Realtime Algorithmic Trading with Apache Flink - End-to-End Data Engineering Project
Develop an end-to-end algorithmic trading system using Apache Flink, Kafka, and Python. Learn real-time data processing, custom algorithms, and financial market insights.
Debezium - Building Streaming Data Pipelines with Change Data Capture
Explore Debezium's features for building streaming data pipelines using popular databases as sources, with a focus on Apache Kafka integration and alternative data sinks.
Optimizing Apache JVMs for Apache Kafka Performance
Optimize Apache JVMs for Apache Kafka performance. Learn about JVM internals, garbage collection, JIT compilation, and cloud-native compilers to enhance real-time data pipelines and reduce costs.
Top 6 Worst Apache Kafka JIRA Bugs
Explore six critical Apache Kafka bugs with expert Anna McDonald. Gain insights into batching, replication protocols, networking, and Scala implementation, enhancing your understanding of Kafka's inner workings.
Migrate Your Kafka Cluster with Minimal Downtime
Learn strategies and tools for migrating Kafka clusters with minimal downtime. Explore MirrorMaker, Confluent Replicator, and Cluster Linking. Gain insights on planning, execution, and overcoming challenges in Kafka migration.
Kafka, Flink, and Beyond: Current Developments and Future Innovations in Data Streaming - 2023
Explore recent advancements, upcoming improvements, and innovative applications in Kafka and Flink data streaming. Gain insights from industry leaders on tiered storage, queues, use cases, and two-phase commit protocol.
Using OpenTelemetry for Deep Observability Within Messaging Queues
Discover how to implement deep observability in messaging queues using OpenTelemetry's semantic conventions, with practical insights on monitoring Kafka, RabbitMQ, and Amazon SQS for enhanced system performance.
Effective Data Platforming with Open Source Tools for Faster Insights
Discover how to build robust data streaming platforms using Strimzi, Kafka, and other open-source tools on Kubernetes, while learning architectural best practices and solutions to common challenges.
Elastic Data Streaming: Autoscaling Apache Kafka on Kubernetes
Discover how to implement autoscaling for Apache Kafka on Kubernetes, exploring key features like auto-rebalancing, node pools, and tiered storage for optimal cloud-native deployment and cost efficiency.
Building a ChatGPT RAG Data Pipeline with RisingWave Stream Processor and Vector Store
Discover how to build a real-time ChatGPT data pipeline using RisingWave stream processor, integrating Twitter feeds with vector embeddings for enhanced similarity search and RAG-based chatbot functionality.
The Power of Apache Pulsar - Harnessing Dapr to Build High Scale Messaging
Discover how FICO leverages Apache Pulsar and Dapr for high-scale messaging, exploring migration strategies, performance benchmarks, and practical implementation tips for event-driven architectures.
How to Migrate from Apache Kafka to Confluent Cloud with Limited Downtime
Learn essential steps and strategies for migrating from Kafka to Confluent Cloud while maintaining service continuity, with practical guidance on planning, setup, and validation processes.
Effective Data Platforming with Open Source Tools for Faster Insights
Discover how to build robust data streaming platforms using open-source tools like Strimzi, Kafka, and Confluent, while applying core software engineering principles for optimal architecture and performance.
AI Workflows with Kafka and Modern Architectures
Discover how to build secure, real-time AI workflows using Apache Kafka, exploring key features, integration patterns, and zero-trust architecture implementation for robust AI data pipelines.
Setting Up a Multi-Node Kafka Cluster for CI Testing
Master setting up and managing a lightweight multi-node Kafka cluster for CI/CD environments, enabling efficient development and testing of streaming applications with GitHub Actions.
Inference on Streaming Data at Scale Using Numaflow
Discover how Numaflow enables scalable ML inference on streaming data, simplifying event processing and integration with messaging systems like Kafka and Pulsar in Kubernetes environments.