Why Serverless Flink Matters - Blazing Fast Stream Processing Made Scalable
Discover how serverless Flink revolutionizes real-time data processing, offering improved scalability, reduced costs, and increased flexibility. Learn to build low-latency applications focusing on business logic rather than infrastructure management.
Deeply Declarative Data Pipelines with Flink and Kubernetes
Explore declarative streaming data pipelines on Kubernetes using Flink and SQL. Learn to simplify development, integrate systems, and optimize configurations for efficient stream processing.
Real-time Analytics at IoT Scale for Electric Vehicle Systems
Explore how Rivian leverages real-time analytics and IoT technologies to power their electric vehicles through an advanced stack combining Kafka, Flink, and Druid with custom solutions.
Stream Processing with Redpanda and Apache Flink
Master stream processing fundamentals and advanced concepts using Redpanda and Apache Flink, from stateless operations to fault tolerance, followed by hands-on application building and deployment in Java.
Build ML-Enhanced Event Streaming Apps with Python Microservices - Conf42 Python 2023
Develop ML-enhanced event streaming applications using Python microservices, exploring real-time data processing and machine learning integration.
Using the FLiPN Stack for Edge AI
Explore the FLiPN stack for building fast IoT and AI applications. Learn how Apache Flink, NiFi, and Pulsar combine to create scalable streaming solutions for edge computing and rapid data ingestion.
Whisky Clustering with Apache Projects - Groovy, Commons Math, Ignite, Spark, Wayang, Beam and Flink
Analyze top distilleries' whiskeys using K-means clustering from Apache projects to identify the perfect single-malt Scotch. Explore data analysis with Groovy, Commons Math, Ignite, Spark, Wayang, Beam, and Flink.
Apache Flink for Sales Analytics - End-to-End Data Engineering Project
Develop an end-to-end sales analytics project using Apache Flink. Learn data ingestion, processing, complex transformations, and custom output formats for big data processing.
Building Data Lakehouse from Scratch - End-to-End Data Engineering Project
Design, implement, and maintain scalable lakehouse architectures using Apache Spark, Kafka, Flink, Delta Lake, AWS, and open-source tools. Enhance data potential through advanced analytics and machine learning.
Flink SQL: The Challenges to Build a Streaming SQL Engine
Explore challenges in building a streaming SQL engine like Flink SQL. Learn about late data handling, change data processing, event ordering, nondeterminism, and state storage in stream processing.
Dynamic Change Data Capture with Flink CDC and Consistent Hashing
Implement dynamic Change Data Capture for large databases using Flink CDC connectors and consistent hashing. Overcome challenges with incremental snapshotting and Postgres replication slots.
Exactly-Once Semantics Revisited: Distributed Transactions Across Flink and Kafka
Explore challenges and improvements in Exactly-Once Semantics for distributed transactions between Apache Flink and Kafka. Learn about proposed protocol changes and enhanced integration for robust data processing.
Anomaly Detection on Time Series Data Using Apache Flink
Implement real-time anomaly detection on network activity time series data using Apache Flink. Compare EWMA and PEWMA algorithms for effective intrusion detection in cloud-native deployments.
Building Nucleus: Community Brands' Real-Time Analytics Platform
Explore the architecture and design of a real-time analytics platform, featuring sub-second latency, cloud-native services, and CDC streams for efficient data processing and customer insights.
CDC Stream Processing with Apache Flink
Explore Apache Flink's capabilities as a data integration hub, focusing on its SQL engine for changelog processing, CDC data handling, and materialized view maintenance. Learn about data source semantics and system integrations.
Change Data Streaming Patterns with Debezium and Apache Flink
Explore change data capture with Debezium and Apache Flink for microservices. Learn outbox pattern, strangler fig pattern, and saga orchestration for reliable data exchange and long-running transactions.
Realtime Streaming with Data Lakehouse - End-to-End Data Engineering Project
Design, implement, and maintain secure, scalable lakehouse architectures using Apache Spark, Kafka, Flink, Delta Lake, AWS, and open-source tools. Unlock data's potential through advanced analytics and machine learning.
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.
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.
Design Patterns for Running AI/ML and Big Data Workloads on Kubernetes
Explore essential design patterns and solutions for deploying AI/ML and big data workloads on Kubernetes, addressing challenges in container management, data handling, and system optimization.