Tech Buzz Online

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.

Learn how LLM quantization reduces local model memory, compare common GGUF formats, estimate VRAM needs, and measure quality and inference speed locally.

Learn how TCP congestion control works, how CUBIC and BBR respond to network capacity and loss, and how to compare them safely on Linux across varied paths.

Learn how UEFI Secure Boot verifies boot software, how TPM-measured boot records platform state, and how administrators inspect attestation and recovery risks.

Learn how CRDTs merge concurrent edits across replicas, how common data types work, and the trade-offs in convergence, metadata, and offline collaboration.

Understand how distributed locks and leases coordinate shared work, why stale owners remain dangerous, and how fencing tokens protect writes during failures.

Learn how LLM serving schedulers use continuous batching to balance throughput, latency, memory, and fairness, with vLLM configuration and measurement.

Compare NTP and PTP clock synchronization, learn how offset, drift, asymmetry, and hardware timestamping affect accuracy, and configure chrony or linuxptp.

Understand NUMA nodes, CPU affinity, and Linux memory policies, plus practical commands to improve locality for database, virtualization, and AI workloads.

Learn how the transactional outbox pattern prevents lost events between databases and brokers, with PostgreSQL examples, retries, and ordering trade-offs.

Understand how inference-time scaling spends computation on model responses, which methods help, and how to measure quality, latency, and cost in practice.

Learn how LLM structured outputs and tool calling use schemas, validation, and retry-safe execution to connect model responses with reliable software actions.

Learn how S3 multipart uploads split objects into retryable parts, when the completed object becomes visible, and how checksums and cleanup affect recovery.