What this is, and who it is for
This practice covers the parts of PostgreSQL that decide whether a product can grow: connection pooling with PgBouncer or Supavisor, continuous WAL archiving to object storage with WAL-G for point-in-time recovery, zero-downtime DDL on very large tables, and vector search with pgvector and HNSW indexes as a self-hosted alternative to managed vector databases. It is for teams whose database is the bottleneck under concurrency, whose recovery plan has never been tested, or who are paying managed vector database prices for workloads PostgreSQL already handles.
Start a conversationArchitect immutable, bare-metal Kubernetes clusters with Talos Linux, Cilium eBPF network security, and declarative GitOps pipelines.
Direct daily working-hour overlap with engineering teams in Europe (CET/GMT+1), the GCC (GMT+3), and US East Coast.
Production Kubernetes & Talos Linux
Capabilities
Talos Linux immutable cluster setup (zero OS drift)
Cilium eBPF network policies & service mesh
ArgoCD & Flux automated GitOps deployment
Zero-downtime rolling node upgrades
Delivered architecture
Zero-Downtime PostgreSQL Disaster Recovery
Questions, answered
Technical questions, answered directly.
What is the recovery point objective for this architecture?
Near-instantaneous. Continuous Write-Ahead Log streaming via WAL-G to S3 object storage enables automated point-in-time recovery, so a restore lands on a chosen timestamp rather than relying on nightly snapshots.
How long does a restore actually take?
A verified recovery of more than 100GB completed in under 12 minutes with zero data corruption.
Why is connection pooling part of the design?
PostgreSQL allocates a backend process per connection, so high concurrency exhausts memory and latency long before CPU. PgBouncer or Supavisor pools and multiplexes client connections so the database sees a stable, small number of backends.
Can schema migrations run without downtime?
Yes. Adding indexes and constraints on tables with hundreds of millions of rows is done with concurrent DDL and staged backfills, so the application never takes an outage for a schema change.
Can PostgreSQL replace a dedicated vector database?
For most workloads, yes. pgvector with HNSW indexes scales to millions of embeddings, which removes a separate managed service, its cost and its data-egress boundary.
Production Kubernetes & Talos Linux