
Explore real-world distributed system failures and troubleshooting processes. Learn about failure modes, system anatomy, and key lessons for effective problem-solving in complex environments.

Explore innovative topic filtering techniques for managing large-scale real-time data in distributed systems, enhancing IoT insights and publish/subscribe patterns.

Explore innovative topic filtering techniques for managing large-scale real-time data in distributed systems, enhancing IoT projects and enabling quick, actionable insights.

Explore machine learning applications in cryptocurrency and NFTs, analyzing blockchain technology through deep learning models and discussing ML solutions for enhanced blockchain security.

Explore a case study on implementing Kafka-based microservices data pipelines at scale in Evernorth Health Services, showcasing real-world applications and challenges.

Explore Apache Kafka's transaction evolution, from KIP-98 to KIP-890, covering idempotency, protocol improvements, and solutions for hanging transactions.

Explore partition multihoming (PMH) to mitigate Kafka broker gray failures, enhancing reliability for key-based partitioning. Learn implementation details, workflow, and future roadmap for virtual partitioning in Apache Kafka.

Explore the multi-year journey to enhance Confluent Cloud's performance, learning about workload design, cloud-native complexities, challenges faced, and key principles for improving data streaming systems.

Explore active-active geo-replication in Venice, addressing challenges of last-writer-wins scenarios and enhancing data infrastructure for real-time, multi-source streaming across organizations.

Explore the challenges and solutions of decoupled compute and storage in stream processing systems, focusing on tiered storage mechanisms to balance performance and cost-efficiency.

Optimize automation schedules and reduce failure detection time using self-service reinforcement learning tools. Learn from Netflix's applied RL service deployment experience.

Explore ROSiE, an Erlang implementation of ROS, enabling BEAM-based interaction with robotics ecosystems. Learn its architecture, advantages, and witness live demonstrations including hot code upgrades on active robots.

Explore advanced testing techniques for distributed Erlang applications using trace specifications and chaos engineering. Learn to verify complex scenarios and improve fault tolerance in production systems.

Explore Erlang's application in untrusted decentralized systems, covering HoneyBadgerBFT, threshold cryptography, distributed key generation, and P2P networking for multi-party collaboration.

Learn to connect distributed GraphQL microservices using Apollo Federation, enabling seamless querying of multiple APIs through a single endpoint. Explore implementation with AWS AppSync and Apollo Server in Azure Function.

Explore techniques for investigating failures in distributed systems, including modeling, integration testing, and OpenTelemetry instrumentation to enhance system observability and troubleshooting.

Explore patterns and strategies for handling eventual consistency in software systems, balancing user expectations for immediate feedback with backend performance and decomposability.

Explore strategies for deploying critical health systems using Kubernetes and Kafka, ensuring seamless updates without compromising patient safety or data integrity.

Explore the complexities of asynchronous communication in distributed systems, debunking misconceptions and examining various interpretations to enhance understanding of inter-process communication.

Explore OpenTelemetry tracing principles and implementation in .NET for distributed systems. Learn to trace workflows, identify bottlenecks, and export data to popular visualization backends.

Explore challenges in tracking logs and debugging in microservices architecture. Learn about clock synchronization issues, happened-before relation, vector clocks, and correlation IDs to introduce meaningful order in distributed systems.