InfoQ Homepage Scaling Content on InfoQ
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Uber Separates Scaling Intent From Execution on Kubernetes Platform
Uber has published a detailed account of its new ServiceScale controller, which allows multiple orchestrators to safely manage the scaling of the same Kubernetes workloads. The blog post, written by senior software engineers Egor Grishechko and Srikar Paruchuru, describes how the company separated scaling intent from execution to support regional failover without carrying reserved idle capacity.
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Stateless MCP Removes Session Affinity Requirements for AWS Server Deployments
AWS details how the latest Model Context Protocol specification removes protocol-level sessions, sticky-session requirements, and session storage for remote MCP servers. The change enables independent request routing and simpler horizontal scaling while shifting application state, retries, observability, and idempotency concerns to other layers.
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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.
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How HubSpot Scaled Semantic Search to 20 Billion Vectors
SaaS software vendor HubSpot has described how its semantic search platform grew from a proof of concept into an internal service that now manages more than 20 billion vectors across 38-plus teams. The company says the system now supports agents, RAG, and contact deduplication, and that the increase in agent usage has made retrieval quality and latency more important than before.
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From Camera to Cloud: Netflix’s Scalable Media Processing Pipeline
Netflix has detailed a cloud-based system for scaling camera file processing across global film and TV workflows. The pipeline handles ingest, validation, metadata extraction, and media transformation at scale using FilmLight API and distributed compute. It standardizes workflows across editorial, VFX, and color pipelines, improving consistency and reducing manual handling across productions.
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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.
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Scaling Social Systems in Software Organizations
Fast-scaling teams must rebuild trust and psychological safety as their social systems expand. Intentional, redundant communication across multiple formats can keep everyone aligned. Cross-team rituals, buddy systems, and rotating facilitators can reduce silos by building bridges between teams. Leaders accelerate this by modeling the vulnerability they want to see.
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Meta Deploys Unified AI Agents to Automate Performance Optimization at Hyperscale
Meta has unveiled a new AI-driven capacity efficiency platform that uses unified AI agents to automatically detect and resolve performance issues across its global infrastructure, marking a significant step toward self-optimizing systems at hyperscale.
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Netflix Scales "Human Infrastructure" to Manage Global Live Operations
Netflix has introduced a "human infrastructure" layer to manage live broadcasts at scale. Using a low-latency "telemetry hot path" and a Live Operations Centre, the company now balances automated scaling with human oversight. This shift, which mirrors strategies at AWS and Disney+, focuses on maintaining reliability through expert intervention during high-concurrency global events.
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Cloudflare Outlines MCP Architecture as Enterprises Confront Security and Governance Risks
Cloudflare has outlined a reference architecture for scaling Model Context Protocol (MCP) deployments across the enterprise, positioning centralized governance, remote server infrastructure, and cost controls as key requirements for production-ready agent systems.
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GitHub Acknowledges Recent Outages, Cites Scaling Challenges and Architectural Weaknesses
GitHub has publicly addressed a series of recent availability and performance issues that disrupted services across its platform, attributing the incidents to rapid growth, architectural coupling, and limitations in handling system load.
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How to Handle Trust and Psychological Safety When Scaling Organizations
As organizations scale, communication overload, loss of shared context, and trust gaps emerge, Charlotte de Jong Schouwenburg mentioned. Trust must be built team by team; it can’t be replicated. Trust is interpersonal, while psychological safety exists among people and fuels learning. Leaders must deliberately design structures, rituals, and metrics that reward transparency and cohesion at scale.
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QCon London 2026: Shielding the Core: Architecting Resilience with Multi-Layer Defenses
Anderson Parra, staff software engineer at SeatGeek, presented “Shielding the Core: Architecting Resilience with Multi-Layer Defenses” at QCon London 2026. Parra discussed strategies on how to handle significant traffic spikes in systems that can overwhelm an even well-designed infrastructure.
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OpenAI Scales Single Primary PostgreSQL Instance to Millions of Queries per Second for ChatGPT
OpenAI described how it scaled PostgreSQL to support ChatGPT and its API platform, handling millions of queries per second for hundreds of millions of users. By running a single-primary PostgreSQL deployment on Azure with nearly 50 read replicas, optimizing query patterns, and offloading write-heavy workloads to sharded systems, OpenAI maintained low-latency reads while managing write pressure.
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Enhancing Reliability Using Service-Level Prioritized Load Shedding: Netflix at QCon SF 2025
At QCon San Francisco, Netflix engineers unveiled their advanced Service-Level-Prioritized Load-Shedding strategy, enhancing reliability during traffic spikes. By prioritizing high-value requests and automating management across microservices, they safeguard user experience and system stability. Key insights stress prioritization, automation, and structured load shedding for optimal resilience.