Software and SaaS development
Digital products that solve, scale and evolve.
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Guides, analysis and lessons on product, artificial intelligence, growth, communications and cloud.
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Digital products that solve, scale and evolve.
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Learn how to deploy schema changes while application versions coexist, using validation and gradual removal to reduce disruption and risk.
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Learn when a backfill is necessary, how to define its scope and choose a method, and how to validate results without duplicating notifications, charges, or changes.
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Learn how to decide when a feature flag is ready to retire, check its dependencies, remove alternative code paths, and validate the change without losing control of your product.
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Retiring an API requires understanding its consumers, agreeing on timelines, and validating the migration. This guide explains when to proceed and how to limit risks.
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A complete handover combines documentation, access, operational practice, and clear responsibilities so the incoming team can maintain and evolve the project.
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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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Compare persistent migration with read-time transformation based on consistency, performance, and consumers. Use practical criteria to choose an approach and plan a reversible transition.
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A practical framework for deciding whether to fix an individual incident, eliminate its root cause, or redesign the process based on frequency, impact, and risk.
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Learn how to assess whether you can replace a SaaS solution without losing data or disrupting workflows by reviewing exports, dependencies, exit tests, and responsibilities.
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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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Shadow mode compares an automated decision with real operations before activation, helping teams identify risks and make evidence-based choices.
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Plan digital maintenance using impact, communication, rollback, and validation criteria to reduce technical and operational risks.
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