
Practical guide to refactoring monolithic applications using Domain-Driven Design. Learn to encapsulate data, implement Bounded Contexts, and evolve towards distributed Domain Events through live coding and real-world examples.

Explore Java vulnerabilities, their impact, and defense strategies. Learn about reporting, management, and mitigation techniques to enhance code security and protect against cyber threats.

Explore Java 9's garbage collection improvements for large memory applications, including G1 architecture, concurrent marking, and enhanced performance for data-intensive software.

Explore Redis with Spring Data: high availability, clustering, data structures, and seamless interaction using Spring Data Repository abstraction for efficient key-value store management.

Explore Terracotta's open-source offheap library, providing efficient maps and caches with low heap overhead and high scalability. Learn its implementation using CS concepts from managed and unmanaged environments.

Efficient algorithm for modeling NFS and SAN workloads using Bloom Filter sampling, addressing challenges in file trace modeling for improved system design and testing.

Explore functional exception handling in Java using Vavr, covering Optional, Try, and Either. Learn to avoid "throws" and leverage type-driven development for cleaner, more efficient code.

Explore building a distributed indexing layer for big data, covering design principles, data ingestion, storage, modeling, and in-memory computing techniques for scalable, real-time querying.

Explore functional error handling in Java without "throws" and "try-catch" using type-driven development techniques like Optional, Try, and Either for cleaner, more aesthetic code.

Explore functional error handling in Java, learning from functional languages to avoid traditional exception handling using type-driven development with Optional, Try, and Either.

Explore blockchain technology, from basic concepts to advanced implementations, understanding its advantages, applications, and potential for solving real-world problems.

Explore advanced PHP data structures beyond arrays, including SPL and extensions, to optimize code performance and efficiency in complex applications.

Explore enterprise JVM performance tuning with real-world scenarios, covering memory usage, object creation, I/O throttling, serialization, and benchmarking. Learn practical optimization techniques for significant performance improvements.

Exploring immutable data structures for efficient programming on modern devices. Discusses historical context, persistent data structures, and practical applications in libraries like Om and React.

Explore the potential of connected information beyond traditional web applications, and learn how emerging technologies are reshaping data integration and global identity.

Explores data management challenges in the digital age, discussing scale, speed, persistence, and context. Critiques current trends and technologies, emphasizing the importance of understanding data's lifecycle and structure.

Explore distributed programming with Hazelcast, an open-source solution for easy scaling. Learn about data structures, partitioning, and practical applications in this informative talk.

Explore lambda expressions in Java SE 8, their implementation using invokedynamic, and the performance implications. Gain insights into JVM architecture and language design.

Explore real-time analytics using Apache Cassandra, covering design solutions, data structures, and techniques for maintaining counters and precomputing queries with low latency.

Explore strategies for deploying production models, including data sharing, service building, and AB testing. Learn about ML pipelines, engineering requirements, and effective handoff between data scientists and software engineers.

Discover how Careem optimized its ride-hailing system, reducing response times from minutes to seconds. Learn about the challenges, solutions, and key pillars for building a reliable and scalable marketplace platform.