Why Does the Cloud Stop Computing?: Lessons from Hundreds of Service Outages (2016)
Summary
Analyzes hundreds of cloud service outages to derive lessons on improving reliability and understanding why cloud computing fails.
Similar Articles
Lessons Learned from Building Cloud Agents (12 minute read)
Cursor shares key lessons from building cloud agents, emphasizing that providing a full development environment is critical for agent output quality, and that long-running agents require durable execution and enterprise-like infrastructure.
21 years and counting of 'eight fallacies of distributed computing' (2025)
A retrospective on the eight fallacies of distributed computing, originally formulated by Sun Microsystems engineers, examining their continued relevance 21 years later for network operators and developers.
A single federal order switched off the best cloud model overnight. Clearest case for running local I've seen yet.
A federal order forced a frontier AI lab to suspend its most capable cloud model globally, highlighting the risks of cloud dependency and making a strong case for running local models as a continuity fallback.
On the Reliability of Computer Use Agents
A preprint analyzing why computer-use agents succeed once but fail on repeated executions, attributing unreliability to execution stochasticity, task ambiguity, and behavioral variability, and advocating repeated evaluation and stable strategies.
Something I keep seeing with AI projects that nobody talks about openly
This article highlights that many AI agent projects fail in production not because of model quality, but because teams launch without clearly defining what constitutes failure, missing critical edge cases that lead to confident incorrect outputs.