Build with intent.
Ship with confidence.

The problem

More worker processes could improve job throughput while exhausting a database role’s connection budget. Backups also needed a demonstrated recovery path before an infrastructure transition.

The implementation

I implemented local infrastructure and test tooling across Ansible provisioning, k6 scenarios, a mock LLM, infrastructure monitoring, and PgBouncer transaction pooling. The tests examined job concurrency, slow and failing providers, backups under load, and a pooler restart.

What the measurements showed

At 100 simulated users, a direct-connection run peaked at 70 application-role database connections; a pooled run peaked at 18. Both recorded zero HTTP request failures. These were separate lab runs, not a controlled proof of a production latency improvement.

At higher load, connections stayed bounded while CPU load and job queues grew. A pooler restart caused 7 failed HTTP requests out of 5,756 and one reply timeout. At 150 users, zero HTTP failures still accompanied two reply timeouts: successful HTTP responses did not establish successful completion.

Proving recovery

An encrypted pgBackRest backup and WAL replay restored an earlier 1,000-row batch and excluded a later batch on a fresh VM. The original repository stayed separate from the restored timeline. A 22 MB database proves the procedure, not a production recovery-time objective.

The boundaries

Local VMs, synthetic admin users, a mock model, and polling instead of the real streaming client. Cloud rollout, learner paths, production capacity, production-size recovery, and automatic failover are not established by these tests.

The problem

A Rails platform needed coordinated database, storage, and backup changes ahead of a high-risk production release.

My decision & contribution

I executed staging rehearsal, production-data restore, PostgreSQL upgrades, backup verification, and the storage cutover. Mirrored storage allowed a transition before switching to S3; application-level checks verified behavior.

The result

The production upgrade and cutover completed with less than one hour of customer-visible downtime and no known migration failure. This demonstrates a PostgreSQL/storage modernization, rather than a Rails major-version upgrade or measured recovery-time objective.

The problem

Services shared memory and disk. Unbounded database diagnostic logs could consume shared storage and impair another service’s persistence; worker settings also needed to reflect the actual workload.

My implementation

I contributed Compose deployment configuration, ingestion routing, ClickHouse diagnostic-log caps, Celery worker tuning, and operational documentation. Later authored changes sized resource limits from recorded memory peaks and swap, with the concurrency trade-offs documented.

Backup operations

Transactional PostgreSQL dumps precede file snapshots. Repository-lock retries, retention, and less frequent prune/check operations separate routine backups from expensive maintenance. A daily read of a data subset checks more than the existence of a snapshot.

The trade-offs

Lower worker concurrency saves memory but can delay scheduled tasks. Live analytics-file snapshots remain crash-consistent; partial-read handling requires care. Shared hosting and same-provider backups retain common failure risks.

What is established

The previously reviewed PostHog/Langfuse baseline was confirmed deployed. Later tuning is supported by authored configuration and source-recorded operational observations; its deployment and broader impact are not independently verified. No measured cost savings, uptime improvement, or tested recovery-time claim is made.

The problem

A successful router response did not prove that a home network could receive an inbound connection. A false positive could lead to hardware that could not work in that network.

My decision & contribution

Discover the router, create a temporary port mapping, open a phone-side TCP listener, request an external probe, then clean up. I evolved service detection to handle inconsistent device/XML structures safely.

Ongoing ownership

Primary owner of the React Native mobile architecture, native dependencies, iOS/Android compatibility, testing, and Fastlane/Azure DevOps release workflows. Backend and pod software are outside this ownership claim. No adoption or pass-rate metric is claimed.

The problem

Prompt composition mixed rendering, context loading, and snippet resolution. Chat loading could rebuild prompts and repeat database lookups; shared agent prompts embedded organization-specific instructions.

My contribution

Shipped native Liquid partial rendering, avoided unnecessary rebuilding during chat loading, reduced repeated lookups, and composed organization context around reusable agent behavior.

The boundary

Further decomposition and cache-freshness work was staged or proposed. Separate local benchmarks do not establish shipped production latency or cost improvements.

The change

Required a passing test suite and approximately 70% coverage for new or changed code. Monthly manual DORA-informed reviews of releases and incidents guided smaller batches and pipeline improvements.

The result

The confirmed improvement is deployment frequency, not measured lead time or 70% whole-repository coverage. The reviews were manual, rather than an audited automated DORA dashboard.

A second engagement

On an anonymized SaaS engagement, smaller batches, stronger tests, and automated gates were followed by approximately one-third as many release-caused incidents over roughly three months. The estimated 67% reduction is based on recalled operational experience, not audited metrics.

The problem

Generated invoices and account-balance behavior needed reconciliation against real data. Duplicate calculation paths produced inconsistent totals.

My decision & contribution

I organized fixes by risk, corrected a CHF 1,778 discrepancy, and made affected views consume the same source of truth. Business-policy ambiguity was resolved with the appropriate stakeholder before implementation.

The result

The correction and regression coverage shipped. No related recurrence, reconciliation issue, or stakeholder complaint was known afterward; a quantified support reduction is unavailable.