Work

Impact

• • Enabled bi-directional live sync between Snowflake and Ping Advanced Identity Cloud for 250,000+ student and staff identities.
• • Replaced legacy IAM, unlocking LAUSD’s migration to modern cloud identity at district scale.
• • Improved reliability and reduced operational overhead from nightly manual reconciliations.

Problem

Snowflake write operations were failing during identity syncs because the ForgeRock Database Table Connector incorrectly attempted `RETURN_GENERATED_KEYS` on non-INSERT operations. Since Snowflake views are immutable, deletes/updates failed, blocking the migration and stalling LAUSD’s IAM modernization.

Approach

1. Diagnosed connector’s JDBC misuse (`RETURN_GENERATED_KEYS` on DELETE/PATCH).
2. Patched ForgeRock Database Table Connector to skip unsupported calls.
3. Designed and deployed live sync so that identity changes in Snowflake automatically propagated to Ping AIC—and vice versa.
4. Validated integration with test cohorts; rolled out incrementally to 250K users.
5. Implemented monitoring and alerting for sync reliability.

Results

• • Migration unblocked; Snowflake ↔ Ping AIC synchronization stable in production.
• • LAUSD successfully cut over from legacy IAM, covering quarter-million identities.
• • Reduced sync failures to near-zero; eliminated manual reconciliation overhead.

Impact

• • Modernized docket notice pipeline to Kotlin with stricter contracts and versioned REST.
• • Produced deterministic PDF notices via Freemarker + FlyingSaucer replacement, improving reliability and debuggability.

Problem

Legacy Java utilities and Velocity templates caused brittle formatting and null-handling issues in docket data.

Approach

1. Ported Java to Kotlin with data classes; enforced enums and date formatting in DocketNoticeData.
2. Replaced Velocity with Freemarker; added safe URL escaping via String?.escapeUrlString().
3. Fixed ResultSet mapping, null safety, and associated-case queries.
4. Added tests around getAssociateCaseView; stabilized template rendering.

Results

• • Eliminated classes of null and formatting errors; predictable PDFs and simpler diffs.
• • Clearer API boundaries and easier future changes.

Impact

• • Created a Docker Compose test rig for eDirectory with init imports and cert generation, enabling consistent IdMUnit runs in CI.
• • Reduced flaky start and wait issues with a dynamic readiness gate instead of hardcoded sleeps.

Problem

Manual setup of directory state and TLS blocked reliable automated tests and slowed builds.

Approach

1. Four-service Compose: cert-generator, eDir, eDir-init, test-runner.
2. Dynamic wait for TLS port and health checks before tests.
3. Jenkins pipeline with stages for container startup, AD↔eDir network verification, and Ant build.
4. Host-network config for Maven stages; artifact gating for snapshot and release.

Results

• • Reproducible local and CI environment; fewer flakes and faster feedback loops.
• • Clear runbook and predictable test outcomes.

Impact

• • Built Python pipelines on Azure HPC clusters to analyze GPU thermal and telemetry data used for model training and tuning cycles.
• • Automated access-review compliance workflows, processing 50K+ records and surfacing insights via dashboards.

Problem

Telemetry was scattered and manual compliance processing slowed operations.

Approach

1. Orchestrated Python jobs on Azure and stored and queried data in Azure Data Explorer.
2. Automated access-review workflows with Logic Apps and standardized the data shape.
3. Published interactive dashboards for stakeholders.

Results

• • Faster tuning feedback for HPC users and reduced manual compliance effort.
• • Centralized data with repeatable workflows.

Impact

• • Designed the pipeline to transform Ping Advanced Identity Cloud authentication logs into Verafin-compatible records for fraud and AML workflows.

Problem

Raw Ping logs did not match Verafin’s required schema.

Approach

1. Defined record mapping rules and field normalization in Fluentd using Ruby filters.
2. Built dev and test topology and sample validations against the Verafin specification.
3. Documented deployment and runbook for operations.

Results

• • Clear path to compliant ingestion with auditable transforms.
• • Reduced manual reconciliation by enforcing a single normalized record shape.