Tag: Platform Engineering

GitHub has added enterprise MCP allow and deny lists alongside third-party agent activity in usage metrics; this article explains the policy semantics, telemetry boundary, and a practical rollout loop.

Anthropic's Managed Agents now expose session budgets, advisors, inference geography, repository skills, and inference hooks as runtime controls; this article maps their value and remaining boundaries.

An architectural deep dive into Cloudflare's proposed Agentic Internet framework, spanning Web Bot Auth, Markdown for Agents, WebMCP browser tool exposure, and x402 micro-payments.

A comprehensive breakdown of GPU memory topologies, server hardware budgets, 3-phase power, liquid cooling requirements, and a 5-stage TCO evaluation framework for deploying Moonshot's Kimi-K3 2.8T MoE on-premises.

A deep dive into deploying Moonshot Kimi-K3 2.8T MoE on 80 consumer RTX 5090 GPUs: why 44 GPUs fall short, node topologies, 25GbE networking, TCO ledger, and power constraints.

A comprehensive deep dive into OpenAI's official GPT-5.6 release: Sol/Terra/Luna tiering, pricing matrices, Terminal-Bench 2.1 data, Triton kernels, and Agentic Harness routing.

A structured look at Gemini Enterprise Agent Platform's development, runtime, governance, and evaluation capabilities, with the integration boundaries and adoption conditions that matter in enterprise deployments.

Summary of the AWS × Pocketpair session: Amazon GameLift's managed value and cost optimization, and how Palworld achieved the migration of persistent worlds from Kubernetes to GameLift using state externalization, lifecycle adapters, exactly-one world instances, and existing monitoring assets. Also, a breakdown of three major failure cases: Terraform Drift, false-healthy Fleets, and Ping Beacons.

A summary of eCloudvalley Enterprise Solution Architect Elmer's talk: In the face of exponential growth in AI application costs, how to balance innovation with controllable operations using FinOps (OmiFin) and AI Agent governance (MAIAH Platform); covering governance/compliance concepts, the PPT (People/Process/Cloud & Platform) cloud governance model, FOCUS billing standards, and BYOA/Guardrails/Token controls.

A summary of the talk by AWS's Howard and Tomofun (Furbo)'s Ricky, supplemented with the official AWS tech blog: from the vertical integration of Trainium/Inferentia/Graviton/Nitro, to Furbo porting BLIP to Inferentia 2, two-tier Auto Scaling, and AMI cold start optimization, successfully saving 81.6%–83% in AI computing costs.

An in-depth look at how delivery giant DoorDash combined LLMs, domain-specific AI Agents, Model Context Protocol (MCP), and a three-tier memory system to build an enterprise-grade AI shopping assistant capable of running 2,000 automated evaluations daily.