Cloud hub scalability and availabilityShanky Gupta
Mulesoft cloubhub scalability and availability. Continuation of presentation CloudHub architecture from http://www.slideshare.net/ShankyGupta7/cloud-hub-architecture-63765847
Cloud hub scalability and availabilityShanky Gupta
Mulesoft cloubhub scalability and availability. Continuation of presentation CloudHub architecture from http://www.slideshare.net/ShankyGupta7/cloud-hub-architecture-63765847
On a business level, everyone wants to get hold of the business value and other organizational advantages that big data has to offer. Analytics has arisen as the primitive path to business value from big data. Hadoop is not just a storage platform for big data; it’s also a computational and processing platform for business analytics. Hadoop is, however, unsuccessful in fulfilling business requirements when it comes to live data streaming. The initial architecture of Apache Hadoop did not solve the problem of live stream data mining. In summary, the traditional approach of big data being co-relational to Hadoop is false; focus needs to be given on business value as well. Data Warehousing, Hadoop and stream processing complement each other very well. In this paper, we have tried reviewing a few frameworks and products
which use real time data streaming by providing modifications to Hadoop.
A whitepaper is about How big data engines are used for exploring and preparing data, building pipelines, and delivering data sets to ML applications.
https://www.qubole.com/resources/white-papers/big-data-engineering-for-machine-learning
HMR LOG ANALYZER: ANALYZE WEB APPLICATION LOGS OVER HADOOP MAPREDUCEijujournal
In today’s Internet world, log file analysis is becoming a necessary task for analyzing the customer’s
behavior in order to improve advertising and sales as well as for datasets like environment, medical,
banking system it is important to analyze the log data to get required knowledge from it. Web mining is the
process of discovering the knowledge from the web data. Log files are getting generated very fast at the
rate of 1-10 Mb/s per machine, a single data center can generate tens of terabytes of log data in a day.
These datasets are huge. In order to analyze such large datasets we need parallel processing system and
reliable data storage mechanism. Virtual database system is an effective solution for integrating the data
but it becomes inefficient for large datasets. The Hadoop framework provides reliable data storage by
Hadoop Distributed File System and MapReduce programming model which is a parallel processing
system for large datasets. Hadoop distributed file system breaks up input data and sends fractions of the
original data to several machines in hadoop cluster to hold blocks of data. This mechanism helps to
process log data in parallel using all the machines in the hadoop cluster and computes result efficiently.
The dominant approach provided by hadoop to “Store first query later”, loads the data to the Hadoop
Distributed File System and then executes queries written in Pig Latin. This approach reduces the response
time as well as the load on to the end system. This paper proposes a log analysis system using Hadoop
MapReduce which will provide accurate results in minimum response time.
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.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
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
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
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.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
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
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.
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.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
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.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
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.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
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.
2. 2
Batch Processing in Mule
Batch is a Mule construct that provides the ability to process messages in
batches. Within an application, you can initiate a batch job which is a block
of code that splits messages into individual records, performs actions upon
each record, then reports on the results and potentially pushes the
processed output to other systems or queues.
3. 3
Batch processing is particularly useful when working with the following
scenarios:
Integrating data sets, small or large, streaming or not, to parallel process
records
Synchronising data sets between business applications, such as syncing
contacts between Netsuite and Salesforce, effecting “near real-time”data
integration
Extracting, transforming and loading (ETL) information into a target system,
such as uploading data from a flat file (CSV) to Hadoop
Handling large quantities of incoming data from an API into a legacy
system
5. 5
Learn Batch Fundamentals
Mule’s December 2013 release shipped with a major leap forward feature
that will massively change and simplify Mule’s user experience for both
SaaS and On-Premise users. Yes, we are talking about the new Batch
jobs. If you need to handle massive amounts of data, or you’re longing for
record based reporting and error handling, or even if you are all about
resilience and reliability with parallel processing, then this post is for you!
6. 6
What's new in Batch
We received great feedback about it and we even have some CloudHub
users happily using it in production! However, we know that the journey of
Batch has just begun and for the Early Access release of Mule 3.5 we
added a bunch of improvements.
Let’s have a look!
https://www.mulesoft.com/exchange#!/batch-process-mule?
filters=Business%20Process%20Administration
7. 7
Error handling in Batch
Fact: Batch Jobs are tricky to handle when exceptions raise. The problem
is the huge amounts of data that these jobs are designed to take. If you’re
processing 1 million records you simply can’t log everything. Logs would
become huge and unreadable. Not to mention the performance toll it would
take. On the other hand, if you log too little then it’s impossible to know
what went wrong, and if 30 thousand records failed, not knowing what’s
wrong with them can be a royal pain. This is a trade-off not simple to
overcome.
8. 8
Near real time sync with Batch
Learn how to do Real time sync with Mule ESB. We’ll use several of the
newest features that Mule has to offer – like the improved Poll component
with watermarking and the Batch Module. Finally we’ll use one of our
Anypoint Templates as an example application to illustrate the concepts.