Mule is a lightweight Java-based ESB and integration platform that allows applications to connect and exchange data through message processing. Flows link together individual message processing elements to handle message receipt, processing, and routing. At its simplest, a flow is a sequence of message processing events where a message passing through may be transformed or have other operations performed. Flows support various configurations including subflows, synchronous flows, asynchronous flows, and batch jobs. Transformers convert message formats between different destinations and can rearrange or modify message fields using tools like DataWeave. Connectors function as endpoints to send and receive messages between flows and external data sources.
This document contains top 50 MuleSoft Interview questions for the MuleSoft software development job aspirants. Also, this helps, who are taking MCD API Design Associate exam.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
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Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
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The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
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Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
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This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
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2. • Mule, the runtime engine of Anypoint Platform, is a
lightweight Java-based enterprise service bus (ESB) and
integration platform that allows developers to connect
applications together quickly and easily, enabling them to
exchange data.
• Mule applications accept and process events
as messages through several message processors plugged
together in a flow.
3. A flow is the construct within which you link together several
individual elements to handle the receipt, processing, and
eventual routing of a message.
How flows look like?
4. • Select From mule pallete flow.
• Drag flow icon from mule pallete to message flow.
• Its looks like something
5. AT THE SIMPLEST LEVEL, FLOWS ARE SEQUENCES OF
MESSAGE-PROCESSING EVENTS. A MESSAGE THAT
ENTERS A FLOW MAY PASS THROUGH A WIDE
VARIETY OFPROCESSORS.
6. FLOW
. In general, a building block corresponds to an icon in the Anypoint Studio
GUI, which in turn represents a message source, processor, or component.
10. Asynchronous flows begin processing a message when triggered
by another flow. Since this type of flow does not need to return
data to the flow which triggered it, it can execute simultaneously
to its triggering flow.
11. A batch job is a top-level element in Mule which exists outside all Mule flows.
Batch jobs split large messages into records which Mule processes
asynchronously; just as flows process messages, batch jobs process records.
13. Transformers convert message payloads to formats expected by
their destinations. Mule ESB provides many standard
transformers, which you configure using predefined elements and
attributes in your Mule XML configuration file
The most powerful tool for transforming a message is
the DataWeave Transformer, which can not only change the
format of the message, but also rename, aggregate, split or
rearrange the fields in it in any way you desire.
14. CONFIGURING TRANSFORMERS-:YOU CAN
CONFIGURE A
transformer locally or globally. You configure a local transformer right
on the endpoint or in a flow or where you want to apply it, whereas you
configure a global transformer before
any <model> or <flow> elements in your Mule configuration file and
then reference it.
Chaining Transformers-:You can chain transformers together so
that the output from one transformer becomes the input for the next.
To chain transformers, you create a space-separated list of transformers
in thetransformer-refs or responseTransformer-refs attributes or by
creating multiple <transformer>elements as shown above.
TRANSFORMERS
15. ObjectToOutputHandler-: Converts a byte array into a String.
ObjectToString-: Returns human-readable output for various kinds of objects.
Useful for debugging.
StringAppendTransformer-: Appends a string to an existing string.
StringToObjectArray-: Converts a string to an object array. Use the
configuration element <string-to-byte-array-transformer>
17. CONNECTOR
All connectors can function as endpoints by sending and
receiving messages between flows or between a flow and some
other data source outside of Mule. Some connectors
are endpoint-based, meaning that you configure them either as
inbound or outbound endpoints in your flow, then specify other
operation logic within the configuration of that endpoint. Some
connectors are operation-based, meaning that they allow you to
invoke specific actions against an API, Web service, or database.