AI 资讯
How DoorDash Built an AI Shopping Assistant That Doesn’t Rely on the LLM Alone
DoorDash details the architecture behind Ask DoorDash, its AI-powered conversational shopping assistant, combining LLMs, specialized AI agents, MCP-based tooling, and an intelligence layer with persistent consumer memory and live backend data. Early results show up to 24% higher checkout conversion, 17% larger baskets, and improved intent accuracy using memory-backed sessions. By Leela Kumili
AI 资讯
Presentation: Road to Compliance: Will Your Internal Users Hate Your Platform Team?
Davide de Paolis discusses the realities of rolling out cloud infrastructure compliance without fracturing developer relations. Drawing from a real-world platform team reboot at Sevdesk, he explains how to implement "minimum viable governance" on AWS, utilize event-driven Slack alerting to automate policy feedback, and shift from rigid enforcement to high-empathy, data-driven collaboration. By Davide de Paolis
AI 资讯
AWS Details How One Customer Scaled to One Million Lambda Functions
AWS has outlined how ProGlove, an industrial-wearables manufacturer, was able to scale its SaaS platform to run more than one million AWS Lambda functions spread across thousands of dedicated customer accounts. By Matt Foster
产品设计
Cycle Introduces EU Control Plane as Sovereignty Debate Continues
Cycle recently introduced a separate EU-based control plane, allowing European customers to keep platform management data and telemetry within Europe. The new offering is designed to improve compliance, operational isolation, and responsiveness for European organizations. By Renato Losio
AI 资讯
Cloudflare Details Unified Data Platform Where Billing Workloads Account for 53% of Queries
Cloudflare details Town Lake, an internal unified data platform, and Skipper, an AI analytics agent unifying access to operational, billing, security, and business data. The platform processed ~91K billing queries, with billing forming majority usage. Built on a lakehouse architecture using Trino, Iceberg, R2, and DataHub, it enables governed cross-system analytics and natural language access. By Leela Kumili
开发者
Shifting Platform Development from Projects to Products
A company shifted from project- to product-thinking after their platform outgrew single-team use. The limitations that they felt with their platform were one-off deliveries, lack of product vision, and weak feedback loops. They have moved toward a self-service, API-driven, multi-tenant infrastructure with clearer ownership and better abstractions. By Ben Linders
AI 资讯
Presentation: Enhancing Reliability Using Service-Level Prioritized Load Shedding at Netflix
The speakers discuss Netflix’s architecture for surviving extreme traffic spikes. They explain the mechanics of prioritized load shedding embedded in their Envoy sidecar proxy, allowing user-initiated requests to steal capacity from non-critical traffic. They share automated platform strategies for continuous chaos load testing, config generation, and retry storm mitigation. By Anirudh Mendiratta, Benjamin Fedorka
AI 资讯
Presentation: Write-Ahead Intent Log: A Foundation for Efficient CDC at Scale
Vinay Chella and Akshat Goel discuss the challenges of running traditional CDC across heterogeneous databases during peak order traffic. They explain how Debezium hit limits under high load and share how they built Write-Ahead Intent Log (WAIL) - a custom architecture that utilizes a dumb producer proxy and a smart consumer pattern to cleanly separate the intent from the state payload. By Vinay Chella, Akshat Goel
AI 资讯
Presentation: Confidently Automating Changes Across a Diverse Fleet
Netflix engineer Casey Bleifer shares how to achieve rapid, automated code changes across a massive, diverse software fleet. She discusses building an event-driven orchestration platform using composable, Lego-like steps, and explains how Netflix utilizes automated canary validation, compliance checks, and a custom "confidence metric" to eliminate the long tail of manual engineering migrations. By Casey Bleifer
AI 资讯
Pinterest Uses Content Fingerprints for URL Deduplication Across Millions of Domains
Pinterest introduced MIQPS, a URL normalization system that identifies which query parameters affect page identity using rendered content fingerprints. It reduces duplicate processing across millions of domains by replacing rule-based approaches with offline analysis, anomaly detection, and runtime parameter maps, improving ingestion efficiency and scalability in large-scale content pipelines. By Leela Kumili
产品设计
How a Culture of Data-Driven Conversations Can Support Platform Engineering
To provide SRE as a service, a team built a center of excellence, introducing Federated SREs and roles like production manager and technical tribe lead. They created a culture of data-driven conversations where SLOs and SLAs were democratised. Surviving growing cognitive load meant continuously simplifying architecture and embedding sovereignty and resilience into platform design decisions. By Ben Linders
AI 资讯
Presentation: Architecting a Centralized Platform for Data Deletion at Netflix
The speakers discuss the architectural challenges of executing safe data deletion across distributed datastores. Balancing durability, availability & correctness, they explain how to orchestrate multi-system deletion propagation without impacting live traffic. They share lessons on controlling tombstone accumulation, building continuous audit loops, and gaining trust with a centralized platform. By Vidhya Arvind, Shawn Liu
AI 资讯
Shopify Reports 15X Faster Graphql Execution with Breadth First Engine
Shopify introduced GraphQL Cardinal, a new execution engine replacing depth-first traversal with breadth-first execution. The redesign improves large-scale GraphQL performance with up to 15x faster field execution, 6x lower GC overhead, and +4s P50 latency gains. It focuses on execution-layer efficiency and batched resolver processing for high-cardinality commerce queries. By Leela Kumili
AI 资讯
Presentation: From Legacy to Sovereignty: Driving the Future of Insurance through Platform Engineering
Sergiu Petean discusses the strategic journey of evolving DevOps into platform engineering within heavily regulated enterprise environments. He explains how to maximize efficiency using dynamic reference architectures, align platform KPIs directly with board-level business goals, reduce cognitive load via custom team topologies, and maintain innovation sovereignty through open-source technology. By Sergiu Petean