Bye Bye Batch, Hallo Events: Der Kafka-Weg von SIEMENS in die Cloud

Data in Motion Tour Frankfurt

Software

Product master data
streaming
public | © Siemens 2022 | Stefan Baer | DI IT DSP CIC GP | 2022-09-13

PMDS – Product Master Data Streaming
public | © Siemens 2022 | Stefan Baer | DI IT DSP CIC GP | 2022-09-13
Page 2
• Product Master Data provisioning the next level
• Event-based data streaming supersedes batch
• Easy connecting Producer & Consumer
• Main Producer
• Complex and grown SAP System running on high load
• Additional interfaces increase load
• Consumers
• regional salessystems
• Product master data provisioning System (eCatalog)
• Siemens MALL
• …

Batch to data streaming – As is
Spaghetti to Kafka
public | © Siemens 2022 | Stefan Baer | DI IT DSP CIC GP | 2022-09-13
Page 3
Regional sale system
Product
master
data
IT Systems
BU Systems
Producer systems Consumer systems
Monthly /weekly updates
Online Request
Delta Batch Delta Batch (weekly/daily)
Online Request
Online Request Replication
System
Generation of daily/weekly update
files
Handling interfaces for multiple
consumers
Transforming data
Generation of daily/weekly update
files
Online requests forwarded for
missing products only
Importing daily/weekly update files
Online requests (Also same data
multiple times)

Batch to data streaming – Step 1
Spaghetti to Kafka
public | © Siemens 2022 | Stefan Baer | DI IT DSP CIC GP | 2022-09-13
Page 4
Regional sale system
On Demand
Update Feeds
Online Request
eCatalog generation
Product
master
data
IT Systems
BU Systems
integration
intermediary
Producer systems Consumer systems
Generation of daily update files
Using existing interfaces
Integration Intermediary
- Transforming data
- Pushing data to Topics
- Handling on demand requests
- Reducing online requests
Decreased response time for on
demand request for products
already in Kafka

Batch to data streaming – Step 2
Spaghetti to Kafka
public | © Siemens 2022 | Stefan Baer | DI IT DSP CIC GP | 2022-09-13
Page 5
Regional sale system
On Demand
Update Feeds
Online Request
eCatalog generation
Product
master
data
IT Systems
BU Systems
integration
intermediary
Producer systems Consumer systems
Confluent
Cloud
&
Datastore
Subscribe to Datastore Topics
Generation and collection of
updated product master data on
daily basis
Provided via new direct connection
Handling one consumer
Integration Intermediary
- Transforming data
- Pushing data to Topics
- Handling on demand requests
Confluent Cloud
- Easy migration via replicator
Decreased response time for on
demand request for products
already in Kafka
Consumer subscribe to topics and
receive updated products
immediately after processing by
integration intermediary

Published by Siemens 2022 LinkedIn
Stefan Baer
Solution Specialist
DI IT DSP CIC GP
Gleiwitzer Str. 555
90475 Nürnberg
Germany
Mobile +49 173 281 08 19
E-mail baer.stefan@siemens.com
public | © Siemens 2022 | Stefan Baer | DI IT DSP CIC GP | 2022-09-13
Page 6

James Gollan, Confluent, Senior Solutions Engineer From digital banking to industry 4.0 the nature of business is changing. Increasingly businesses are becoming software. And the lifeblood of software is data. Dealing with data at the enterprise level is tough, and their have been some missteps along the way. This session will consider the increasingly popular idea of a 'data mesh' - the problems it solves and, perhaps most importantly, how an event streaming platform forms the bedrock of this new paradigm. Recording to be available cnfl.io/meetup-hub https://www.meetup.com/KafkaMelbourne/events/277076626/

Evolution from EDA to Data Mesh: Data in Motion

Thoughtworks Zhamak Dehghani observations on these traditional approaches’s failure modes, inspired her to develop an alternative big data management architecture that she aptly named the Data Mesh. This represents a paradigm shift that draws from modern distributed architecture and is founded on the principles of domain-driven design, self-serve platform, and product thinking with Data. In the last decade Apache Kafka has established a new category of data management infrastructure for data in motion that has been leveraged in modern distributed data architectures.

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An important underlying concept behind location-based applications is called geofencing. Geofencing is a process that allows acting on users and/or devices who enter/exit a specific geographical area, known as a geo-fence. A geo-fence can be dynamically generated—as in a radius around a point location, or a geo-fence can be a predefined set of boundaries (such as secured areas, buildings, boarders of counties, states or countries). Geofencing lays the foundation for realizing use cases around fleet monitoring, asset tracking, phone tracking across cell sites, connected manufacturing, ride-sharing solutions and many others. GPS tracking tells constantly and in real time where a device is located and forms the stream of events which needs to be analyzed against the much more static set of geo-fences. Many of the use cases mentioned above require low-latency actions taken place, if either a device enters or leaves a geo-fence or when it is approaching such a geo-fence. That’s where streaming data ingestion and streaming analytics and therefore the Kafka ecosystem comes into play. This session will present how location analytics applications can be implemented using Kafka and KSQL & Kafka Streams. It highlights the exiting features available out-of-the-box and then shows how easy it is to extend it by custom defined functions (UDFs). The design of such solution so that it can scale with both an increasing amount of position events as well as geo-fences will be discussed as well.

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A talk presented by Max Schultze from Zalando and Arif Wider from ThoughtWorks at NDC Oslo 2020. Abstract: The Data Lake paradigm is often considered the scalable successor of the more curated Data Warehouse approach when it comes to democratization of data. However, many who went out to build a centralized Data Lake came out with a data swamp of unclear responsibilities, a lack of data ownership, and sub-par data availability. At Zalando - europe’s biggest online fashion retailer - we realised that accessibility and availability at scale can only be guaranteed when moving more responsibilities to those who pick up the data and have the respective domain knowledge - the data owners - while keeping only data governance and metadata information central. Such a decentralized and domain focused approach has recently been coined a Data Mesh. The Data Mesh paradigm promotes the concept of Data Products which go beyond sharing of files and towards guarantees of quality and acknowledgement of data ownership. This talk will take you on a journey of how we went from a centralized Data Lake to embrace a distributed Data Mesh architecture and will outline the ongoing efforts to make creation of data products as simple as applying a template.

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Streaming all over the World: Real-Life Use Cases & Architectures for Event Streaming with Apache Kafka. Learn about various case studies for event streaming with Apache Kafka across industries. The talk explores architectures for real-world deployments from Audi, BMW, Disney, Generali, Paypal, Tesla, Unity, Walmart, William Hill, and more. Use cases include fraud detection, mainframe offloading, predictive maintenance, cybersecurity, edge computing, track&trace, live betting, and much more.

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Data is increasingly becoming core to many products. Whether to provide recommendations for users, getting insights on how they use the product, or using machine learning to improve the experience. This creates a critical need for reliable data operations and understanding how data is flowing through our systems. Data pipelines must be auditable, reliable, and run on time. This proves particularly difficult in a constantly changing, fast-paced environment. Collecting this lineage metadata as data pipelines are running provides an understanding of dependencies between many teams consuming and producing data and how constant changes impact them. It is the underlying foundation that enables the many use cases related to data operations. The OpenLineage project is an API standardizing this metadata across the ecosystem, reducing complexity and duplicate work in collecting lineage information. It enables many projects, consumers of lineage in the ecosystem whether they focus on operations, governance or security. Marquez is an open source project part of the LF AI & Data foundation which instruments data pipelines to collect lineage and metadata and enable those use cases. It implements the OpenLineage API and provides context by making visible dependencies across organizations and technologies as they change over time.

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Dominate Social Media with TubeTrivia AI’s Addictive Quiz Videos https://www.amb-review.com/tubetrivia-ai Exclusive Features: AI-Powered Questions, Wide Range of Categories, Adaptive Difficulty, User-Friendly Interface, Multiplayer Mode, Regular Updates. #TubeTriviaAI #QuizVideoMagic #ViralQuizVideos #AIQuizGenerator #EngageExciteExplode #MarketingRevolution #BoostYourTraffic #SocialMediaSuccess #AIContentCreation #UnlimitedTraffic

Enterprise Resource Planning System in Telangana

NYGGS Automation Suite

Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics. To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/

Climate Science Flows: Enabling Petabyte-Scale Climate Analysis with the Eart...

The Earth System Grid Federation (ESGF) is a global network of data servers that archives and distributes the planet’s largest collection of Earth system model output for thousands of climate and environmental scientists worldwide. Many of these petabyte-scale data archives are located in proximity to large high-performance computing (HPC) or cloud computing resources, but the primary workflow for data users consists of transferring data, and applying computations on a different system. As a part of the ESGF 2.0 US project (funded by the United States Department of Energy Office of Science), we developed pre-defined data workflows, which can be run on-demand, capable of applying many data reduction and data analysis to the large ESGF data archives, transferring only the resultant analysis (ex. visualizations, smaller data files). In this talk, we will showcase a few of these workflows, highlighting how Globus Flows can be used for petabyte-scale climate analysis.

Cracking the code review at SpringIO 2024

Paco van Beckhoven

Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production. Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process? In this session we will cover: - The Art of Effective Code Reviews - Streamlining the Review Process - Elevating Reviews with Automated Tools By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces

Enhancing Project Management Efficiency_ Leveraging AI Tools like ChatGPT.pdf

Jay Das

Top Features to Include in Your Winzo Clone App for Business Growth (4).pptx

rickgrimesss22

Globus Compute wth IRI Workflows - GlobusWorld 2024

As part of the DOE Integrated Research Infrastructure (IRI) program, NERSC at Lawrence Berkeley National Lab and ALCF at Argonne National Lab are working closely with General Atomics on accelerating the computing requirements of the DIII-D experiment. As part of the work the team is investigating ways to speedup the time to solution for many different parts of the DIII-D workflow including how they run jobs on HPC systems. One of these routes is looking at Globus Compute as a way to replace the current method for managing tasks and we describe a brief proof of concept showing how Globus Compute could help to schedule jobs and be a tool to connect compute at different facilities.

BoxLang: Review our Visionary Licenses of 2024

Ortus Solutions, Corp

First Steps with Globus Compute Multi-User Endpoints

In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.

Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...

The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.

Graphic Design Crash Course for beginners

e20449

OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoam

takuyayamamoto1800

Quarkus Hidden and Forbidden Extensions

Max Andersen

Enhancing Research Orchestration Capabilities at ORNL.pdf

Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.

Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...

Anthony Dahanne

Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ? Venez le découvrir lors de cette session ignite

AI Pilot Review: The World’s First Virtual Assistant Marketing Suite

Google

AI Pilot Review: The World’s First Virtual Assistant Marketing Suite 👉👉 Click Here To Get More Info 👇👇 https://sumonreview.com/ai-pilot-review/ AI Pilot Review: Key Features ✅Deploy AI expert bots in Any Niche With Just A Click ✅With one keyword, generate complete funnels, websites, landing pages, and more. ✅More than 85 AI features are included in the AI pilot. ✅No setup or configuration; use your voice (like Siri) to do whatever you want. ✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It… ✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again. ✅ZERO Limits On Features Or Usages ✅Use Our AI-powered Traffic To Get Hundreds Of Customers ✅No Complicated Setup: Get Up And Running In 2 Minutes ✅99.99% Up-Time Guaranteed ✅30 Days Money-Back Guarantee ✅ZERO Upfront Cost See My Other Reviews Article: (1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review (2) SocioWave Review: https://sumonreview.com/sociowave-review (3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review (4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review

Webinar: Salesforce Document Management 2.0 - Smarter, Faster, Better

XfilesPro

SOCRadar Research Team: Latest Activities of IntelBroker

SOCRadar

The European Union Agency for Law Enforcement Cooperation (Europol) has suffered an alleged data breach after a notorious threat actor claimed to have exfiltrated data from its systems. Infamous data leaker IntelBroker posted on the even more infamous BreachForums hacking forum, saying that Europol suffered a data breach this month. The alleged breach affected Europol agencies CCSE, EC3, Europol Platform for Experts, Law Enforcement Forum, and SIRIUS. Infiltration of these entities can disrupt ongoing investigations and compromise sensitive intelligence shared among international law enforcement agencies. However, this is neither the first nor the last activity of IntekBroker. We have compiled for you what happened in the last few days. To track such hacker activities on dark web sources like hacker forums, private Telegram channels, and other hidden platforms where cyber threats often originate, you can check SOCRadar’s Dark Web News. Stay Informed on Threat Actors’ Activity on the Dark Web with SOCRadar!

Understanding Globus Data Transfers with NetSage