Mule applications use flows and batch jobs to process messages. Flows contain a series of message processors that accept and process messages as they flow through. Batch jobs split large messages into individual records and process them asynchronously through batch steps. The key components of flows and batch jobs are message sources that input messages, message processors that transform or route messages, and connectors that integrate with external systems.
This presentation discusses Mule ESB and how to simplify integration. It briefly mentions a brief history of integration, information silos, SOA. It also highlights several integration patterns.
Summer School: Achievements and Applications of Contemporary Informatics, Mat...YSF-2015
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Presented by Sandra Yaremchuk,
Student Science Association of National Technical University "Kyiv Polytechnic Institute", at the Workshop of Opportunities, the satellite meeting of the International Young Scientists Forum on Applied Physics YSF-2015
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
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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.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
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A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
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Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
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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.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
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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:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
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Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
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In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
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Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
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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.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
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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.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
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Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
2. • Based on the concept of Event Driven Architecture
(EDA).
• Works by responding to messages initiated by
external resources (such as, events).
• Mule applications accept and process events
as messages through several message processors
plugged together in a flow.
• Large or streaming messages can be processed
as records in a batch job.
Mule Concepts : Intro
3. • Every Mule flow contains a series of message
processors that accept, then process messages.
• Mule applications usually contain multiple linked
flows and/or batch jobs.
• These applications perform the integration required
for the use case.
Mule Concepts : Intro
4. Mule Concepts : Intro
• Every Mule Applications can consists of below :
– Flows
– Batch Jobs
5. Mule Concepts : Flows
• A flow is the construct within which you link
together several individual elements to handle the
receipt, processing, and eventual routing of a
message.
• Flows are sequences of message-processing events.
• A message that enters a flow may pass through a
wide variety of processors.
• Multiple flows can be connected together to build a
complete application.
6. Mule Concepts : Flows
• As shown in below diagram, each flow consists of:
– Message Source
– Message Processors
7. Mule Concepts : Batch Jobs
• A top-level element in Mule that exists outside all
Mule flows.
• provides record I/O for Mule message processing.
• Batch jobs split large messages into records which
Mule processes asynchronously.
• Just as flows process messages, batch jobs process
records.
8. Mule Concepts : Batch Jobs
• Contains one or more batch steps.
• Each batch step contains any number of message
processors that act upon records as they move
through the batch job.
• record-level variables (recordVars) and MEL (Mule
Expression Language) expressions to enrich, route or
otherwise act upon records.
9. Mule Concepts : Batch Jobs
• A batch job is executes when :
– Triggered by a batch executor in a Mule flow, or
– Message source in a batch-accepting input.
• When triggered, Mule creates a new batch job
instance.
• Once every record has passed through all batch
steps, the batch job instance ends and the batch job
result can be summarized in a report.
• Report indicates which records succeeded and which
failed.
10. Mule Concepts : Message Sources
• Mule processes messages, also known as events,
which may be transmitted from resources external to
Mule.
• First building block of most flows or batch jobs is a
message receiver.
• Receiver receives new messages and places them in
the queue for processing.
• These Receivers are the Message Sources.
• Message Sources on receiving of the messages from
one or more external sources trigger the execution of
the flow or the batch job.
11. Mule Concepts : Message Sources
• Message sources in Mule are usually Anypoint
Connectors.
• Anypoint Connectors elements provide
connectivity to a specific external source.
• The connectivity is provided via a standard
protocol (such as HTTP, FTP, SMTP) or a third-
party API (such as Salesforce.com, Twitter, or
MongoDB.)
12. Mule Concepts : Message Processors
• Mule processors are the elements which acts on the
received messages and perform operations to modify
the message or to create a new one.
• In Mule, message processors are grouped together
by category.
13. Mule Concepts : Message Processors
• Message Processors are grouped in below categories:
– Message Transformers :
• key to exchanging data between nodes
• Allow Mule to convert message payload data to a format that another application
can understand.
• Through Message Enrichers Mule enables to retrieve additional data during
processing and attach it to the message.
– Components :
• To conduct backend processes for specific business logic.
• Components route messages to the correct application.
• Components don’t have to have any Mule-specific code.
• They can simply be POJOs, Spring beans, Java beans, Groovy scripts, or web
services containing the business logic for processing data.
• Components can even be developed in other languages such as Python, JavaScript,
Ruby, and PHP.
14. Mule Concepts : Message Processors
• Message Processors are grouped in below categories:
– Filters :
• To filter out the messages based on the set criteria.
– Scopes :
• To "wrap" around several message processors together as a single unit.
E.g. Cache the result of the processing they perform
– Routers :
• To send messages down different paths in your application depending on the
content of the message payload.
– Mainly Mule Expression Language is used to
extract information about the message or its
environment and instruct Mule to make
processing decisions based on that information.