Software and SaaS development
Digital products that solve, scale and evolve.
Insights
Guides, analysis and lessons on product, artificial intelligence, growth, communications and cloud.
Editorial themes
Digital products that solve, scale and evolve.
AI systems for real-world processes.
Demand, catalogue, partners and conversion.
Every conversation in the right channel.
Available, observable and ready services.
Choose the right test level, limit the scope, and agree on stop signals before you begin. This guide explains how to verify service recovery without unnecessary production changes.
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Prioritize testing based on a failure’s impact, likelihood, and detectability. This practical framework helps validate changes without slowing releases or leaving critical risks uncovered.
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A multi-region deployment can improve continuity or reduce latency, but it adds complexity. Assess data, dependencies, operating costs, and team capacity before deciding.
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Define data freshness according to the decisions it supports. Set acceptable delays, make lag visible, and decide what to do when information becomes outdated.
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Compare shared databases, separate schemas, and dedicated databases to choose the data isolation model that fits your SaaS risks, customers, and team.
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Define users, cases, exceptions, and dependencies to run a representative, safe digital pilot that can guide the next decision.
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A practical framework for assigning autonomy to automations based on impact, reversibility, uncertainty, context, and the ability to correct errors.
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A practical framework for deciding which internal processes require an SLA and which need reviewable operational targets, without inflating costs.
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Learn how to select the first process to digitise with a practical matrix covering impact, urgency, operational capacity, risks and dependencies.
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A practical framework for deciding whether to keep, redesign, restrict, or retire a digital feature using evidence, risk controls, and reversibility.
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Choose between real-time and batch integration based on the cost of delay, volume, available recovery options, and operational capacity.
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A practical framework for deciding whether to retain, integrate, or replace internal tools before building a platform that amplifies existing problems.
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