The Monolith Decision
You're the incoming CTO of FinScale, a Series B fintech processing $2M in daily transactions. The monolith is cracking under 10x growth pressure. You have a weekend to choose a strategy.
Explore all content tagged with "Architecture" across insights, frameworks, and resources.
RSS FeedYou're the incoming CTO of FinScale, a Series B fintech processing $2M in daily transactions. The monolith is cracking under 10x growth pressure. You have a weekend to choose a strategy.
You're the new CTO of a mid-stage startup with a 500K-line monolith. Revenue is growing 3x YoY, but deployments take 4 hours and the on-call team is burning out. It's time to make some hard decisions.
Build scalable, decoupled systems with event-driven architecture. Production-ready event bus, domain events, outbox pattern, and dead letter queues.
The Cloudflare crash on November 18th, coupled with recent AWS and Azure outages, reveals an uncomfortable truth: our industry's consolidation has created catastrophic single points of failure at scale. It's time for CTOs to rethink resiliency architecture.
A comprehensive guide to creating, communicating, and executing a technical strategy that drives business value. Includes frameworks, templates, and real-world examples.
A practical framework for evaluating and choosing technologies that will serve your team and business for years to come.
Strategic comparison of microservices and monolithic architectures. Team size, complexity, deployment, costs, and when to choose each approach.
Strategic comparison of REST, GraphQL, and gRPC API architectures. Performance, complexity, tooling, team expertise, and when to choose each approach.
Strategic comparison of MySQL and PostgreSQL. Performance, features, costs, team expertise, and when to choose each relational database.
A systematic approach to evaluating and choosing technology stacks. Includes comparison matrices, risk assessments, and decision frameworks for databases, languages, frameworks, and infrastructure.
A systematic approach to making high-stakes technical decisions that balance speed, cost, and long-term maintainability. Includes decision matrices, evaluation templates, and real-world examples.
A systematic framework for reviewing architecture proposals that balances speed with rigor. Includes review criteria, decision templates, and governance models for teams of all sizes.
Enterprise AI is shifting from pilot chatbots to tool-using, action-taking systems—driving a parallel shift toward standardized interfaces (function calling/MCP), end-to-end model governance...
Teams are moving from experimenting with AI agents to building production-grade, stateful agent platforms—while simultaneously adopting a hardened security posture (assume-compromise, least...
Engineering organizations are treating evaluation as infrastructure: automated LLM-based judging for content quality and rigorous latency/SLO engineering are becoming the control planes that shape...
CTOs are being pushed toward resilience- and efficiency-first engineering as geopolitical/energy shocks and regulatory scrutiny raise the cost of downtime, compute, and poor traceability—reviving...
Engineering resilience is shifting from a cost/availability conversation to a geopolitical and regulatory one: organizations are revisiting data residency, sovereign failover, and distributed...
AI is becoming a production-grade, regulated system: orgs are optimizing for latency, cost, and operational reliability while simultaneously preparing for auditability, measurement, and governance as...
CTOs are entering an era where “compliance” isn’t a separate function: geopolitical exposure and fast-moving tech regulation are directly shaping cloud/AI architecture, third-party vendor strategy,...
AI adoption is colliding with government procurement, supply-chain risk designations, and standards-setting—pushing enterprises to architect for sudden vendor disruption, auditable controls, and...
AI is forcing a “plumbing upgrade”: standardizing agent interfaces, adding AI-ready operational databases into lakehouse stacks, and revisiting messaging/event-streaming choices to support real-time...
The pattern this week: "integration" is the real product (and governance is the bottleneck)
AI adoption is shifting from model selection to building an "AI integration platform" (agents + standardized API access + governance).
AI agent systems are shifting from bespoke integrations to protocol-driven architectures (e.g., MCP, A2A) that decouple orchestration from execution and enable multi-agent coordination at scale.
Have experience to share? We welcome contributions from technical leaders.
Learn how to contribute