Cloud database reliability engineering
Database reliability decisions your team can defend.
I help engineering teams running PostgreSQL and AWS Aurora/RDS diagnose performance and resilience risks, test candidate fixes, and deliver an evidence-backed change plan.
Alex Ivanov · 35+ years across databases and data platforms
PostgreSQL · AWS Aurora/RDS · Snowflake · Redshift · SQL Server · Oracle
When to call
A consequential database decision needs independent depth.
Performance symptoms persist and several remedies appear equally plausible.
Incidents recur because evidence, ownership, runbooks, and change controls do not connect.
What you receive
Enough evidence to act—and clear boundaries where evidence stops.
Findings
What is known, what is risky, and what still needs evidence.
Options
Candidate remedies compared against explicit tradeoffs.
Change plan
The recommended action, prerequisites, rollback, and authority boundaries.
Verification
Acceptance criteria, evidence record, and operational follow-through.
Engagements
Bounded work. Concrete outputs.
Expert-led consulting delivered with product discipline—not a SaaS product and not open-ended platform transformation.
Database Reliability Review
Architecture or operational risk is unclear before growth, migration, or a high-impact change.
DeliverableRisk findings, priorities, remediation roadmap, and validation plan.
Performance Qualification
Several fixes look plausible, but the team needs to know which one survives measurement.
DeliverableBaseline, candidate comparison, recommendation, rollback, and verification plan.
DBRE Readiness
Incidents repeat, knowledge is tribal, or database changes lack clear ownership and gates.
DeliverableOperating model, runbooks, review controls, and an automation backlog.
Selected case study
The plan improved. The outcome did not.
A PostgreSQL index changed the execution plan but failed the latency test. The investigation continued until a different design produced a material local result.
See the decision, evidence, and limitations →Field Notes
What difficult database incidents actually teach.
Short accounts from the field: the problem, the decision, the outcome, and the operating practice that followed.
A backup is not real until you can restore it.
A Friday release damaged a live e-commerce database. The immediate recovery mattered; the durable result was a restore discipline the company could rely on.
Read the field note →The PostgreSQL database that was never lost.
PostgreSQL was running and the expected data was gone. The breakthrough came from questioning which instance was actually answering on port 5432.
Read the field note →A fleet report is not an operating model.
A reusable assessment surfaced likely database pressure and likely excess capacity. It also revealed why visibility without ownership and follow-through does not become reliability.
Read the field note →How I work
From symptom to verified decision.
Automation can accelerate evidence and drafts. Production authority remains explicit, reviewable, and human.
01Observe→
02Diagnose→
03Compare→
04Decide→
05Control→
06Verify
Alex Ivanov
Tools can draft a fix. Judgment decides whether it is safe to trust.
I started in software and database work in 1990 and moved through DBA, database engineering, data engineering, and cloud platforms. I bring the context AI does not own: operational tradeoffs, contradictory evidence, failure history, change authority, and accountability for a recommendation your team can review.
Start with the decision