Technical Debt and Sustainability Questions

Covers strategies and practices for managing technical debt while ensuring long term operational sustainability of systems and infrastructure. Topics include identifying and classifying technical debt, prioritization frameworks, balancing refactoring and feature delivery, and aligning remediation with business timelines. Also covers operational concerns such as monitoring, observability, alerting, incident response, on call burden, runbook and lifecycle management, infrastructure investments, and architectural changes to reduce long term cost and risk. Includes engineering practices like test coverage, continuous integration and deployment hygiene, code reviews, automated testing, and incremental refactoring techniques, as well as organizational approaches for coaching teams, defining metrics and dashboards for system health, tracking debt backlogs, and making trade off decisions with product and leadership stakeholders.

HardTechnical

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You must choose between building an in-house model serving platform or adopting a managed model serving service. Evaluate the decision from the perspective of technical debt, sustainability, long-term cost, control, and testability. Provide criteria that would push you to one choice over the other.

HardSystem Design

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Design an automated rollback mechanism that uses model quality SLIs to trigger rollback to a previous model version. Specify monitoring latency, decision logic, safety checks to avoid oscillation, and how you would test this mechanism end to end before enabling it in production.

EasyTechnical

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List and classify common sources of technical debt specific to ML systems. For each category provide practical indicators to monitor (what metrics or symptoms you'd see) and a simple detection method to use on an existing codebase or pipeline to surface that debt.

HardSystem Design

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You must migrate a monolithic training job to microservices that run distributed training on a cluster. Propose a migration plan that limits regression risk, includes test strategies to ensure functional parity, and details how to monitor for regressions during and after migration.

MediumTechnical

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You inherit a debt backlog of 40 ML-related tickets. Propose a prioritization framework using risk and ROI that sorts the backlog. Explain what metrics you would compute for each ticket, how to present trade-offs to product, and an example of prioritizing three hypothetical items.

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