Mule exception strategies
•Download as PPTX, PDF•
0 likes•726 views
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.
Report
Share
Report
Share
Recommended
Error Handling Framework in Mule ESB
This document discusses Mule's error handling framework. It describes the two types of errors that can occur - system exceptions with no message, and messaging exceptions within a flow. A global exception handler is used to provide uniform handling across applications. There are three types of exceptions it handles: fatal exceptions requiring abort, non-retryable requiring resubmission, and retryable using retries or replays. Current exception handling relies on custom error management rather than native message stores or channels. Synchronous exceptions require transaction rollback and HTTP status codes, while asynchronous use retries and replays. A notification service is proposed to independently handle different notification types including email.
Mule - error handling
Mule ESB provides options for handling errors through exception strategies. The default exception strategy implicitly manages errors in Mule flows by logging exceptions and rolling back transactions. Users can also implement custom exception strategies like catch, rollback, and choice strategies to handle errors more precisely. Catch strategies always commit transactions after exceptions while rollback strategies attempt to redeliver messages after exceptions before logging failures. Choice strategies make routing decisions for messages based on exception details.
Error handling
This is about the basic introduction of error handling strategies that mule provides to handle exceptions.
Mule exception strategies - Reference Exception Strategy
This document discusses exception handling strategies in Mule, focusing on the reference exception strategy. It defines a reference exception strategy as one that refers to error handling parameters defined in a global catch, rollback, or choice exception strategy. An example XML configuration is provided of a flow that uses a reference exception strategy to redirect to a catch exception strategy containing a Java component for handling errors. The result is that when a call to the flow causes an exception, the message configured in the catch strategy Java class will be returned.
Anypoint Studio - Mule ESB Error Handling
Exception Handling plays a vital role in running the application smooth. It helps to handle the exceptions properly so that the application will run properly.
Mule exception strategies - Choice Exception Strategy
This document discusses choice exception strategies in Mule. It defines an exception as an event that disrupts normal program flow. Choice exception strategies allow configuring different exception handling logic based on the exception type. The document provides an XML example of a flow that uses a choice exception strategy with two catch exception strategies - one to handle NullPointerExceptions and one to handle ArithmeticExceptions. When this flow is called, the response will contain the message returned from the appropriate error handler Java class based on the exception thrown.
Mule filters
Mule filters evaluate Mule messages and route them through flows based on conditions. There are several types of filters including custom filters, exception filters, logic filters, and message filters. Custom filters allow referencing user-implemented filters, exception filters route messages based on exception type, and logic filters apply Boolean AND, OR, and NOT operations to nested filters.
Mule esb examples
This document provides an overview of various Mulesoft concepts and components including HTTP, routing, filters, data mapping, JMS, databases, web services, Java custom components, and message enrichers. It includes configuration examples and use cases for each concept.
Recommended
Error Handling Framework in Mule ESB
This document discusses Mule's error handling framework. It describes the two types of errors that can occur - system exceptions with no message, and messaging exceptions within a flow. A global exception handler is used to provide uniform handling across applications. There are three types of exceptions it handles: fatal exceptions requiring abort, non-retryable requiring resubmission, and retryable using retries or replays. Current exception handling relies on custom error management rather than native message stores or channels. Synchronous exceptions require transaction rollback and HTTP status codes, while asynchronous use retries and replays. A notification service is proposed to independently handle different notification types including email.
Mule - error handling
Mule ESB provides options for handling errors through exception strategies. The default exception strategy implicitly manages errors in Mule flows by logging exceptions and rolling back transactions. Users can also implement custom exception strategies like catch, rollback, and choice strategies to handle errors more precisely. Catch strategies always commit transactions after exceptions while rollback strategies attempt to redeliver messages after exceptions before logging failures. Choice strategies make routing decisions for messages based on exception details.
Error handling
This is about the basic introduction of error handling strategies that mule provides to handle exceptions.
Mule exception strategies - Reference Exception Strategy
This document discusses exception handling strategies in Mule, focusing on the reference exception strategy. It defines a reference exception strategy as one that refers to error handling parameters defined in a global catch, rollback, or choice exception strategy. An example XML configuration is provided of a flow that uses a reference exception strategy to redirect to a catch exception strategy containing a Java component for handling errors. The result is that when a call to the flow causes an exception, the message configured in the catch strategy Java class will be returned.
Anypoint Studio - Mule ESB Error Handling
Exception Handling plays a vital role in running the application smooth. It helps to handle the exceptions properly so that the application will run properly.
Mule exception strategies - Choice Exception Strategy
This document discusses choice exception strategies in Mule. It defines an exception as an event that disrupts normal program flow. Choice exception strategies allow configuring different exception handling logic based on the exception type. The document provides an XML example of a flow that uses a choice exception strategy with two catch exception strategies - one to handle NullPointerExceptions and one to handle ArithmeticExceptions. When this flow is called, the response will contain the message returned from the appropriate error handler Java class based on the exception thrown.
Mule filters
Mule filters evaluate Mule messages and route them through flows based on conditions. There are several types of filters including custom filters, exception filters, logic filters, and message filters. Custom filters allow referencing user-implemented filters, exception filters route messages based on exception type, and logic filters apply Boolean AND, OR, and NOT operations to nested filters.
Mule esb examples
This document provides an overview of various Mulesoft concepts and components including HTTP, routing, filters, data mapping, JMS, databases, web services, Java custom components, and message enrichers. It includes configuration examples and use cases for each concept.
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.
Validations module
This short document promotes creating presentations using Haiku Deck, an online presentation tool. It encourages the reader to get started making their own Haiku Deck presentation and sharing it on SlideShare. In just one sentence, it pitches the idea of using Haiku Deck to easily create engaging presentations.
Exception handling in mule
Mule has a way to handle exceptions called an "exception strategy" that allows you to associate an exception handling path with connectors, components, or entire models. The example shows configuring an exception strategy to redirect any invalid documents to an error folder using a file endpoint. It then validates an XML sample against an XML schema, which generates an error message when it encounters an invalid data element as expected.
Exception strategies in MuleSoft Anypoint Studio
Various exception strategies has been described and what are various ways of defining the exception strategies.
Mule expression component
These Slides explain the implementation of Expression component in Mule Esb with Slides and decent Examples with Explanation.
Message enricher in mule
The document discusses different ways to enrich messages in Mule including enriching flow variables, message headers, and using enricher tags. It provides examples of enriching payload with additional information from external resources like another flow, HTTP request, or static expression.
Mulesoft ppt
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.
A short introduction on error handling in anypoint studio
Mule provides options for handling errors through exception strategies. There are two categories of exceptions in Mule: system exceptions and messaging exceptions. System exceptions are handled by system exception strategies when no message is involved. Messaging exceptions are handled by messaging exception strategies when a message is being processed through a Mule flow and throws an exception. Messaging exception strategies can contain message processors and nested exception strategies to precisely handle exceptions. Each flow can contain one messaging exception strategy which can be a choice strategy referring to other nested strategies.
Mule exception strategies
Mule applications have two types of exceptions: system exceptions and messaging exceptions. System exceptions occur at the application level while no message is involved. Messaging exceptions occur when processing a message through a Mule flow. There are several exception strategies in Mule including catch, rollback, reference, and choice strategies. Catch strategies consume messages while rollback strategies roll messages back for reprocessing. Choice strategies handle exceptions based on message content.
Mule concepts exception strategies
Explains how the exceptions are handled in mule, what re the different exception strategies available, and what do they do.
Mule error handling
Mule provides options for handling errors called exceptions. There are two categories of exceptions in Mule: system exceptions which occur during application startup or connection failures, and are handled by system exception strategies; and messaging exceptions which occur within flows and are handled by messaging exception strategies. Mule supports five types of messaging exception strategies to handle errors in transactions: default, catch, choice, reference, and rollback strategies. It is best practice to create a global default exception strategy and add reference strategies in flows to refer to the global strategy.
Mule error handling
Mule ESB provides options for handling errors through exception strategies. The default exception strategy handles errors globally by rolling back transactions and logging exceptions. Additional exception strategies like catch, rollback, and choice strategies can be used to customize error handling for specific flows. Messaging exceptions are thrown when errors occur during message processing, while system exceptions handle errors outside of message processing like during application startup.
Error handling in mule
Mule ESB provides options to handle errors through exception strategies. The default exception strategy handles all messaging exceptions by rolling back transactions and logging exceptions. Users can configure alternative exception strategies like catch, rollback, reference, and choice strategies to customize error handling for different situations. Catch strategies always commit transactions after exceptions while rollback strategies attempt to redeliver messages before committing failed transactions. Reference strategies refer to global exception handling and choice strategies route messages based on content during exceptions. Exception strategies provide flexibility in how Mule applications manage errors and exceptions.
Mule errors
Mule ESB provides options for handling errors through exception strategies. The default exception strategy handles errors globally by rolling back transactions and logging exceptions. Alternative exception strategies like catch, rollback, and choice strategies allow more customized error handling. Catch strategies always commit transactions after exceptions while rollback strategies attempt to redeliver messages before committing. Choice strategies route messages based on content after exceptions.
Error handling with respect to mule
Mule ESB provides options for handling errors through exception strategies. The default exception strategy implicitly handles all messaging exceptions by rolling back transactions and logging exceptions. Alternative exception strategies include catch, which commits transactions and consumes messages; rollback, which attempts to redeliver messages before committing failed transactions; reference, which refers to a global exception strategy; and choice, which customizes error handling based on message content. Exception strategies provide flexible ways to manage errors within Mule applications and flows.
Mule error handling
This presentation provides an overview on Mule ESB's error handling capabilities. System and Messaging exception strategies are explained with examples in this presentation.
Handle exceptions in mule
Mule provides default exception handling but also allows custom exception strategies to implement more precise error management. Exception strategies include choice, catch, and rollback strategies. A rollback strategy reverts a message flow to an earlier state if an exception occurs during a transactional flow.
Mule exception strategies - Catch exception strategy
The document discusses exception handling strategies in Mule. It defines an exception as an event that disrupts normal program flow. Mule has different exception strategies, including catch exception strategy. The catch exception strategy commits transactions and consumes messages when exceptions are thrown. The document provides an XML code example of configuring a flow with a catch exception strategy that catches a divide by zero exception and routes it to a Java class for handling.
Mule exceptions Strategy
This document discusses how to handle exceptions in Mule applications. There are two types of exceptions: system exceptions which occur at the system level, and messaging exceptions which occur when messages are involved. By default, exceptions stop flow execution, log the exception, and roll back transactions. To continue execution, reconnection strategies can be used for system exceptions while messaging exception strategies specify custom exception handling. Messaging exception strategies contain catch, rollback, choice, reference, and custom handlers and can be defined globally for reuse in multiple flows.
Mule error handling_choice exception strategy
The choice exception strategy allows Mule to customize error handling for messages based on message content and exception type. It catches exceptions from its parent flow, evaluates the exception and message, then routes the message to the appropriate child exception strategy based on matching expressions. If no child matches, it uses the default strategy. It is useful for applying different error handling rules depending on exception type.
Vancouver mulesoft meetup_23-july
The document summarizes a presentation on Mule 4 exception handling and Munit. It covers error handling in Mule 4 including system errors, messaging errors, and the error hierarchy. It also discusses default error handling, creating error handlers, and differences between error handling in Mule 3 and 4. The presentation includes a demo of error handling and introduces Munit for testing Mule applications with capabilities like mocking and validating processors.
More Related Content
Viewers also liked
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.
Validations module
This short document promotes creating presentations using Haiku Deck, an online presentation tool. It encourages the reader to get started making their own Haiku Deck presentation and sharing it on SlideShare. In just one sentence, it pitches the idea of using Haiku Deck to easily create engaging presentations.
Exception handling in mule
Mule has a way to handle exceptions called an "exception strategy" that allows you to associate an exception handling path with connectors, components, or entire models. The example shows configuring an exception strategy to redirect any invalid documents to an error folder using a file endpoint. It then validates an XML sample against an XML schema, which generates an error message when it encounters an invalid data element as expected.
Exception strategies in MuleSoft Anypoint Studio
Various exception strategies has been described and what are various ways of defining the exception strategies.
Mule expression component
These Slides explain the implementation of Expression component in Mule Esb with Slides and decent Examples with Explanation.
Message enricher in mule
The document discusses different ways to enrich messages in Mule including enriching flow variables, message headers, and using enricher tags. It provides examples of enriching payload with additional information from external resources like another flow, HTTP request, or static expression.
Mulesoft ppt
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.
Viewers also liked (8)
Similar to Mule exception strategies
A short introduction on error handling in anypoint studio
Mule provides options for handling errors through exception strategies. There are two categories of exceptions in Mule: system exceptions and messaging exceptions. System exceptions are handled by system exception strategies when no message is involved. Messaging exceptions are handled by messaging exception strategies when a message is being processed through a Mule flow and throws an exception. Messaging exception strategies can contain message processors and nested exception strategies to precisely handle exceptions. Each flow can contain one messaging exception strategy which can be a choice strategy referring to other nested strategies.
Mule exception strategies
Mule applications have two types of exceptions: system exceptions and messaging exceptions. System exceptions occur at the application level while no message is involved. Messaging exceptions occur when processing a message through a Mule flow. There are several exception strategies in Mule including catch, rollback, reference, and choice strategies. Catch strategies consume messages while rollback strategies roll messages back for reprocessing. Choice strategies handle exceptions based on message content.
Mule concepts exception strategies
Explains how the exceptions are handled in mule, what re the different exception strategies available, and what do they do.
Mule error handling
Mule provides options for handling errors called exceptions. There are two categories of exceptions in Mule: system exceptions which occur during application startup or connection failures, and are handled by system exception strategies; and messaging exceptions which occur within flows and are handled by messaging exception strategies. Mule supports five types of messaging exception strategies to handle errors in transactions: default, catch, choice, reference, and rollback strategies. It is best practice to create a global default exception strategy and add reference strategies in flows to refer to the global strategy.
Mule error handling
Mule ESB provides options for handling errors through exception strategies. The default exception strategy handles errors globally by rolling back transactions and logging exceptions. Additional exception strategies like catch, rollback, and choice strategies can be used to customize error handling for specific flows. Messaging exceptions are thrown when errors occur during message processing, while system exceptions handle errors outside of message processing like during application startup.
Error handling in mule
Mule ESB provides options to handle errors through exception strategies. The default exception strategy handles all messaging exceptions by rolling back transactions and logging exceptions. Users can configure alternative exception strategies like catch, rollback, reference, and choice strategies to customize error handling for different situations. Catch strategies always commit transactions after exceptions while rollback strategies attempt to redeliver messages before committing failed transactions. Reference strategies refer to global exception handling and choice strategies route messages based on content during exceptions. Exception strategies provide flexibility in how Mule applications manage errors and exceptions.
Mule errors
Mule ESB provides options for handling errors through exception strategies. The default exception strategy handles errors globally by rolling back transactions and logging exceptions. Alternative exception strategies like catch, rollback, and choice strategies allow more customized error handling. Catch strategies always commit transactions after exceptions while rollback strategies attempt to redeliver messages before committing. Choice strategies route messages based on content after exceptions.
Error handling with respect to mule
Mule ESB provides options for handling errors through exception strategies. The default exception strategy implicitly handles all messaging exceptions by rolling back transactions and logging exceptions. Alternative exception strategies include catch, which commits transactions and consumes messages; rollback, which attempts to redeliver messages before committing failed transactions; reference, which refers to a global exception strategy; and choice, which customizes error handling based on message content. Exception strategies provide flexible ways to manage errors within Mule applications and flows.
Mule error handling
This presentation provides an overview on Mule ESB's error handling capabilities. System and Messaging exception strategies are explained with examples in this presentation.
Handle exceptions in mule
Mule provides default exception handling but also allows custom exception strategies to implement more precise error management. Exception strategies include choice, catch, and rollback strategies. A rollback strategy reverts a message flow to an earlier state if an exception occurs during a transactional flow.
Mule exception strategies - Catch exception strategy
The document discusses exception handling strategies in Mule. It defines an exception as an event that disrupts normal program flow. Mule has different exception strategies, including catch exception strategy. The catch exception strategy commits transactions and consumes messages when exceptions are thrown. The document provides an XML code example of configuring a flow with a catch exception strategy that catches a divide by zero exception and routes it to a Java class for handling.
Mule exceptions Strategy
This document discusses how to handle exceptions in Mule applications. There are two types of exceptions: system exceptions which occur at the system level, and messaging exceptions which occur when messages are involved. By default, exceptions stop flow execution, log the exception, and roll back transactions. To continue execution, reconnection strategies can be used for system exceptions while messaging exception strategies specify custom exception handling. Messaging exception strategies contain catch, rollback, choice, reference, and custom handlers and can be defined globally for reuse in multiple flows.
Mule error handling_choice exception strategy
The choice exception strategy allows Mule to customize error handling for messages based on message content and exception type. It catches exceptions from its parent flow, evaluates the exception and message, then routes the message to the appropriate child exception strategy based on matching expressions. If no child matches, it uses the default strategy. It is useful for applying different error handling rules depending on exception type.
Vancouver mulesoft meetup_23-july
The document summarizes a presentation on Mule 4 exception handling and Munit. It covers error handling in Mule 4 including system errors, messaging errors, and the error hierarchy. It also discusses default error handling, creating error handlers, and differences between error handling in Mule 3 and 4. The presentation includes a demo of error handling and introduces Munit for testing Mule applications with capabilities like mocking and validating processors.
Online Spanish meetup #1
En este evento hablaremos sobre una introducción a Dataweave 2.0, que te puede ayudar mucho si eres nuevo a Mule 4 y quieres aprender la sintaxis. También se verá sobre las excepciones "on propagate" y "on continue", ya que es un tema que viene incluido en el examen de certificación para Mule 4 (Level 1), y que hemos notado que no es muy claro para muchos Muleys.
Mule error handling_rollback exception strategy
The document discusses the rollback exception strategy in Mule. A rollback exception strategy rolls back transactions when exceptions occur to allow messages to be reprocessed. It can be used for transactional errors or unhandled exceptions. A rollback strategy may cause infinite loops, so maximum redelivery attempts and error handling flows are recommended. Transactional transports like JDBC roll messages back to original state, while reliable transports discard messages and reprocess fresh copies. The strategy differs from the default exception strategy in how it handles message payloads and exceptions.
Mule exception handlingstrategies
Mule ESB provides robust exception handling capabilities with configurable exception strategies. There are two main categories of exceptions: system exceptions thrown during startup or connectivity issues, and messaging exceptions thrown during message processing. Developers can create global exception strategies to handle errors and reference those strategies from flows. The default exception strategy logs errors and rolls back transactions. Rollback strategies ensure messages that cause exceptions are requeued for reprocessing up to a configured limit.
Exception handling basics in mule
Exception handling in MULE involves messaging exception strategies and reference exception strategies. A messaging exception strategy contains message processors to handle exceptions thrown in flows. The default exception strategy automatically rolls back transactions and logs exceptions for messaging exceptions. A reference exception strategy allows applying a global exception strategy defined elsewhere to a specific flow. Rollback exception strategies ensure messages that cause exceptions are rolled back for reprocessing up to a configurable number of attempts.
Muleflowarchitecturepart2
The document discusses Mule Flow architecture and message processing. It describes how composite source scopes can embed multiple connectors to trigger flows. Message processors like filters and transformers can be combined using scopes to implement parallel processing and reusable sequences. Exception strategies determine how Mule responds to errors during message processing, and pre-packaged strategies handle exceptions at different points. Flows typically use an inbound endpoint as a message source, may include a filter and transformer, and allow sending messages to queues and calling other flows throughout.
1st Feb 2020 MuleSoft Meetup
MuleSoft Meetup Saturday 1st Feb 2020 which covers MuleSoft Overview, EAI Design patterns, Central Repository
Similar to Mule exception strategies (20)
A short introduction on error handling in anypoint studio
A short introduction on error handling in anypoint studio
Mule exception strategies - Catch exception strategy
Mule exception strategies - Catch exception strategy
More from Krishna_in
Mule maven Plugin
This short document promotes the creation of Haiku Deck presentations on SlideShare by stating "Inspired?" and providing a button to "GET STARTED" making your own Haiku Deck presentation. It encourages the reader to try making presentations on the Haiku Deck platform hosted on SlideShare in a concise and engaging manner using just two words and a call to action.
API Policies
This short document promotes the creation of Haiku Deck presentations on SlideShare by stating "Inspired?" and providing a button to "GET STARTED" making your own Haiku Deck presentation. It encourages the reader to try making presentations on the Haiku Deck platform hosted on SlideShare in a concise and engaging manner using just two words and a call to action.
Data Weave
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 the idea of using Haiku Deck to easily create and publish online presentations.
Splitter flow control reference
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.
Scatter gather flow control
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.
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.
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.
Cloud hub
CloudHub is a Platform as a Service (PaaS) that allows users to integrate SaaS applications, cloud services, and enterprise applications in real-time. It is built on Mule, the most widely used integration platform, and provides a scalable architecture that can be used to build integration applications. CloudHub also allows users to manage applications in the cloud as well as servers located on-premises. It offers predefined connectors to popular services, an API for automation, and management of applications from an intuitive console.
Cloud hub architecture
CloudHub is an integration platform as a service (iPaaS) that provides a multi-tenant, secure, elastic, and highly available integration platform. It includes three major components: the management console, platform services, and worker clouds. Integration applications are run on workers located in global worker clouds for scalability and high availability, with redundant platform services and zero downtime updates.
Anypoint platform for api
Anypoint Platform for APIs and Anypoint Data Gateway allow integration of data between legacy systems and Salesforce. Anypoint Data Gateway installs as a Salesforce app and provides a point-and-click interface to access external data sources like SAP, Oracle, and SQL from within Salesforce. It supports instant connection to external systems by configuring host, user, etc. parameters and publishing the gateway to specified entities.
More from Krishna_in (20)
Recently uploaded
Fueling AI with Great Data with Airbyte Webinar
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Artificial Intelligence for XMLDevelopment
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
Generating privacy-protected synthetic data using Secludy and Milvus
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.
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
CAKE: Sharing Slices of Confidential Data on Blockchain
Presented at the CAiSE 2024 Forum, Intelligent Information Systems, June 6th, Limassol, Cyprus.
Synopsis: Cooperative information systems typically involve various entities in a collaborative process within a distributed environment. Blockchain technology offers a mechanism for automating such processes, even when only partial trust exists among participants. The data stored on the blockchain is replicated across all nodes in the network, ensuring accessibility to all participants. While this aspect facilitates traceability, integrity, and persistence, it poses challenges for adopting public blockchains in enterprise settings due to confidentiality issues. In this paper, we present a software tool named Control Access via Key Encryption (CAKE), designed to ensure data confidentiality in scenarios involving public blockchains. After outlining its core components and functionalities, we showcase the application of CAKE in the context of a real-world cyber-security project within the logistics domain.
Paper: https://doi.org/10.1007/978-3-031-61000-4_16
Presentation of the OECD Artificial Intelligence Review of Germany
Consult the full report at https://www.oecd.org/digital/oecd-artificial-intelligence-review-of-germany-609808d6-en.htm
Infrastructure Challenges in Scaling RAG with Custom AI models
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
Removing Uninteresting Bytes in Software Fuzzing
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.
Programming Foundation Models with DSPy - Meetup Slides
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
20240607 QFM018 Elixir Reading List May 2024
Everything I found interesting about the Elixir programming ecosystem in May 2024
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Video Streaming: Then, Now, and in the Future
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.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
TrustArc Webinar - 2024 Global Privacy Survey
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Essentials of Automations: The Art of Triggers and Actions in FME
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!
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
ここ3000字までしか入らないけどタイトルの方がたくさん文字入ると思います。
Recently uploaded (20)
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
Generating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and Milvus
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift.pdf
CAKE: Sharing Slices of Confidential Data on Blockchain
CAKE: Sharing Slices of Confidential Data on Blockchain
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
Infrastructure Challenges in Scaling RAG with Custom AI models
Infrastructure Challenges in Scaling RAG with Custom AI models
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Essentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FME
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
Mule exception strategies
- 2. • Mule provides numerous options for handling errors. Errors, or faults, that occur within Mule are referred to as exceptions; when an activity in your Mule instance fails, Mule throws an exception. To manage these exceptions, Mule allows you to configure exception strategies. • Mule’s default exception strategy — which implicitly applies to all Mule applications — manages errors (such as, thrown exceptions) in Mule flows. When your flows require more sophisticated error management, you can implement one or more exception strategies to construct precise, efficient protocols for handling errors.
- 3. • From a high level perspective, errors that occur in Mule fall into one of two categories: • System Exceptions • Messaging Exceptions.
- 4. System Exceptions • Mule invokes a System Exception Strategy when an exception is thrown at the system-level (i.e., when no message is involved, exceptions are handled by system exception strategies). For example, system exception strategies handle exceptions that occur: • During application start-up • When a connection to an external system fails
- 5. Messaging Exceptions • Mule invokes a Messaging Exception Strategy whenever an exception is thrown within a flow. Whenever a message is involved, exceptions are handled by messaging exception strategies. • When a message being processed through a Mule flow throws an exception, normal flow execution stops. Mule transfers the message to the message processor sequence within the exception strategy.
- 6. • You can incorporate any number of message processors into an exception strategy to handle the exception precisely as you wish. The diagram below illustrates what happens when a message throws an exception.
- 7. Characteristics of Messaging Exception Strategies • Each flow can contain only one exception strategy. • Each exception strategy can contain any number of message processors. • Choice exception strategies can contain one or more catch and/or rollback exception strategies. (Rollback and catch exception strategies cannot, however, contain other exception strategies.) • You can create one or more global exception strategies to reuse in flows throughout your entire Mule application.