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Apache Kafka is an open-source distributed event streaming platform used for building real-time data pipelines and streaming apps. It was developed by LinkedIn in 2011 to solve problems with data integration and processing. Kafka uses a publish-subscribe messaging model and is designed to be fast, scalable, and durable. It allows both streaming and storage of data and acts as a central data backbone for large organizations.
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Apache kafka
This document provides an introduction to Apache Kafka, an open-source distributed event streaming platform. It discusses Kafka's history as a project originally developed by LinkedIn, its use cases like messaging, activity tracking and stream processing. It describes key Kafka concepts like topics, partitions, offsets, replicas, brokers and producers/consumers. It also gives examples of how companies like Netflix, Uber and LinkedIn use Kafka in their applications and provides a comparison to Apache Spark.
Building streaming data applications using Kafka*[Connect + Core + Streams] b...
Abstract:- Apache Kafka evolved from an enterprise messaging system to a fully distributed streaming data platform for building real-time streaming data pipelines and streaming data applications without the need for other tools/clusters for data ingestion, storage and stream processing. In this talk you will learn more about: A quick introduction to Kafka Core, Kafka Connect and Kafka Streams through code examples, key concepts and key features. A reference architecture for building such Kafka-based streaming data applications. A demo of an end-to-end Kafka-based streaming data application.
Kafka presentation
Kafka is an open source messaging system that can handle massive streams of data in real-time. It is fast, scalable, durable, and fault-tolerant. Kafka is commonly used for stream processing, website activity tracking, metrics collection, and log aggregation. It supports high throughput, reliable delivery, and horizontal scalability. Some examples of real-time use cases for Kafka include website monitoring, network monitoring, fraud detection, and IoT applications.
Building Streaming Data Applications Using Apache Kafka
Apache Kafka evolved from an enterprise messaging system to a fully distributed streaming data platform for building real-time streaming data pipelines and streaming data applications without the need for other tools/clusters for data ingestion, storage and stream processing.
In this talk you will learn more about:
1. A quick introduction to Kafka Core, Kafka Connect and Kafka Streams: What is and why?
2. Code and step-by-step instructions to build an end-to-end streaming data application using Apache Kafka
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Kafka is primarily used to build real-time streaming data pipelines and applications that adapt to the data streams. It combines messaging, storage, and stream processing to allow storage and analysis of both historical and real-time data.
Kafka Streams for Java enthusiasts
Kafka, Apache Kafka evolved from an enterprise messaging system to a fully distributed streaming data platform (Kafka Core + Kafka Connect + Kafka Streams) for building streaming data pipelines and streaming data applications.
This talk, that I gave at the Chicago Java Users Group (CJUG) on June 8th 2017, is mainly focusing on Kafka Streams, a lightweight open source Java library for building stream processing applications on top of Kafka using Kafka topics as input/output.
You will learn more about the following:
1. Apache Kafka: a Streaming Data Platform
2. Overview of Kafka Streams: Before Kafka Streams? What is Kafka Streams? Why Kafka Streams? What are Kafka Streams key concepts? Kafka Streams APIs and code examples?
3. Writing, deploying and running your first Kafka Streams application
4. Code and Demo of an end-to-end Kafka-based Streaming Data Application
5. Where to go from here?
Trivadis TechEvent 2016 Apache Kafka - Scalable Massage Processing and more! ...
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Spark Streaming + Kafka 0.10: an integration story by Joan Viladrosa Riera at...
This document provides an overview of Apache Kafka and Spark Streaming and their integration. It discusses:
- What Apache Kafka is and how it works as a publish-subscribe messaging system with topics, partitions, producers, and consumers.
- What Apache Spark Streaming is and how it provides streaming data processing using micro-batching and leveraging Spark's APIs and engine.
- The evolution of the integration between Kafka and Spark Streaming, from using receivers to the direct approach without receivers in Spark 1.3+.
- Details on how to use the new direct Kafka integration in Spark 2.0+ including location strategies, consumer strategies, and committing offsets directly to Kafka.
- Considerations around at-least
Recommended
Apache kafka
This document provides an introduction to Apache Kafka, an open-source distributed event streaming platform. It discusses Kafka's history as a project originally developed by LinkedIn, its use cases like messaging, activity tracking and stream processing. It describes key Kafka concepts like topics, partitions, offsets, replicas, brokers and producers/consumers. It also gives examples of how companies like Netflix, Uber and LinkedIn use Kafka in their applications and provides a comparison to Apache Spark.
Building streaming data applications using Kafka*[Connect + Core + Streams] b...
Abstract:- Apache Kafka evolved from an enterprise messaging system to a fully distributed streaming data platform for building real-time streaming data pipelines and streaming data applications without the need for other tools/clusters for data ingestion, storage and stream processing. In this talk you will learn more about: A quick introduction to Kafka Core, Kafka Connect and Kafka Streams through code examples, key concepts and key features. A reference architecture for building such Kafka-based streaming data applications. A demo of an end-to-end Kafka-based streaming data application.
Kafka presentation
Kafka is an open source messaging system that can handle massive streams of data in real-time. It is fast, scalable, durable, and fault-tolerant. Kafka is commonly used for stream processing, website activity tracking, metrics collection, and log aggregation. It supports high throughput, reliable delivery, and horizontal scalability. Some examples of real-time use cases for Kafka include website monitoring, network monitoring, fraud detection, and IoT applications.
Building Streaming Data Applications Using Apache Kafka
Apache Kafka evolved from an enterprise messaging system to a fully distributed streaming data platform for building real-time streaming data pipelines and streaming data applications without the need for other tools/clusters for data ingestion, storage and stream processing.
In this talk you will learn more about:
1. A quick introduction to Kafka Core, Kafka Connect and Kafka Streams: What is and why?
2. Code and step-by-step instructions to build an end-to-end streaming data application using Apache Kafka
Kafka Explainaton
Kafka is primarily used to build real-time streaming data pipelines and applications that adapt to the data streams. It combines messaging, storage, and stream processing to allow storage and analysis of both historical and real-time data.
Kafka Streams for Java enthusiasts
Kafka, Apache Kafka evolved from an enterprise messaging system to a fully distributed streaming data platform (Kafka Core + Kafka Connect + Kafka Streams) for building streaming data pipelines and streaming data applications.
This talk, that I gave at the Chicago Java Users Group (CJUG) on June 8th 2017, is mainly focusing on Kafka Streams, a lightweight open source Java library for building stream processing applications on top of Kafka using Kafka topics as input/output.
You will learn more about the following:
1. Apache Kafka: a Streaming Data Platform
2. Overview of Kafka Streams: Before Kafka Streams? What is Kafka Streams? Why Kafka Streams? What are Kafka Streams key concepts? Kafka Streams APIs and code examples?
3. Writing, deploying and running your first Kafka Streams application
4. Code and Demo of an end-to-end Kafka-based Streaming Data Application
5. Where to go from here?
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This document provides an overview of Apache Kafka and Spark Streaming and their integration. It discusses:
- What Apache Kafka is and how it works as a publish-subscribe messaging system with topics, partitions, producers, and consumers.
- What Apache Spark Streaming is and how it provides streaming data processing using micro-batching and leveraging Spark's APIs and engine.
- The evolution of the integration between Kafka and Spark Streaming, from using receivers to the direct approach without receivers in Spark 1.3+.
- Details on how to use the new direct Kafka integration in Spark 2.0+ including location strategies, consumer strategies, and committing offsets directly to Kafka.
- Considerations around at-least
Apache kafka
Apache Kafka is a distributed publish-subscribe messaging system that can handle high volumes of data and enable messages to be passed from one endpoint to another. It uses a distributed commit log that allows messages to be persisted on disk for durability. Kafka is fast, scalable, fault-tolerant, and guarantees zero data loss. It is used by companies like LinkedIn, Twitter, and Netflix to handle high volumes of real-time data and streaming workloads.
kafka_session_updated.pptx
This document provides an overview of Apache Kafka including:
- Apache Kafka is a distributed streaming platform that allows for publishing and subscribing to streams of records.
- It introduces key Apache Kafka concepts like topics, producers, consumers, brokers, and components.
- Use cases for Apache Kafka are also discussed such as messaging, metrics collection, and event sourcing.
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The document discusses Urban Airship's use of Apache Kafka for processing continuous data streams. It describes how Urban Airship uses Kafka for analytics, operational data, and presence data. Producers write device data to Kafka topics, and consumers create indexes from the data in databases like HBase and write to operational data warehouses. The document also covers Kafka concepts, best use cases, limitations, and examples of data structures for storing device metadata in Kafka streams.
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In today's fast-paced, data-driven world, organizations need real-time data pipelines and streaming applications to make informed decisions. Apache Kafka, a distributed streaming platform, provides a powerful solution for building such applications and, at the same time, gives the ability to scale without downtime and to work with high volumes of data. At the heart of Apache Kafka lies Kafka Topics, which enable communication between clients and brokers in the Kafka cluster.
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Attend and Learn:
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- Key concepts of Kafka listeners and how they enable real-time communication between clients and brokers.
- Configuration options available for Kafka listeners and how they can be customized to suit specific use cases.
World of Tanks Experience of Using Kafka
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- Extract non-critical processing from the critical path of your application to reduce request latency
- Provide back-pressure to handle both slow and fast producers/consumers
- Maintain high availability, high performance, and reliable messaging
- Evolve message payloads while maintaining backwards and forwards compatibility.
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This presentation includes a demonstration of remote database synchronization through Twitter.
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This session will start with an introduction into Apache and presents the role of Apache Kafka in a modern data / information architecture and the advantages it brings to the table. Additionally the Kafka ecosystem will be covered as well as the integration of Kafka in the Oracle Stack, with products such as Golden Gate, Service Bus and Oracle Stream Analytics all being able to act as a Kafka consumer or producer.
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- handling Kafka protocol in Envoy;
- Kafka-broker-filter for per-connection proxying;
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References:
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Envoy's support for Kafka protocol, in form of broker-filter and mesh-filter.
Contents:
- overview of Kafka (usecases, partitioning, producer/consumer, protocol);
- proxying Kafka (non-Envoy specific);
- proxying Kafka with Envoy;
- handling Kafka protocol in Envoy;
- Kafka-broker-filter for per-connection proxying;
- Kafka-mesh-filter to provide front proxy for multiple Kafka clusters.
References:
- https://adam-kotwasinski.medium.com/deploying-envoy-and-kafka-8aa7513ec0a0
- https://adam-kotwasinski.medium.com/kafka-mesh-filter-in-envoy-a70b3aefcdef
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Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
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.
Microsoft - Power Platform_G.Aspiotis.pdf
Revolutionizing Application Development
with AI-powered low-code, presentation by George Aspiotis, Sr. Partner Development Manager, Microsoft
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
TrustArc Webinar - 2024 Global Privacy Survey
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
20240605 QFM017 Machine Intelligence Reading List May 2024
Everything I found interesting about machines behaving intelligently during May 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Discover how MongoDB Atlas and vector search technology can revolutionize your application's search capabilities. This comprehensive presentation covers:
* What is Vector Search?
* Importance and benefits of vector search
* Practical use cases across various industries
* Step-by-step implementation guide
* Live demos with code snippets
* Enhancing LLM capabilities with vector search
* Best practices and optimization strategies
Perfect for developers, AI enthusiasts, and tech leaders. Learn how to leverage MongoDB Atlas to deliver highly relevant, context-aware search results, transforming your data retrieval process. Stay ahead in tech innovation and maximize the potential of your applications.
#MongoDB #VectorSearch #AI #SemanticSearch #TechInnovation #DataScience #LLM #MachineLearning #SearchTechnology
National Security Agency - NSA mobile device best practices
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
Dr. Sean Tan, Head of Data Science, Changi Airport Group
Discover how Changi Airport Group (CAG) leverages graph technologies and generative AI to revolutionize their search capabilities. This session delves into the unique search needs of CAG’s diverse passengers and customers, showcasing how graph data structures enhance the accuracy and relevance of AI-generated search results, mitigating the risk of “hallucinations” and improving the overall customer journey.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
Essentials of Automations: The Art of Triggers and Actions in FME
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!
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
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.
Full-RAG: A modern architecture for hyper-personalization
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
ここ3000字までしか入らないけどタイトルの方がたくさん文字入ると思います。
A tale of scale & speed: How the US Navy is enabling software delivery from l...
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Communications Mining Series - Zero to Hero - Session 1
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Recently uploaded (20)
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
National Security Agency - NSA mobile device best practices
National Security Agency - NSA mobile device best practices
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Essentials of Automations: The Art of Triggers and Actions in FME
Essentials of Automations: The Art of Triggers and Actions in FME
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...
Full-RAG: A modern architecture for hyper-personalization
Full-RAG: A modern architecture for hyper-personalization
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
A tale of scale & speed: How the US Navy is enabling software delivery from l...
A tale of scale & speed: How the US Navy is enabling software delivery from l...
Communications Mining Series - Zero to Hero - Session 1
Communications Mining Series - Zero to Hero - Session 1
introductiontoapachekafka-201102140206.pdf
- 1. Introduction to Apache Kafka By: Dhaval Thumar WWW.AIMDEK.COM
- 2. Agenda • What is Apache Kafka? • How Kafka works? • History • Kafka Products • Kafka Core Components
- 3. What is Apache Kafka? ● Apache Kafka is a distributed streaming Open source platform developed by Apache Software Foundation, written in Scala and Java ○ A distributed system is a system with multiple components located on different machines that communicate and coordinate actions via messages in order to appear as a single system to the end-user. ○ Create real time data streams ○ Processing real time data stream
- 4. What is Apache Kafka?
- 5. How Kafka Works? • Kafka adopted Pub-Sub messaging architecture. Brocker Publisher Subscriber Message Broker Message Producer Message Consumer
- 6. History • Developed by Linkedin in 2011 to solve data integration problem
- 7. History
- 8. Kafka Products • Kafka Broker - Central server system • Kafka Client - Producer & Consumer Java & Scala Library • Kafka Connect - Data Integration tool • Kafka Stream - Java & Scala library for Real time stream processing application • KSQL
- 9. Kafka Core Concept • Producer • Consumer • Broker/Server • Cluster • Topic • Partition • Offset • Consumer Groups
- 10. Kafka Producer, Consumer, Broker
- 11. Kafka Topic Guys, I am collecting data from multiple producers. Which one do you want?
- 12. Kafka Topic Ok, give me the data sent by the smart- meter aproducer
- 13. Kafka Topic Well, the smart meter producer is sending three different types of data. 1. Current-load-sent every minute 2. Consumed-units-sent every hour 3. Input-current-fluctuations-sent as and when it happens Which one do you want?
- 14. Kafka Topic Well, give me the current-load Message
- 15. Kafka Topic Ok, so you are looking for a current-load message. That’s great! But we have a bunch of smart meter producers, and all of them are sending the current-load message. so which one of those are you interested in?
- 16. Kafka Topic
- 17. Kafka Topic Give me all the data that you received in the current load
- 18. Live Demo
- 20. www.aimdek.com AIMDek Technologies Pvt. Ltd. +91 78747 88766 | +1 844-744-4423 Sales: sales@aimdek.com General: hello@aimdek.com AIMDek Technologies Inc. +1 647-243-6116 Sales: sales@aimdek.com General: hello@aimdek.com AIMDek Technologies Inc. +1 647-243-6116 Sales: sales@aimdek.com General: hello@aimdek.com www.aimdek.com www.aimdek.com Canada India USA