Knative and scale-to-zero for LLM inference: when switching off the GPU saves money and when it costs you the SLOAug 31, 2026
KubeVela and Score: handing over the platform by CLI without teaching the developer KubernetesAug 31, 2026
Kubeflow in depth: which pieces are worth it in an on-premise LLM platform and which ones you already haveAug 31, 2026
Backstage as a self-service portal: giving your teams the LLM platform without giving them the clusterAug 31, 2026
The signature-dish specialist: vLLM's attention backend (FlashAttention, FlashInfer and the prefill/decode asymmetry)Jun 8, 2026
The chef who calls out every order: SMs, CUDA streams and CUDA graphs, or why the GPU gets bored generating tokensJun 7, 2026
The kitchen door the maître d' never looked at: network NUMA, Cilium eBPF and DRANET, the fourth leg of pinningJun 6, 2026
Choosing the switchboard: which OSS gateway to put in front, and why the licence decides before the featuresJun 6, 2026
The maître d' who only seats you if you all fit at one table: CPU, Memory and Topology Manager on RKE2Jun 6, 2026
The floor next door: NUMA, hugepages and CPU isolation, or why your GPU waits on the kernelJun 6, 2026
The shared bench: NVLink, NVSwitch and NCCL, the cable every token crosses in tensor parallelJun 6, 2026
Langfuse from the inside: the sorting centre that must not become the bottleneck it came to observeJun 6, 2026
Function calling and tool-augmented retrieval: the detective who knows which file to ask forJun 4, 2026
Ontologies and knowledge graphs in LLMOps: the Linnaean nomenclature that holds up the six pipeline stagesJun 3, 2026
Embeddings in 2026: the three families (dense, sparse, multi-vector), the model zoo and the decision that matters in productionJun 3, 2026
Mixed NVIDIA + Intel environments for LLM inference: from the central H100 cluster to the NUC in the branch officeJun 2, 2026
Incident response runbooks for LLM inference: every alert to a concrete action with Kafka and KeepJun 2, 2026
Anatomy of the twelve DCGM and five vLLM metrics: analogies, documented anomalies and real cases 2024-2026Jun 2, 2026
Canary, blue-green and shadow for LLM models: how to deploy a new version without breaking the SLOJun 1, 2026
GPU observability for LLM inference: the twelve DCGM and vLLM metrics that dictate the health of your productionJun 1, 2026
Technical controls: the ENS × ISO 42001 × EU AI Act cross-mapping over the on-premise LLM architectureJun 1, 2026
ISO/IEC 42001: the operations manual for the AI system — how the AIMS fits over the on-premise LLM platform described in this blogJun 1, 2026
EU AI Act: the technical dossier, article by article, over the blog's on-premise LLM architectureJun 1, 2026
LLM Guard: the sworn translator with a notebook of equivalences — anatomy, scanners and its integration with Langfuse, vLLM and LiteLLMJun 1, 2026
Seven greenfield deployment phases for an on-premise LLM platform: from hardware in the room to the first production tokenMay 31, 2026
Five maturity levels of the platform under the LLM: from a Linux server to a cluster ready for vLLMMay 31, 2026
Structured output: the form with dropdowns that strikes out invalid answers before the model picks one — Outlines, XGrammar, LLGuidance and the maths of the bitmaskMay 30, 2026
Continuous batching: the salon with 8 chairs that does not wait for the slow customer — Orca, vLLM, chunked prefill and goodputMay 30, 2026
Anatomy of an on-premise LLM inference stack: the seven layers that have to hold each other upMay 30, 2026
Multi-LoRA serving: the single translator with a thousand glossaries — shared base, thousands of concurrent adapters and the SGMV kernelMay 30, 2026
MoE inference: the call centre with 256 specialists and 8 taking each call — fundamentals, expert parallel and the economics of DeepSeek-V3May 30, 2026
FlashAttention v1/v2/v3/v4: the librarian who never clears the desk — IO-awareness, async and Blackwell's asymmetryMay 29, 2026
Speculative decoding: the secretary who types ahead of the boss — fundamentals, maths and state of play in May 2026May 29, 2026
Quantization for LLM inference: FP8, INT4 (GPTQ, AWQ) and GGUF — the model's accounting zoomMay 27, 2026
LLM tracing with OpenTelemetry GenAI: the aircraft black box the field stabilised in 2026May 27, 2026
Modern alignment: DPO, KTO, ORPO and SimPO — the sommelier who learns without a reward modelMay 27, 2026
Reranker and hybrid retrieval: the committee that decides the 5 chunks the LLM will actually readMay 25, 2026
RAG corpus curation: the active librarian who decides what goes in, what goes out and what gets signedMay 25, 2026
Evals for LLMs: the layer after tracing that decides whether your model performs or only looks like it doesMay 25, 2026
The OSS catalogue for LLMOps in six stages: tool by tool, what each one does and when to choose itMay 23, 2026
The parallel catalogue: the six LLMOps stages in open source and on the hyperscalers (AWS, GCP, Azure)May 23, 2026
Anatomy of an LLM request in production, May 2026: a tour of the six stages following a single requestMay 22, 2026
MLOps specific to LLMs in 2026: the landscape of three modalities, six stages and ten tools that make them workMay 21, 2026