Kai Waehner [Confluent] | Real-Time Streaming Analytics with 100,000 Cars Using MQTT, Kafka and InfluxDB 2.0 on Kubernetes | InfluxDays Virtual Experience London 2020
Kai Waehner [Confluent] | Real-Time Streaming Analytics with 100,000 Cars Using MQTT, Kafka and InfluxDB 2.0 on Kubernetes | InfluxDays Virtual Experience London 2020
IoT Architectures for a Digital Twin with Apache Kafka, IoT Platforms and Mac...Kai Wähner
A digital twin is a digital replica of a living or non-living physical entity. This session discusses the benefits and IoT architectures of a Digital Twin in Industrial IoT (IIoT) and its relation to Apache Kafka, IoT frameworks and Machine Learning. Kafka is often used as central event streaming platform to build a scalable and reliable digital twin for real time streaming sensor data. A live demo shows a scalable digital twin infrastructure for condition monitoring and predictive maintenance in real time for a connected car infrastructure leveraging Kafka, MQTT and TensorFlow.
Key Take-Aways:
• Learn about use cases and characteristics of a digital twin in various industries
• Understand how to build a digital twin for every single (of tens of thousands) IoT device or machine
• See different IoT architectures with Kafka and other IoT technologies and products, including edge, hybrid and global deployments
• Understand the relation to Machine Learning and bring added value to your IoT infrastructure by enabling use cases like predictive maintenance
• Understand how the Apache Kafka enables scalable and flexible end-to-end integration processing from IIoT data to various backend applications
• Watch a live demo of an end-to-end integration, real time processing and analytics of thousands of IoT devices
More details:
https://www.kai-waehner.de/blog/2019/11/28/apache-kafka-industrial-iot-iiot-build-an-open-scalable-reliable-digital-twin/
https://www.kai-waehner.de/blog/2020/03/25/architectures-digital-twin-digital-thread-apache-kafka-iot-platforms-machine-learning/
https://youtu.be/Q3eKPEVwNVY
DataOps on Streaming Data: From Kafka to InfluxDB via Kubernetes Native Flows...InfluxData
In this session, we are going to create a Lenses DataOps hub for IoT data with Apache Kafka and InfluxDB flows over Kubernetes. We will demonstrate how to create streaming flows and securely explore and monitor real-time data. We will use Kubernetes to spin up scalable flows and go through how we can simply provision such flows with secret management and monitoring end to end out capabilities.
Event Streaming CTO Roundtable for Cloud-native Kafka ArchitecturesKai Wähner
Technical thought leadership presentation to discuss how leading organizations move to real-time architecture to support business growth and enhance customer experience. This is a forum to discuss use cases with your peers to understand how other digital-native companies are utilizing data in motion to drive competitive advantage.
Agenda:
- Data in Motion with Event Streaming and Apache Kafka
- Streaming ETL Pipelines
- IT Modernisation and Hybrid Multi-Cloud
- Customer Experience and Customer 360
- IoT and Big Data Processing
- Machine Learning and Analytics
Serverless Kafka on AWS as Part of a Cloud-native Data Lake ArchitectureKai Wähner
AWS Data Lake / Lake House + Confluent Cloud for Serverless Apache Kafka. Learn about use cases, architectures, and features.
Data must be continuously collected, processed, and reactively used in applications across the entire enterprise - some in real time, some in batch mode. In other words: As an enterprise becomes increasingly software-defined, it needs a data platform designed primarily for "data in motion" rather than "data at rest."
Apache Kafka is now mainstream when it comes to data in motion! The Kafka API has become the de facto standard for event-driven architectures and event streaming. Unfortunately, the cost of running it yourself is very often too expensive when you add factors like scaling, administration, support, security, creating connectors...and everything else that goes with it. Resources in enterprises are scarce: this applies to both the best team members and the budget.
The cloud - as we all know - offers the perfect solution to such challenges.
Most likely, fully-managed cloud services such as AWS S3, DynamoDB or Redshift are already in use. Now it is time to implement "fully-managed" for Kafka as well - with Confluent Cloud on AWS.
Building a central integration layer that doesn't care where or how much data is coming from.
Implementing scalable data stream processing to gain real-time insights
Leveraging fully managed connectors (like S3, Redshift, Kinesis, MongoDB Atlas & more) to quickly access data
Confluent Cloud in action? Let's show how ao.com made it happen!
Translated with www.DeepL.com/Translator (free version)
Fast Data – Fast Cars: Wie Apache Kafka die Datenwelt revolutioniertconfluent
Für die Automobilindustrie ist die digitale Transformation wie für jede andere Branche zugleich eine digitale Revolution: Neue Marktspieler, neue Technologien und die in immer größeren Mengen anfallenden Daten schaffen neue Chancen, aber auch neue Herausforderungen – und erfordern neben neuen IT-Architekturen auch völlig neue Denkansätze.
60% der Fortune500-Unternehmen setzen zur Umsetzung ihrer Daten-Streaming-Projekte auf die umfassende verteilte Streaming-Plattform Apache Kafka®, darunter auch die AUDI AG.
Erfahren Sie in diesem Webinar:
Wie Kafka als Grundlage sowohl für Daten-Pipelines als auch für Anwendungen dient, die Echtzeit-Datenströme konsumieren und verarbeiten.
Wie Kafka Connect und Kafka Streams geschäftskritische Anwendungen unterstützt
Wie Audi mithilfe von Kafka und Confluent eine Fast Data IoT-Plattform umgesetzt hat, die den Bereich „Connected Car“ revolutioniert
Sprecher:
David Schmitz, Principal Architect, Audi Electronics Venture GmbH
Kai Waehner, Technology Evangelist, Confluent
Apache Kafka and Blockchain - Comparison and a Kafka-native ImplementationKai Wähner
Apache Kafka is an open-source event streaming platform used to complement or replace existing middleware, integrate applications, and build microservice architectures. Used at almost every large company today, it's understood, battled-tested, highly scalable, and reliable.
Blockchain is a different story. Being related to cryptocurrencies like Bitcoin, it's often in the news. But what is the value of software architecture? And how is it related to an integration architecture and event streaming platform?
This session explores blockchain use cases and different alternatives such as Hyperledger, Ethereum, and Kafka-native blockchain implementation. We discuss the value blockchain brings for different architectures, and how it can be integrated with the Kafka ecosystem to build a highly scalable and reliable event streaming infrastructure.
This talk discusses the concepts, use cases, and architectures behind Event Streaming, Apache Kafka, Distributed Ledger (DLT), and Blockchain. A comparison of different technologies such as Confluent, AIBlockchain, Hyperledger, Ethereum, Ripple, IOTA, and Libra explores when to use Kafka, a Kafka-native blockchain, a dedicated blockchain, or Kafka in conjunction with another blockchain.
Serverless London 2019 FaaS composition using Kafka and CloudEventsNeil Avery
FaaS composition using Kafka and Cloud-Events
LOCATION: Burton & Redgrave, DATE: November 7, 2019, TIME: 2:30 pm - 3:15 pm
https://serverlesscomputing.london/sessions/faas-composition-using-kafka-and-cloud-events/
Serverless functions or FaaS are all the rage. By leveraging well established event-driven microservice design principles and applying them to serverless functions we can build a homogenous ecosystem to run FaaS applications.
Kafka’s natural ability to store and replay events means serverless functions can not only be replayed, but they can also be used to choreograph call chains or driven using orchestration. Kafka also means we can democratize and organize FaaS environments in a way that scales across the enterprise.
Underpinning this mantra is the use of Cloud Events by the CNCF serverless working group (of which Confluent is an active member).
Objective of the talk
You will leave the talk with an understanding of what the future of cloud holds, a methodology for embracing serverless functions and how they become part of your journey to a cloud-native, event-driven architecture.
Stream me to the Cloud (and back) with Confluent & MongoDBconfluent
In this online talk, we’ll explore how and why companies are leveraging Confluent and MongoDB to modernize their architecture and leverage the scalability of the cloud and the velocity of streaming. Based upon a sample retail business scenario, we will explain how changes in an on-premise database are streamed via the Confluent Cloud to MongoDB Atlas and back.
IoT Architectures for a Digital Twin with Apache Kafka, IoT Platforms and Mac...Kai Wähner
A digital twin is a digital replica of a living or non-living physical entity. This session discusses the benefits and IoT architectures of a Digital Twin in Industrial IoT (IIoT) and its relation to Apache Kafka, IoT frameworks and Machine Learning. Kafka is often used as central event streaming platform to build a scalable and reliable digital twin for real time streaming sensor data. A live demo shows a scalable digital twin infrastructure for condition monitoring and predictive maintenance in real time for a connected car infrastructure leveraging Kafka, MQTT and TensorFlow.
Key Take-Aways:
• Learn about use cases and characteristics of a digital twin in various industries
• Understand how to build a digital twin for every single (of tens of thousands) IoT device or machine
• See different IoT architectures with Kafka and other IoT technologies and products, including edge, hybrid and global deployments
• Understand the relation to Machine Learning and bring added value to your IoT infrastructure by enabling use cases like predictive maintenance
• Understand how the Apache Kafka enables scalable and flexible end-to-end integration processing from IIoT data to various backend applications
• Watch a live demo of an end-to-end integration, real time processing and analytics of thousands of IoT devices
More details:
https://www.kai-waehner.de/blog/2019/11/28/apache-kafka-industrial-iot-iiot-build-an-open-scalable-reliable-digital-twin/
https://www.kai-waehner.de/blog/2020/03/25/architectures-digital-twin-digital-thread-apache-kafka-iot-platforms-machine-learning/
https://youtu.be/Q3eKPEVwNVY
DataOps on Streaming Data: From Kafka to InfluxDB via Kubernetes Native Flows...InfluxData
In this session, we are going to create a Lenses DataOps hub for IoT data with Apache Kafka and InfluxDB flows over Kubernetes. We will demonstrate how to create streaming flows and securely explore and monitor real-time data. We will use Kubernetes to spin up scalable flows and go through how we can simply provision such flows with secret management and monitoring end to end out capabilities.
Event Streaming CTO Roundtable for Cloud-native Kafka ArchitecturesKai Wähner
Technical thought leadership presentation to discuss how leading organizations move to real-time architecture to support business growth and enhance customer experience. This is a forum to discuss use cases with your peers to understand how other digital-native companies are utilizing data in motion to drive competitive advantage.
Agenda:
- Data in Motion with Event Streaming and Apache Kafka
- Streaming ETL Pipelines
- IT Modernisation and Hybrid Multi-Cloud
- Customer Experience and Customer 360
- IoT and Big Data Processing
- Machine Learning and Analytics
Serverless Kafka on AWS as Part of a Cloud-native Data Lake ArchitectureKai Wähner
AWS Data Lake / Lake House + Confluent Cloud for Serverless Apache Kafka. Learn about use cases, architectures, and features.
Data must be continuously collected, processed, and reactively used in applications across the entire enterprise - some in real time, some in batch mode. In other words: As an enterprise becomes increasingly software-defined, it needs a data platform designed primarily for "data in motion" rather than "data at rest."
Apache Kafka is now mainstream when it comes to data in motion! The Kafka API has become the de facto standard for event-driven architectures and event streaming. Unfortunately, the cost of running it yourself is very often too expensive when you add factors like scaling, administration, support, security, creating connectors...and everything else that goes with it. Resources in enterprises are scarce: this applies to both the best team members and the budget.
The cloud - as we all know - offers the perfect solution to such challenges.
Most likely, fully-managed cloud services such as AWS S3, DynamoDB or Redshift are already in use. Now it is time to implement "fully-managed" for Kafka as well - with Confluent Cloud on AWS.
Building a central integration layer that doesn't care where or how much data is coming from.
Implementing scalable data stream processing to gain real-time insights
Leveraging fully managed connectors (like S3, Redshift, Kinesis, MongoDB Atlas & more) to quickly access data
Confluent Cloud in action? Let's show how ao.com made it happen!
Translated with www.DeepL.com/Translator (free version)
Fast Data – Fast Cars: Wie Apache Kafka die Datenwelt revolutioniertconfluent
Für die Automobilindustrie ist die digitale Transformation wie für jede andere Branche zugleich eine digitale Revolution: Neue Marktspieler, neue Technologien und die in immer größeren Mengen anfallenden Daten schaffen neue Chancen, aber auch neue Herausforderungen – und erfordern neben neuen IT-Architekturen auch völlig neue Denkansätze.
60% der Fortune500-Unternehmen setzen zur Umsetzung ihrer Daten-Streaming-Projekte auf die umfassende verteilte Streaming-Plattform Apache Kafka®, darunter auch die AUDI AG.
Erfahren Sie in diesem Webinar:
Wie Kafka als Grundlage sowohl für Daten-Pipelines als auch für Anwendungen dient, die Echtzeit-Datenströme konsumieren und verarbeiten.
Wie Kafka Connect und Kafka Streams geschäftskritische Anwendungen unterstützt
Wie Audi mithilfe von Kafka und Confluent eine Fast Data IoT-Plattform umgesetzt hat, die den Bereich „Connected Car“ revolutioniert
Sprecher:
David Schmitz, Principal Architect, Audi Electronics Venture GmbH
Kai Waehner, Technology Evangelist, Confluent
Apache Kafka and Blockchain - Comparison and a Kafka-native ImplementationKai Wähner
Apache Kafka is an open-source event streaming platform used to complement or replace existing middleware, integrate applications, and build microservice architectures. Used at almost every large company today, it's understood, battled-tested, highly scalable, and reliable.
Blockchain is a different story. Being related to cryptocurrencies like Bitcoin, it's often in the news. But what is the value of software architecture? And how is it related to an integration architecture and event streaming platform?
This session explores blockchain use cases and different alternatives such as Hyperledger, Ethereum, and Kafka-native blockchain implementation. We discuss the value blockchain brings for different architectures, and how it can be integrated with the Kafka ecosystem to build a highly scalable and reliable event streaming infrastructure.
This talk discusses the concepts, use cases, and architectures behind Event Streaming, Apache Kafka, Distributed Ledger (DLT), and Blockchain. A comparison of different technologies such as Confluent, AIBlockchain, Hyperledger, Ethereum, Ripple, IOTA, and Libra explores when to use Kafka, a Kafka-native blockchain, a dedicated blockchain, or Kafka in conjunction with another blockchain.
Serverless London 2019 FaaS composition using Kafka and CloudEventsNeil Avery
FaaS composition using Kafka and Cloud-Events
LOCATION: Burton & Redgrave, DATE: November 7, 2019, TIME: 2:30 pm - 3:15 pm
https://serverlesscomputing.london/sessions/faas-composition-using-kafka-and-cloud-events/
Serverless functions or FaaS are all the rage. By leveraging well established event-driven microservice design principles and applying them to serverless functions we can build a homogenous ecosystem to run FaaS applications.
Kafka’s natural ability to store and replay events means serverless functions can not only be replayed, but they can also be used to choreograph call chains or driven using orchestration. Kafka also means we can democratize and organize FaaS environments in a way that scales across the enterprise.
Underpinning this mantra is the use of Cloud Events by the CNCF serverless working group (of which Confluent is an active member).
Objective of the talk
You will leave the talk with an understanding of what the future of cloud holds, a methodology for embracing serverless functions and how they become part of your journey to a cloud-native, event-driven architecture.
Stream me to the Cloud (and back) with Confluent & MongoDBconfluent
In this online talk, we’ll explore how and why companies are leveraging Confluent and MongoDB to modernize their architecture and leverage the scalability of the cloud and the velocity of streaming. Based upon a sample retail business scenario, we will explain how changes in an on-premise database are streamed via the Confluent Cloud to MongoDB Atlas and back.
Supply Chain Optimization with Apache KafkaKai Wähner
Supply Chain optimization leveraging Event Streaming with Apache Kafka. See real-world use cases and architectures from Walmart, BMW, Porsche, and other enterprises to improve the Supply Chain Management (SCM) processes. Automation, robustness, flexibility, real-time, decoupling, data integration, and hybrid deployments...
Video recording: https://youtu.be/dUkgungBmPs
Blog post: https://www.kai-waehner.de/apache-kafka-supply-chain-management-scm-optimization-scor-six-sigma-real-time
Real-Life Use Cases & Architectures for Event Streaming with Apache KafkaKai Wähner
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.
Apache Kafka as Event Streaming Platform for Microservice ArchitecturesKai Wähner
This session introduces Apache Kafka, an event-driven open source streaming platform. Apache Kafka goes far beyond scalable, high volume messaging. In addition, you can leverage Kafka Connect for integration and the Kafka Streams API for building lightweight stream processing microservices in autonomous teams. The Confluent Platform adds further components such as a Schema Registry, REST Proxy, KSQL, Clients for different programming languages and Connectors for different technologies.
The session discusses how tech giants like LinkedIn, Ebay or Airbnb leverage Apache Kafka as event streaming platform to solve various different business problems and how to create a scalable, flexible microservice architecture. A live demo shows how you can easily process and analyze streams of events using Apache Kafka and KSQL.
Building a Secure, Tamper-Proof & Scalable Blockchain on Top of Apache Kafka ...confluent
Apache Kafka is an open source event streaming platform. It is often used to complement or even replace existing middleware to integrate applications and build microservice architectures. Apache Kafka is already used in various projects in almost every bigger company today. Understood, battled-tested, highly scalable, reliable, real-time.
Blockchain is a different story. This technology is a lot in the news, especially related to cryptocurrencies like Bitcoin. But what is the added value for software architectures? Is blockchain just hype and adds complexity? Or will it be used by everybody in the future, like a web browser or mobile app today? And how is it related to an integration architecture and event streaming platform?
This session explores use cases for blockchains and discusses different alternatives such as Hyperledger, Ethereum and a Kafka-native tamper-proof blockchain implementation. Different architectures are discussed to understand when blockchain really adds value and how it can be combined with the Apache Kafka ecosystem to integrate blockchain with the rest of the enterprise architecture to build a highly scalable and reliable event streaming infrastructure.
Speakers:
Kai Waehner, Technology Evangelist, Confluent
Stephen Reed, CTO, Co-Founder, AiB
Kafka for Real-Time Replication between Edge and Hybrid CloudKai Wähner
Not all workloads allow cloud computing. Low latency, cybersecurity, and cost-efficiency require a suitable combination of edge computing and cloud integration.
This session explores architectures and design patterns for software and hardware considerations to deploy hybrid data streaming with Apache Kafka anywhere. A live demo shows data synchronization from the edge to the public cloud across continents with Kafka on Hivecell and Confluent Cloud.
Mainframe Integration, Offloading and Replacement with Apache KafkaKai Wähner
Video recording of this presentation:
https://youtu.be/upWzamacOVQ
Blog post with more details:
https://www.kai-waehner.de/blog/2020/04/24/mainframe-offloading-replacement-apache-kafka-connect-ibm-db2-mq-cdc-cobol/
Mainframes are still hard at work, processing over 70 percent of the world’s most essential computing transactions every day. Very high cost, monolithic architectures, and missing experts are the key challenges for mainframe applications. Time to get more innovative, even with the mainframe!
Mainframe offloading with Apache Kafka and its ecosystem can be used to keep a more modern data store in real-time sync with the mainframe. At the same time, it is persisting the event data on the bus to enable microservices, and deliver the data to other systems such as data warehouses and search indexes.
But the final goal and ultimate vision are to replace the mainframe by new applications using modern and less costly technologies. Stand up to the dinosaur, but keep in mind that legacy migration is a journey! Kai will guide you to the next step of your company’s evolution!
You will learn:
- how to not only reduce operational expenses but provide a path for architecture modernization, agility and eventually mainframe replacement
- what steps some of Confluent’s customers already took, leveraging technologies like Change Data Capture (CDC) or MQ for mainframe offloading
- how an event streaming platform enables cost reduction, architecture modernization, and a combination of a mainframe with new technologies
Enabling Smarter Cities and Connected Vehicles with an Event Streaming Platfo...Kai Wähner
Many cities are investing in technologies to transform their cities into smart city- environments in which data collection and analysis is utilized to manage assets and resources efficiently. Modern technology can help connect the right data, at the right time, to the right people, processes and systems. Innovations around smart cities and the Internet of Things give cities the ability to improve motor safety, unify and manage transportation systems and traffic, save energy and provide a better experience for the residents.
By utilizing an event streaming platform, like Confluent, cities are able to process data in real-time from thousands of sources, such as sensors. By aggregating that data and analyzing real-time data streams, more informed decisions can be made and fine-tuned operations developed for a positive impact on everyday challenges faced by cities.
Learn how to:
-Overcome challenges for building a smarter city
-Build a real time infrastructure to correlate relevant events
-Connect thousands of devices, machines, and people
-Leverage open source and fully managed solutions from the Apache Kafka ecosystem
Telco 4.0 - Payment and FinServ Integration for Data in Motion with 5G and Ap...Kai Wähner
The Era of Telco 4.0: Embracing Digital Transformation with Data in Motion. Learn about Payment and FinServ Integration for Data in Motion with 5G and Apache Kafka.
1) The rise of Telco 4.0 and the future forward
2) Data in Motion in the Telco industry
3) Real-world Fintech and Payment examples powered by Data in Motion
Apache Kafka in the Automotive Industry (Connected Vehicles, Manufacturing 4....Kai Wähner
Connect all the things: An intro to event streaming for the automotive industry including connected cars, mobility services, and manufacturing / industrial IoT.
Video recording of this talk: https://www.youtube.com/watch?v=rBfBFrcO-WU
The Fourth Industrial Revolution (also known as Industry 4.0) is the ongoing automation of traditional manufacturing and industrial practices, using modern smart technology. Event Streaming with Apache Kafka plays a massive role in processing massive volumes of data in real-time in a reliable, scalable, and flexible way using integrating with various legacy and modern data sources and sinks.
Other industries—retail, healthcare, government, financial services, energy, and more—also lean into Industry 4.0 technology to take advantage of IoT devices, sensors, smart machines, robotics, and connected data. The variety of these deployments goes from disconnected edge use cases across hybrid architectures to global multi-cloud deployments.
In this presentation, I want to give you an overview of existing use cases for event streaming technology in a connected world across supply chains, industries and customer experiences that come along with these interdisciplinary data intersections:
- The Automotive Industry (and it’s not only Connected Cars)
- Mobility Services across verticals (transportation, logistics, travel industry, retailing, …)
- Smart Cities (including citizen health services, communication infrastructure, …)
Real-world examples include use cases from car makers such as Audi, BMW, Porsche, Tesla, plus many examples from mobility services such as Uber, Lyft, Here Technologies, and more.
Apache Kafka for Smart Grid, Utilities and Energy ProductionKai Wähner
The energy industry is changing from system-centric to smaller-scale and distributed smart grids and microgrids. A smart grid requires a flexible, scalable, elastic, and reliable cloud-native infrastructure for real-time data integration and processing. This post explores use cases, architectures, and real-world deployments of event streaming with Apache Kafka in the energy industry to implement smart grids and real-time end-to-end integration.
Blog Post with more details:
https://www.kai-waehner.de/apache-kafka-smart-grid-energy-production-edge-iot-oil-gas-green-renewable-sensor-analytics
The Fourth Industrial Revolution (also known as Industry 4.0) is the ongoing automation of traditional manufacturing and industrial practices, using modern smart technology.
Event Streaming with Apache Kafka plays a massive role in processing massive volumes of data in real-time in a reliable, scalable, and flexible way integrating with various legacy and modern data sources and sinks.
In this presentation, I want to give you an overview of existing use cases for event streaming technology in a connected world across supply chains, industries and customer experiences that come along with these interdisciplinary data intersections:
• The Automotive Industry (and it’s not only Connected Cars)
• Mobility Services across verticals (transportation, logistics, travel industry, retailing, …)
• Smart Cities (including citizen health services, communication infrastructure, …)
All these industries and sectors do not have new characteristics and requirements. They require data integration, data correlation or real decoupling, just to name a few, but are now facing massively increased volumes of data.
Real-time messaging solutions have existed for many years. Hundreds of platforms exist for data integration (including ETL and ESB tooling or specific IIoT platforms). Proprietary monoliths monitor plants, telco networks, and other infrastructures for decades in real-time. But now, Kafka combines all the above characteristics in an open, scalable, and flexible infrastructure to operate mission-critical workloads at scale in real-time. And is taking over the world of connecting data.
How Apache Kafka helps to create Data Culture – How to Cross the Kafka Chasmconfluent
In this webinar we want to share our experience on how the Swiss Mobiliar, the biggest Swiss household insurance enterprise, introduced Kafka and led it to enterprise-wide adoption with the help of AGOORA.com.
App modernization on AWS with Apache Kafka and Confluent CloudKai Wähner
Presentation from AWS ReInvent 2020.
Learn how you can accelerate application modernization and benefit from the open-source Apache Kafka ecosystem by connecting your legacy, on-premises systems to the cloud. In this session, hear real customer stories about timely insights gained from event-driven applications built on an event streaming platform from Confluent Cloud running on AWS, which stores and processes historical data and real-time data streams. Confluent makes Apache Kafka enterprise-ready using infinite Kafka storage with Amazon S3 and multiple private networking options including AWS PrivateLink, along with self-managed encryption keys for storage volume encryption with AWS Key Management Service (AWS KMS).
IoT Architectures for Apache Kafka and Event Streaming - Industry 4.0, Digita...Kai Wähner
The Internet of Things (IoT) is getting more and more traction as valuable use cases come to light. Whether you are in Healthcare, Telecommunications, Manufacturing, Banking or Retail to name a few industries, there is one key challenge and that's the integration of backend IoT data logs and applications, business services and cloud services to process the data in real time and at scale.
In this talk, we will be sharing how Kafka has become the leading technology used throughout the business to provide Real Time Event Streaming. Explore real life use cases of Kafka Connect, Kafka Streams and KSQL independent of the data deployment be it on a private or public Cloud, On Premise or at the Edge.
Audi - Connected car infrastructure
Robert Bosch Power Tools - Track and Trace of devices and people at construction areas
Deutsche Bahn - Customer 360 for train timetable updates
E.ON - IoT Streaming Platform to integrate and build smart home, smart building and smart grid infrastructures
IIoT with Kafka and Machine Learning for Supply Chain Optimization In Real Ti...Kai Wähner
I did a webinar with Confluent's partner Expero about "Apache Kafka and Machine Learning for Real Time Supply Chain Optimization". This is a great example for anybody in automation industry / Industrial IoT (IIoT) like automotive, manufacturing, logistics, etc.
We explain how a real time event streaming platform can integrate in real time with the legacy world and proprietary IIoT protocols (like Siemens S7, Modbus, Beckhoff ADS, OPC-UA, et al). You can process the data at scale and then ingest it into a modern database (like AWS S3, Snowflake or MongoDB) or analytic / machine learning framework (like TensorFlow, PyTorch or Azure Machine Learning Service).
Confluent Cloud for Apache Kafka® | Google Cloud Next ’19confluent
Google Cloud Next ’19
Speakers:
Gaetan Castelein, Confluent Product Marketing
Kir Titievsky, Google Product Management
Confluent Cloud for Apache Kafka® was a session conducted at Google Cloud Next ’19 on the topic of how Confluent and Google are partnering to give you a complete event-streaming platform that extends Kafka with essential capabilities for developers and enterprises. Confluent is available as a fully managed, first class service on GCP, or can be deployed on-premises on Google Cloud Services Platform. Developers can deploy Confluent Cloud™ in minutes right from the Google Cloud Console to start building event-driven applications. Enterprises can build hybrid cloud streaming solutions with a common platform that spans from on-premises to GCP, streaming data to GCP to leverage best-of-breed services such as BigQuery and TensorFlow. Review this presentation to learn about Confluent and GCP services, and see how you can get started in just minutes with no upfront commitment.
Kafka Streams vs. KSQL for Stream Processing on top of Apache KafkaKai Wähner
Spoilt for Choice – Kafka Streams vs. KSQL for Stream Processing on top of Apache Kafka:
Apache Kafka is a de facto standard streaming data processing platform. It is widely deployed as event streaming platform. Part of Kafka is its stream processing API “Kafka Streams”. In addition, the Kafka ecosystem now offers KSQL, a declarative, SQL-like stream processing language that lets you define powerful stream-processing applications easily. What once took some moderately sophisticated Java code can now be done at the command line with a familiar and eminently approachable syntax.
This session discusses and demos the pros and cons of Kafka Streams and KSQL to understand when to use which stream processing alternative for continuous stream processing natively on Apache Kafka infrastructures. The end of the session compares the trade-offs of Kafka Streams and KSQL to separate stream processing frameworks such as Apache Flink or Spark Streaming.
Explore the various options for streaming data on AWS, such as Amazon Kinesis and Amazon Managed Streaming for Kafka, and the various options for processing streams of data such as Apache Spark, Apache Flink, AWS Lambda, and Amazon Kinesis Analytics for Java. Let's explore what an architecture for processing Australia's new Open Banking data format at 60,000 transactions per second could look like.
Apache Kafka® and Analytics in a Connected IoT Worldconfluent
Apache Kafka® and Analytics in a Connected IoT World, Kai Waehner, Sr. Solutions Engineer Advanced Technology Group, Confluent
https://www.meetup.com/Berlin-Apache-Kafka-Meetup-by-Confluent/events/273166575/
Supply Chain Optimization with Apache KafkaKai Wähner
Supply Chain optimization leveraging Event Streaming with Apache Kafka. See real-world use cases and architectures from Walmart, BMW, Porsche, and other enterprises to improve the Supply Chain Management (SCM) processes. Automation, robustness, flexibility, real-time, decoupling, data integration, and hybrid deployments...
Video recording: https://youtu.be/dUkgungBmPs
Blog post: https://www.kai-waehner.de/apache-kafka-supply-chain-management-scm-optimization-scor-six-sigma-real-time
Real-Life Use Cases & Architectures for Event Streaming with Apache KafkaKai Wähner
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.
Apache Kafka as Event Streaming Platform for Microservice ArchitecturesKai Wähner
This session introduces Apache Kafka, an event-driven open source streaming platform. Apache Kafka goes far beyond scalable, high volume messaging. In addition, you can leverage Kafka Connect for integration and the Kafka Streams API for building lightweight stream processing microservices in autonomous teams. The Confluent Platform adds further components such as a Schema Registry, REST Proxy, KSQL, Clients for different programming languages and Connectors for different technologies.
The session discusses how tech giants like LinkedIn, Ebay or Airbnb leverage Apache Kafka as event streaming platform to solve various different business problems and how to create a scalable, flexible microservice architecture. A live demo shows how you can easily process and analyze streams of events using Apache Kafka and KSQL.
Building a Secure, Tamper-Proof & Scalable Blockchain on Top of Apache Kafka ...confluent
Apache Kafka is an open source event streaming platform. It is often used to complement or even replace existing middleware to integrate applications and build microservice architectures. Apache Kafka is already used in various projects in almost every bigger company today. Understood, battled-tested, highly scalable, reliable, real-time.
Blockchain is a different story. This technology is a lot in the news, especially related to cryptocurrencies like Bitcoin. But what is the added value for software architectures? Is blockchain just hype and adds complexity? Or will it be used by everybody in the future, like a web browser or mobile app today? And how is it related to an integration architecture and event streaming platform?
This session explores use cases for blockchains and discusses different alternatives such as Hyperledger, Ethereum and a Kafka-native tamper-proof blockchain implementation. Different architectures are discussed to understand when blockchain really adds value and how it can be combined with the Apache Kafka ecosystem to integrate blockchain with the rest of the enterprise architecture to build a highly scalable and reliable event streaming infrastructure.
Speakers:
Kai Waehner, Technology Evangelist, Confluent
Stephen Reed, CTO, Co-Founder, AiB
Kafka for Real-Time Replication between Edge and Hybrid CloudKai Wähner
Not all workloads allow cloud computing. Low latency, cybersecurity, and cost-efficiency require a suitable combination of edge computing and cloud integration.
This session explores architectures and design patterns for software and hardware considerations to deploy hybrid data streaming with Apache Kafka anywhere. A live demo shows data synchronization from the edge to the public cloud across continents with Kafka on Hivecell and Confluent Cloud.
Mainframe Integration, Offloading and Replacement with Apache KafkaKai Wähner
Video recording of this presentation:
https://youtu.be/upWzamacOVQ
Blog post with more details:
https://www.kai-waehner.de/blog/2020/04/24/mainframe-offloading-replacement-apache-kafka-connect-ibm-db2-mq-cdc-cobol/
Mainframes are still hard at work, processing over 70 percent of the world’s most essential computing transactions every day. Very high cost, monolithic architectures, and missing experts are the key challenges for mainframe applications. Time to get more innovative, even with the mainframe!
Mainframe offloading with Apache Kafka and its ecosystem can be used to keep a more modern data store in real-time sync with the mainframe. At the same time, it is persisting the event data on the bus to enable microservices, and deliver the data to other systems such as data warehouses and search indexes.
But the final goal and ultimate vision are to replace the mainframe by new applications using modern and less costly technologies. Stand up to the dinosaur, but keep in mind that legacy migration is a journey! Kai will guide you to the next step of your company’s evolution!
You will learn:
- how to not only reduce operational expenses but provide a path for architecture modernization, agility and eventually mainframe replacement
- what steps some of Confluent’s customers already took, leveraging technologies like Change Data Capture (CDC) or MQ for mainframe offloading
- how an event streaming platform enables cost reduction, architecture modernization, and a combination of a mainframe with new technologies
Enabling Smarter Cities and Connected Vehicles with an Event Streaming Platfo...Kai Wähner
Many cities are investing in technologies to transform their cities into smart city- environments in which data collection and analysis is utilized to manage assets and resources efficiently. Modern technology can help connect the right data, at the right time, to the right people, processes and systems. Innovations around smart cities and the Internet of Things give cities the ability to improve motor safety, unify and manage transportation systems and traffic, save energy and provide a better experience for the residents.
By utilizing an event streaming platform, like Confluent, cities are able to process data in real-time from thousands of sources, such as sensors. By aggregating that data and analyzing real-time data streams, more informed decisions can be made and fine-tuned operations developed for a positive impact on everyday challenges faced by cities.
Learn how to:
-Overcome challenges for building a smarter city
-Build a real time infrastructure to correlate relevant events
-Connect thousands of devices, machines, and people
-Leverage open source and fully managed solutions from the Apache Kafka ecosystem
Telco 4.0 - Payment and FinServ Integration for Data in Motion with 5G and Ap...Kai Wähner
The Era of Telco 4.0: Embracing Digital Transformation with Data in Motion. Learn about Payment and FinServ Integration for Data in Motion with 5G and Apache Kafka.
1) The rise of Telco 4.0 and the future forward
2) Data in Motion in the Telco industry
3) Real-world Fintech and Payment examples powered by Data in Motion
Apache Kafka in the Automotive Industry (Connected Vehicles, Manufacturing 4....Kai Wähner
Connect all the things: An intro to event streaming for the automotive industry including connected cars, mobility services, and manufacturing / industrial IoT.
Video recording of this talk: https://www.youtube.com/watch?v=rBfBFrcO-WU
The Fourth Industrial Revolution (also known as Industry 4.0) is the ongoing automation of traditional manufacturing and industrial practices, using modern smart technology. Event Streaming with Apache Kafka plays a massive role in processing massive volumes of data in real-time in a reliable, scalable, and flexible way using integrating with various legacy and modern data sources and sinks.
Other industries—retail, healthcare, government, financial services, energy, and more—also lean into Industry 4.0 technology to take advantage of IoT devices, sensors, smart machines, robotics, and connected data. The variety of these deployments goes from disconnected edge use cases across hybrid architectures to global multi-cloud deployments.
In this presentation, I want to give you an overview of existing use cases for event streaming technology in a connected world across supply chains, industries and customer experiences that come along with these interdisciplinary data intersections:
- The Automotive Industry (and it’s not only Connected Cars)
- Mobility Services across verticals (transportation, logistics, travel industry, retailing, …)
- Smart Cities (including citizen health services, communication infrastructure, …)
Real-world examples include use cases from car makers such as Audi, BMW, Porsche, Tesla, plus many examples from mobility services such as Uber, Lyft, Here Technologies, and more.
Apache Kafka for Smart Grid, Utilities and Energy ProductionKai Wähner
The energy industry is changing from system-centric to smaller-scale and distributed smart grids and microgrids. A smart grid requires a flexible, scalable, elastic, and reliable cloud-native infrastructure for real-time data integration and processing. This post explores use cases, architectures, and real-world deployments of event streaming with Apache Kafka in the energy industry to implement smart grids and real-time end-to-end integration.
Blog Post with more details:
https://www.kai-waehner.de/apache-kafka-smart-grid-energy-production-edge-iot-oil-gas-green-renewable-sensor-analytics
The Fourth Industrial Revolution (also known as Industry 4.0) is the ongoing automation of traditional manufacturing and industrial practices, using modern smart technology.
Event Streaming with Apache Kafka plays a massive role in processing massive volumes of data in real-time in a reliable, scalable, and flexible way integrating with various legacy and modern data sources and sinks.
In this presentation, I want to give you an overview of existing use cases for event streaming technology in a connected world across supply chains, industries and customer experiences that come along with these interdisciplinary data intersections:
• The Automotive Industry (and it’s not only Connected Cars)
• Mobility Services across verticals (transportation, logistics, travel industry, retailing, …)
• Smart Cities (including citizen health services, communication infrastructure, …)
All these industries and sectors do not have new characteristics and requirements. They require data integration, data correlation or real decoupling, just to name a few, but are now facing massively increased volumes of data.
Real-time messaging solutions have existed for many years. Hundreds of platforms exist for data integration (including ETL and ESB tooling or specific IIoT platforms). Proprietary monoliths monitor plants, telco networks, and other infrastructures for decades in real-time. But now, Kafka combines all the above characteristics in an open, scalable, and flexible infrastructure to operate mission-critical workloads at scale in real-time. And is taking over the world of connecting data.
How Apache Kafka helps to create Data Culture – How to Cross the Kafka Chasmconfluent
In this webinar we want to share our experience on how the Swiss Mobiliar, the biggest Swiss household insurance enterprise, introduced Kafka and led it to enterprise-wide adoption with the help of AGOORA.com.
App modernization on AWS with Apache Kafka and Confluent CloudKai Wähner
Presentation from AWS ReInvent 2020.
Learn how you can accelerate application modernization and benefit from the open-source Apache Kafka ecosystem by connecting your legacy, on-premises systems to the cloud. In this session, hear real customer stories about timely insights gained from event-driven applications built on an event streaming platform from Confluent Cloud running on AWS, which stores and processes historical data and real-time data streams. Confluent makes Apache Kafka enterprise-ready using infinite Kafka storage with Amazon S3 and multiple private networking options including AWS PrivateLink, along with self-managed encryption keys for storage volume encryption with AWS Key Management Service (AWS KMS).
IoT Architectures for Apache Kafka and Event Streaming - Industry 4.0, Digita...Kai Wähner
The Internet of Things (IoT) is getting more and more traction as valuable use cases come to light. Whether you are in Healthcare, Telecommunications, Manufacturing, Banking or Retail to name a few industries, there is one key challenge and that's the integration of backend IoT data logs and applications, business services and cloud services to process the data in real time and at scale.
In this talk, we will be sharing how Kafka has become the leading technology used throughout the business to provide Real Time Event Streaming. Explore real life use cases of Kafka Connect, Kafka Streams and KSQL independent of the data deployment be it on a private or public Cloud, On Premise or at the Edge.
Audi - Connected car infrastructure
Robert Bosch Power Tools - Track and Trace of devices and people at construction areas
Deutsche Bahn - Customer 360 for train timetable updates
E.ON - IoT Streaming Platform to integrate and build smart home, smart building and smart grid infrastructures
IIoT with Kafka and Machine Learning for Supply Chain Optimization In Real Ti...Kai Wähner
I did a webinar with Confluent's partner Expero about "Apache Kafka and Machine Learning for Real Time Supply Chain Optimization". This is a great example for anybody in automation industry / Industrial IoT (IIoT) like automotive, manufacturing, logistics, etc.
We explain how a real time event streaming platform can integrate in real time with the legacy world and proprietary IIoT protocols (like Siemens S7, Modbus, Beckhoff ADS, OPC-UA, et al). You can process the data at scale and then ingest it into a modern database (like AWS S3, Snowflake or MongoDB) or analytic / machine learning framework (like TensorFlow, PyTorch or Azure Machine Learning Service).
Confluent Cloud for Apache Kafka® | Google Cloud Next ’19confluent
Google Cloud Next ’19
Speakers:
Gaetan Castelein, Confluent Product Marketing
Kir Titievsky, Google Product Management
Confluent Cloud for Apache Kafka® was a session conducted at Google Cloud Next ’19 on the topic of how Confluent and Google are partnering to give you a complete event-streaming platform that extends Kafka with essential capabilities for developers and enterprises. Confluent is available as a fully managed, first class service on GCP, or can be deployed on-premises on Google Cloud Services Platform. Developers can deploy Confluent Cloud™ in minutes right from the Google Cloud Console to start building event-driven applications. Enterprises can build hybrid cloud streaming solutions with a common platform that spans from on-premises to GCP, streaming data to GCP to leverage best-of-breed services such as BigQuery and TensorFlow. Review this presentation to learn about Confluent and GCP services, and see how you can get started in just minutes with no upfront commitment.
Kafka Streams vs. KSQL for Stream Processing on top of Apache KafkaKai Wähner
Spoilt for Choice – Kafka Streams vs. KSQL for Stream Processing on top of Apache Kafka:
Apache Kafka is a de facto standard streaming data processing platform. It is widely deployed as event streaming platform. Part of Kafka is its stream processing API “Kafka Streams”. In addition, the Kafka ecosystem now offers KSQL, a declarative, SQL-like stream processing language that lets you define powerful stream-processing applications easily. What once took some moderately sophisticated Java code can now be done at the command line with a familiar and eminently approachable syntax.
This session discusses and demos the pros and cons of Kafka Streams and KSQL to understand when to use which stream processing alternative for continuous stream processing natively on Apache Kafka infrastructures. The end of the session compares the trade-offs of Kafka Streams and KSQL to separate stream processing frameworks such as Apache Flink or Spark Streaming.
Explore the various options for streaming data on AWS, such as Amazon Kinesis and Amazon Managed Streaming for Kafka, and the various options for processing streams of data such as Apache Spark, Apache Flink, AWS Lambda, and Amazon Kinesis Analytics for Java. Let's explore what an architecture for processing Australia's new Open Banking data format at 60,000 transactions per second could look like.
Similar to Kai Waehner [Confluent] | Real-Time Streaming Analytics with 100,000 Cars Using MQTT, Kafka and InfluxDB 2.0 on Kubernetes | InfluxDays Virtual Experience London 2020
Apache Kafka® and Analytics in a Connected IoT Worldconfluent
Apache Kafka® and Analytics in a Connected IoT World, Kai Waehner, Sr. Solutions Engineer Advanced Technology Group, Confluent
https://www.meetup.com/Berlin-Apache-Kafka-Meetup-by-Confluent/events/273166575/
Connected Vehicles and V2X with Apache KafkaKai Wähner
This session discusses uses cases leveraging Apache Kafka open source ecosystem as streaming platform to process IoT data.
See use cases, architectural alternatives and a live demo of how devices connect to Kafka via MQTT. Learn how to analyze the IoT data either natively on Kafka with Kafka Streams/KSQL, or on an external big data cluster like Spark, Flink or Elastic leveraging Kafka Connect, and how to leverage TensorFlow for Machine Learning.
The focus is on connected cars / connected vehicles and V2X use cases respectively mobility services.
A live demo shows how to build a cloud-native IoT infrastructure on Kubernetes to connect and process streaming data in real-time from 100.000 cars to do predictive maintenance at scale in real-time.
Code for the live demo on Github:
https://github.com/kaiwaehner/hivemq-mqtt-tensorflow-kafka-realtime-iot-machine-learning-training-inference
Data Warehouse vs. Data Lake vs. Data Streaming – Friends, Enemies, Frenemies?Kai Wähner
The concepts and architectures of a data warehouse, a data lake, and data streaming are complementary to solving business problems.
Unfortunately, the underlying technologies are often misunderstood, overused for monolithic and inflexible architectures, and pitched for wrong use cases by vendors. Let’s explore this dilemma in a presentation.
The slides cover technologies such as Apache Kafka, Apache Spark, Confluent, Databricks, Snowflake, Elasticsearch, AWS Redshift, GCP with Google Bigquery, and Azure Synapse.
Apache Kafka in the Transportation and LogisticsKai Wähner
Event Streaming with Apache Kafka in the Transportation and Logistics.
Track & Trace, Real-time Locating System, Customer 360, Open API, and more…
Examples include Swiss Post, SBB, Deutsche Bahn, Hermes, Migros, Here Technologies, Otonomo, Lyft, Uber, Free Now, Lufthansa, Air France, Singapore Airlines, Amadeus Group, and more.
Confluent hosted a technical thought leadership session to discuss how leading organisations move to real-time architecture to support business growth and enhance customer experience.
Apache Kafka in Financial Services - Use Cases and ArchitecturesKai Wähner
The Rise of Event Streaming in Financial Services - Use Cases, Architectures and Examples powered by Apache Kafka.
The New FinServ Enterprise Reality: Every company is a software company. Innovate OR be Disrupted. Learn how Event Streaming with Apache Kafka and its ecosystem help...
More details:
https://www.kai-waehner.de/apache-kafka-financial-services-industry-banking-finserv-payment-fraud-middleware-messaging-transactions
https://www.kai-waehner.de/blog/2020/04/15/apache-kafka-machine-learning-banking-finance-industry/
https://www.kai-waehner.de/blog/2020/04/24/mainframe-offloading-replacement-apache-kafka-connect-ibm-db2-mq-cdc-cobol/
Event: https://www.meetup.com/de-DE/Vienna-Kafka-meetup/events/262314643/
Speaker: Patrik Kleindl (patrik.kleindl@bearingpoint.com)
Slides of the introduction to Apache Kafka and some popular use cases.
Slides were provided by Confluent (confluent.io)
Apache Kafka in the Telco Industry (OSS, BSS, OTT, IMS, NFV, Middleware, Main...Kai Wähner
Real-time data streaming is a hot topic in the Telecommunications Industry / Telecom Sector. As telecommunications companies strive to offer high speed, integrated networks with reduced connection times, connect countless devices at reduced latency, and transform the digital experience worldwide, more and more companies are turning to Apache Kafka’s data stream processing solutions to deliver a scalable, real-time infrastructure for OSS and BSS scenarios. Enabling a combination of on-premise data centers, edge processing, and multi-cloud architectures is becoming the new normal in the Telco Industry. This combination is enabling accelerated growth from value-added services delivered over mobile networks.
Join Kai Waehner, Technology Evangelist at Confluent, for this session which explores various telecommunications use cases, including data integration, infrastructure monitoring, data distribution, data processing and business applications. Different architectures and components from the Kafka ecosystem are also discussed.
This talk explores:
- Overcome challenges for building a modern hybrid telco infrastructure
- Build a real time infrastructure to correlate relevant events
- Connect thousands of devices, networks, infrastructures, and people
- Work together with different companies, organisations and business models
- Leverage open source and fully managed solutions from the Apache Kafka ecosystem, Confluent Platform and Confluent Cloud
Event Streaming in the Telco Industry with Apache Kafka® and Confluentconfluent
Real-time data streaming is a hot topic in the Telecommunications Industry. As telecommunications companies strive to offer high speed, integrated networks with reduced connection times, connect countless devices at reduced latency, and transform the digital experience worldwide, more and more companies are turning to Apache Kafka’s data stream processing solutions to deliver a scalable, real-time infrastructure for OSS and BSS scenarios. Enabling a combination of on-premise data centres, edge processing, and multi-cloud architectures is becoming the new normal in the Telco Industry. This combination is enabling accelerated growth from value-added services delivered over mobile networks.
Join Kai Waehner, Technology Evangelist at Confluent, for this session which explores various telecommunications use cases, including data integration, infrastructure monitoring, data distribution, data processing and business applications. Different architectures and components from the Kafka ecosystem are also discussed.
Review this online talk to learn how to:
- Overcome challenges for building a modern hybrid telco infrastructure
- Build a real time infrastructure to correlate relevant events
- Connect thousands of devices, networks, infrastructures, and people
- Work together with different companies, organisations and business models
- Leverage open source and fully managed solutions from the Apache Kafka ecosystem, Confluent Platform and Confluent Cloud
Speaker: Kai Waehner
Resilient Real-time Data Streaming across the Edge and Hybrid Cloud with Apac...Kai Wähner
Hybrid cloud architectures are the new black for most companies. A cloud-first strategy is evident for many new enterprise architectures, but some use cases require resiliency across edge sites and multiple cloud regions. Data streaming with the Apache Kafka ecosystem is a perfect technology for building resilient and hybrid real-time applications at any scale. This talk explores different architectures and their trade-offs for transactional and analytical workloads. Real-world examples include financial services, retail, and the automotive industry.
Video recording:
https://qconlondon.com/london2022/presentation/resilient-real-time-data-streaming-across-the-edge-and-hybrid-cloud
Serverless Kafka and Spark in a Multi-Cloud Lakehouse ArchitectureKai Wähner
Apache Kafka in conjunction with Apache Spark became the de facto standard for processing and analyzing data. Both frameworks are open, flexible, and scalable.
Unfortunately, the latter makes operations a challenge for many teams. Ideally, teams can use serverless SaaS offerings to focus on business logic. However, hybrid and multi-cloud scenarios require a cloud-native platform that provides automated and elastic tooling to reduce the operations burden.
This session explores different architectures to build serverless Apache Kafka and Apache Spark multi-cloud architectures across regions and continents.
We start from the analytics perspective of a data lake and explore its relation to a fully integrated data streaming layer with Kafka to build a modern data Data Lakehouse.
Real-world use cases show the joint value and explore the benefit of the "delta lake" integration.
Apache Kafka for Real-time Supply Chainin the Food and Retail IndustryKai Wähner
Use Cases, Architectures, and Real-World Examples for data in motion and real-time event streaming powered by Apache Kafka across the supply chain and logistics. Case studies and deployments include Baader, Walmart, Migros, Albertsons, Domino's Pizza, Instacart, Grab, Royal Caribbean, and more.
Apache Kafka and API Management / API Gateway – Friends, Enemies or Frenemies...HostedbyConfluent
Microservices became the new black in enterprise architectures. APIs provide functions to other applications or end users. Even if your architecture uses another pattern than microservices, like SOA (Service-Oriented Architecture) or Client-Server communication, APIs are used between the different applications and end users.
Apache Kafka plays a key role in modern microservice architectures to build open, scalable, flexible and decoupled real time applications. API Management complements Kafka by providing a way to implement and govern the full life cycle of the APIs.
This session explores how event streaming with Apache Kafka and API Management (including API Gateway and Service Mesh technologies) complement and compete with each other depending on the use case and point of view of the project team. The session concludes exploring the vision of event streaming APIs instead of RPC calls.
Apache Kafka and API Management / API Gateway – Friends, Enemies or Frenemies?Kai Wähner
Microservices became the new black in enterprise architectures. APIs provide functions to other applications or end users. Even if your architecture uses another pattern than microservices, like SOA (Service-Oriented Architecture) or Client-Server communication, APIs are used between the different applications and end users.
Apache Kafka plays a key role in modern microservice architectures to build open, scalable, flexible and decoupled real time applications. API Management complements Kafka by providing a way to implement and govern the full life cycle of the APIs.
This session explores how event streaming with Apache Kafka and API Management (including API Gateway and Service Mesh technologies) complement and compete with each other depending on the use case and point of view of the project team. The session concludes exploring the vision of event streaming APIs instead of RPC calls.
Understand how event streaming with Kafka and Confluent complements tools and frameworks such as Kong, Mulesoft, Apigee, Envoy, Istio, Linkerd, Software AG, TIBCO Mashery, IBM, Axway, etc.
A Streaming API Data Exchangeprovides streaming replication between business units and companies. API Management with REST/HTTP is not appropriate for streaming data.
Apache Kafka in the Airline, Aviation and Travel IndustryKai Wähner
Aviation and travel are notoriously vulnerable to social, economic, and political events, as well as the ever-changing expectations of consumers. Coronavirus is just a piece of the challenge.
This presentation explores use cases, architectures, and references for Apache Kafka as event streaming technology in the aviation industry, including airline, airports, global distribution systems (GDS), aircraft manufacturers, and more.
Examples include Lufthansa, Singapore Airlines, Air France Hop, Amadeus, and more. Technologies include Kafka, Kafka Connect, Kafka Streams, ksqlDB, Machine Learning, Cloud, and more.
Apache Kafka, Tiered Storage and TensorFlow for Streaming Machine Learning wi...Kai Wähner
Don’t underestimate the Hidden Technical Debt in Machine Learning Systems.
Leverage Apache Kafka’s open ecosystem as a scalable and flexible Event Streaming Platform to build one pipeline for real-time and batch use cases.
Use Streaming Machine Learning with Apache Kafka, Tiered Storage, and TensorFlow IO to simplify your big data architecture.
Tiered Storage for Kafka provides:
- one platform for all data processing
- an event-based source of truth for materialized views
- no need for a pipeline between Kafka and a Data Lake like Hadoop
Benefits:
- cost reduction
- long-term backup
- performance isolation (real-time and historical analysis in the same cluster)
Use Cases for Reprocessing Historical Events:
- New consumer application
- Error-handling
- Compliance / regulatory processing
- Query and analyze existing events
- Model training
Similar to Kai Waehner [Confluent] | Real-Time Streaming Analytics with 100,000 Cars Using MQTT, Kafka and InfluxDB 2.0 on Kubernetes | InfluxDays Virtual Experience London 2020 (20)
InfluxData is excited to announce InfluxDB Clustered, the self-managed version of InfluxDB 3.0 with unparalleled flexibility, speed, performance, and scale. The evolution of InfluxDB Enterprise, InfluxDB Clustered is delivered as a collection of Kubernetes-based containers and services, which enables you to run and operate InfluxDB 3.0 where you need it, whether that's on-premises or in a private cloud environment. With this new enterprise offering, we’re excited to provide our customers with real-time queries, low-cost object storage, unlimited cardinality, and SQL language support – all with improved data access, support, and security! The newest version of InfluxDB was built on Apache Arrow, and through the open source ecosystem and integrations, extends the value of your time-stamped data.
Join this webinar to learn more about InfluxDB Clustered, and how to manage your large mission-critical workloads in the highly available database service offering!
In this webinar, Balaji Palani and Gunnar Aasen will dive into:
Key features of the new InfluxDB Clustered solution
Use cases for using the newest version of the purpose-built time series database
Live demo
During this 1-hour technical webinar, you’ll also get a chance to ask your questions live.
Best Practices for Leveraging the Apache Arrow EcosystemInfluxData
Apache Arrow is an open source project intended to provide a standardized columnar memory format for flat and hierarchical data. It enables more efficient analytics workloads for modern CPU and GPU hardware, which makes working with large data sets easier and cheaper.
InfluxData and Dremio are both members of the Apache Software Foundation (ASF). Dremio is a data lakehouse management service known for its scalability and capacity for direct querying across diverse data sources. InfluxDB is the purpose-built time series database, and InfluxDB 3.0 has a new columnar storage engine and uses the Arrow format for representing data and moving data to and from Parquet. Discover how InfluxDB and Dremio have advanced their solutions by relying on the Apache Arrow framework.
Join this live panel as Alex Merced and Anais Dotis-Georgiou dive into:
Advantages to utilizing the Apache Arrow ecosystem
Tips and tricks for implementing the columnar data structure
How developers can best utilize the ASF to innovate and contribute to new industry standards
How Bevi Uses InfluxDB and Grafana to Improve Predictive Maintenance and Redu...InfluxData
Bevi are the creators of smart water dispensers which empower people to choose their desired beverage — flat or sparkling, their desired flavor and temperature. Since 2014, Bevi users have saved more than 350 million bottles and cans. Their "smart" water coolers have prevented the extraction of 1.4 trillion oz of oil from Earth and have saved 21.7 billion grams of CO2 from the atmosphere.
Discover how Bevi uses a time series database to enable better predictive maintenance and alerting of their entire ecosystem — including the hardware and software. They are using InfluxDB to collect sensor data in real-time remotely from their internet-connected machines about their status and activity — i.e., flavor and CO2 levels, water temp, filter status, etc. They a7re using these metrics to improve their customer experience and continuously improve their sustainability practices. Gain tips and tricks on how to best utilize InfluxDB's schema-less design.
Join this webinar as Spencer Gagnon dives into:
Bevi's approach to reducing organizations' carbon footprint — they are saving 50K+ bottles and cans annually
Their entire system architecture — including InfluxDB Cloud, Grafana, Kafka, and DigitalOcean
The importance of using time-stamped data to extend the life of their machines
Power Your Predictive Analytics with InfluxDBInfluxData
If you're using InfluxDB to store and manage your time series data, you're already off to a great start. But why stop there? In our upcoming webinar, we'll show you how to take your data analysis to the next level by building predictive analytics using a variety of tools and techniques.
We will demonstrate how to use Quix to create custom dashboards and visualizations that allow you to monitor your data in real-time. We'll also introduce you to Hugging Face, a powerful tool for building models that can predict future trends and identify anomalies. With these tools at your disposal, you'll be able to extract valuable insights from your data and make more informed decisions about the future. Don't miss out on this opportunity to improve your data analysis skills and take your business to the next level!
What you will learn:
Use InfluxDB to store and manage time series data
Utilize Quix and Hugging Face to build models, visualize trends, and identify anomalies
Extract valuable insights from your data
Improve your data analysis skills to make informed decision
How Teréga Replaces Legacy Data Historians with InfluxDB, AWS and IO-Base InfluxData
Are you considering replacing your legacy data historian and moving your OT data to the cloud? Join this technical webinar to learn how to adopt InfluxDB and IO Base - a digital platform used to improve operational efficiencies!
Teréga Solutions are the creators of digital solutions used to improve energy efficiencies and to address decarbonization challenges. Their network includes 5,000+ km of gas pipelines within France; they aim to help France attain carbon neutrality by 2050. With these impressive goals in mind, Teréga has created IO-Base — the digital platform to improve industrial performance, and increase profitability. Creating digital twins for their clients allows them to collect data from all production sites and view it in real time, from anywhere and at any time.
Discover how Teréga uses InfluxDB, Docker, and AWS to monitor its gas and hydrogen pipeline infrastructure. They chose to replace their legacy data historian with InfluxDB — the purpose built time series database. They are collecting more than 100K different metrics at various frequencies — some are collected every 5 seconds to only every 1-2 minutes. THey have reduced overall IT spend by 50% and collect 2x the amount of data at 20x frequency! By using various industrial protocols (Modbus, OPC-UA, etc.), Teréga improved output, reduced the TCO, and is now able to create added-value services: forecast, monitoring, predictive maintenance.
Join this webinar as Thomas Delquié dives into:
Teréga's approach to modernizing fossil fuel pipelines IT systems while improving yields and safety
Their centralized methodology to collecting sensor, hardware, and network metrics
The importance of time series data and why they chose InfluxDB
Build an Edge-to-Cloud Solution with the MING StackInfluxData
FlowForge enables organizations to reliably deliver Node-RED applications in a continuous, collaborative, and secure manner. Node-RED is the popular, low-code programming solution that makes it easy to connect different services using a visual programming environment. InfluxData is the creator of InfluxDB, the purpose-built time series database run by developers at scale and in any environment in the cloud, on-premises, or at the edge.
Jump-start monitoring your industrial IoT devices and discover how to build an edge-to-cloud solution with the MING stack. The MING stack includes Mosquitto/MQTT, InfluxDB, Node-RED, and Grafana. This solution can be used to improve fleet management, enable predictive maintenance of industrial machines and power generation equipment (i.e. turbines and generators) and increase safety practices (i.e. buildings, construction sites). Join this webinar to learn best practices from industrial IoT SME's.
In this webinar, Robert Marcer and Jay Clifford dive into:
Best practices for monitoring sensor data collected by everyone — from the edge to the factory
Tips and tricks for using Node-RED and InfluxDB together
Demo — see Node-RED and InfluxDB live
Meet the Founders: An Open Discussion About Rewriting Using RustInfluxData
Rust is a systems programming language designed for high performance, type safety, and concurrency. According to Stack Overflow’s annual survey in 2022, Rust is the most loved language with 87% of developers saying they want to continue using it. The same survey also reported that nearly 20% of developers aren’t currently using Rust, but want to start developing using it.
Ockam’s suite of programming libraries, command line tools, and managed cloud services enable developers to orchestrate end-to-end encryption. InfluxDB is the purpose-built time series database developed to handle time series data for IoT, monitoring, and real-time analytics. Ockam was originally developed using C, and InfluxDB was originally written using Go; both solutions have been completely rewritten in Rust. Discover why two founders decided to rewrite their developer tools using Rust, and gain insight into the strategy beforehand and the entire process.
Join this live panel as Mrinal Wadhwa and Paul Dix dive into:
Their approach to rewriting a project in Rust
How to build and train engineering teams
Tips and tricks learned along the way - pitfalls to look out for!
Join this webinar as there will be a live discussion with Q&A
InfluxData is excited to announce the general availability of InfluxDB Cloud Dedicated! It is a fully managed time series database service running on cloud infrastructure resources that are dedicated to a single tenant. With this new offering, we’re excited to provide our customers with additional security options, and more custom configuration options to best suit customers’ workload requirements. Join this webinar to learn more about InfluxDB Cloud, and the new dedicated database service offering!
In this webinar, Balaji Palani and Gary Fowler will dive into:
Key features of the new InfluxDB Cloud Dedicated solution
Use cases for using the newest version of the purpose-built time series database
Live demo
During this 1-hour technical webinar, you’ll also get a chance to ask your questions live.
Gain Better Observability with OpenTelemetry and InfluxDB InfluxData
Many developers and DevOps engineers have become aware of using their observability data to gain greater insights into their infrastructure systems. InfluxDB is the purpose-built time series database used to collect metrics and gain observability into apps, servers, containers, and networks. Developers use InfluxDB to improve the quality and efficiency of their CI/CD pipelines. Start using InfluxDB to aggregate infrastructure and application performance monitoring metrics to enable better anomaly detection, root-cause analysis, and alerting.
This session will demonstrate how to record metrics, logs, and traces with one library — OpenTelemetry — and store them in one open source time series database — InfluxDB. Zoe will demonstrate how easy it is to set up the OpenTelemetry Operator for Kubernetes and to store and analyze your data in InfluxDB.
How a Heat Treating Plant Ensures Tight Process Control and Exceptional Quali...InfluxData
American Metal Processing Company ("AMP") is the US' largest commercial rotary heat treat facility with customers in the automotive, construction, military, and agriculture industries. They use their atmosphere-protected rotary retort furnaces to provide their clients with three primary hardening services: neutral hardening (quench and temper), carburizing, and carbonitriding.
This furnace style ensures consistent, uniform heat treatment process vs. traditional batch-or-belt-style furnaces; excels at processing high volumes of smaller parts with tight tolerances; and improves the strength and toughness of plain carbon steels. Discover why AMP’s use of Telegraf, InfluxDB, Node-RED, and Grafana allows them to gain 24/7 insights into their plant operations and metallurgical results. Learn how they use time-stamped data to gain accurate metrics about their consumables usage, furnace profiles, and machine status.
Join this webinar as Grant Pinkos dives into:
American Metal Processing's approach to heat treating in a digitized environment through connected systems
Their approach to collecting and measuring sensor data to enable predictive maintenance and improve product quality
Why they need a time series database for managing and analyzing vast amounts of time-stamped data
How Delft University's Engineering Students Make Their EV Formula-Style Race ...InfluxData
Delft University is the oldest and largest technical university in the Netherlands with 25,000+ students. Since 1999, they have had a team of students (undergraduate and graduate) designing, building, and racing cars, as part of the Formula Student worldwide competition. The competition has grown to include teams from 1K+ universities in 20+ countries. Students are responsible for all aspects of car manufacturing (research, construction, testing, developing, marketing, management, and fundraising). Delft University's team includes 90 students across disciplines.
Discover how Delft University's team uses Marple and InfluxDB to collect telemetry and sensor metrics while they develop, test, and race their electrics cars. They collect sensor data about their EV's control systems using a time series platform. During races, they are collecting IoT data about their batteries, accelerometer, gyroscope, tires, etc. The engineers are able to share important car stats during races which help the drivers tweak their driving decisions — all with the goal of winning. After races, the entire team are able to analyze data in Marple to understand what to do better next time. By using Marple + InfluxDB, their team are able to collect, share and analyze high frequency car data used to make their car faster at competitions.
Join this webinar as Robbin Baauw and Nero Vanbiervliet dive into:
Marple's approach to empowering engineers to organize, analyze, and visualize their data
Delft University's collaborative methodology to building and racing their Formula-style race car
How InfluxDB is crucial to their collaborative engineering and racing process
Introducing InfluxDB’s New Time Series Database Storage EngineInfluxData
InfluxData is excited to announce the general availability of InfluxDB Cloud's new storage engine! It is a cloud-native, real-time, columnar database optimized for time series data. InfluxDB's rebuilt core was coded in Rust and sits on top of Apache Arrow and DataFusion. InfluxData's team picked Apache Parquet as the persistent format. In this webinar, Paul Dix and Balaji Palani will demonstrate key product features including the removal of cardinality limits!
They will dive into:
The next phase of the InfluxDB platform
How using Apache Arrow's ecosystem has improved InfluxDB's performance and scalability
Key features of InfluxDB Cloud's new core — including SQL native support
Start Automating InfluxDB Deployments at the Edge with balena InfluxData
balena.io helps companies develop, deploy, update, and manage IoT devices. By using Linux containers and other cloud technologies, balena enables teams to quickly and easily build fleets of connected devices. Developers are able to use containers with the language of choice and pull IoT sensor data from 70+ different single board computers into balenaCloud. Discover how to use balena.io to automate your InfluxDB deployments at the edge!
During this one-hour session, experts from balena and InfluxData will demonstrate how to build and deploy your own air quality IoT solution. You will learn:
The fundamentals of IoT sensor deployment and management using balena.
How to use a time series platform to collect and visualize metrics from edge devices.
Tips and tricks to using balenaCloud to automate InfluxDB deployments and Telegraf configurations.
How to use InfluxDB's Edge Data Replication feature to collect sensor data and push it to InfluxDB Cloud for analysis.
No coding experience required, just a curiosity to start your own IoT adventure.
Understanding InfluxDB’s New Storage EngineInfluxData
Learn more about InfluxDB’s new storage engine! The team developed a cloud-native, real-time, columnar database optimized for time series data. We built it all in Rust and it sits on top of Apache Arrow and DataFusion. We chose Apache Parquet as the persistent format, which is an open source columnar data file format. This new storage engine provides InfluxDB Cloud users with new functionality, including the removal of cardinality limits, so developers can bring in massive amounts of time series data at scale.
In this webinar, Anais Dotis-Georgiou will dive into:
Requirements for rebuilding InfluxDB’s core
Key product features and timeline
How Apache Arrow’s ecosystem is used to meet those requirements
Stick around for a demo and live Q&A
Streamline and Scale Out Data Pipelines with Kubernetes, Telegraf, and InfluxDBInfluxData
RudderStack — the creators of the leading open source Customer Data Platform (CDP) — needed a scalable way to collect and store metrics related to customer events and processing times (down to the nanosecond). They provide their clients with data pipelines that simplify data collection from applications, websites, and SaaS platforms. RudderStack's solution enables clients to stream customer data in real time — they quickly deploy flexible data pipelines that send the data to the customer's entire stack without engineering headaches. Customers are able to stream data from any tool using their 16+ SDK's, and they are able to transform the data in-transit using JavaScript or Python. How does RudderStack use a time series platform to provide their customers with real-time analytics?
Join this webinar as Ryan McCrary dives into:
RudderStack's approach to streamlining data pipelines with their 180+ out-of-the-box integrations
Their data architecture including Kapacitor for alerting and Grafana for customized dashboards
Why using InfluxDB was crucial for them for fast data collection and providing single-sources of truths for their customers
Ward Bowman [PTC] | ThingWorx Long-Term Data Storage with InfluxDB | InfluxDa...InfluxData
Customers using ThingWorx and the Manufacturing Solutions often need to store property data longer than the Solutions default to. These customers are recommended to use InfluxDB, and this presentation will cover the key considerations for moving to InfluxDB vs the standard ThingWorx value streams. Join this session as Ward highlights ThingWorx’s solution and its easy implementation process.
Scott Anderson [InfluxData] | New & Upcoming Flux Features | InfluxDays 2022InfluxData
Two new features are coming to Flux that add flexibility
and functionality to your data workflow—polymorphic
labels and dynamic types. This session walks through
these new features and shows how they work.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
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
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Le nuove frontiere dell'AI nell'RPA con UiPath Autopilot™UiPathCommunity
In questo evento online gratuito, organizzato dalla Community Italiana di UiPath, potrai esplorare le nuove funzionalità di Autopilot, il tool che integra l'Intelligenza Artificiale nei processi di sviluppo e utilizzo delle Automazioni.
📕 Vedremo insieme alcuni esempi dell'utilizzo di Autopilot in diversi tool della Suite UiPath:
Autopilot per Studio Web
Autopilot per Studio
Autopilot per Apps
Clipboard AI
GenAI applicata alla Document Understanding
👨🏫👨💻 Speakers:
Stefano Negro, UiPath MVPx3, RPA Tech Lead @ BSP Consultant
Flavio Martinelli, UiPath MVP 2023, Technical Account Manager @UiPath
Andrei Tasca, RPA Solutions Team Lead @NTT Data
zkStudyClub - Reef: Fast Succinct Non-Interactive Zero-Knowledge Regex ProofsAlex Pruden
This paper presents Reef, a system for generating publicly verifiable succinct non-interactive zero-knowledge proofs that a committed document matches or does not match a regular expression. We describe applications such as proving the strength of passwords, the provenance of email despite redactions, the validity of oblivious DNS queries, and the existence of mutations in DNA. Reef supports the Perl Compatible Regular Expression syntax, including wildcards, alternation, ranges, capture groups, Kleene star, negations, and lookarounds. Reef introduces a new type of automata, Skipping Alternating Finite Automata (SAFA), that skips irrelevant parts of a document when producing proofs without undermining soundness, and instantiates SAFA with a lookup argument. Our experimental evaluation confirms that Reef can generate proofs for documents with 32M characters; the proofs are small and cheap to verify (under a second).
Paper: https://eprint.iacr.org/2023/1886
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.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
The Metaverse and AI: how can decision-makers harness the Metaverse for their...Jen Stirrup
The Metaverse is popularized in science fiction, and now it is becoming closer to being a part of our daily lives through the use of social media and shopping companies. How can businesses survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and how does the Metaverse fit into business strategy when futurist ideas are developing into reality at accelerated rates? How do we do this when our data isn't up to scratch? How can we move towards success with our data so we are set up for the Metaverse when it arrives?
How can you help your company evolve, adapt, and succeed using Artificial Intelligence and the Metaverse to stay ahead of the competition? What are the potential issues, complications, and benefits that these technologies could bring to us and our organizations? In this session, Jen Stirrup will explain how to start thinking about these technologies as an organisation.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Quantum Computing: Current Landscape and the Future Role of APIs
Kai Waehner [Confluent] | Real-Time Streaming Analytics with 100,000 Cars Using MQTT, Kafka and InfluxDB 2.0 on Kubernetes | InfluxDays Virtual Experience London 2020
1. IoT Architectures for a Digital Twin
with Apache Kafka and InfluxDB
A Digital Replica of Things - Open, Scalable and Reliable
Kai Waehner
Technology Evangelist
contact@kai-waehner.de
LinkedIn
@KaiWaehner
www.confluent.io
www.kai-waehner.de
2. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Agenda
• Digital Twin - Merging the Physical and the Digital World
• Real World Challenges
• Apache Kafka as Event Streaming Solution for IoT
• IoT Platforms
• Spoilt for Choice for a Digital Twin
• IoT Architectures with Kafka and InfluxDB
• A Digital Twin for 100000 Connected Cars
3
3. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Agenda
• Digital Twin - Merging the Physical and the Digital World
• Real World Challenges
• Apache Kafka as Event Streaming Solution for IoT
• IoT Platforms
• Spoilt for Choice for a Digital Twin
• IoT Architectures with Kafka and InfluxDB
• A Digital Twin for 100000 Connected Cars
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4. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Software and Digital Services become the Key Differentiator
5
https://www.mckinsey.com/industries/advanced-electronics/our-insights/iiot-platforms-the-technology-stack-as-value-driver-in-industrial-equipment-and-machinery
5. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Digital Twin – Merging the Physical and the Digital World
6
• Downtime reduction
• Inventory management
• Fleet management
• What-if simulations
• Operational planning
• Servitization
• Product development
• Healthcare
• Customer experience
“Virtual representation of something else (Physical thing, process, service)”
“A living model that drives a business outcome”
https://www.youtube.com/watch?v=Ri0TD7kYsIQ
6. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Smart Infrastructure:
Digital Solutions for Entire Building Lifecycle
7
https://new.siemens.com/global/en/products/buildings/digitalization/digital-building-lifecycle.html
7. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Connected Car Infrastructure
8
https://www.youtube.com/watch?v=yGLKi3TMJv8
8. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Twinning the Human Body to Enhance Medical Care
9
https://www.challenge.org/insights/digital-twin-in-healthcare/
https://youtu.be/H6JzPCbyVSM
9. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Digital Twin and Artificial Intelligence (AI) / Machine Learning
• Complementary Concepts
• Continuous Learning, Monitoring and Acting
• (Good) Data is key for success
10
https://towardsdatascience.com/understanding-feature-engineering-part-1-continuous-numeric-data-da4e47099a7b
10. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Agenda
• Digital Twin - Merging the Physical and the Digital World
• Real World Challenges
• Apache Kafka as Event Streaming Solution for IoT
• IoT Platforms
• Spoilt for Choice for a Digital Twin
• IoT Architectures with Kafka and InfluxDB
• A Digital Twin for 100000 Connected Cars
11
11. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
History of Automation Industry vs. Big Data and Cloud
https://foss-backstage.de/sites/foss-backstage.de/files/2018-07/Revolutionizing%20Industrial%20IoT%20with%20Apache%20PLC4X.pdf
12. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Trends: Evolution of Convergence between IT and Industrial Automation
https://iot-analytics.com/5-industrial-connectivity-trends-driving-the-it-ot-convergence
13. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Complexity, Cost and Scalability are Main Blockers
14
14. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Huge demand to build an open, flexible, scalable platform
• Real time
• Scalability
• High availability
• Decoupling
• Cost reduction
• Flexibility
• Standards-based
• Extendibility
• Security
• Infrastructure-independent
• Multi-region / global
15. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Agenda
• Digital Twin - Merging the Physical and the Digital World
• Real World Challenges
• Apache Kafka as Event Streaming Solution for IoT
• IoT Platforms
• Spoilt for Choice for a Digital Twin
• IoT Architectures with Kafka and InfluxDB
• A Digital Twin for 100000 Connected Cars
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16. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
The Log ConnectorsConnectors
Producer Consumer
Streaming Engine
Apache Kafka - The Rise of an Event Streaming Platform
17
=
Messaging
+
Storage
+
Integration
+
Processing
17. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
P
Decoupling of Producers and Consumers
Time
C2 C3C1
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18. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Apache Kafka at Scale at Tech Giants
> 7 trillion messages / day > 6 Petabytes / day
“You name it”
* Kafka Is not just used by tech giants
** Kafka is not just used for big data
19
19. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Improve
Customer
Experience
(CX)
Increase
Revenue
(make money)
Business
Value
Decrease
Costs
(save money)
Core Business
Platform
Increase
Operational
Efficiency
Migrate to
Cloud
Mitigate Risk
(protect money)
Key Drivers
Strategic Objectives
(sample)
Fraud
Detection
IoT sensor
ingestion
Digital
replatforming/
Mainframe Offload
Connected Car: Navigation & improved in-
car experience: Audi
Customer 360
Simplifying Omni-channel Retail at Scale:
Target
Faster transactional
processing / analysis
incl. Machine Learning / AI
Mainframe Offload: RBC
Microservices
Architecture
Online Fraud Detection
Online Security
(syslog, log aggregation,
Splunk replacement)
Middleware
replacement
Regulatory
Digital
Transformation
Application Modernization: Multiple
Examples
Website / Core
Operations
(Central Nervous System)
The [Silicon Valley] Digital Natives;
LinkedIn, Netflix, Uber, Yelp...
Predictive Maintenance: Audi
Streaming Platform in a regulated
environment (e.g. Electronic Medical
Records): Celmatix
Real-time app
updates
Real Time Streaming Platform for
Communications and Beyond: Capital One
Developer Velocity - Building Stateful
Financial Applications with Kafka Streams:
Funding Circle
Detect Fraud & Prevent Fraud in Real Time:
PayPal
Kafka as a Service - A Tale of Security and
Multi-Tenancy: Apple
Example Use Cases
$↑
$↓
$↔
Example Case Studies
(of many)
Confluent - Business Value per Use Case
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20. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
10 Reasons for Event Streaming with Apache Kafka
Real Time
Scalable
Cost Reduction
24/7 – Zero downtime, zero data loss
Decoupling – Storage, Domain-driven Design
Data (re-)processing and stateful client applications
Integration – Connectivity to IoT, legacy, big data, everything
Hybrid Architecture – On Premises, multi cloud, edge computing
Fully managed cloud
No vendor locking
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21. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Digital Twin and AI / Machine Learning (with Kafka)
• Complementary Concepts
• Continuous Learning, Monitoring and Acting à Real time, scalable
• (Good) data is key for success à Integration, data processing
22
22. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Hold on…
Kafka is NOT
an IoT Platform!
23. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Device management
Unreliable networks
Connectivity beyond standards
Edge hardware
…
24. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Agenda
• Digital Twin - Merging the Physical and the Digital World
• Real World Challenges
• Apache Kafka as Event Streaming Solution for IoT
• IoT Platforms
• Spoilt for Choice for a Digital Twin
• IoT Architectures with Kafka and InfluxDB
• A Digital Twin for 100000 Connected Cars
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25. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
600+ IoT Platforms
26
https://iot-analytics.com/iot-platform-companies-landscape-2020/
26. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Proprietary IoT Platforms
27
27. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
IoT Offerings from Cloud Providers
28
28. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Standards-based / Open Source IoT Platforms
29
29. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Agenda
• Digital Twin - Merging the Physical and the Digital World
• Real World Challenges
• Apache Kafka as Event Streaming Solution for IoT
• IoT Platforms
• Spoilt for Choice for a Digital Twin
• IoT Architectures with Kafka and InfluxDB
• A Digital Twin for 100000 Connected Cars
30
30. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Characteristics of Digital Twin Technology
• Connectivity
• Physical assets, enterprise software, customers
• Bidirectional communication
• Homogenization
• Decoupling and standardization
• Virtualization of information
• Shared with multiple agents
• Lower cost
• Reprogrammable and smart
• Adjust and improve characteristics
• Digital traces
• Diagnose problems
• Modularity
• Tweak modules of models and machines
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31. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Scenario 1: Digital Twin Monolith
32
Siemens S7, Modbus, Allen Bradley, Beckhoff ADS
IoT
Platform
Digital
Twin
Device Mgt.
Analytics
Connectivity
Homogenization
Reprogrammable and smart
Digital traces
Modularity
32. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Scenario 2: Digital Twin as External Database
33
Siemens S7, Modbus, Allen Bradley, Beckhoff ADS
IoT
Platform
Digital
Twin
Device Mgt.
InfluxDB
Analytics
Connectivity
Homogenization
Reprogrammable and smart
Digital traces
Modularity
33. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Apache
Kafka
Scenario 3: Kafka as Backbone for the
Digital Twin and the Rest of the Enterprise
34
Siemens S7, Modbus, Allen Bradley, Beckhoff ADS
IoT
Platform
Digital
Twin
InfluxDB
Real
Time
App
Batch
App
Request
Response
App
Kafka
Connect
Connectivity
Homogenization
Reprogrammable and smart
Digital traces
Modularity
34. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Apache Kafka
Scenario 4: Kafka as IoT Platform
35
Siemens S7, Modbus, Allen Bradley, Beckhoff ADS
Digital
Twin
InfluxD
B
Real
Time
App
Batch
App
Request
Response
App
Kafka Connect
Connectivity
Homogenization
Reprogrammable and smart
Digital traces
Modularity
Storage Processing
35. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Agenda
• Digital Twin - Merging the Physical and the Digital World
• Real World Challenges
• Apache Kafka as Event Streaming Solution for IoT
• IoT Platforms
• Spoilt for Choice for a Digital Twin
• IoT Architectures with Kafka and InfluxDB
• A Digital Twin for 100000 Connected Cars
36
36. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Building a Digital Twin with Kafka and InfluxDB
Apache Kafka
• Integration
• Decoupling and Backpressure
• Data Processing
• Ingest into InfluxDB
• Consume from InfluxDB
• Consumption by other Applications
InfluxDB
• Storage
• Batch and Real Time Analytics
• Dashboards
Þ Open
Þ Scalable
Þ Mission-critical
37
Data Lake
Batch Analytics
Kafka Streams /
ksqlDB
Stream
Processing
Databases
Message Queues
Sensors
Applications
37. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Edge Digital Twin
Single Broker
(or Cluster)
Digital Twin
Self-managed or
certified OEM Hardware
Kafka
Cluster
in DC /
Cloud
Replicator
Siemens S7, Modbus, Allen Bradley, Beckhoff ADS
38. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Centralized Digital Twin
Single
Kafka Broker
(or Cluster)
Self-managed or
certified OEM Hardware
Siemens S7, Modbus, Allen Bradley, Beckhoff ADS
Single
Kafka Broker
(or Cluster)
Self-managed or
certified OEM Hardware
Siemens S7, Modbus, Allen Bradley, Beckhoff ADS
39. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Global Digital Twin Architecture
Multiple Clusters and Aggregation
Factories à Analytics Cluster
Multi-Region Cluster
High Availability (Disaster Recovery)
Global Data Streaming
Outsourced
Development
40. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Agenda
• Digital Twin - Merging the Physical and the Digital World
• Real World Challenges
• Apache Kafka as Event Streaming Solution for IoT
• IoT Platforms
• Spoilt for Choice for a Digital Twin
• IoT Architectures with Kafka and InfluxDB
• A Digital Twin for 100000 Connected Cars
41
41. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
A Digital Twin with
Kafka, TensorFlow and InfluxDB
42
MQTT
Proxy
InfluxDB
Storage
InfluxDB
Dashboards
+
Analytics
Kafka
Cluster
Kafka
Connect
Car Sensors
Kafka Ecosystem
TensorFlow
InfluxDB
Other Components
Kafka
Streams
(Java)
All
Data
Critical
Data
Ingest
Data
Potential
Detect
KSQL
TensorFlow
Train
Analytic
Model
Consume
Data
Preprocess
Data
Analytic
Model
Deploy
Analytic
Model
Python
https://github.com/kaiwaehner/hivemq-mqtt-tensorflow-kafka-realtime-iot-machine-learning-training-inference
Connectivity
Homogenization
Reprogrammable and smart
Digital traces
Modularity
Mobile App
BI Tool
42. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Architecture for 100000 Connected Cars
Kafka + KSQL + MQTT + TensorFlow + Kubernetes
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https://www.kai-waehner.de/blog/2019/11/08/live-demo-iot-100-000-connected-cars-kubernetes-kafka-mqtt-tensorflow/
43. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Kafka Connect Connector for InfluxDB
44
https://www.confluent.io/hub/confluentinc/kafka-connect-influxdb
44. IoT and Digital Twin with Apache Kafka and InfluxDB – @KaiWaehner - www.kai-waehner.de
Key Takeaways
• A Digital Twin merges the physical and the digital world
• Apache Kafka + InfluxDB enable an open, scalable and reliable infrastructure for a Digital Twin
• Event Streaming complements IoT platforms and other backend applications / databases.
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