Candidate A
Database reliability, grounded in evidence
Reliable data systems are built through disciplined decisions.
Cloud database reliability architecture for PostgreSQL, Aurora/RDS, Snowflake, and modern data platforms—from signals and diagnosis to controlled change and verified outcomes.
30+ years across database and data platforms
Qualification record Reviewed evidence
Slow reporting queryIndex candidateMonthly read model
Candidate D
Major local improvement
Accepted for local demo onlySignalsObserve
EvidenceCapture
DiagnosisExplain
DecisionReview
ChangeControl
VerificationProve
Reliability is a decision system
Move from symptoms to evidence before touching production.
The work is not simply making a query faster or adding another dashboard. It is establishing what changed, why it matters, which remedy is justified, and how the result will be verified and documented.
Observe before prescribing
Collect plans, timings, system context, baselines, and failure boundaries before selecting a remedy.
Compare real alternatives
Indexes, rewrites, read models, configuration, and operational controls are evaluated against explicit trade-offs.
Keep approval human
Automation can assemble evidence and draft changes. Production authority remains bounded, reviewable, and auditable.
Cloud DBRE Reference Stack
A useful result is not always the first plausible result.
In the local PostgreSQL scenario, an index candidate changed the plan but did not materially improve p95 latency. A monthly reporting read model performed substantially better—yet the conclusion stayed deliberately local-only.
ProblemSlow reporting query without an index
First candidateRejected: plan changed, p95 did not materially improve
Winning candidateMonthly reporting read model
DecisionAccept for local demonstration only
Production statusNot approved
Where the work applies
Architecture, performance, and operational readiness.
Cloud DBRE Tech helps turn reliability concerns into bounded, evidence-producing work—not open-ended platform transformation.
Reliability architecture review
Workload separation, availability, recovery, observability, change control, and operational ownership.
Performance qualification
Reproducible baselines, candidate matrices, controlled tests, concurrency checks, and explicit acceptance criteria.
DBRE operating model
Runbooks, safe automation, evidence artifacts, review gates, verification, and feedback into future diagnosis.