Go microservices with PostgreSQL scale to millions of agentic operations daily. Senrok pairs deterministic state machines with row-level security to prevent data leaks and burst failures.
Each Go microservice runs as a stateless HTTP handler. Webhook payloads arrive as JSON, validated against a strict schema before insertion into PostgreSQL. Burst protection uses a token bucket per tenant in a Redis sidecar, failing fast on overflow.
Data sync between services uses PostgreSQL’s LISTEN/NOTIFY for real-time events. No message broker needed. This avoids serialization overhead and keeps the architecture simple. Write-ahead logs provide crash recovery without application-level retries.
Bottleneck: connection pooling. We use PgBouncer in transaction mode. Each microservice caches frequently accessed tenant configuration in Go’s sync.Map, invalidated via channel-based triggers from a background goroutine that polls pg_stat_replication.
Permissions are scoped per user and tenant using PostgreSQL Row-Level Security (RLS). Each microservice connects with a single service role, then sets a session variable via SET session.authorization before every query. This eliminates the need for per-service database credentials.
Rate limits are enforced at the API gateway (Envoy) using JWT claims. The gateway validates the token, extracts tenant ID, and applies a Redis-based sliding window counter. Over-limit requests receive a 429 with a Retry-After header corresponding to the next available slot.
Audit logging: every mutation writes to an append-only log table. Go’s database/sql executes two statements in a transaction: the main DML and the log insert. Since all writes are deterministic, we can replay the log to reconstruct state – no event sourcing framework needed.
Each webhook carries a unique hash of its payload in an Idempotency-Key header. Go’s HTTP middleware checks a UNIQUE INDEX on (key, service) in PostgreSQL before processing. Ignore duplicate inserts; no extra tooling.
Yes. Senrok uses application-side sharding: each tenant is pinned to a dedicated PostgreSQL vCore via a routing table in etcd. The Go microservice queries etcd on startup, then routes all tenant reads/writes to the correct shard. No cross-shard queries in the hot path.
RLS policies reference a session variable set after authentication. The variable contains the user’s role and tenant ID. The Go middleware sets it via a raw SQL SET statement before each request. The pool reuses connections; the variable is reset after the transaction using SET LOCAL.
Engineering services
Go Microservices · PostgreSQL is the kind of workflow we build as an AI agent system: deterministic checks, human checkpoints, and an audit trail operators can trust. We start from your real process boundaries and ship software that holds up in production.
We build production-ready, highly observable agentic systems engineered for enterprise scale. No black boxes, no magic—just systematized workflows with systemic safeguards.
We don't build fragile wrappers. Complex decisions and exceptions are automatically routed to your team for approval, ensuring zero unverified actions in production.
Every AI-generated output is validated against deterministic, programmatic rules before execution, guaranteeing structural integrity and compliance.
Our architecture records every state change, agent reasoning step, and user interaction, providing complete observability into your automated workflows.
Built for enterprise scale. We optimize for high-throughput, low-latency execution using edge infrastructure and efficient state management.
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