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Learn how Kafka's KRaft metadata quorum elects controllers, replicates cluster metadata, handles failures, and differs from broker and consumer coordination.

Learn how Cilium Cluster Mesh connects Kubernetes clusters, shares service endpoints and identities, and what to plan for cross-cluster networking.

Learn how Firecracker microVMs combine KVM, a minimal device model, and a process jailer to isolate workloads, where they fit, and how to launch one on Linux.

Learn how Kubernetes JobSet groups Jobs for distributed training and HPC, including networking, lifecycle policies, installation, and scheduler limitations.

Learn how Kubernetes Kueue admits batch and AI workloads with LocalQueues, ClusterQueues, quotas, cohorts, fair sharing, preemption, and practical setup.

Learn how Linux sched_ext lets BPF programs define CPU scheduling policies, how its dispatch queues work, and how the kernel recovers when a scheduler exits.

Learn how remote snapshotters speed container image startup, fetch OCI layers on demand, and balance faster launches against cache and registry latency.

Learn how gossip protocols spread cluster membership, detect suspected failures, and converge without all-to-all heartbeats, plus a practical Consul example.

Learn how Kafka transactions combine idempotent writes and offset commits, where exactly-once processing applies, and why external side effects still need care.

Learn how the Kubernetes Gateway API Inference Extension routes requests to model servers, what InferencePool and Endpoint Picker do, and how to validate them.

Learn what Linux Pressure Stall Information measures, how CPU, memory, and I/O stalls appear in PSI, and how to use pressure data to diagnose contention.

Understand how RDMA moves data between hosts, how InfiniBand and RoCEv2 differ, and how Ethernet congestion control shapes reliable cluster networks at scale.

Learn how the A2A protocol lets AI agents discover one another, exchange tasks, track long-running work, and interoperate without sharing internal tools.

Understand Apache Iceberg's table format, metadata tree, snapshots, schema evolution, catalogs, and maintenance workflows for reliable data lake analytics.

Compare CUDA, AMD ROCm and HIP, and Vulkan compute to understand execution models, GPU support, libraries, portability, and best-fit AI and compute workloads.