Kafka Consulting Services - 2025

🚀 Kafka Consulting Services 2025

What’s New in Our Consulting Practice

• KRaft Migration Experts - Seamless ZooKeeper to KRaft transitions
• Cloud-Native Specialists - Kubernetes, serverless, and managed services
• AI/ML Integration - Streaming data pipelines for machine learning
• Multi-Cloud Expertise - AWS, GCP, Azure, and hybrid deployments
• Security First - Zero-trust architectures and compliance
• Cost Optimization - Right-sizing and efficient resource usage

Expert Kafka Consulting for Modern Data Platforms

Transform your data infrastructure with Apache Kafka 4.0. Cloudurable’s expert consultants help organizations build, optimize, and operate high-performance streaming platforms that process billions of events daily.

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Kafka Broker Startup Scripts and Configuration - 2025 Edition

🚀 What’s New in This 2025 Update

Major Updates and Changes

• KRaft Mode by Default - No ZooKeeper required
• Container-First Approach - Docker and Kubernetes native
• Dynamic Configuration - Minimal restarts needed
• Automated Management - Operators handle lifecycle
• Enhanced Monitoring - Built-in observability
• Cloud-Native Patterns - Auto-scaling and self-healing

Broker Startup Evolution Since 2017

• ✅ No ZooKeeper - KRaft provides native consensus
• ✅ Declarative Config - GitOps and Infrastructure as Code
• ✅ Container Ready - Optimized for Kubernetes
• ✅ Zero-Downtime - Rolling updates standard

Running a Kafka Broker in 2025

Starting Kafka brokers has evolved significantly with KRaft mode and cloud-native practices. This guide covers modern approaches from simple local development to production Kubernetes deployments.

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Introduction to Apache Kafka - 2025 Edition

🚀 What’s New in This 2025 Update

Major Updates and Changes

• Kafka 4.0 with KRaft - ZooKeeper completely eliminated
• Cloud-Native Default - Managed services dominate deployments
• 200+ Connectors - Massive ecosystem expansion
• AI/ML Integration - Direct streaming to ML pipelines
• Simplified Operations - Automated scaling and management
• Enterprise Adoption - Used across all industries

Industry Evolution

• ✅ Event Streaming Standard - De facto platform for real-time data
• ✅ Managed Services - AWS MSK, Confluent Cloud mainstream
• ✅ Kubernetes Native - Operators and serverless integration
• ✅ Global Scale - Petabyte deployments common

Ready to understand why Kafka powers the world’s data infrastructure? Let’s explore the streaming platform that processes trillions of events daily.

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Kafka Consulting

Kafka Consulting

Learn how to employ best practices for your teams’ Kafka deployments. Cloudurable has a range of consulting services and training to help you get the most out of Kafka from architecture to help with setting up health checks.

If you are new to Apache Kafka, Cloudurable has mentoring, consulting, and training to help you get the most of the Kafka streaming data platform. Our professional services teams can support your team designing a real-time streaming platform using Kafka. We can work shoulder to shoulder with your DevOps, Ops, and development team. Learn about the best practices, trade-offs, and avoid costly pitfalls to ensure a successful Kafka deployment.

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Kinesis vs. Kafka

Kinesis vs. Kafka

Kinesis works with streaming data.

• Stock prices
• Game data (scores from game)
• Social network data
• Geospatial data like Uber data where you are
• IOT sensors

Kafka works with streaming data too.

Kinesis Streams is like Kafka Core. Kinesis Analytics is like Kafka Streams. A Kinesis Shard is like Kafka Partition.

They are similar and get used in similar use cases.

Data is stored in Kinesis for default 24 hours, and you can increase that up to 7 days.

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Kafka Broker Startup Scripts

Running a Kafka Broker

Starting brokers in Kafka is pretty straightforward, here are some simple quick start instructions. But as developers, we want to do at least a little more than just the basics. For instance my first needs were to start multiple brokers on the same machine, and also to enable JMX.

Out of the box, you can simply rely on the supplied server.properties Each broker needs a unique id and needs a unique port. These are the corresponding properties from server.properties:

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Kafka Tutorial with Examples

Kafka Tutorial

Kafka Tutorial for the Kafka streaming platform. Covers Kafka Architecture with some small examples from the command line. Then we expand on this with a multi-server example. Lastly, we added some simple Java client examples for a Kafka Producer and a Kafka Consumer. We have started to expand on the Java examples to correlate with the design discussion of Kafka. We have also expanded on the Kafka design section and added references.

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High-Speed Microservices

Microservices Architecture | High-Speed Microservices

This article endeavors to explain high-speed microservices architecture. If you are unfamiliar with the term microservices, you may want to first read this blog post on microservices by Michael Brunton and if have more time on your hands this one by James Lewis and Martin Fowler.

High-speed microservices is a philosophy and set of patterns for building services that can readily back mobile and web applications at scale. It uses a scale up and out versus just a scale-out model to do more with less hardware. A scale-up and out model uses in-memory operational data, efficient queue hand-off, and async calls to handle more calls on a single node.

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Microservices Architecture

Microservices

The term “Microservices Architecture” is now a popular trend. Unlike many trends, this one seems to have some momentum and is more about how people are developing services versus vendors commandeering and needlessly complicating something simple. For example, SOA started off as a rather simple set of concepts and became something vast and complex. Services are excellent. Web Services are good. SOA has a bad reputation and is associated with being overly complicated (WSDL, BPEL, WS-blah, etc.). Microservices is not SOA. In fact, it in many ways it is directly the opposite. For example, SOA often embraces WSDL which is a very strongly typed and rigid way to define a service endpoint. WSDL and XML schema takes all of the X out of XML.

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Learn about Kafka Architecture

Learning about the Kafka Streaming Platform

Slideshare Kafka Architecture. PDF: Introduction to Kafka Architecture.

Related content

• Kafka Architecture
• What is Kafka?
• Kafka and Schema Registry
• Kafka and Avro
• Kafka Tutorial

Kafka Training

Training for DevOps, Architects and Developers

This Kafka training course teaches the basics of the Apache Kafka distributed streaming platform. The Apache Kafka distributed streaming platform is one of the most powerful and widely used reliable streaming platforms. Kafka is a fault tolerant, highly scalable and used for log aggregation, stream processing, event sources and commit logs. Kafka is used by LinkedIn, Yahoo, Twitter, Square, Uber, Box, PayPal, Etsy and more to enable stream processing, online messaging, facilitate in-memory computing by providing a distributed commit log, data collection for big data and so much more.

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Learn about Kafka Architecture with Java examples

Learning about the Kafka Streaming Platform with simple Java examples

This picks up where the last blog post left off. We added a multi-server version of the Kafka setup. Then we wrote some simple sample Java Kafka producer and a Java Kafka consumer.

Slideshare Kafka Architecture. PDF: Introduction to Kafka Architecture.

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Reactive Microservices Architecture

Reactive Microservices Architecture

Many disciplines of software development came to the same conclusion. They are building systems that react to modern demands on services. Reactive services live up to the Reactive Manifesto. Reactive microservices are built to be robust, resilient, flexible and written with modern hardware, virtualization, rich web clients and mobile clients in mind.

By the original definition of microservices, all microservices are reactive. A microservices that is not reactive is akin a bird without wings or a fish who can’t swim.

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