Mark Sayson

Why data deletion is still an unsolved infrastructure problem

May 31, 2026: Customer data may span hundreds of services, datasets, and integrations. Deleting it consistently requires coordinating execution, validation, and auditability across distributed systems, not just propagating a privacy request.

Why deletion means different things in different systems

Jun 4, 2026: A deletion request may succeed in every system yet produce different outcomes across databases, data warehouses, search indexes, and event streams. Effective deletion begins with defining what "delete" means in each system.

Gaps in data deletion verification and auditability

Jun 13, 2026: Most deletion programs can prove a request was processed. Far fewer can prove that personal data was actually removed everywhere it existed and remained absent over time.

Deletion is not always deletion: retention exceptions and competing obligations

Jun 21, 2026: One of the more surprising aspects of privacy engineering is how many different deletion and retention requirements can apply to the same customer data. A single deletion request may result in immediate deletion in some systems, multi-year retention in others, and event-driven retention in cases such as legal holds.

Deleted and back again: mitigating unintended data resurrection

Aug 31, 2026: A persistent challenge in complex data architectures is keeping data that is subject to deletion from continuing to resurface, as systems re-ingest and propagate data even after executing a deletion request.

Using AWS Organizations to standardize security controls across AWS accounts

May 7, 2025: AWS Organizations provide a helpful, zero-cost way to centralize management of AWS accounts, with support for consolidating billing, role-based permission sets, service and resource control policies, and AWS service configurations.

Process for designing distributed systems

May 31, 2023: A step-by-step framework for designing distributed systems, from validating the problem and gathering requirements to defining APIs, data flows, architecture, and technology choices that scale with future needs.