Daniel Byun

Led architecture and development of Hivemind Forge, a full-featured autonomy development environment within the Hivemind Enterprise suite—a composable set of API services and MCP-based extensions covering build, test, and deploy for mission autonomy, with LLM integration throughout.

• Gateway service that dynamically loads registered extensions and federates their API surface and UI contributions into a unified platform entry point.
• VSCode-style extension system with isolated, composable UI panels per service extension so teams ship and version domain-specific tooling independently.
• Core ontology service: schema-driven, domain-agnostic data model for structured storage and querying of autonomy entities.
• Data layer
  • Shared relational and analytical layer: PostgreSQL, Elasticsearch, Trino + Apache Iceberg for distributed analytical queries.
  • Document storage on Elasticsearch for full-text indexing of unstructured autonomy artifacts.
  • Polycloud file storage with pluggable backends (AWS S3, Azure Blob, GCS, on-premises MinIO).
  • Data lake on Apache Iceberg, Trino, and Hive Metastore for large-scale, schema-evolved autonomy datasets.
• Configuration service for schema definition and validation—typed configuration contracts across autonomy pipelines.
• Event bus on NATS for high-throughput publish/subscribe across services.
• Simulation integration exposing a hardware-agnostic interface to NGTS, AFSIM, JSBSim, and more for platform-agnostic V&V orchestration.
• Data recording and playback integrated with Foxglove for real-time visualization and post-hoc analysis of simulation and flight data.
• Analysis service with automated ETL over ontology-tagged data, materializing columnar, vector, or time-series outputs for ML evaluation and performance analysis.
• Kubernetes deployment suite via Terraform and Helm for reproducible cluster provisioning and service lifecycle.
• Infrastructure
  • Resource orchestration for dynamic provisioning, task scheduling, and data pipeline execution.
  • Networking emulation with Multus CNI (unicast, broadcast, multicast radio simulation) and Chaos Mesh for comms-denied and degraded-link scenarios.

• Query engine features for Azure Synapse Analytics and SQL Server (C++, C#), including MERGE (atomic INSERT/UPDATE/DELETE for Dedicated SQL Pools), compatibility level for safe engine upgrades, and Showplan XML for distributed MPP diagnostics.
• Maintained the Service Fabric control plane and internal tooling for performance, reliability, and security SLAs across worldwide production database services.
• Led an internal support and on-call tooling portal (React, C#, KQL) for structured log queries and telemetry during live incidents.
• Customer buddy for a complex enterprise migration from a competing analytics platform to Azure Synapse.

• CI/CD foundations for Teradata Vantage: automated integration and release across a multi-team, multi-component cloud analytics architecture.
• Plugin-driven CLI framework so product teams developed, tested, and shipped components in isolation without cross-team integration bottlenecks.
• On-premises Jenkins from scratch, with pipelines orchestrating integration, deployment, and multi-version compatibility testing.
• Automated failure alerting by owning team and gated stable version-set releases through progressive test stages.
• Grafana telemetry and KPI dashboards for pipeline health, pass rates, and quality trends across release candidates.

• Custom product preview using Adobe Scene7 (Dynamic Media Classic): server-side compositing of personalization and add-ons onto base imagery so customers could visualize orders before purchase.