AWS giới thiệu Lambda MicroVMs, một giải pháp compute mới kết hợp tính cô lập cấp VM (qua Firecracker), khởi động nhanh từ snapshot đã khởi tạo sẵn, và phiên session kéo dài tới 8 giờ. Khác biệt so với Lambda tiêu chuẩn, MicroVMs cung cấp endpoint HTTPS bền vững, hỗ trợ HTTP/2, gRPC, WebSockets, cũng như truy cập shell và Docker bên trong VM, nhằm mục đích chạy code do AI hoặc người dùng cung cấp trong môi trường sandbox. Tuy nhiên, giải pháp này chỉ hỗ trợ ARM64, có sẵn ở 5 vùng (region) và có mức giá tương tự Fargate. Bài viết cũng so sánh Lambda MicroVMs với AgentCore Runtime: AgentCore là nền tảng agent quản lý có sẵn giao thức tích hợp, trong khi Lambda MicroVMs là giải pháp nguyên thủy cấp thấp mang lại toàn quyền kiểm soát VM.
Vì sao nên đọc: Là người phát triển cần tìm giải pháp an toàn cho các ứng dụng yêu cầu môi trường VM hoàn toàn riêng biệt, như chạy mã AI hoặc code từ người dùng trong môi trường sandbox, thì Lambda MicroVMs từ AWS sẽ cung cấp giải pháp hiệu quả hơn so với các phương pháp truyền thống.
Nguồn: https://theburningmonk.com/2026/06/what-you-need-to-know-about-lambda-microvms. 8sync News chỉ tóm tắt và dẫn link; bản quyền nội dung thuộc tác giả và nguồn gốc.
Modal has built a new ultra-low-latency HTTP serving primitive called Servers, designed for workloads like LLM inference where every millisecond matters. Unlike Modal Web Functions (which include queueing and retries), Servers use a lightweight reverse proxy routing system with no control-plane lookups on the hot path. The architecture uses an AWS NLB at L4, Envoy for TLS termination and HTTP/2 normalization, and an in-house Rust proxy called fprs (built on Cloudflare's Pingora library) for domain association and load balancing. Configuration state is read from Google Spanner via change streams and cached in-memory to avoid per-request network calls. The system also handles autoscaling metrics, proxy auth to block unauthorized requests before they reach containers, and traffic mirroring for A/B testing and continual learning. End-to-end latency is 5–7ms.
The Agent Toolkit for AWS ships three layers: an MCP server with 300+ AWS APIs, 20+ domain-specific skills, and a rules file. Without the rules file, agents have passive access to skills but won't proactively load them before answering. A 17-line rules file in the repo's rules/ directory instructs the agent to check for relevant skills before starting any AWS task, use retrieve_skill to load them, and verify against documentation rather than guessing. Adding the file changed agent behavior from generic architecture advice to specific, justified recommendations — including which API Gateway variant to use and why, exact constraints like the 30s timeout and 10 MB payload limit, and best-practice patterns like one function per route.
Vercel giờ đây hỗ trợ triển khai máy chủ Node.js không cần cấu hình, tự động phát hiện file server.ts ở thư mục gốc hoặc src/server.ts và triển khai dưới dạng ứng dụng Node.js. Tính năng này hoạt động song song với các backend zero-config khác như Express, Koa và NestJS, đồng thời Vercel CLI quản lý phát triển cục bộ (vc dev) và triển khai (vc deploy) mà không cần file cấu hình.
Lập trình viên Node.js sẽ tiết kiệm thời gian và tránh rắc rối khi phát triển, test và triển khai ứng dụng backend mà không cần thiết lập cấu hình thủ công.
Wrangler is the CLI for Cloudflare Workers, used to run code locally, deploy, stream logs, manage secrets, and provision resources like D1 databases, KV, R2, and Queues. Key commands covered include wrangler dev for local development, wrangler deploy for publishing, wrangler tail for live log streaming, wrangler secret put for secure credential storage, and wrangler types for TypeScript binding generation. The config file wrangler.jsonc drives all behavior, and named environments allow separate staging and production setups.
AWS has launched Lambda MicroVMs, a new feature built on the Firecracker virtual machine monitor that allows isolated Linux containers to run for up to eight hours — a significant extension beyond the existing 15-minute Lambda function limit. Developers supply a Dockerfile and artifacts, which Lambda converts into a Firecracker snapshot. MicroVMs support suspend/resume with state preservation, auto-scaling up to 4x base spec, and consumption-based per-second pricing that stops accruing compute charges when suspended. Primary use cases include sandboxed code execution (e.g., scanning malicious packages, running AI-generated code safely), CI/CD pipelines, and AI agent workloads. Currently available in US East, US West, Tokyo, and Ireland regions on Arm-based Graviton instances only.
AWS released Blocks in public preview, an open-source TypeScript framework that bundles application code, local mocks, and AWS infrastructure into composable npm packages called Blocks. Designed with AI agents in mind, it ships with built-in steering files that guide coding agents toward correct architecture. Developers can run a full backend locally without an AWS account using npm run dev, then deploy the same code unchanged to Lambda, DynamoDB, Aurora, API Gateway, and Bedrock. Around 20 Blocks are available covering databases, authentication, AI agents, file storage, real-time messaging, and more. Type safety flows end-to-end from schema to frontend across major web frameworks and native clients. Blocks applications are CDK applications, allowing escape hatches to raw CDK when needed. The framework is free; users pay only for underlying AWS services consumed.
Amazon RDS Multi-AZ DB clusters don't support cross-account snapshot sharing, but this post presents a serverless workaround using AWS Lambda, Step Functions, and EventBridge. The pipeline automates environment refresh across two AWS accounts in seven steps: creating a cluster snapshot, restoring it to a temporary single-AZ instance, creating a shareable instance snapshot, sharing it cross-account, cleaning up the temporary instance, copying and re-encrypting the snapshot in the destination account, and finally restoring it as a Multi-AZ DB cluster. The solution is deployed via CloudFormation templates and triggered with a single CLI command. Extensions include scheduled refreshes via EventBridge Scheduler and data masking for non-production environments.

Amazon EMR Serverless now allows updates to key application configurations — such as maximum capacity and custom image settings — without stopping and restarting the application. New workloads submitted after an update automatically use the new settings, while existing workloads continue uninterrupted. Previously, these changes required a full stop-and-restart cycle, forcing maintenance windows and blocking job submissions. The feature is available across all EMR releases and AWS Regions where EMR Serverless is supported.