Mule is an open-source enterprise service bus (ESB) that allows for flexible movement of data between different endpoints and systems. It uses a staged event-driven architecture and non-blocking Java I/O to provide scalability. Core Mule concepts include universal message objects, endpoints, transports, connectors, routers, filters and transformers that allow data to be routed and transformed declaratively between systems and applications. Mule provides capabilities for XML validation, transformation and routing through its built-in components.
This document provides an overview of Mule Web Services. Mule can be used to build and integrate web services. It supports various web service standards like SOAP, WSDL, WS-Addressing. The document demonstrates how to create a bookstore web service using JAX-WS annotations, generate a client, and configure Mule to expose the service and route messages to and from it. It also shows how to transform CSV files to web service requests and send email messages after orders are placed by routing through Mule.
This document provides an overview of Mule, an open-source enterprise service bus (ESB). It discusses key Mule concepts like the universal message object (UMO), endpoints, transports, connectors, routers, filters, transformers, and the Mule event flow. It provides examples of using Mule with file endpoints to move files between directories and validate XML files against a schema. It also covers exception handling in Mule and generating error messages when validation fails.
WSDL is an XML language used to describe web services, defining operations provided by the service, data formats, and location. It describes what a service does via operations, how it is accessed via protocols and data formats, and where it is located via URLs. A WSDL document defines types, messages, operations, bindings and services. Translators can generate code from WSDL or derive WSDL from existing code.
Mule Transformers can alter message properties, variables, or payloads to prepare them for further processing. Standard transformers are provided to handle common data conversion scenarios, such as XML-to-Object. If no single transformer achieves the needed output, multiple transformers can be used sequentially. Transformer categories include those for Java Objects, Content, SAP, Scripting, Properties/Variables/Attachments. The DataWeave transformer provides powerful data querying and transformation capabilities.
The document provides an overview of Java Messaging Services (JMS) in MuleSoft Mule ESB 3.6. It describes key JMS concepts like the JMS messaging model with queues and topics, backchannels, message filtering using selectors, transformers, and provides an example ActiveMQ configuration with inbound and outbound endpoints.
The document discusses the open-source enterprise service bus Mule, including what Mule is, its core concepts like the universal message object and endpoints, and how Mule uses technologies like staged event-driven architecture and non-blocking I/O to move data between different systems and formats in a flexible way. It also provides examples of using Mule to move XML files between directories and handling exceptions.
This document provides an introduction to Mule, an open-source enterprise service backbone. It describes some of Mule's core concepts including its use of staged event-driven architecture (SEDA) and Java NIO for efficient I/O operations. Key components of Mule discussed include universal message objects (UMO), endpoints, transports, connectors, routers, filters and transformers. The document emphasizes Mule's declarative approach to specify what operations to perform rather than how to perform them.
This document provides an overview of Mule Web Services. Mule can be used to build and integrate web services. It supports various web service standards like SOAP, WSDL, WS-Addressing. The document demonstrates how to create a bookstore web service using JAX-WS annotations, generate a client, and configure Mule to expose the service and route messages to and from it. It also shows how to transform CSV files to web service requests and send email messages after orders are placed by routing through Mule.
This document provides an overview of Mule, an open-source enterprise service bus (ESB). It discusses key Mule concepts like the universal message object (UMO), endpoints, transports, connectors, routers, filters, transformers, and the Mule event flow. It provides examples of using Mule with file endpoints to move files between directories and validate XML files against a schema. It also covers exception handling in Mule and generating error messages when validation fails.
WSDL is an XML language used to describe web services, defining operations provided by the service, data formats, and location. It describes what a service does via operations, how it is accessed via protocols and data formats, and where it is located via URLs. A WSDL document defines types, messages, operations, bindings and services. Translators can generate code from WSDL or derive WSDL from existing code.
Mule Transformers can alter message properties, variables, or payloads to prepare them for further processing. Standard transformers are provided to handle common data conversion scenarios, such as XML-to-Object. If no single transformer achieves the needed output, multiple transformers can be used sequentially. Transformer categories include those for Java Objects, Content, SAP, Scripting, Properties/Variables/Attachments. The DataWeave transformer provides powerful data querying and transformation capabilities.
The document provides an overview of Java Messaging Services (JMS) in MuleSoft Mule ESB 3.6. It describes key JMS concepts like the JMS messaging model with queues and topics, backchannels, message filtering using selectors, transformers, and provides an example ActiveMQ configuration with inbound and outbound endpoints.
The document discusses the open-source enterprise service bus Mule, including what Mule is, its core concepts like the universal message object and endpoints, and how Mule uses technologies like staged event-driven architecture and non-blocking I/O to move data between different systems and formats in a flexible way. It also provides examples of using Mule to move XML files between directories and handling exceptions.
This document provides an introduction to Mule, an open-source enterprise service backbone. It describes some of Mule's core concepts including its use of staged event-driven architecture (SEDA) and Java NIO for efficient I/O operations. Key components of Mule discussed include universal message objects (UMO), endpoints, transports, connectors, routers, filters and transformers. The document emphasizes Mule's declarative approach to specify what operations to perform rather than how to perform them.
Anypoint MQ allows applications to communicate by publishing messages to queues. This document describes how to create queues and exchanges, send messages to a queue, and retrieve messages from a queue using Anypoint Platform. Key steps include logging into Anypoint Platform, clicking MQ, clicking Destinations, clicking the blue plus circle to create a new queue or exchange, specifying configuration details, and then sending or receiving messages. Organization administrators can also view Anypoint MQ usage statistics.
This document provides an introduction and overview of Mule, an open-source enterprise service bus (ESB). It discusses what Mule is, how it uses advanced technologies like staged event-driven architecture (SEDA) and Java NIO. The core concepts of Mule like the universal message object, endpoints, transports, connectors, routers, filters and transformers are explained. Examples are given of using Mule for file processing and XML pipelines. Exception handling in Mule is also covered.
Mule can be used to build and integrate web services. It provides the CXF connector for connecting to and building web services that are compliant with JAX-WS standards. A bookstore web service was built to demonstrate adding and getting books. Mule was configured with a CXF endpoint to expose the web service and a file endpoint to read a CSV file and publish the books to the web service using a generated CXF client. An email integration was also demonstrated to send order confirmations via SMTP using transformers.
The document discusses Mule TCP transport which allows sending and receiving messages over TCP connections. TCP is a layer above IP that is used to implement reliable protocols like HTTP and FTP. The Mule TCP transport can be used directly if a custom protocol is required that is not supported by higher level protocols. The document then describes the configuration options on the general, advanced, reconnection, transformers, notes and metadata tabs when configuring a Mule TCP transport component.
RabbitMQ is an open source message broker software written in Erlang. It uses exchanges to route messages from producers to queues based on routing keys or bindings. There are four main exchange types - direct, fanout, topic, and headers. Mule can connect to RabbitMQ using the AMQP connector to send and receive messages. For example, one flow can send a message to a queue using a direct exchange, while another flow receives messages from the same queue using the direct exchange.
The document introduces Enterprise Service Buses (ESBs) and the Mule ESB. It defines ESBs as a way to integrate existing systems, leverage standards, and share services across an enterprise. The document then discusses the Mule architecture in particular, including its use of connectors, transformers, routers and programming model. It provides examples of how Mule implements features like routing, message transformation and orchestration that are common to ESBs.
This document discusses EAI (Enterprise Application Integration) patterns using Spring Integration. It provides an overview of messaging, pipes and filters, and common EAI patterns. It then demonstrates how Spring Integration implements these patterns through its API, with an emphasis on messaging channels. Examples are given for sending and receiving JMS, AMQP, HTTP, and email messages. Common patterns like filtering, routing, splitting, and aggregating messages are also explained.
The Mule Message Chunk Aggregator can be used to aggregate messages that are split into parts by a message splitter. It accepts incoming message parts and uses message attributes to correlate the parts into complete messages that are then sent to downstream flows. The aggregator can be configured with options like a timeout, message ID and correlation ID expressions to map attributes, and a store prefix for object stores. Additional tabs allow adding business events tracking and notes or metadata.
Mule ESB is an open source integration platform that allows users to connect applications together and easily integrate existing systems regardless of technology. It provides key capabilities like service creation and hosting, service mediation, message routing, and data transformation across formats and protocols. Mule uses common components like filters, routers, transformers and scopes to route messages and make decisions. Core concepts include the Mule Expression Language for evaluating expressions and routing messages based on headers and payloads.
This document provides an introduction to Mule, an open-source enterprise service bus (ESB). It discusses what Mule is, how to use it, and some of its core concepts. Mule uses technologies like staged event-driven architecture (SEDA) and Java NIO to process events and messages asynchronously and efficiently. The document then explains Mule concepts like endpoints, transports, connectors, routers, filters, transformers and the universal message object (UMO) that Mule uses to process events through its pipeline. It provides examples of using Mule with file endpoints and XML pipelines.
This document summarizes different routing techniques in Mule including splitters, aggregators, collection splitters, message chunk splitters, scatter gather, and filters. It provides examples of using a collection splitter to split a list object and process each item individually, then resequence and aggregate the results. It also shows an example of using a message chunk splitter to split a message payload into fixed-length chunks, route each chunk individually, and then aggregate the responses. Scatter gather is described as sending a single message to multiple endpoints concurrently and aggregating the responses into one message.
Mule provides several threading models and strategies for processing messages:
- SEDA decomposes applications into stages connected by queues to improve parallelism.
- Thread pools are configured based on exchange patterns, processors, transactions, and processing strategies.
- Asynchronous processing uses receiver threads to queue messages and flow threads to process them in parallel, improving throughput.
The document discusses the different elements in a Mule flow. It describes components as message processors that execute business logic without Mule-specific code. Components can be divided into scripting, web service, HTTP, and other components. Scripting components allow custom logic, web service components support SOAP and REST, and HTTP handles HTTP calls. Other components include loggers, expressions, invokers, echoes, and batch jobs.
RabbitMQ is an open-source message broker software written in Erlang. It uses exchanges to route messages from producers to queues based on routing keys or bindings. There are four main exchange types - direct, fanout, topic, and headers. Mule connects to RabbitMQ using the AMQP connector. It can send and receive messages to/from RabbitMQ queues using different exchange types like direct exchanges as demonstrated in the example config with two flows, one to send and one to receive a message.
The document discusses the open-source Mule Enterprise Service Bus (ESB). Mule is an ESB that uses a staged event-driven architecture (SEDA) and non-blocking Java NIO to move data between different endpoints and applications in a flexible way. The core Mule concepts include connectors that interface with endpoints, routers that route messages, filters that filter messages, and transformers that transform message formats.
Java is the native language in which Mule is coded.
The Java component enables the developer to package custom Java code that executes when the component receives a message.
The Java component can be used to enhance the functionality and capability of your web-based applications written in Java.
This document provides an introduction to using Mule, an open-source enterprise service bus (ESB). It discusses key Mule concepts like the universal message object, endpoints, transports, connectors, routers, filters, transformers and the message flow. It provides examples of using Mule for tasks like moving files between folders and validating XML files against a schema. It also covers exception handling in Mule.
The document discusses the open-source enterprise service bus Mule, including what Mule is, its core concepts like the universal message object and endpoints, and how Mule uses technologies like staged event-driven architecture and non-blocking I/O to move data between different systems and formats in a flexible way. It also provides examples of using Mule to move XML files between directories and handling exceptions.
The document discusses the open-source enterprise service bus Mule, including what Mule is, its core concepts like the universal message object and endpoints, and how Mule uses technologies like staged event-driven architecture and non-blocking I/O to move data between different systems and formats in a flexible way. It also provides examples of using Mule to move XML files between directories and handling exceptions.
This document provides an introduction to Mule, an open-source enterprise service bus (ESB). It discusses what Mule is, how it can be used, and its core concepts. Mule uses technologies like staged event-driven architecture (SEDA) and Java NIO to facilitate integration. Core Mule concepts include endpoints, routers, filters, transformers, and the universal message object (UMO). The document also provides examples of using Mule for file processing and XML pipelines. It demonstrates how Mule handles normal processing as well as exceptions.
This document provides an overview of Mule, an open-source enterprise service backbone. It discusses key Mule concepts like the universal message object, transports, connectors, routers, filters, transformers and the Mule event flow. It also covers how Mule uses staged event-driven architecture and Java NIO for advanced technologies. Specific examples are provided around using Mule with file endpoints and for XML pipelines. The document concludes with a discussion of exception handling in Mule.
Anypoint MQ allows applications to communicate by publishing messages to queues. This document describes how to create queues and exchanges, send messages to a queue, and retrieve messages from a queue using Anypoint Platform. Key steps include logging into Anypoint Platform, clicking MQ, clicking Destinations, clicking the blue plus circle to create a new queue or exchange, specifying configuration details, and then sending or receiving messages. Organization administrators can also view Anypoint MQ usage statistics.
This document provides an introduction and overview of Mule, an open-source enterprise service bus (ESB). It discusses what Mule is, how it uses advanced technologies like staged event-driven architecture (SEDA) and Java NIO. The core concepts of Mule like the universal message object, endpoints, transports, connectors, routers, filters and transformers are explained. Examples are given of using Mule for file processing and XML pipelines. Exception handling in Mule is also covered.
Mule can be used to build and integrate web services. It provides the CXF connector for connecting to and building web services that are compliant with JAX-WS standards. A bookstore web service was built to demonstrate adding and getting books. Mule was configured with a CXF endpoint to expose the web service and a file endpoint to read a CSV file and publish the books to the web service using a generated CXF client. An email integration was also demonstrated to send order confirmations via SMTP using transformers.
The document discusses Mule TCP transport which allows sending and receiving messages over TCP connections. TCP is a layer above IP that is used to implement reliable protocols like HTTP and FTP. The Mule TCP transport can be used directly if a custom protocol is required that is not supported by higher level protocols. The document then describes the configuration options on the general, advanced, reconnection, transformers, notes and metadata tabs when configuring a Mule TCP transport component.
RabbitMQ is an open source message broker software written in Erlang. It uses exchanges to route messages from producers to queues based on routing keys or bindings. There are four main exchange types - direct, fanout, topic, and headers. Mule can connect to RabbitMQ using the AMQP connector to send and receive messages. For example, one flow can send a message to a queue using a direct exchange, while another flow receives messages from the same queue using the direct exchange.
The document introduces Enterprise Service Buses (ESBs) and the Mule ESB. It defines ESBs as a way to integrate existing systems, leverage standards, and share services across an enterprise. The document then discusses the Mule architecture in particular, including its use of connectors, transformers, routers and programming model. It provides examples of how Mule implements features like routing, message transformation and orchestration that are common to ESBs.
This document discusses EAI (Enterprise Application Integration) patterns using Spring Integration. It provides an overview of messaging, pipes and filters, and common EAI patterns. It then demonstrates how Spring Integration implements these patterns through its API, with an emphasis on messaging channels. Examples are given for sending and receiving JMS, AMQP, HTTP, and email messages. Common patterns like filtering, routing, splitting, and aggregating messages are also explained.
The Mule Message Chunk Aggregator can be used to aggregate messages that are split into parts by a message splitter. It accepts incoming message parts and uses message attributes to correlate the parts into complete messages that are then sent to downstream flows. The aggregator can be configured with options like a timeout, message ID and correlation ID expressions to map attributes, and a store prefix for object stores. Additional tabs allow adding business events tracking and notes or metadata.
Mule ESB is an open source integration platform that allows users to connect applications together and easily integrate existing systems regardless of technology. It provides key capabilities like service creation and hosting, service mediation, message routing, and data transformation across formats and protocols. Mule uses common components like filters, routers, transformers and scopes to route messages and make decisions. Core concepts include the Mule Expression Language for evaluating expressions and routing messages based on headers and payloads.
This document provides an introduction to Mule, an open-source enterprise service bus (ESB). It discusses what Mule is, how to use it, and some of its core concepts. Mule uses technologies like staged event-driven architecture (SEDA) and Java NIO to process events and messages asynchronously and efficiently. The document then explains Mule concepts like endpoints, transports, connectors, routers, filters, transformers and the universal message object (UMO) that Mule uses to process events through its pipeline. It provides examples of using Mule with file endpoints and XML pipelines.
This document summarizes different routing techniques in Mule including splitters, aggregators, collection splitters, message chunk splitters, scatter gather, and filters. It provides examples of using a collection splitter to split a list object and process each item individually, then resequence and aggregate the results. It also shows an example of using a message chunk splitter to split a message payload into fixed-length chunks, route each chunk individually, and then aggregate the responses. Scatter gather is described as sending a single message to multiple endpoints concurrently and aggregating the responses into one message.
Mule provides several threading models and strategies for processing messages:
- SEDA decomposes applications into stages connected by queues to improve parallelism.
- Thread pools are configured based on exchange patterns, processors, transactions, and processing strategies.
- Asynchronous processing uses receiver threads to queue messages and flow threads to process them in parallel, improving throughput.
The document discusses the different elements in a Mule flow. It describes components as message processors that execute business logic without Mule-specific code. Components can be divided into scripting, web service, HTTP, and other components. Scripting components allow custom logic, web service components support SOAP and REST, and HTTP handles HTTP calls. Other components include loggers, expressions, invokers, echoes, and batch jobs.
RabbitMQ is an open-source message broker software written in Erlang. It uses exchanges to route messages from producers to queues based on routing keys or bindings. There are four main exchange types - direct, fanout, topic, and headers. Mule connects to RabbitMQ using the AMQP connector. It can send and receive messages to/from RabbitMQ queues using different exchange types like direct exchanges as demonstrated in the example config with two flows, one to send and one to receive a message.
The document discusses the open-source Mule Enterprise Service Bus (ESB). Mule is an ESB that uses a staged event-driven architecture (SEDA) and non-blocking Java NIO to move data between different endpoints and applications in a flexible way. The core Mule concepts include connectors that interface with endpoints, routers that route messages, filters that filter messages, and transformers that transform message formats.
Java is the native language in which Mule is coded.
The Java component enables the developer to package custom Java code that executes when the component receives a message.
The Java component can be used to enhance the functionality and capability of your web-based applications written in Java.
This document provides an introduction to using Mule, an open-source enterprise service bus (ESB). It discusses key Mule concepts like the universal message object, endpoints, transports, connectors, routers, filters, transformers and the message flow. It provides examples of using Mule for tasks like moving files between folders and validating XML files against a schema. It also covers exception handling in Mule.
The document discusses the open-source enterprise service bus Mule, including what Mule is, its core concepts like the universal message object and endpoints, and how Mule uses technologies like staged event-driven architecture and non-blocking I/O to move data between different systems and formats in a flexible way. It also provides examples of using Mule to move XML files between directories and handling exceptions.
The document discusses the open-source enterprise service bus Mule, including what Mule is, its core concepts like the universal message object and endpoints, and how Mule uses technologies like staged event-driven architecture and non-blocking I/O to move data between different systems and formats in a flexible way. It also provides examples of using Mule to move XML files between directories and handling exceptions.
This document provides an introduction to Mule, an open-source enterprise service bus (ESB). It discusses what Mule is, how it can be used, and its core concepts. Mule uses technologies like staged event-driven architecture (SEDA) and Java NIO to facilitate integration. Core Mule concepts include endpoints, routers, filters, transformers, and the universal message object (UMO). The document also provides examples of using Mule for file processing and XML pipelines. It demonstrates how Mule handles normal processing as well as exceptions.
This document provides an overview of Mule, an open-source enterprise service backbone. It discusses key Mule concepts like the universal message object, transports, connectors, routers, filters, transformers and the Mule event flow. It also covers how Mule uses staged event-driven architecture and Java NIO for advanced technologies. Specific examples are provided around using Mule with file endpoints and for XML pipelines. The document concludes with a discussion of exception handling in Mule.
The document provides an introduction to Mule, an open-source enterprise service backbone. It describes key Mule concepts like staged event-driven architecture (SEDA) and Java NIO, and how Mule uses these concepts to provide a scalable and modular integration platform. It also summarizes core Mule components like endpoints, routers, transformers and how they facilitate message flow and integration. XML examples are provided to demonstrate basic Mule configuration and exception handling.
Mule is an open-source ESB that uses a staged event-driven architecture and non-blocking I/O. It allows components to be connected through queues and employs dynamic control to manage load. Mule configurations are defined through XML files and involve endpoints, routers, transformers and other components to route events through the ESB. Exceptions can be handled through defined exception strategies that redirect invalid messages.
The document discusses the Enterprise Service Bus (ESB) Mule and its core concepts. Mule is an open-source ESB that uses advanced technologies like Staged Event-Driven Architecture (SEDA) and Java New Input/Output (NIO) to route messages between applications. It decomposes applications into stages connected by queues to improve performance. Mule's universal message object (UMO) allows messages to be received and sent from anywhere. Core concepts include endpoints, transports, connectors, routers, filters and transformers that define how messages flow through the system.
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.
This document provides an introduction and overview of Mule, an open-source enterprise service bus (ESB). It discusses what Mule is, how it is used, and its core concepts. Mule uses a staged event-driven architecture and Java NIO for advanced technologies. Core concepts covered include the universal message object, endpoints, transports, connectors, routers, filters, transformers, and the mule event flow. The document provides examples of using Mule with file endpoints and XML pipelines. It also discusses exception handling in Mule.
This document provides an introduction to using Mule, an open-source enterprise service bus (ESB). It discusses core Mule concepts like the universal message object, endpoints, transports, connectors, routers, filters, transformers and the Mule event flow. It provides examples of using Mule to move files between directories and validate an XML file against a schema. Exceptions are handled by associating an exception strategy to redirect invalid files to an error folder.
This document provides an introduction to using Mule, an open-source enterprise service bus (ESB). It discusses Mule's core concepts like the universal message object, endpoints, transports, connectors, routers, filters and transformers. It provides examples of using Mule to move files between directories and validate XML files against a schema. The document is intended to explain Mule's declarative approach and how data flows through various stages of receiving, routing, transforming and dispatching events.
This document provides an overview of Apache Camel, an open source framework for integration. It discusses key Camel concepts like routes, endpoints, components, messages and integration patterns. It provides examples of routing messages between different endpoints using the Java and XML domain specific languages.
Managing Microservices With The Istio Service Mesh on KubernetesIftach Schonbaum
Istio is an open source service mesh that provides traffic management, service identity and security, observability and policy enforcement capabilities for microservices. At its core, Istio uses the Envoy proxy as a sidecar for each microservice to mediate all inbound and outbound traffic. It provides features like load balancing, failure recovery, metrics and monitoring out of the box without requiring any code changes to the application. Istio's control plane components like Pilot, Mixer and Citadel manage the proxy configuration, collect telemetry, and handle authentication tasks.
Apache Camel is an open-source integration framework that allows applications to integrate various systems together. It uses Enterprise Integration Patterns to provide routing and mediation between endpoints. Camel supports various languages and has a large number of components for integration with different systems like files, databases, messaging systems etc. It allows configuration of routes using a simple domain specific language to perform operations like transforming messages, splitting/aggregating data between endpoints.
This document provides an introduction to Mule ESB, an open-source integration platform. It discusses what Mule ESB is, how it is used, and its core concepts. Key points covered include Mule ESB being an enterprise service backbone, its use of advanced technologies like SEDA and Java NIO, how it moves data between different endpoints and transports, its use of XML pipelines to perform operations on files, and its core concepts like the universal message object and endpoints.
This document provides an overview of Mule ESB, including:
- Mule ESB is an open source enterprise service bus that provides lightweight and flexible integration capabilities.
- It uses a loosely coupled architecture and supports major protocols and technologies.
- Mule ESB uses a staged event-driven (SEDA) architecture to avoid overhead of thread-based concurrency models.
- Key concepts include universal message objects (UMOs), endpoints, transports, connectors, transformers, routing, and exception handling strategies.
3450 - Writing and optimising applications for performance in a hybrid messag...Timothy McCormick
Messaging architectures in any environment, from local standalone deployments through to public clouds, must provide the highest reliability yet maximize their performance. This session gives you an insight into IBM MQ and how applications can be made to perform to their absolute best while maintaining the data integrity that IBM MQ is renowned for. We'll see how this can be achieved through a combination of good application design, system tuning and architectural patterns.
Mule ESB is an open source enterprise service bus (ESB) that allows for lightweight and flexible integration. It uses a loosely coupled architecture and supports major protocols and technologies. Mule ESB uses a staged event-driven (SEDA) architecture that decomposes services into stages for modularity and code reuse. It processes messages using universal message objects (UMOs) and endpoints, with transports handling specific protocols and connectors sending/receiving messages. Transformation and routing are done through transformers, routers, and an exception strategy handles errors.
The document introduces Enterprise Service Buses (ESBs) and the Mule ESB. It defines ESBs as a way to integrate existing systems, leverage standards, and share services across an enterprise. The document then discusses the Mule architecture in particular, including its use of connectors, transformers, routers and programming model. It provides examples of how Mule implements features like routing, message transformation and orchestration that are common to ESBs.
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 routing, transformations, and processing of data through components. Mule handles exception handling by associating exception strategies with connectors, components, or for all components in a configuration to redirect errors to a specified endpoint.
The Mule File Connector allows applications to exchange files with a file system by implementing the File connector as either an inbound or outbound endpoint, and it can be configured by placing the File endpoint in a Mule flow and providing values for fields like path, polling frequency, and file name on various property tabs.
The document discusses the Box Connector for Anypoint Platform, which allows synchronization of data and automation of processes between Box and third party applications. It provides instructions on installing the connector, configuring it using OAuth 2.0 authentication with a developer token, and includes an example use case of creating a folder in Box. Requirements include Anypoint Studio 5.4 or higher and a Box developer account.
The document provides information about the Amazon S3 connector for MuleSoft, including:
- Amazon S3 is AWS storage that allows storing and retrieving data from anywhere on the web.
- The connector requires AWS credentials and is compatible with Mule Runtime 3.5+ and AWS SDK for Java 1.11.21.
- It describes how to install, configure, and use the connector to perform various Amazon S3 operations like creating/deleting buckets and objects.
Mule flows allow developers to implement message processing in multiple stages by using standard synchronous flows, asynchronous flows, and subflows. Using multiple flows provides advantages like performing time-consuming tasks asynchronously, handling errors differently across flows, improving readability, and enabling reuse of processing logic. Multiple flows also allow for load balancing and higher performance applications.
The HTTP connector can be used as an HTTP listener connector to receive HTTP requests at a specified address and generate responses, or as an HTTP requester connector to send requests to an address and receive responses. It supports TLS encryption for HTTPS and authentication via basic, digest, and OAuth. When used as a listener, it is placed in the source of a flow, and as a requester, in the process section. Debugging HTTP activity can be done by enabling loggers for listener/request activity and packet metadata. The connector also supports non-blocking processing.
This document provides steps to install Tcat Server and the Tcat Administration Console on a single machine or multiple machines. The steps include downloading the installer, running the installer, starting the Tcat server, registering the server with the Console, managing and monitoring the server instance, deploying new applications, and pairing additional servers with the Administration Console.
The Mule File Connector allows applications to exchange files with a file system by implementing the File connector as either an inbound or outbound endpoint, with the inbound endpoint acting as a message source and the outbound writing files to a destination directory; the File endpoint is configured by placing it in a Mule flow and providing properties for the endpoint like the file path, polling frequency, and transformers; and the endpoint can be used to read, write, move, and filter files through its various configuration tabs.
The document discusses how Mule message processors transform messages as they pass through a flow. It provides an example of a message before and after it passes through a Transform Message component. The message contains a header, payload, and properties. Before being transformed, the example message's payload is a simple string and it contains certain inbound and outbound properties. After transformation, the payload is now an XML document, while the message header and properties remain unchanged.
The FTP Connector allows a Mule application to exchange files with an external FTP server. It can be configured as an inbound endpoint to receive files or an outbound endpoint to send files. When configuring an FTP endpoint, values must be provided for properties on the General, Advanced, Reconnection, and Transformers tabs such as the host, port, username, password, transfer mode, polling frequency, and transformers. Global connector configurations can also be associated with endpoint instances.
Mule Transformers can alter message properties, variables, or payloads to prepare them for further processing. Standard transformers are provided to handle common data conversion scenarios, such as XML-to-Object. If no single transformer achieves the needed output, multiple transformers can be used sequentially. Transformer categories include those for Java Objects, Content, SAP, Scripting, Properties/Variables/Attachments. The DataWeave transformer provides powerful data querying and transformation capabilities.
The HTTP connector can be used as an HTTP listener connector to receive HTTP requests at a specified address and generate responses, or as an HTTP requester connector to send requests to an address and receive responses. It supports TLS encryption for HTTPS and authentication via basic, digest, and OAuth. When used as a listener, it is placed in the source of a flow, and as a requester, in the process section. Debugging HTTP activity can be done by enabling loggers for listener/request activity and packet metadata. The connector also supports non-blocking processing.
MongoDB is a document-oriented database designed for scalability and developer agility. The MongoDB connector provides a connection between Mule and MongoDB servers, implementing the MongoDB API. It includes various transformers for data management. The connector configuration wizard allows configuring properties like connection details, pooling profiles, and reconnection strategies when establishing connections to MongoDB.
The document describes the state of a message before and after being transformed by a message processor in a Mule application. Before transforming, the message contains a header, payload, inbound properties containing metadata, and variables indicating where to move files and polling frequency. After transforming, the message header and payload remain, but inbound properties are unchanged and no outbound properties or variables were added or removed by the transform message component.
Mule Transformers prepare messages for further processing by altering message properties, variables, or payload. Transformers include the Anypoint DataMapper Transformer which can both transform data formats and map input fields to different output fields. Out of the box, Mule provides standard transformers to handle common data transformation scenarios with minimal configuration.
This document describes various elements that compose Mule flows, including connectors, components, transformers, and exception handling strategies. Connectors receive and send messages from external sources and can act as sources, processors, or destinations in a flow. Components enable custom business logic without code. Transformers prepare messages for further processing by altering properties, variables, or payloads. Exception strategies precisely handle errors that occur in flows.
Maven is a project management utility that can be used to develop Mule projects. Mule provides built-in Maven functionality including building Mule apps with Maven in Anypoint Studio, enabling Maven support for existing Studio projects, and importing Maven projects into Studio. The muleesb-maven-plugin and Maven-Mule ESB plugin provide Maven integration, allowing development of Mule apps from within Maven. The document provides steps for building a simple HTTP request-response app with Maven in Studio, enabling Maven support for an existing Studio project, and importing an existing Maven project into Studio.
This document outlines a Mule flow that calls a SOAP web service, retrieves response data from the service, and writes the response to a file in JSON format. The flow first reads a name from an input text file. It then calls the SOAP service, passing the name. Due to the streaming response, the flow uses a "File to String" transformer to convert the stream to a string payload containing the SOAP response. Finally, it transforms the response object to JSON and writes it to an output file. The key is embedding the SOAP response in an XML payload to properly extract the response object properties rather than just the raw SOAP message.
The document discusses using Mule's poll scheduler to trigger scheduled tasks. Poll can be used to extract data from a database to CSV every 15 seconds, or call a web service to check an application's status periodically. The example Mule configuration shows a poll scheduled to run every 15 seconds that calls a HTTP request, with simple logging to demonstrate how the poll mechanism works.
Mule Flows enable the orchestration of services through message processing. A flow contains a chain of message processors with a message source that processes incoming messages. Flows are configured in XML using the <flow> element and can include transformers, filters, routers, and message enrichers leveraging expressions. Private flows cannot be accessed from outside the JVM as they have no defined message source and are only used if referenced from another construct running in the same Mule instance.
Mule applications accept and process events as messages through connected message processors in a flow. Large messages can be processed in batch jobs which split messages into records. Flows link message processors to handle message receipt, processing, and routing. Batch jobs process records asynchronously outside of flows. Mule receives messages from external sources via connectors and routes them through processors that transform data between applications.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Full-RAG: A modern architecture for hyper-personalizationZilliz
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
20 Comprehensive Checklist of Designing and Developing a WebsitePixlogix Infotech
Dive into the world of Website Designing and Developing with Pixlogix! Looking to create a stunning online presence? Look no further! Our comprehensive checklist covers everything you need to know to craft a website that stands out. From user-friendly design to seamless functionality, we've got you covered. Don't miss out on this invaluable resource! Check out our checklist now at Pixlogix and start your journey towards a captivating online presence today.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
4. 4
Mule is Has Advanced
Technologies
• SEDA
– Staged Event-Driven Architecture
• Java NIO
– Java New Input/Output
5. 5
SEDA
• SEDA decomposes a complex, event-driven software application into a set
of stages connected by queues
• This design avoids the high overhead associated with thread-based
concurrency models, and decouples event and thread scheduling from
application logic
• By performing admission control on each event queue, the service can be
well-conditioned to load, preventing resources from being overcommitted
when demand exceeds service capacity
• SEDA employs dynamic control to automatically tune runtime parameters
(such as the scheduling parameters of each stage) as well as to manage
load, for example, by performing adaptive load shedding
• Decomposing services into a set of stages also enables modularity and code
reuse, as well as the development of debugging tools for complex event-
driven applications
6. 6
Java NIO
• NIO is a collection of Java programming language APIs
that offer advanced features for intensive I/O operations
• NIO facilitates an implementations that can directly use
the most efficient operations of the underlying platform
• NIO includes:
– Buffers for data of primitive types
– Character set encoders and decoders
– A pattern-matching facility based on Perl-style regular expressions
(in package java.util.regex)
– Channels, a new primitive I/O abstraction
– A file interface that supports locks and memory mapping
– A multiplexed, non-blocking I/O facility for writing scalable
servers
7. 7
Mule’s “Moves Things Around”
• Folder to folder
• Queue to queue
• Shared memory to shared memory
• Using different types of transports
• In a flexible way
8. 8
XML Pipeline
• An XML pipeline is a series of operation
that are performed on one or more XML
files
• Examples include:
– validate
– transform
– prune (remove nodes)
– split (break a single XML file into many files)
– merge (join two or more files together)
9. 9
CRV Example
• Flow of XML document through approval
processes
Submit
CRV
Deed
Matched
CRV
SSN
Stripped
CRV
Income
Tax
Audit
County
Audit
County
Approval
State
Audit
State
Approval
10. 10
Decomposition
• Example of XML Operations used on CRV
Validate Split
Remove
SSN
Element
Store
Modify
Value
Add
Element
Modify
Value
Add
Element
11. 11
Declarative Approach
• Focus on specifying "What" not "How"
• Empower business analysis to write
machine-readable specifications
• Hide the "How" behind services with clear
interfaces (SOA)
13. 13
Universal Message Object (UMO)
• A UMO is a type of Java object that can
– receive events "from anywhere"
– send events
• UMO Components are usually your business
objects. They are components that execute
business logic on an incoming event
• UMO are standard JavaBeans (containers)
• There is no Mule-specific code in your
components
• Mule handles all routing and transformation of
events to and from your objects based on the
configuration of your component
14. 14
Transport
• A transport or "provider", is a set of objects
that add support to Mule to handle a
specific kind of transport or protocol
• Examples
– the "Email Provider" enables Mule to send and
receive messages via the SMTP, POP and
IMAP protocols
15. 15
Connector
• A connector is the object that sends and
receives messages on behalf of an endpoint.
• Connectors are bundled as part of specific
transports or providers.
• For example, the FileConnector can
read and write file system files.
16. 16
Router
• A router is the object that do something
with messages once they have been
received by a connector, or prior to being
sent out by the connector
17. 17
Filter
• A filter optionally filters incoming or outgoing
messages that are coming into or going out from a
connector.
• For example, the File Provider comes with a
FilenameWildcardFilter that restricts
which files are read by the connector based on file
name patterns. For example only files with the
.xml extension can be routed.
• Filters are used in conjunction with Routers.
18. 18
Transformer
• A transformer optionally changes incoming
or outgoing messages in some way
• This is usually done to make the message
format useable by a downstream function
• Examples:
– the ByteArrayToString transformer converts
byte arrays into String objects.
19. 19
Mule Event Flow
• The nine stages of a
mule event
– first 2 – inbound
– middle 4 –
component
– last 2 – outbound
Endpoint
(Message Receiver)
Endpoint
(Message Dispatcher)
Inbound Router
Outbound Router
Inbound Transformer
Outbound Transformer
Interceptor
Service Invocation
Interceptor
Inbound
Component
Outbound
Optional Step
20. 20
Message Receiver Endpoint
• Some event triggers a
message flow
– A file being written into a
folder
– A message arriving on a
message queue
– A record in a database
– Data written to a socket
Endpoint
(Message Dispatcher)
Inbound Router
Outbound Router
Inbound Transformer
Outbound Transformer
Interceptor
Service Invocation
Interceptor
Endpoint
(Message Receiver)
21. 21
Inbound Router
• The inbound router is the fist step in a
message. Functions typically
performed by an inbound router
– Filtering
– Remove duplicate messages
– Matching messages
– Aggregation (combining)
– Re-sequence data
– Forwarding
• See also
– IdempotentReceiver
– CorrolationAggregator
– CorrelationResequencer
Endpoint
(Message Dispatcher)
Inbound Router
Outbound Router
Inbound Transformer
Outbound Transformer
Interceptor
Service Invocation
Interceptor
Endpoint
(Message Receiver)
22. 22
Interceptor
• Used to intercept message flow
into your service component
• Used trigger monitor/events or
interrupt the flow of the message
• Example: an authorization
interceptor could ensure that the
current request has the correct
credentials to invoke the service.
Endpoint
(Message Dispatcher)
Inbound Router
Outbound Router
Inbound Transformer
Outbound Transformer
Service Invocation
Interceptor
Endpoint
(Message Receiver)
Interceptor
23. 23
Inbound Transformer
• If the inbound data is
not in the correct
format for the
service it must be
transformed at this
point
Endpoint
(Message Receiver)
Endpoint
(Message Dispatcher)
Inbound Router
Outbound Router
Outbound Transformer
Interceptor
Service Invocation
Interceptor
Inbound Transformer
24. 24
Service Invocation
• The actual service is
performed
• In mule, this is generally a
Java object
• Service invocation can also
be a "pass through"
Endpoint
(Message Receiver)
Endpoint
(Message Dispatcher)
Inbound Router
Outbound Router
Outbound Transformer
Interceptor
Interceptor
Inbound Transformer
Service Invocation
25. 25
Outbound Router
• Dispatching the data
to all the relevant
endpoints
Endpoint
(Message Receiver)
Endpoint
(Message Dispatcher)
Inbound Router
Outbound Transformer
Interceptor
Interceptor
Inbound Transformer
Service Invocation
Outbound Router
26. 26
Built-in Router Classes
Inbound Outbound Response
Idempotent Receiver Filtering Outbound Router Response Aggregator
Selective Consumer Recipient List
Aggregator Multicasting Router
Resequencer Chaining Router
Forwarding Consumer Message Splitter
Filtering List Message
Splitter
Filtering Xml Message
Splitter
Exception Based Router
27. 27
Outbound Transformer
• Any transformations that needs to be
done on the message after a service
has been performed on the message
can be executed before it is put into
the endpoint
• See Also
– EnvelopeInterceptor
Endpoint
(Message Receiver)
Endpoint
(Message Dispatcher)
Inbound Router
Interceptor
Interceptor
Inbound Transformer
Service Invocation
Outbound Router
Outbound Transformer
29. 29
Omitted From Examples for Brevity
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE mule-configuration PUBLIC "-//MuleSource
//DTD mule-configuration XML V1.0//EN"
"http://mule.mulesource.org/dtds/mule-
configuration.dtd">
32. 32
Only Moving XML Files
<inbound-router>
<endpoint address="file:///c:/mule-class/in">
<filter pattern="*.xml"
className=
"org.mule.providers.file.filters.FilenameWildcardFilter"/>
</endpoint>
</inbound-router>
Add the filter line to only move files with the extension
"*.xml". If you add a file "foobar.txt to the input folder it
will not be moved.
33. 33
Keeping the Name The Same
<outbound-router>
<router
className="org.mule.routing.outbound.OutboundPassThroughRouter">
<endpoint
address=
"file:///c:/mule-class/out?outputPattern=$[ORIGINALNAME]"
/>
</router>
</outbound-router>
Add the outputPattern parameter to keep the output
name the same as the input.
34. 34
Happy Path and Exceptions
• By default, error free documents follow a central path known as
the "happy path"
• Documents that have errors may be handled in different ways
(rejected, warnings etc.)
Start StopStep 1 Step 2 Step 3
Stop Stop Stop
35. 35
Exception Handling
• Mule has a special way of handling non-happy path processing. This
is called an "Exception Strategy" but is it really just and exception
path and there is very little strategy involved.
• There are three places you can associate an exception strategy
– connector
– component
– model (set for all components in a model)
37. 37
Sample XML
<?xml version="1.0" encoding="UTF-8"?>
<Data>
<Element1>Hello World!</Element1>
<Element2>String</Element2>
<Element3>String</Element3>
<DansInvalidDataElement>This is Dans invalid data element</DansInvalidDataElement>
</Data>
XML Schema validation will generate an error message
when it gets to the fourth invalid data element:
Given the following XML Schema file:
38. 38
Validating against an XML Schema
<outbound-router>
<router className="org.mule.routing.outbound.FilteringXmlMessageSplitter">
<endpoint
address="file:///c:/mule-class/out?outputPattern=$[ORIGINALNAME]"/>
<properties>
<property name="validateSchema" value="true"/>
<property name="externalSchemaLocation"
value="file:///c:/mule-class/labs/07-validate/my-
schema.xsd"/>
</properties>
</router>
</outbound-router>
To validate the XML Schema, just add two properties:
1) tell it to validate the document
2) tell it what file to use and where to find it
39. 39
Error Message
document : cvc-complex-type.2.4.d: Invalid content was found
starting with element 'DansInvalidDataElement'. No child
element is expected at this point.
This error message is generated on the Mule console
when an invalid data element is found. But what should
we do with it? How do we redirect it to the appropriate
user?