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The read side of archive-on-delete: querying archives through promoted typed columns, digging into jsonb payloads for everything else, polling snapshots with a 202 pattern, and an honest accounting of the restore path ArchiveKit doesn't have yet. Part 9 wraps up the Archive-on-Delete with ArchiveKit series.
ArchiveKit's snapshot service assembles a full JSON tree of a deleted object graph using nothing but archive rows - the primary data is already gone. Job tickets, a four-state machine, retries with a terminal Failed state, and the single-table assembly limitation I still owe a fix for. Part 7 of the Archive-on-Delete with ArchiveKit series.
Correlation ids and cascade archiving in ArchiveKit - how one Guid per save turns scattered archive rows into a reconstructable object graph, why cascade happens through the EF change tracker rather than the database, and two honest limits: a naive root heuristic and a CascadeArchive flag the interceptor doesn't read yet. Part 6 of the Archive-on-Delete with ArchiveKit series.
The storage design behind ArchiveKit - typed queryable columns and a jsonb payload from a single write, why the archive's EntityId is an index but deliberately not a foreign key, and the reflective model configuration that builds every archive table from one method call. Part 4 of the Archive-on-Delete with ArchiveKit series.
The anatomy of ArchiveKit's SaveChangesInterceptor - detecting soft-deleted entities in the change tracker, building archive rows with zero extra database reads, and the one line of state-flip ordering that keeps EF from cascade-deleting the archive you just wrote. Part 2 of the Archive-on-Delete with ArchiveKit series.
Hard deletes destroy the audit trail; soft deletes clutter live tables forever. Introducing ArchiveKit, a .NET library that intercepts deletions and stores immutable archive snapshots with TTL policies and cascade archiving.
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Applied AI
Agentic AI & Cloud Engineer · multi-agent systems, RAG and MCP on AWS
Cloud & .NET
C#, .NET 10 and ASP.NET Core microservices on AWS and Azure · Terraform & AWS CDK
Data Engineering
AWS lakehouse · Kinesis, Glue (PySpark), Apache Iceberg, Lake Formation
Everything
All three domains, with the standout project from each