Rate limiting breaks without input data
Rate limiting without data breaks architectural analysis. We examine why the lack of observability makes optimization impossible.
Rate limiting without data breaks architectural analysis. We examine why the lack of observability makes optimization impossible.
Event-driven architecture in banks: how to reduce coupling and not lose reliability. Outbox/inbox patterns, contracts, and real compromises.
AI Infrastructure, GPU Compilers, Agentic Systems, Distributed Systems, High Performance Computing, HPC, Telecommunications, SRE
FSM benchmark network configuration: how NetAgentBench reveals failures of LLM agents in dynamic network scenarios and multi-turn behavior.
Hive federation in a data warehouse: how to move from a monolith to a distributed architecture without downtime or loss of data consistency.
Edge-cloud multi-agent architecture with decentralized management: how to reduce latency, traffic, and enhance resilience in mobile automation. –>
English:
How to design low-latency systems: controlling communication, Disruptor, Aeron, and the trade-offs between speed and architecture.
CPU-free LLM inference: how to remove the CPU from the critical path and stabilize latency in LLM serving architectures.
How an agentic system manages the context window through Journal, Review, and Timeline, reducing latency and improving consistency in multi-agent reasoning.
KV cache optimization in multi-LoRA serving: how ForkKV reduces memory consumption and increases throughput of LLM inference.
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