
Explore event-driven architecture and Apache Kafka for building scalable, real-time systems with efficient data streaming and communication between components.

Explore MACH Architecture, API limitations, and platform engineering paradigm shifts to enhance business agility and speed to market. Gain insights into coupling patterns and key platform components.

Explore multi-cluster Kubernetes topologies and learn to create a platform using open-source technologies. Discover how to manage complexity and leverage benefits across multiple clusters.

Explore Google Cloud's architecture, solving infinite scale challenges and leveraging distributed infrastructure for high-performance databases.

Revolutionize data engineering with BigQuery continuous queries for real-time AI insights. Explore event-driven pipelines using Vertex AI, Pub/Sub, and Bigtable through Cloud SQL.

Explore scalable ML systems using Ray, GKE, and ML accelerators. Learn to tackle challenges in training LLMs and distributing RL systems for advanced machine learning at scale.

Explore Lingua Franca integration with RIOT for improved reliability in cyber-physical systems. Learn about this time-centric language for concurrent, distributed development.

Explore Dapr's cloud-native capabilities for distributed systems. Learn implementation strategies, custom extensions, and organizational implications for production deployment.

Learn to migrate Kafka clusters from ZooKeeper to KRaft using Strimzi, covering the migration process, Strimzi's support, and a practical demonstration with step-by-step guidance.

Explore foundation models for time series data, addressing challenges in science applications and discussing future research directions in deep learning for time series analysis.

Explore a insightful conversation with Matei Zaharia, creator of Apache Spark, on open-source success, MLflow development, and the future of AI applications combining LLMs with other systems.

Explore chaos engineering to build reliable systems under unpredictable conditions. Learn benefits, trends, and integration with ML systems for improved resilience and observability.

Explore large language model deployment on Polaris supercomputer, focusing on efficient scaling and performance optimization techniques.

Explore secure federated learning with EIFFeL, a framework ensuring update privacy and integrity while detecting and removing malformed data to prevent model poisoning.

Explore advanced FinOps methodology for large organizations. Learn to establish observability at scale, detect usage patterns, and foster dialogue between teams to achieve long-term financial and technical goals.

Explore Apache Kafka's transition from ZooKeeper to KRaft, understanding advantages, challenges, and implications for Kubernetes deployments and the Strimzi project.

Explore CODECO, an innovative open-source framework optimizing Edge-Cloud infrastructure efficiency through cognitive orchestration. Learn its principles, objectives, and potential impact across industries.

Explore Rook and Ceph's security model, examining hardening options for various threat profiles. Learn about encryption, access controls, and containerization benefits for robust data protection.

Explore locationless API management for enhanced security and control across multiple clouds and clusters, leveraging Layer 7 service networks without public internet exposure.

Explore auto-instrumentation for Go using eBPF and OpenTelemetry, enabling context propagation and tracing without code changes or restarts. Learn technical details, challenges, and future plans.

Gain intuition on coroutines in C++20. Explore stackless asyncrony, generators, and senders/receivers through concise examples to improve code readability, maintainability, and composability.