Distributed Readings

Aggregating engineering wisdom, one blog at a time.

24 new this week
0 bookmarked
11 sources
Fetched June 8th, 2026
AWS

Scaling oncology patient support: How New York Cancer and Blood Specialists transformed customer experience with AWS and Pronetx, now part of Caylent

NYCBS needed to modernize their patient engagement and contact center infrastructure to improve patient enrollment and streamline communication with oncology patients.

general api-design
4 min
Airbnb

Sitar-agent: Building a reliable dynamic configuration sidecar at scale

Reliably delivering configuration changes to thousands of Airbnb service instances in Kubernetes, with changes occurring multiple times per minute at scale.

distributed-systems microservices
5 min
Airbnb

When history fails you, borrow from geography

Building reliable forecasting models for marketplace demand when historical data is unavailable or unreliable due to unprecedented market shocks.

ml-systems real-time-systems
5 min
Cloudflare

How we reduced core unit boot time from hours to minutes

Firmware updates were causing core servers to take four hours to reboot, creating operational inefficiency and extended downtime.

observability security
4 min
Cloudflare

Your AI bill is out of control. Cloudflare can fix it now.

Uncontrolled spending on API calls to multiple AI providers due to lack of visibility and budget enforcement mechanisms.

rate-limiting api-design
4 min
Google Cloud

Experimenting with TPUs, GKE Managed DRANET, and Multi-cluster Inference Gateway

Ensuring high availability and service continuity when AI inference workloads fail in one region while maintaining access to the service across multiple regions.

distributed-systems load-balancing
5 min
Google Cloud

Scaling AI Agents: A Step-by-Step Guide to Deploying ADK on GKE Autopilot

Moving AI agents built with Google's Agent Development Kit from local prototypes to production-ready, scalable infrastructure.

distributed-systems microservices
5 min
Meta

Lights Out, Systems On: Validating Instant Power Loss Readiness

Meta needed to validate and ensure their data center infrastructure could survive instantaneous power loss without data corruption or service degradation.

chaos-engineering distributed-systems
5 min
Spotify

Coding Is No Longer the Constraint: Scaling Developer Experience to Teams and Agents at Spotify

Scaling developer productivity and experience when coding is no longer the primary bottleneck, requiring infrastructure and tooling that enable both human teams and AI agents to work effectively.

observability microservices
4 min

Fetched June 1st, 2026
Cloudflare

How we built Cloudflare's data platform and an AI agent on top of it

Cloudflare needed to unify fragmented analytics data across its global edge network and enable intelligent querying of that data at scale.

distributed-systems observability
3 min
Cloudflare

Iran's Internet is partially restored, Cloudflare Radar data shows

How to detect and monitor large-scale Internet shutdowns and measure the extent of network restoration in real-time across a country.

observability distributed-systems
4 min
Dropbox

Beyond code generation: rethinking engineering productivity in the age of AI agents

How to transition from code-generation AI tools that only assist engineers to autonomous agentic systems capable of executing complete, scoped engineering tasks independently.

microservices api-design
3 min
Google

Supercharge your integration workflow with the Google Pay & Wallet Developer MCP server

Developers integrating with Google Pay & Wallet APIs experienced friction by having to context-switch between their IDE and external documentation/tools to validate implementations and manage accounts.

api-design sdks
5 min
Google Cloud

A Guide to AI Cold Starts on Cloud Run

Managing startup latencies up to 20 seconds for AI workloads on Cloud Run serverless GPUs, which causes poor user experience and is driving developers back to traditional container orchestration.

ml-systems distributed-systems
5 min
Netflix

From Silos to Service Topology: Why Netflix Built a Real-Time Service Map

Netflix needed a real-time, dynamic way for engineers to understand service dependencies and troubleshoot issues quickly across their complex distributed microservices infrastructure.

microservices observability
5 min