Distributed Locking in Mule
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Mule provides distributed locking capabilities through a lock factory that custom components can access programmatically to synchronize access to resources across a server cluster. With Mule's locks, code can be deployed to a single server or cluster without issues coordinating shared resources. Mule's locking system offers a simple API for components to use shared locks.
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Abstract
Concurrency is everywhere. Prior to Java 5, concurrency was difficult
and error prone. Since Java 5, it's far more prevalent in our
application code, and through time it's been lurking in open-source
frameworks and containers. Concurrency is also a fundamental part of
Shopzilla's web-site and services ecosystem.
Introduction
Rod Barlow from Shopzilla will explore a brief history of concurrency, and the key
concurrency features and techniques provided by the Java API since
Java 5. Topics covered include Immutability, Atomic References, Blocking
Queues, Locks and Deadlocks. Also covered is Concurrency in
Frameworks, and Shopzilla's Website Concurrency Framework, including
Thread Pools, Executors and Futures.
Object store
This document provides an example of how to use the Object Store Connector in Mule to store and retrieve data. It shows storing a Map containing key-value pairs in the object store using the <objectstore:store> element. It then retrieves the stored data using the <objectstore:retrieve> element and sets it as the payload to log and return the value.
Object store
This document provides an example of how to use the Object Store Connector in Mule to store and retrieve data. It shows storing a Java map containing key-value pairs in the object store using the <objectstore:store> element. It then retrieves data from the object store using the <objectstore:retrieve> element based on a query parameter sent in the HTTP request.
Abhishek Kumar - CloudStack Locking Service
Abhishek Kumar proposes developing a new locking service, manager, and pluggable interface for CloudStack to enable high availability of the CloudStack database. The new service would use distributed lock managers like ZooKeeper or Hazelcast to allow for multi-master database replication. Currently, CloudStack uses MySQL locks that do not support database clustering solutions. A distributed locking approach would allow the database to be clustered for active-active or active-passive configurations. Abhishek then discusses database locking, distributed locking, ZooKeeper, and Hazelcast as potential implementations and demonstrates a proof of concept using ZooKeeper and Hazelcast before considering future work.
Mule soft ppt
This document provides an overview of MuleSoft and Mule cloud integration platform. It discusses key features of Mule such as drag-and-drop design, pre-built connectors, and one-click deployments. The document also describes Mule architecture, components including flows, message sources and processors. It lists the various supported technologies for transport, web services, middleware, databases and security. Finally, it provides a high-level description of Mule Cloud Hub which offers a fully-managed integration platform as a service.
Ahmedabad MuleSoft Meetup #4
The document summarizes the agenda and key topics for the MuleSoft Meetup #4 in Ahmedabad on August 3rd, 2019. The meetup included:
1) A introduction and overview of migrating applications from Mule 3 to Mule 4.
2) A presentation on Anypoint Runtime Manager, MuleSoft's platform for deploying and managing APIs and integrations.
3) A Q&A session.
4) Discussion of the topic for the next meetup and refreshments.
The document then provides more details on selected migration challenges from Mule 3 to Mule 4, such as changes to the event structure and classloading model in Mule 4. It
Introduction testingmule
The document discusses different types of software testing for Mule applications, including unit testing, integration testing, and functional testing. It provides details on unit testing individual units of code in isolation. Integration testing involves combining units of code and testing them as a group. Functional testing uses the FunctionalTestCase class to test Mule flows by starting an embedded Mule server within a test case.
.NET: Thread Synchronization Constructs
This document discusses various thread synchronization constructs in .NET. It begins with an overview of threads and multithreading concepts. It then covers challenges in sharing data between threads and ensuring thread safety. The document proceeds to explain common synchronization constructs like locks, mutexes, semaphores, and event wait handles. It also discusses atomic interlocked operations and hybrid constructs like concurrent collections. Examples are provided for many of the synchronization primitives.
Cmm vm 002
2:00 PM Check In, Welcome & Intro
2:15 PM Using Secured Properties in Mule 4
3:15 PM Thread Pools with Mule 4.3 (Uber & Dedicated Scheduling Strategy)
4:00 PM Networking, Wrapup and planning for next meetup
JBCNConf: jBPM & Vert.x Reactive and Polyglot BPM
This document discusses polyglot and reactive jBPM. It introduces jBPM, a lightweight Java process engine that can be embedded in applications. It also introduces Vert.x, an event-driven application framework that allows building reactive applications. The document discusses how jBPM can be integrated with Vert.x to build polyglot and reactive business processes. It provides an overview of a demo that will illustrate polyglot interactions with jBPM using different languages, reactive processes using an event bus, and integration with jBPM tooling.
MuleSoft Meetup Charlotte 2 - 2019
The document summarizes an agenda for a MuleSoft meetup in Charlotte on custom connectors in Mule 4. The meetup will include introductions, then three technical sessions: the first on creating custom connectors in Mule 4, the second on error handling in Mule 4, and the third on API gateways and security models. An open discussion period will follow. The document provides details on the prerequisites and types of connectors that can be created with the Mule SDK and differences from the older DevKit. It also outlines the basic elements of a Mule connector like operations, configurations, and parameters.
Concurrency Utilities Overview
The Java 2 platform includes a new package of concurrency utilities that are designed to simplify building concurrent applications. The concurrency utilities provide commonly used building blocks such as thread pools, asynchronous task execution frameworks, concurrent collections, atomic variables, locks, and condition variables. Using these utilities reduces programming effort, improves performance, reliability, maintainability and productivity when building concurrent applications compared to developing these components from scratch. The concurrency utilities package aims to make concurrent programs clearer, shorter, faster, more reliable, scalable, easier to write, read and maintain.
Mule overview
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.
Mule
Mule ESB is a lightweight Java-based integration platform that allows applications to connect and exchange data. It acts as an integration bus carrying data between applications within or across organizations. Mule enables easy integration of existing systems regardless of technology and provides capabilities like service creation, mediation, routing, and transformation. When integrating 3 or more applications that may need to connect more applications or use different protocols, or requiring capabilities like routing or publishing services, an ESB like Mule can help. Mule provides advantages over competitors like scalability, reusability, and ability to integrate existing components without changes.
Sai mule esb batch
Mule ESB is a lightweight Java-based enterprise service bus and integration platform that allows developers to connect applications together quickly and easily, enabling data exchange between applications. It provides capabilities like service creation and hosting, service mediation, message routing, and data transformation to integrate existing systems regardless of technology. Mule ESB evaluates whether an ESB is needed based on factors like integrating multiple applications, supporting future application integration, requiring different communication protocols, and needing message routing capabilities.
Esb process
Mule ESB is a lightweight Java-based integration platform that allows applications to connect and exchange data. It acts as an integration bus carrying data between applications within or across organizations. Mule enables easy integration of existing systems regardless of technology and provides capabilities like service creation, mediation, routing, and transformation. When integrating 3 or more applications that may need to connect with more in the future or use different communication protocols, an ESB like Mule can provide scalability, reuse, and separation of concerns.
Ashok mule esb
Mule ESB is a lightweight Java-based integration platform that allows applications to connect and exchange data. It acts as an integration bus carrying data between applications within or across organizations. Mule enables easy integration of existing systems regardless of technology and provides capabilities like service creation, mediation, routing, and transformation. When integrating 3 or more applications that may need to connect more applications or use different protocols, or requiring message routing, Mule can provide an advantage over custom coding.
Mule esb
Mule ESB is a lightweight Java-based integration platform that allows applications to connect and exchange data. It acts as a transit system carrying data between applications within or across organizations. Mule enables integration regardless of technology and provides capabilities like service creation, mediation, routing, and transformation. When integrating 3 or more applications that may need to connect more in the future or use different protocols, an ESB like Mule can help with its scalability and reusable components. Mule Studio provides a graphical interface to design integration flows by connecting message sources, processors, and connectors.
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IP Based Security Filter in Mule
The IP Based Security Filter in Mule evaluates message properties like IP address and creation timestamp against configured parameters. If the IP address falls outside the allowed range or the timestamp shows the message is older than expected, Mule will not process the message. It can filter by specific IP, an IP range, or a CIDR IP range to control which messages are allowed through the flow.
Time based Security Filter in Mule
The Time Based Security Filter in Mule evaluates message properties like IP address and creation timestamps against configured parameters, rejecting messages that fall outside the allowed ranges to prevent processing. It checks that the IP address is within an allowed address range and that the message creation time is not older than the filter's maximum lifespan configuration. The filter provides security by only allowing in messages from authorized sources and dropping expired messages.
Parallel processing for splitter in mule esb
The Splitter Flow Control splits messages into fragments and sends them one by one to the next processor. This document describes encapsulating the Splitter and Aggregator within virtual machine endpoints to process fragments in parallel threads. Both endpoints are wrapped in a Request-Reply component to wait for asynchronous processes to complete and return the combined response.
Start stop mule flow using java
This document discusses starting and stopping Mule flows using Java. It describes using the MuleContext and Callable interface to control the lifecycle of flows. The document shows how to get a flow object from the MuleContext registry and then use it to start or stop the flow. It provides an example of a Java component that implements Callable to start a flow that is initially stopped on application deployment.
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This document discusses how to find the number of VM messages using a Java component in Mule. It uses an HTTP inbound endpoint, stores messages in a VM queue named "sunil", and implements a Callable Java class that injects the MuleContext and uses it to get the size of the VM queue.
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Custom transformer and annotation
The document discusses how to create custom transformers in Mule by writing Java code. It provides examples of creating a Student POJO class, a custom transformer that extends AbstractMessageTransformer to transform the payload, and using annotations like @ContainsTransformerMethods and @Transformer to mark a class and methods as custom transformers available in Mule. The custom transformers allow incorporating custom Java operations into Mule flows to transform data as needed beyond the standard components.
Custom processor
We can create custom processors in Mule that implement the MessageProcessor interface and override the process method. This allows processing of Mule events by passing them through custom classes that can access and modify the event payload according to business logic. The custom processor is added to the flow using the custom-processor element.
Signature Security mule
Mule adds digital signatures to messages to verify sender authenticity. It supports JCE and XML signing strategies. To sign data, Mule converts the payload to bytes, applies the signature, and stores the result. Verification compares a provided signature to the signed content. Configuration specifies the signer and signing algorithm and key. Flows demonstrate signing data on request and verifying a signature.
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Presented by Vladimir Iglovikov:
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Distributed Locking in Mule
- 1. Distributed Locking Mule Mule provides the ability to create locks for synchronizing access to resources within Mule components. To manage concurrent access to resources within a server cluster, Mule provides a lock factory which custom components – such as custom transformers and DevKit-built components – access programmatically. With the locks in place, you can deploy code in a single mule server or a Mule cluster without causing any issues with resource synchronization. Further, Mule’s locking system offers a simple API to access shared locks.
- 2. Distributed Locking Mule - Flow
- 3. Distributed Locking Mule - Java
- 4. Distributed Locking Mule – Flow Contd… • Business logic inside try block will be executed Synchronously • Java Transform component to apply locking • Extends “AbstractMessageTransformer” (org.mule.transformer.AbstractMessageTransformer) to access muleContext Object • Create Lock (java.util.concurrent.locks.Lock) Object for lockid “1234” • Used lock() to get lock • Used unlock() to release the lock
- 5. Distributed Locking Mule - XML
- 6. Distributed Locking Mule - XML