Real ClickHouse capacity in Langfuse v4: 2,782 bytes per observation, and why almost half of that is not dataSep 15, 2026
deepagents on a cluster of your own: the SDK is free, the server is not, and what you have to build in betweenSep 15, 2026
Making the model prefer our tools: the priority that exists in no layer, the two primitives that do, and the `_meta` that crosses the gatewaySep 15, 2026
Completing Keycloak for MCP: the protected resource no SDK hands you ready-made, and the enterprise extension that skips the whole flowSep 12, 2026
Keycloak in an AI platform: where it fits, what it solves and the two standards MCP requires and it does not implementSep 12, 2026
Langfuse v4, day 2 (1 of 10): the data model changed underneath, and what really goes into a traceSep 12, 2026
The gateway does not live alone: the JWT that does not validate the audience, the user who never reaches the trace, and the seams you have to write by handSep 12, 2026
Sizing for agents: 275 input tokens for every output token, and why the bottleneck is still decodeSep 12, 2026
LiteLLM's MCP gateway: the second front door, the tool catalogue nobody bills, and why filtering it can make selection worseSep 11, 2026
Humans and agents on the same gateway: why `priority` does not prioritise, the 429 that brings down the whole pool, and the two ways to separate trafficSep 10, 2026
Virtual keys, budgets and limits in LiteLLM: the layer that decides who gets the GPU, and the four things the documentation gets wrongSep 8, 2026
LiteLLM on day 2: one worker per pod, six thousand seconds of timeout and the other five things to change before opening the trafficSep 8, 2026
LiteLLM and Langfuse: the operational pair, and the four places where the trace is lost between the gateway and the dashboardSep 7, 2026
Full TCO of an on-premise GPU cluster: from capex to the all-in €/GPU-hour and the break-even against cloudJun 16, 2026
Sovereign on-premise vs hyperscalers: the case with data (cost, energy, performance and sovereignty)Jun 14, 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
Mixed NVIDIA + Intel environments for LLM inference: from the central H100 cluster to the NUC in the branch officeJun 2, 2026
GPU observability for LLM inference: the twelve DCGM and vLLM metrics that dictate the health of your productionJun 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
Anatomy of an on-premise LLM inference stack: the seven layers that have to hold each other upMay 30, 2026