Scatter gather flow control
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The document discusses scatter-gather flow control in Mulesoft. Scatter-gather sends a request message concurrently to multiple targets and aggregates the responses. It replaces the deprecated all message processor by executing routes in parallel instead of sequentially, improving efficiency. Scatter-gather collects results into a message collection. If a route fails, it sets the exception payload and throws a composite exception mapping failures to routes.
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The Splitter Flow Control splits a message into fragments based on an expression, usually written in Mule Expression Language. A Collection Aggregator can then reassemble the original message parts. Together, the splitter and aggregator allow processing of split message parts on separate servers while reassembling the message. The splitter adds correlation variables to fragments used by the Aggregator for reassembly.
Datasense
This document discusses testing connections to external resources in Mulesoft DataSense. It explains that when configuring connectors in Studio, you can test the connection to ensure it is working properly. It provides details on testing new connections, such as filling out the configuration values and testing before saving, and on testing existing connections to identify potential issues. Limitations around call limits are also covered.
Choice flow control reference
The document describes the choice flow control in Mulesoft, which dynamically routes messages based on message properties or payload. It uses expressions to evaluate the message and route it to the first matching routing option, or the default route if none match. The document provides details on adding, configuring, and changing the default route of the choice flow control, and includes an example code snippet.
Soa(service oriented architecture)
Traditional SOA implementations take years and millions of dollars, while custom code welds systems together rigidly. An API-led SOA solution offers immediate value, phased growth, and lower risk. With Anypoint Platform, legacy on-premises data can be seamlessly and securely connected to the cloud, devices, and APIs. Implementing SOA with an API-led approach delivers business agility, better customer experiences, and competitive advantage through unified connectivity, lowest friction development, and a future-proof architecture.
Soa project fundamentals
This document outlines the key stages of a Service Oriented Architecture (SOA) project lifecycle:
1. Planning stages include SOA Adoption Planning to determine scope, timeline, funding and governance models.
2. Service Inventory Analysis identifies existing services across business units.
3. Later stages involve modeling services (Service-Oriented Analysis), designing service contracts (Service-Oriented Design), developing service logic, deploying services, and monitoring service usage.
Soa planning
This document discusses key factors for planning a successful SOA initiative:
- A sound methodology and proven processes are needed to reduce risk and provide a path to realizing benefits while meeting goals.
- Cooperation across multiple project teams is required, unlike traditional siloed applications, as services involve many teams.
- Teams must use a common framework of vocabulary, concepts, and understanding of the target state to build reliability and trust.
- Consistency in applying knowledge and practices is critical for success, as teams must be disciplined in their roles and methodology.
Soa methodology
This document discusses an SOA methodology and service layers. It introduces SOA methodology as a way to reduce risk by providing processes and practices for SOA projects. There are three common types of services: entity services which represent business entities, task services which are associated with business tasks and processes, and utility services which provide non-business logic. Each service type has a different focus and level of reuse potential.
Soa governance
This document discusses SOA governance and its key components. It defines governance as a system for administering and making decisions within an organization. A governance system establishes who can make decisions, constraints on decisions, and consequences for noncompliance. The primary building blocks of a governance system are precepts (authoritative rules), processes (activities), people (roles), and metrics (measuring compliance). Precepts determine authority and constraints. Processes control and guide decisions. People make decisions within precept constraints. Metrics measure compliance with precepts.
Principles of soa
This document discusses the key principles of service-oriented architecture (SOA), including standardized service contracts, loose coupling between services, reusability of services, service autonomy, and statelessness. Services should comply with common contract standards, have low dependencies on other services or their environment, contain reusable logic, control their runtime environment, and minimize state when possible. Following these principles allows solutions to gain the benefits of SOA.
Mule transformers
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 fields, such as mapping a "last_name" field to a "family_name" field. Out of the box, Mule provides standard transformers to handle common data transformation scenarios with minimal configuration.
Mule exception strategies
Mule provides exception strategies to handle errors that occur within Mule flows. There are two categories of exceptions: system exceptions which occur during startup or connection failures, and are handled by system strategies; and messaging exceptions which occur during message processing and are handled by messaging strategies. When a message throws an exception, normal flow stops and the message is passed to the messaging exception strategy containing message processors to handle the error.
Mule components
Mule components allow you to add custom business logic to flows without writing Mule-specific code. Components include scripting components to add custom scripts, web service components to expose and consume web services, and an HTTP component to make HTTP calls. Examples demonstrate using a Groovy script component and various other common components like logger, echo, and flow reference.
Mule agent architecture
The document provides an overview of the main components and architecture of the Mule Agent, which exposes the Mule ESB Java API as a service allowing external systems to manipulate and monitor Mule instances. The key components are the Mule Service for connecting to the Mule API, the Transport for handling communication, External Message Handlers for exposing the API and routing requests, and Internal Message Handlers for handling Mule notifications. Communication can be synchronous, asynchronous, or push-based. The architecture diagram shows how the components interact through the transport layer.
Message state
This document summarizes the key components of a Mule message - header, payload, properties, and variables - and how they may change when a message passes through a message processor like a transformer. It provides examples of a message before and after being processed by a DataMapper transformer, demonstrating how the payload, properties, and variables can be modified. It also provides an example of how to set a variable on a message using the set-variable processor.
Global elements
Global elements in Mule allow configurations to be defined once and then referenced across multiple flows. This provides flexibility, reusability, and efficiency compared to repeating the same configuration in multiple places. Common examples of global elements include HTTP, JDBC, and JMS connectors. To create a global element, you define the configuration with attributes like username and password, then reference it using config-ref when needed in flows.
Flows and subflows
Flows and subflows allow for breaking up complex Mule applications into discrete processing units. A flow processes messages, and can route them to other flows or subflows. Subflows process messages synchronously and inherit processing strategies, pausing the triggering flow. Synchronous flows also process synchronously but do not inherit strategies. Asynchronous flows process messages independently and in parallel to the triggering flow, allowing for improved performance.
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- 1. Scatter Gather Flow Control in Mulesoft
- 2. Scatter-Gather • The routing message processor Scatter-Gather sends a request message to multiple targets concurrently. It collects the responses from all routes, and aggregates them into a single message.
- 3. • Scatter-Gather replaces the All message processor, which is deprecated as of Mule 3.5.0. Note that, unlike All, Scatter-Gather executes routes concurrently instead of sequentially. • Parallel execution of routes can greatly increase the efficiency of your application and provides more information than sequential processing. Refer to migration details below for more information about the differences you can expect.
- 4. • Scatter-Gather Behavior and Exceptions • CompositeRoutingException • Customizing Aggregation Strategies • Configuration • Modeling Scatter-Gather in a Flow • General Tab
- 5. • Advanced Tab • Scatter-Gather Threading Profiles • Migrating to Scatter-Gather from the All Message Router • Why Migrate? • Differences Between Scatter-Gather and the All Router • Complete Code Example • Serial Multicast with Scatter-Gather
- 6. • The Scatter-Gather router sends a message for concurrent processing to all configured routes. The thread executing the flow that owns the router waits until all routes complete or time out. • If there are no failures, Mule aggregates the results from each of the routes into a message collection (MessageCollection class). Failure in one route does not stop the Scatter-Gather from sending messages to its other configured routes, so it is possible that many, or all routes may fail concurrently.
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