBroker service, CreditAgency, LenderService, and multiple Bank components. Messages are routed between components, transforming data and aggregating responses to return the best loan quote to the client.
Subscription based control system to automate management of events for robotsdbpublications
This document proposes a subscription-based control system using websockets to automate event management for robots. The current polling method used in human-machine interfaces restricts automation capabilities. The proposed system allows clients to subscribe to events and receive asynchronous updates from the server, making responses more reliable. It also explores using semantic web technologies to enable coordinated multi-robot activities through ontologies and web services.
This document provides a summary of Purnima Balla's professional experience and qualifications. She has over 7 years of experience as a Senior WebSphere Commerce Developer specializing in designing and developing B2C and B2B e-commerce applications. She has extensive skills in technologies like WebSphere Commerce, Java, J2EE, and has led development teams and client projects for companies like IBM, Accenture, and Virtusa.
Constraint Aware Dynamic Web Service Composition for A Specific Business Requ...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
This document provides an introduction and overview of Windows Communication Foundation (WCF). It discusses what WCF is, how it differs from web services, and some of its key advantages and disadvantages. Development tools for WCF like Visual Studio are also mentioned. The document concludes by outlining some of the fundamental concepts in WCF like endpoints, bindings, contracts, and messages.
Tamer Mohamed has over 10 years of experience as a senior Java developer and technical team leader. He has extensive experience developing web and enterprise applications using technologies like Java, JSP, Servlets, JSF, EJB, Oracle, and Hibernate. Some of the projects he has worked on include a smart payment system for Masary, a SMS gateway for Koryolink, and a payment gateway for Vodafone Egypt. He holds a BSc in Computer Science and has strong skills in Java, databases, web development, and open-source technologies.
In this presentation we will talk about the Microservices approach and how it can be implemented in IoT ecosystem.
The microservice architectural style is an approach to developing a single application as a suite of small services, each running in its own process and communicating with lightweight mechanisms, often an HTTP resource API.
A possible solution to easily control the IoT systems is to create an intelligent platform using a microservices architecture.
The document discusses various Java EE technologies including Enterprise JavaBeans, session beans, message driven beans, servlets, JavaServer Faces, Java Transaction API, REST web services, testing frameworks, and recent architecture trends like microservices and Spring Boot. It provides details on how these technologies work and compares approaches to transaction management and database access in Java EE applications.
Rational Host Access Transformation Services (HATS) transforms traditional text-based interfaces into web, portlet, rich client or mobile device interfaces. It allows extending existing 3270, 5250, and VT applications as standard web services. HATS can easily convert host application screens to user-friendly GUIs. It uses macros to extract and prompt for data, which can then be used to generate Integration Objects and create RESTful or SOAP web services from them. This allows extending the reach of legacy applications to new users and integrating them with other systems.
Enhancement in Web Service ArchitectureIJERA Editor
Web services provide a standard means of interoperating between different software applications, running on a
variety of platforms and/or frameworks. Web services are increasingly used to integrate and build business
application on the internet. Failure of web services is not acceptable in many situations such as online banking,
so fault tolerance is a key challenge of web services. This paper elaborates the concept of web service
architecture and its enhancement. Traditional web service architecture lacks facilities to support fault tolerance.
To better cope with the fundamental issues of the traditional client-server based web service architecture, peer to
peer web service architecture have been introduced. The purpose of this paper is to elaborate the architecture,
construction methods and steps of web services and possible weaknesses in scalability and fault tolerance in
traditional client server architecture and a solution for that, peer to peer web service technology has evolved.
Offline and Online Bank Data Synchronization Systemijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Microservices architecture is an evolution of service-oriented architecture (SOA) principles applied to application design and development. Some key differences include:
- SOA focuses on exposing application functionality as services at the enterprise level, while microservices focus on developing individual applications as a suite of independently deployable services.
- Microservices are typically smaller, lighter weight services focused on a single task, as opposed to monolithic applications. They communicate with lightweight protocols like HTTP.
- Microservices aim to support continuous delivery and deployment, with goals of automation, resilience, and loose coupling between services.
- Individual microservices can be developed and scaled independently. This provides benefits like enabling continuous delivery and deployment.
So in summary,
- Web services allow for two-way communication between a service provider and consumer using XML and SOAP.
- Orbit and Travelocity publish their WSDL files to a UDDI registry, allowing consumers like Kayak.com to access their services.
- A SOAP request contains an envelope with a header and body, while a response contains a header, body, and potential fault message.
This document presents an approach for composing semantic web services using agents in a mobile ad hoc network (MANET). It proposes an ontology-based framework where JADE agents can link web services and agents to enable semantic web applications. The approach involves three phases - service registration, construction of a service graph by matching input/output parameters, and service discovery and composition. It describes using three sample agents (TrainNameService, TrainNumberService, CompositeTrainService) to demonstrate how the composition works. The composed web services are then shown to work properly when accessed over the MANET architecture. The approach aims to automate web service composition by semantically matching parameters.
Key features of Using Service Discovery and Service Proxy:
*Automated registration of microservices
*Find microservices by logical name
*Supports broad multiple APIs including Eureka
Anypoint Data Gateway allows users to easily integrate Salesforce with external legacy data sources like SAP, Oracle, and SQL. It provides a simple point-and-click interface to access and wield Salesforce functionality on external data. Data Gateway supports instant connections to various back-end systems, eliminating the need for separate design environments or extensive user training. It is installed via Salesforce AppExchange and its designer interface allows quick configuration of gateways to external data sources and creation of new objects.
DataWeave can be used in Mule to transform message payloads and other properties. The Transform Message element allows writing DataWeave code to read input from a Mule message and generate output. The editor assists with input/output previews, autocomplete, and automatically generating scaffolding. DataWeave expressions can also be used directly in other Mule components using the dw() function.
This document provides an example of how to use an expression filter in Mule applications. It shows XML configuration with two flows, one that sets a session property and logs it, and another that is called by the first flow via VM connector if the session property value is not equal to "mule". The output logs from both flows are displayed, demonstrating the expression filter functionality.
The document discusses how to use message properties in Mule applications. It provides an example Mule flow that demonstrates setting message properties in different scopes and logging their values. The flow shows setting a property in the session scope and outbound scope in one flow, and accessing the same properties from the inbound scope in a second flow.
Mule ESB allows defining variables to store data. Variables can be flow variables, with scope limited to a flow, or session variables, with scope to the entire application. Lists and maps can be defined as Mule variables similarly to how they are defined in Java. A List variable can be set using #[{values}] syntax and accessed using indexes. A Map variable can be set using #[{key:value}] syntax and accessed using keys. An example flow demonstrates reassigning List index values and logging List and Map variable values.
This document outlines the REST API operations for user groups in MMC, including creating, getting, updating, deleting user groups, and getting permissions. It provides the URL, HTTP method, and sample curl commands for each operation: to create a user group a POST request is used, GET is used to get user groups or a specific one, PUT updates a group, DELETE removes a group, and GET also retrieves all permissions. References for more documentation are included at the end.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms for those who already suffer from conditions like depression and anxiety.
MuleSoft's Stripe connector allows developers to integrate their MuleSoft applications with the Stripe API to perform payment-related functions like accepting payments, creating invoices and customers. The document provides steps for setting up a Stripe developer account, configuring the Stripe API key, and using the Stripe connector in a Mule flow to create a customer and coupon in Stripe. Sample Mule flows are demonstrated to showcase how to trigger customer and coupon creation via HTTP requests.
The document discusses using a foreach scope to process a list of values passed as a query parameter in a URL. It describes how a Java component can convert a comma-separated string of query parameter values into a list, which can then be iterated over using a foreach scope. The flow listens on an HTTP listener, uses the Java component to convert the query parameter to a list, and then processes that list with a foreach scope to output each value individually.
The document discusses Mule Enterprise Service Bus (ESB). Key points:
- Mule ESB is a lightweight Java-based integration platform that allows connecting applications together quickly through various protocols including JMS, HTTP, FTP, and more.
- It acts as a transit system carrying data between applications within or across organizations.
- Mule ESB includes capabilities for data transformations, routing, messaging, and integration with existing systems regardless of technology used.
The document discusses using a foreach scope to process a list of values passed as a query parameter in a URL. It describes how a Java component can convert a comma-separated string of query parameter values into a list, which can then be iterated over using a foreach scope. The flow listens on an HTTP listener, uses the Java component to convert the query parameter to a list, and then processes that list with a foreach scope to output each value individually.
The document discusses using a foreach scope to process a list of values passed as a query parameter in a URL. It describes how a Java component can convert a comma-separated string of query parameter values into a list, which can then be iterated over using a foreach scope. The flow listens on an HTTP listener, uses the Java component to convert the query parameter to a list, and then processes that list with a foreach scope to output each value individually.
The document discusses Mule Enterprise Service Bus (ESB). Key points:
- Mule ESB is a lightweight Java-based integration platform that allows connecting applications together quickly through various protocols including JMS, HTTP, FTP, and more.
- It acts as a transit system carrying data between applications within or across organizations.
- Mule ESB includes capabilities for data transformations, routing, messaging, and integration with existing systems regardless of technology used.
The document discusses using a foreach scope to process a list of values passed as a query parameter in a URL. It describes how a Java component can convert a comma-separated string of query parameter values into a list, which can then be iterated over using a foreach scope. The flow listens on an HTTP listener, uses the Java component to convert the query parameter to a list, and then processes that list with a foreach scope to output the individual values.
The document discusses how to configure the JaasSimpleAuthenticationProvider security provider in Mule to use the Jaas Authentication Service. It describes two configuration methods - passing a Jaas configuration file that defines login modules and credentials, or configuring attributes directly on the provider. The Jaas configuration file example shows a file defining a login module, required flag, and authorized users mapped to passwords.
The document discusses how to configure the JaasSimpleAuthenticationProvider security provider in Mule to use the Jaas Authentication Service. It describes two configuration methods - passing a Jaas configuration file that defines login modules and credentials, or configuring attributes directly on the provider. The Jaas configuration file example shows a file defining a login module, required flag, and authorized users mapped to passwords.
The document discusses Mule's support for SAML, which allows exchange of security information between systems. The current version supports SAML 1.1 with CXF web services. It describes how to configure the SAML module by adding the JAR, configuring a security manager with realms and key providers, and applying security filters to CXF endpoints. It also explains the differences between the Sender Vouches and Holder of Key SAML profiles.
1. The document discusses selecting Mule as an ESB over other open source options like Fuse after evaluating criteria like maintenance, support, licensing, performance, and integration capabilities.
2. Examples of Mule use cases are presented, including embedding Mule in a Java web application, controlling access to endpoints using Spring security, and routing requests to different data sources using Groovy.
3. Best practices discussed include using Mule testing components during development, combining SoapUI tests with mock services, and developing as much as possible using POJOs for easier unit testing. A staged migration approach is also recommended over a single big change.
This document discusses how to validate SOAP requests against an XSD schema file using a schema validation filter in Mule. The schema validation filter refers to XSD files to validate the SOAP request. If invalid, a custom error message is returned. The code example shows adding the schema validation filter to the flow and configuring it with the XSD schema location.
Discover top-tier mobile app development services, offering innovative solutions for iOS and Android. Enhance your business with custom, user-friendly mobile applications.
Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectorsDianaGray10
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host
Northern Engraving | Nameplate Manufacturing Process - 2024Northern Engraving
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
The Microsoft 365 Migration Tutorial For Beginner.pptxoperationspcvita
This presentation will help you understand the power of Microsoft 365. However, we have mentioned every productivity app included in Office 365. Additionally, we have suggested the migration situation related to Office 365 and how we can help you.
You can also read: https://www.systoolsgroup.com/updates/office-365-tenant-to-tenant-migration-step-by-step-complete-guide/
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
"Frontline Battles with DDoS: Best practices and Lessons Learned", Igor IvaniukFwdays
At this talk we will discuss DDoS protection tools and best practices, discuss network architectures and what AWS has to offer. Also, we will look into one of the largest DDoS attacks on Ukrainian infrastructure that happened in February 2022. We'll see, what techniques helped to keep the web resources available for Ukrainians and how AWS improved DDoS protection for all customers based on Ukraine experience
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/how-axelera-ai-uses-digital-compute-in-memory-to-deliver-fast-and-energy-efficient-computer-vision-a-presentation-from-axelera-ai/
Bram Verhoef, Head of Machine Learning at Axelera AI, presents the “How Axelera AI Uses Digital Compute-in-memory to Deliver Fast and Energy-efficient Computer Vision” tutorial at the May 2024 Embedded Vision Summit.
As artificial intelligence inference transitions from cloud environments to edge locations, computer vision applications achieve heightened responsiveness, reliability and privacy. This migration, however, introduces the challenge of operating within the stringent confines of resource constraints typical at the edge, including small form factors, low energy budgets and diminished memory and computational capacities. Axelera AI addresses these challenges through an innovative approach of performing digital computations within memory itself. This technique facilitates the realization of high-performance, energy-efficient and cost-effective computer vision capabilities at the thin and thick edge, extending the frontier of what is achievable with current technologies.
In this presentation, Verhoef unveils his company’s pioneering chip technology and demonstrates its capacity to deliver exceptional frames-per-second performance across a range of standard computer vision networks typical of applications in security, surveillance and the industrial sector. This shows that advanced computer vision can be accessible and efficient, even at the very edge of our technological ecosystem.
AppSec PNW: Android and iOS Application Security with MobSFAjin Abraham
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Mule execution
1.
2. • Overview of ESB
• Introduction to Mule
• Mule and JBI
• Real-world Application
Application Overview
Systems Involved
Design Considerations
Event Flows
• Implementation with Mule
Components
Transports
Returning the Loan Quote
Fault Tolerance
Scaling
• Summary
3. What is it?
Enterprise Service Bus is an evolving architecture technique to integrate
incompatible business applications over a common messaging bus.
Why do we need it?
Many of the applications we write are in fact integration projects. Only
the most simple applications do not need to interact with other
applications.
Where does SOA fit in?
ESB is one architecture style that abides by the rules of a Service
Orientated Architecture.
What is JBI?
Java Business Integration (JSR:208) is an emerging standard that defines
common interfaces for components and message exchanges for
application integration.
Does this all sound familiar?
There is nothing new about integration, we've been doing it for years.
So why the hype?
5. • Service container and messaging platform
• Supports a variety of topologies including ESB
• Highly Scalable; uses SEDA event model
• Lightweight and embeddable
• Transactional; Local and Distributed
• Fault tolerance; Exception management
• Secure; authentication/authorization (Using
Spring/Acegi)
• Powerful event routing capabilities (based on EIP book)
• Support for over 20 messaging protocols/transports
• End-to-End Data Transformation
• Management and Monitoring using JMX
• BPEL Support
• Deployment: JAR, WAR, RAR, EAR.
7. Is Mule a JBI container?
There is a separate project called Mule JBI that is a JBI implementation
that reuses the Mule service stack.
Does Mule work with JBI?
You can use Mule transports, components and transformers inside any
JBI container. Mule provides a couple of components that allows JBI
components to subscribe and publish events to and from Mule.
Do Mule and JBI compete?
JBI solves a subset of messaging problems. Mule addresses the basic
need to move any kind of data (not just XML) between services in an
organization
Which is best for me?
Mule of course!
The reason Mule integrates with other JBI engines and provides it own
JBI container is that one integration solution will never satisfy all
integration needs.
Mule levels the playing field allowing you to pick and choose which
technologies to integrate with.
8. JBI
Described in terms of Service Engines (SEs) which are akin to
components that execute business logic.
Binding Components (BCs) implement protocols to provide
connectivity to SEs.
JBI uses a Message Exchange to manage interactions between
components.
Targeted a specifically at integration. Normalized Message
Mule
Components are POJOs, EJBs, Spring Beans, Remote objects.
The component never needs to call Mule APIs making them totally
portable.
Flexible endpoint model where a component may have zero or more
inbound and outbound endpoints.
Message routing is done via routers that are associated with the
component.
Mule is a ubiquitous messaging platform.
A distributed container for wiring components.
10. Customer calls different banks to find the best deal.
Each bank asks customer for his or her social security number, the
amount of the loan and the desired term.
Each bank then investigates the customer's credit background, usually
by contacting a credit agency, before it finally sends the customer a
quote.
Once the customer has received quotes from all banks, he or she can
then select the best offer, i.e. the lowest rate. [1]
11. This process can be automated to allow customers to obtain the
best quote on-line from a far broader range of banks, in much less
time than if he or she were to obtain all the quotes one by one.
Upon receiving customer request, Loan Broker:
obtains the credit information for that customer from the credit agency
requests quotes for the customer from banks listed with the Lender
Service
sends aggregate compilation of quotes to the customer for selection.
[2]
12. Loan Broker Service Receives LoanRequests (customer, SS
number, loan amount, duration) and is
responsible for aggregating LoanQuotes
into response for the request.
Credit Agency Service An external service provider that provides
crediting checking on customers to ensure
the loan amount requested is feesible.
Credit Agency Gateway Marshals a request between the message
bus and the Credit Agency Application.
Lender Service Based on the customer's credit scoring,
loan amount and duration, the lender
service will select banks from which to
request a LoanQuote.
Lender Gateway Marshals a request from the message bus
to the Lender Application.
Banking Gateway Dispatches LoanRequests to one or more
banks.
13. LoanBroker (Http/Rest)
Receives Requests over Http from a client application, such as a web browser.
Credit Agency (EJB)
Is an EJB application that is managed by the Loan Broker company. It exposes
an EJB called creditAgency with a method getCreditProfile.
Lender Application (VM)
Is a local component, a Pojo that will determine which lenders should be used.
Banks (SOAP)
For simplicity of this example all banks expose the same WS interface, though
it's quite feasible to configure Mule to invoke different interfaces for different
banks.
Gateways (JMS)
Gateways marshal the requests from the message bus to external applications
and services.
14. Constraints
Application needs to support request/response processing
model.
Will get a high volume of requests.
Synchronous processing will not give us enough throughput.
Transports
Using a JMS message bus
Need to invoke services over JMS, Http/Rest, VM, and SOAP.
Need to invoke services in external application containers
(EJB).
Expose components as Web services (Banks).
Message
The message on the bus is referred to as a LoanQuoteRequest.
In this example this is a Java bean but in real scenarios an XML
15.
16. 1. Client application makes a request sending the LoanBroker a
CustomerQuoteRequest Message.
2. LoanBroker creates a LoanQuoteRequest Message.
3. Mule sends the message to the Credit Agency Gateway via JMS
4. The Gateway marshals the request and invokes the CreditAgency EJB.
The component used in the RelectionMessageBuilder which automatically
attaches the CreditProfile to the LoanQuoteRequest message.
5. Mule sends the Message to the Lender Gateway via JMS
6. The Gateway uses the VM transport to invoke the Lender Application.
7. Mule sends the Message to the Banking Gateway via JMS
8. The Banking Gateway in this example invokes the Banks using SOAP.
9. Each of the Banks attaches a quote to the request and sends it back to the
LoanBroker via the ReplyTo address provided by the Banking Gateway.
10. The ResponseRouter on the Loan Broker Service receives the responses on
the ReplyTo address. It selects the lowest quote received for the request
and returns it to the client.
19. Lets start by defining the LoanQuoteRequest Message. In this example the
Message is a Java bean and is the common message format on the bus.
Normally this would be XML, but Mule allows us to pass any data format
around.
public class LoanQuoteRequest implements Serializable
{
/** The request contains Customer info and loan amount and duration*/
private CustomerQuoteRequest customerRequest;
/** credit profile for the customer */
private CreditProfile creditProfile;
/** A list of lenders for this request */
private Bank[] lenders;
/** A loan quote from a bank */
private LoanQuote loanQuote;
.......
}
20. The whole chain of events is initiated with a client request. This is
done over Http using Mule's REST support. It is described in the
Endpoint address –
jetty:rest://localhost:8080/loanbroker
Here we're saying -
Embed a Jetty Servlet Engine
Use the Rest servlet for receiving requests
Listen on localhost:8080
Bind the Rest servlet to the context /loanbroker
The request from the client would look like –
http://localhost:8080/loanbroker/?
name=Ross+Mason&ssn=1234&
loanAmount=10000&loanDuration=24
21. The Loan Broker endpoint receives the request as a set of Http parameters,
but we need to transform this into a CustomerQuoteRequest object before
the Loan Broker component receives it.
We do this by configuring a custom transformer on the endpoint.
public Object transform(Object src, UMOEventContext context)
throws TransformerException {
String name = context.getStringProperty("name");
int ssn = context.getIntProperty("ssn");
double amount = context.getDoubleProperty("loanAmount");
double duration = context.getDoubleProperty("loanDuration");
Customer customer = new Customer(name, ssn);
CustomerQuoteRequest request =
new CustomerQuoteRequest(customer, amount, duration);
return request;
}
22. The Loanbroker service actually doesn't need to do anything but trigger the
LoanQuoteRequest on the bus. Mule handles all routing transformation and passing
the quote back to the callee.
The transformer configured on the REST inbound endpoint for the LoanBroker
converts the REST parameters into a CustomerQuoteRequest object.
public class LoanBroker
{
public LoanQuoteRequest requestLoanQuote(
CustomerQuoteRequest request) throws Exception
{
LoanQuoteRequest bqr = new LoanQuoteRequest();
bqr.setCustomerRequest(request);
return bqr;
}
}
23. All the detail is in the Loan Broker configuration.
<mule-descriptor name="LoanBroker"
implementation="org.mule.samples.loanbroker.esb.LoanBroker">
<inbound-router>
<endpoint address="jetty:rest://localhost:8080/loanbroker"/>
</inbound-router>
<outbound-router>
<router className="org.mule.routing.outbound.OutboundPassThroughRouter">
<endpoint address="jms://esb.credit.agency"/>
</router>
</outbound-router>
<response-router timeout="10000">
<endpoint address="jms://esb.loan.quotes"/>
<router className="
org.mule.samples.loanbroker.esb.routers.BankQuotesResponseAggregator"/>
</response-router>
</mule-descriptor>
24. The Credit Agency code is even easier! We use a
standard Mule Component called a
ReflectionMessageBuilder which builds a message
based on a set of results from endpoint invocations.
It will use reflection to determine how to set the result
of the last endpoint invocation as a property on the
master message.
There are other MessageBuilder components such as
the ScriptMessageBuilder component which is a JSR-
223 (Scripting) component that allows you to
manipulate the payload after each request using
Groovy, JavaScript, Rhino or any other supported
26. We invoke the CreditAgency application using an EJB endpoint –
ejb://localhost:1099/local/CreditAgency?method=getCreditProfile
This endpoint tells Mule to –
Look up an EJB object at localhost:1099
Use the JNDI name local/CreditAgency
Invoke the method getCreditProfile on the EJB object
Notice also the transformers and responseTransformers attibutes on the
endpoint. These tell Mule how to marshal for the Application.
LoanQuoteRequestToCreditProfileArgs – Extracts the method arguments
from the request as an array used to invoke getCreditProfile.
CreditProfileXmlToCreditProfile – Parses the response Xml and creates a
CreditProfile object that will be set on the LoanQuoteRequest.
27. Lender Service
The Lender Agency is a Mule component, that receives events
directly using the VM transport.
Leander Gateway
The Lender Gateway marshals requests from the bus to the
lender service.
29. The Banking Gateway is responsible for distributing requests to a list of lenders.
The ReciptientList router configured on this gateway is responsible for extracting the
endpoints from the message and invoking them. The RecipientList is a type of
Itinerary-based router that extracts its itinerary as a static list from the event.
<mule-descriptor name="BankingGateway"
implementation="org.mule.components.simple.BridgeComponent">
<inbound-router>
<endpoint address="jms://esb.banks"/>
</inbound-router>
<outbound-router>
<router className="org.mule.routing.outbound.StaticRecipientList">
<reply-to address="jms://esb.loan.quotes"/>
</router>
</outbound-router>
</mule-descriptor>
30. The banks in this example are just simple beans that
return a fixed interest rate and are exposed as SOAP
services.
<mule-descriptor name="Bank1"
inboundEndpoint="axis:http://localhost:10001/services"
implementation="org.mule.samples.loanbroker.Bank">
</mule-descriptor>
• Note to expose a component as an Axis service all you
need to do is add an Axis endpoint!
31. Once a back has a quote it passes it to Mule which will send the
Quote on the reply-to endpoint specified by the Banking Gateway.
Looking back at the LoanBroker configuration, there is a response-
router configured as -
<response-router timeout="10000">
<endpoint address="jms://esb.loan.quotes"/>
<router className="org.mule.samples.loanbroker.esb.routers.
BankQuotesResponseAggregator"/>
</response-router>
• The BankQuoteResponseAggregator is responsible for picking the
lowest quote. But before that happens Mule needs to make sure all
responses are received for the request.
• This is done using message correlation managed by Mule.
32. When a event is dispatched from the Banking Gateway a
correlationId and correlationGroupSize is attached to the SOAP
message. This is a function of the Recipient List router. It attaches
the following information -
CorrelationId – and Id that associates all the dispatched events to the
same group
CorrelationGroupSize – how many events are in the group.
CorrelationSequence – the order in which the events were dispatched.
The Response Router reads these correlation headers when events
are received and correlates the events.
When the event group correlation is complete the response-router
invokes itself where developers can plug in custom logic.
33. The BankQuoteResponseAggregator implements a single method
that works out the lowest quote before passing it back to Mule to
route the response back to the client.
protected UMOMessage aggregateEvents(EventGroup events) throws RoutingException {
. . . .
List list = events.getEvents();
for (Iterator iterator = list.iterator(); iterator.hasNext();) {
event = (UMOEvent) iterator.next();
quote = (LoanQuote)event.getTransformedMessage();
logger.info("Processing quote: " + quote);
if (lowestQuote == null) {
lowestQuote = quote;
} else if (quote.getInterestRate() < lowestQuote.getInterestRate()) {
lowestQuote = quote;
}
}
return new MuleMessage(lowestQuote, event.getProperties());
}
34. Most Mule transports can be configured using
just the endpoint address. i.e.
tcp://localhost:45454 contains all the
information necessary to make a TCP
connection.
However for JMS and EJB we need to define
configuration properties for each such as Jndi
information.
This is done by configuring connectors in our
MuleXml.
36. Exception Strategies
Can be defined on components and connectors
Can be defined globally of for each connector or component
Can handle different exception types differently.
Exception hierarchy provides all available information
Event payloads can be re-routed on exception
Connection Strategies
Control how connectors connect to underlying resources
Allow for flexible retry policies
Notifications of failed connections
Consistent endpoint state maintained
Can alter routing paths based on failed connections
37. SEDA Model
Mule is SEDA-based, which is an architecture designed for high
concurrency and throughput.
JMS Clustering
Currently Mule can use JMS clustering to distribute events to a cluster of
Mule Nodes.
Application Server Clustering
Mule can be embedded inside a JCA container and allow the App server
to manage its resources and cluster instances.
New Clustering Support
The next release of Mule will provide clustering and distribution using
JGroups/JBossCache.
Load Balancing using Mule
You can use a Mule instance to provide load-balancing over any
transport.
38. An ESB integrating a client application and 3 back
office systems.
Combined a number of transports including
HTTP, JMS, EJB and Web Services.
Easy to add in Exception handling, transactions,
etc. All done through configuration.
All event routing, management, transformation is
handled by Mule.
Very little code to write. Just domain-specific
logic.
A fully functional ESB in about an hour!
39. Project was founded in 2003.
It was started after experiences with a large Financial ESB
project.
There are now 10 developers who help support it and add
new features.
Has an active user community.
Is being used in companies such as HP, Sony, Deutche
Bank and CitiBank.
SymphonySoft has been started by Mule developers to
help support and provide professional services to these
projects.
For more information go to - http://mule.codehaus.org.
40. EIP Book (Loan Broker Example) [1][2]
http://www.eaipatterns.com/ComposedMessagingExample.html
http://www.eaipatterns.com/index.html
Introduction to ESBs – Rick Robinson
http://www-106.ibm.com/developerworks/xml/library/ws-
esbscen/
ESB Learning Guide
http://searchwebservices.techtarget.com/general/1,295582,sid26
_gci1085711,00.html
Introduction to SEDA – Matt Welsh
http://www.eecs.harvard.edu/~mdw/papers/mdw-
phdthesis.pdf
Mule User Guide
http://mule.codehaus.org/User+Guide
41. To get this Loan Broker ESB code and these
slides go to -
http://mule.codehaus.org/LoanBroker
There are other examples too -
http://mule.codehaus.org/Examples