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You said: SEA-main.zip Zip Archive VibesPro™-main (2).zip Zip Archive GovernedSpeed™-refactor-nx-migration.zip Zip Archive how does it work it work when you embed one repo into another for a project. given i use Nx i envision that i’d embed the project as an blackbox app and use ports and adapters to communicate to it from my app. in this case i’m talking about embedding vibespro into SEA™. I think i’m just going to integrate GovernedSpeed™ into SEA™ seamlessly. how does the main project actually communicate with the embedded one when deployed? am i asking the right question ChatGPT said: You are asking the right question — but it’s slightly under-specified. The “how does the main project communicate with the embedded one when deployed?” answer depends 100% on what boundary you choose at deploy/runtime, not on the fact that one repo is embedded in another.

There are really two different “integration” problems that people accidentally mix:

Build-time composition: “Can SEA™ build VibesPro™/GovernedSpeed™ from the same Nx workspace and produce artifacts?”

Runtime composition: “When running in prod, are we in the same process (direct function calls), different processes (HTTP/gRPC), or different UIs (microfrontend/iframe/module federation)?”

Once you pick the runtime topology, the communication mechanism becomes almost automatic.

The 4 deployment topologies (and how communication works) A) Same process (tightest): Nx workspace library What it is: You fold the code in as an Nx lib (or multiple libs) and SEA™ imports it like normal TS/JS/Python module boundaries.

Runtime communication:

Direct function calls across an interface (your “ports”).

Adapters are just concrete implementations wired via DI / factory.

When it’s right: “Integrate GovernedSpeed™ into SEA™ seamlessly” sounds like this: a shared runtime with no network hop.

Observable success:

One deployment artifact (one container/image/app bundle per service).

No service discovery, no extra URLs.

Calls are stack traces, not network traces.

Common failure mode: boundary erosion (SEA™ starts importing internal modules instead of ports). Symptom: dependency graph shows cross-layer imports; refactors get scary.

B) Same deploy, separate process (moderate): Sidecar / internal service What it is: SEA™ ships a container that includes both, or deploys them together (same K8s pod / compose stack), but they’re separate processes.

Runtime communication:

localhost HTTP/gRPC between SEA™ and the embedded service

OR IPC (less common)

When it’s right: you want “blackbox app” operationally (separate process, separate scaling knobs), but still co-located.

Observable success:

SEA™ talks to http://localhost: (or a unix socket).

You can restart the embedded process without restarting SEA™.

Common failure mode: hidden coupling via shared filesystem/env vars. Symptom: works locally, breaks in K8s due to missing mounts/ports.

C) Separate deployables (loosest backend): Independent service What it is: VibesPro™ runs as its own service/deployment. SEA™ treats it as an external dependency.

Runtime communication:

HTTP/gRPC (sync)

Message bus events (async)

Often both: commands via HTTP, events via Kafka/Rabbit.

This matches SEA™’s event-driven governance loop patterns (e.g., emitting change/violation events) as described in your architecture docs. Updated_SDSs

Observable success:

Clear service boundaries in CALM models; independent release cadence. Updated_ADRs

Failure isolation: VibesPro™ down ≠ SEA™ down (if you design for it).

Common failure mode: “blackbox” becomes “mysterybox” (no contract tests). Symptom: version bumps break prod.

D) UI embedding (frontend): Microfrontend / iframe / module federation This is a different category: it’s about embedding a UI app, not a backend.

Runtime communication:

postMessage (iframe)

Module Federation shared contracts

Shared API + shared auth/session

Observable success:

Separate UI build artifacts loaded at runtime.

Cross-app navigation/auth works without weird reload loops.

Common failure mode: auth/session drift. Symptom: repeated logins, broken deep links, CORS issues.

“Blackbox app + ports/adapters” — the key correction Ports/adapters is a great instinct, but it doesn’t by itself answer “how do they communicate?”

A port is just “the shape of interaction.” The transport is chosen by topology:

Topology A → port is a code interface (function calls)

Topology B/C → port is a network contract (OpenAPI/Protobuf)

Topology C (async) → port is an event contract (schema + topic)

Topology D → port is a UI contract (events/messages + routes)

So the real question is:

“Do I want VibesPro™ inside SEA™’s runtime (library), beside it (sidecar), or outside it (service), and what contract enforces the boundary?”

Yes — that’s the question you’re circling.

What I’d do given your stated intent “Integrate GovernedSpeed™ into SEA™ seamlessly” Default to Topology A (Nx lib) unless you have a strong operational reason not to.

Put GovernedSpeed™ behind a ports/ package (interfaces + types)

Implement adapters in adapters/ packages

SEA™ depends only on ports; DI selects adapters

Add Nx module-boundary rules so “SEA™ can’t import adapters directly”

This lines up with SEA™’s “isomorphic” governance mindset: keep meaning/contract stable, swap implementations safely. Updated_ADRs

SEA™

“Embed VibesPro™ as a blackbox” “Blackbox” usually means Topology C (separate service) or Topology D (UI embed). If you meant “blackbox backend,” pick Topology C and treat it like an external integration with strict contracts + versioning.

Quick decision table Goal Best topology Communication Seamless integration, shared runtime, easiest dev A: Nx lib direct calls (ports as interfaces) Operational isolation but co-located B: sidecar localhost HTTP/gRPC True blackbox + independent releases C: separate service HTTP/gRPC + events Embed a UI app D: microfrontend/iframe postMessage + shared APIs Does this match your constraint? When you say “embed VibesPro™ into SEA™,” do you mean embedding a UI (someone uses VibesPro™ screens inside SEA™) or embedding backend capabilities (SEA™ calls VibesPro™ APIs)? If you answer that, we can pick the topology and I can outline the exact Nx structure + contracts + deployment wiring.

Sources You said: i want to embed vibespro as a backend and as for GovernedSpeed™, i mean i’m going to take it apart and build it into SEA™, it was actually built to as a protoype for SEA™
ChatGPT said: Got it — that’s a clean split:

VibesPro™ = embedded backend capability but you still want it to remain a blackbox (owned/released somewhat independently).

GovernedSpeed™ = prototype for SEA™, so you want to dissolve it into SEA™ (shared runtime / shared domain).

Those are two different integration topologies, and they communicate very differently at deployment time.

1) “Embedding VibesPro™ as a backend” (blackbox) — how SEA™ talks to it in prod If VibesPro™ stays a blackbox, SEA™ does not “call code inside it” when deployed. It calls it like any other backend dependency:

The runtime communication options (pick one primary) A. HTTP/REST (most common)

SEA™ talks to VIBESPRO_BASE_URL (env var).

In Kubernetes that’s usually http://vibespro..svc.cluster.local (or just http://vibespro within the namespace).

In docker-compose it’s http://vibespro:PORT.

B. gRPC

Same deployment wiring as HTTP, but contract is protobuf.

Better for strict contracts + performance, slightly more tooling overhead.

C. Async events (Kafka/Rabbit/SQS)

SEA™ publishes commands/events; VibesPro™ consumes and emits results/events.

Great when you want loose coupling and resilience; harder to debug.

In all cases, the “embed” is a repo/build concern. At runtime, the boundary is process/network, and communication is via an address + a contract.

Ports & Adapters shape here (the right way) In SEA™, define a driven port like:

VibesPro™ClientPort (methods: createVibe(), scoreVibe(), etc.)

Adapter: HttpVibesPro™Client (or GrpcVibesPro™Client)

Then your SEA™ domain/app layer depends only on the port, never on transport details.

Observable success in deployment: you can change VibesPro™’s implementation or language and SEA™ doesn’t change — only the adapter or contract versioning does.

Most common failure mode: people “blackbox” the service but don’t lock the contract.

Symptom: VibesPro™ deploy works, SEA™ deploy works, but integration breaks with 400/500s after a version bump.

Fix: consumer-driven contract tests (or at minimum pinned OpenAPI/proto versions + compatibility gates).

2) “Taking apart GovernedSpeed™ and building it into SEA™” — how communication works This is the opposite: you do want shared runtime and shared internals (within controlled boundaries).

That means the “communication” becomes direct calls (in-process), and Nx’s job is to keep the boundaries honest.

A practical refactor pattern (Nx-friendly):

Convert GovernedSpeed™ “apps/” into SEA™ “libs/” (or SEA™ “packages/*”) by layer:

domain/* (pure business rules + types)

ports/* (interfaces/protocols)

adapters/* (http, db, queues)

app/* (use-cases/orchestration)

Then SEA™’s runnable targets (apps/services) wire ports → adapters via DI/factories.

Observable success: you can run unit tests for domain without any infra; integration tests swap in adapters.

Common failure mode: cyclic dependencies appear once you start “pulling it apart.”

Symptom: Nx graph cycles / weird import paths / “works locally but CI fails.”

Fix: tag libs by layer and enforce module boundaries (domain cannot import adapters, etc.).

The key clarification: “embedded repo” ≠ “embedded runtime” You can physically place VibesPro™ inside SEA™’s repo (git subtree/submodule, Nx workspace, whatever)… and still deploy it as a separate service.

So the real decision for VibesPro™ is:

Do you want one deployment artifact (single process)?

Then it’s not a blackbox; it’s a library/internal module.

Or do you want independent deployability / blackbox behavior?

Then it’s a service boundary, and communication is HTTP/gRPC/events.

Given what you said (“blackbox backend”), the consistent answer is:

VibesPro™ should be a separately deployed service, even if its code lives in the same repo.

Are you asking the right question? Yes, but the sharper version is:

“At runtime, is VibesPro™ in the same process as SEA™, the same pod but separate process, or a separately deployed service — and what contract will we enforce at that boundary?”

For your stated intent, the best default is:

VibesPro™: separate service (HTTP or gRPC; optionally events)

GovernedSpeed™: dissolved into SEA™ libs (direct calls)

If you tell me where SEA™ itself runs today (Kubernetes? docker-compose? serverless? something else), I’ll give you the exact wiring pattern (service names, env vars, health checks, and what the Nx targets should output) that makes “SEA™ → VibesPro™” work reliably in prod. Does that match your constraint?

You said: i think i like the library/internal module. for context initially building SEA™ but it became vibespro and I planed to extend it into SEA™ so it was going to server kindof like the kernel of SEA™ but i noticed that it could stand alone as well, kindof like what happened to GovernedSpeed™ but i didn’t build out Governed speed to much (though i could). I’m not against dissolving vibespro into sea as well then add zed ide as a black box ui (or maybe LibreChat). what do you think? ChatGPT said: If you’re willing to dissolve VibesPro™ into SEA™, the cleanest mental model is:

“One kernel, multiple shells.”

Kernel = the stable domain + use-cases + ports (SEA™ core)

Shells = different runtimes/UI hosts that talk to the kernel (CLI, HTTP API, worker, Zed extension, LibreChat UI, etc.)

That lets VibesPro™ remain runnable as a product without staying a separate blackbox service.

Recommendation: dissolve VibesPro™, but keep it independently runnable Why this is the sweet spot You get:

Seamless internal module calls (fast, testable, no network boundary)

No duplicated “proto → SEA™” rewrite (you reuse what already exists)

Preserved “standalone” behavior by keeping a thin app wrapper around the kernel

You avoid:

“Blackbox backend” operational complexity (service discovery, contract drift, version skew)

Boundary erosion (if you enforce Nx module boundaries properly)

The trick is to not dissolve it as “everything imports everything,” but to dissolve it as well-layered libs.

The concrete structure that makes this work in Nx 1) Create a kernel package boundary Put the real logic in libs that are intentionally boring:

libs/sea/domain/* (pure domain: types, invariants, rules)

libs/sea/app/* (use-cases/orchestration)

libs/sea/ports/* (interfaces/protocols: repos, llm, fs, events, auth)

libs/sea/adapters/* (http, db, queue, file, vendor APIs)

Rule: domain/app imports only ports (never adapters). Adapters import domain/app.

2) Make “VibesPro™” a shell, not a second core Keep a runnable target that packages the kernel with specific adapters + config:

apps/vibespro-api (or apps/vibespro-worker, apps/vibespro-cli)

wires ports → adapters

owns deployment config

can have its own release cadence if you want

This preserves “VibesPro™ can stand alone” as a host, not a separate logic fork.

Observable success: You can delete the VibesPro™ app layer and still have a fully working SEA™ kernel, and you can also run the VibesPro™ app without “SEA™ UI.”

Where GovernedSpeed™ fits Given GovernedSpeed™ was a prototype for SEA™, it should be treated as a donor:

extract any valuable domain/use-case pieces into libs/sea/*

keep only a minimal wrapper app if you still want a runnable demo

This is the same “kernel + shells” approach, just with less to preserve.

UI as a blackbox: Zed vs LibreChat (they imply different integration shapes) Zed IDE as UI Zed’s extension model is Wasm + Rust extension APIs, and it commonly integrates via LSP/tooling patterns rather than embedding your whole app UI inside it. Zed +2 Zed +2

So the “blackbox UI” integration tends to look like:

SEA™ exposes HTTP/gRPC + maybe streaming (SSE/WebSocket)

Zed extension (or an LSP server you ship) calls SEA™ endpoints

Good when: you want SEA™ capabilities to feel like “editor-native actions” (generate, refactor, validate specs, etc.).

LibreChat as UI LibreChat is basically a configurable chat UI that can point at OpenAI-compatible custom endpoints via librechat.yaml. librechat.ai +2 librechat.ai +2

That means you can make SEA™ expose an OpenAI-ish API facade (adapter) and plug it into LibreChat without forking LibreChat.

Good when: you want a fast “chat-first” interface with minimal UI engineering.

One gotcha: LibreChat’s ecosystem is actively evolving around tools/plugins (some deprecation notes exist), so treat it as a UI client, not your core. librechat.ai

The key decision you’re making (and I agree with your direction) If SEA™ is the “real product,” then:

Kernel belongs in SEA™.

VibesPro™ and GovernedSpeed™ are hosts that should become:

either thin apps in the same Nx workspace

or deployable variants built from the same kernel

That’s the most sustainable “proto → platform” path.

Does this match your constraint? When you say “VibesPro™ can stand alone,” do you mean:

“It can be deployed separately with its own API,” or

“It can be used independently as a CLI/tooling workflow,” or

“It has a separate domain that SEA™ shouldn’t own”?

Answering that determines whether the VibesPro™ shell should be an API service, CLI, or toolchain (or all three), but the kernel approach works for any of them.

You said: all three ChatGPT said: All three is doable, but it only stays sane if we separate “where code lives” from “what owns the domain.” In practice: one repo/workspace, multiple bounded contexts, multiple shells, strict contracts.

Here’s the architecture I’d recommend for your situation.

The integration shape that satisfies all three goals Goal 1: “VibesPro™ can be deployed separately with its own API” Make apps/vibespro-api a first-class deployable that composes the VibesPro™ domain + its adapters.

It imports libs, not the other way around.

It owns its own config, auth integration, persistence adapter selection, etc.

What you’ll see when it’s right: you can deploy vibespro-api without shipping any SEA™ UI or SEA™ runtime, and it runs with a stable contract.

Goal 2: “VibesPro™ can be used independently as a CLI / workflow tool” Create apps/vibespro-cli (or tools/vibespro-cli) that invokes the same use-cases as the API app.

CLI is just another driving adapter (like HTTP is).

The CLI depends on libs/vibespro/app (use-cases) and on ports for I/O.

What you’ll see when it’s right: CLI and API share behavior; a bugfix in one fixes the other.

Goal 3: “VibesPro™ has a separate domain that SEA™ shouldn’t own” This is the big one. It means: VibesPro™ is a bounded context even if it lives inside SEA™’s workspace.

So SEA™ should not “reach into” VibesPro™ internals. SEA™ should integrate via:

a public port / façade exposed by VibesPro™ (in-process), or

a network contract if you later decide to deploy it separately.

What you’ll see when it’s right: SEA™ imports only @vibespro/public (or libs/vibespro/public-api) and cannot import libs/vibespro/domain/* directly.

The concrete Nx layout I’d implement VibesPro™ bounded context libs libs/vibespro/domain — entities/value objects/invariants (no IO)

libs/vibespro/app — use-cases (depends on ports)

libs/vibespro/ports — interfaces/types for repos, events, llm, fs, etc.

libs/vibespro/adapters/* — db/http/queue/filesystem implementations

libs/vibespro/public-api — the only thing SEA™ is allowed to call

SEA™ core libs (kernel) libs/sea/domain

libs/sea/app

libs/sea/ports

libs/sea/adapters/*

Shells (apps) apps/vibespro-api

apps/vibespro-cli

apps/sea-api (or worker/cli/etc.)

apps/sea-ui (if any)

This gives you “dissolved into SEA™” operationally (same repo, same build), while keeping “separate domain” true (strict boundaries).

The key mechanism: enforce boundaries with Nx tags (or it will rot) You want tags like:

type:domain, type:app, type:ports, type:adapters, type:shell

scope:sea, scope:vibespro

And dependency rules like:

scope:sea may depend on scope:vibespro only via type:public

type:domain may not depend on type:adapters

type:app may depend on type:ports + type:domain only

type:adapters can depend inward (ports/app/domain), never the reverse

Observable success: Nx graph stays acyclic and “illegal import” attempts fail fast in CI.

Failure symptom if you skip this: after a month, SEA™ will import random VibesPro™ internals “just this once,” and your bounded context is gone.

How SEA™ uses VibesPro™ (in-process) without “owning” it SEA™ should depend on a narrow “capability interface,” for example:

VibesPro™Capability (port) exposed by libs/vibespro/public-api

SEA™ calls vibesproCapability.createVibe(…) etc.

Internally VibesPro™’s public layer wires to libs/vibespro/app use-cases

That’s still ports/adapters — just in-process rather than network.

Upgrade path: if later you want VibesPro™ as a separate service again, you keep the same “public API contract” and swap the adapter in SEA™ from InProcessVibesPro™Adapter to HttpVibesPro™Adapter.

Where Zed IDE / LibreChat fits Treat both as UI shells that talk to SEA™ over a stable API.

LibreChat is easiest if you expose an OpenAI-compatible endpoint (thin adapter) and point LibreChat at it.

Zed is best if you expose “editor actions” endpoints (or an LSP-ish service) and let the extension be a client.

Either way: UI stays blackbox, SEA™ kernel stays authoritative.

My opinion on your direction Dissolving VibesPro™ into SEA™ is the right move if you simultaneously:

keep VibesPro™ as its own bounded context (scope:vibespro)

keep it independently runnable (API + CLI shells)

enforce boundaries with Nx rules from day 1

That gives you platform leverage without turning SEA™ into a spaghetti monolith.

Does this match your constraint? When you say “separate domain SEA™ shouldn’t own,” do you mean:

data ownership (VibesPro™ owns its DB/tables), or

conceptual ownership (SEA™ can call capabilities but not manipulate internals), or

both?

If it’s both, we’ll also design a clean “data boundary” (separate schemas/repos + no shared persistence layer), which is the most common place these integrations quietly fail.

You said: i like the idea of both ChatGPT said: Cool — “both” (conceptual + data ownership) is the most robust version. It basically means:

SEA™ can use VibesPro™ as a capability

SEA™ cannot directly read/write VibesPro™’s persistence

Integration happens through a narrow contract (in-process now, network later if you want)

Here’s the concrete way to do that without creating a distributed-systems headache.

The mechanism: “In-process service boundary” with a hard data wall 1) Give VibesPro™ its own data store boundary Pick one of these (in descending strictness):

Option A (strictest): separate DB instance

vibespro-db (own creds, backups, migrations, retention)

SEA™ DB never shares credentials

Option B: same DB server, separate database

sea database and vibespro database on same Postgres cluster

Option C: same database, separate schema (least strict, still acceptable)

sea.* and vibespro.* schemas

separate migration pipelines

separate DB roles: sea_rw can’t access vibespro.*

Adoption indicator: SEA™ code literally cannot query VibesPro™ tables because the DB user doesn’t have permission. Failure symptom: someone “just joins tables” during a feature crunch.

If you want this to survive growth, do A or B. If you want speed early, C is fine as long as you enforce privileges.

2) VibesPro™ exposes a “public capability” API inside the monorepo Treat VibesPro™ like an internal microservice even though it’s in-process:

libs/vibespro/public-api exposes interfaces + DTOs + command/query functions

SEA™ depends on that package only

SEA™ never imports VibesPro™ domain entities directly

Example shape (conceptually):

Commands: createVibe, updateVibe, scoreVibe

Queries: getVibeSummary, listVibesForUser

Events: VibeCreated, VibeScored, etc.

Adoption indicator: SEA™ can only talk to VibesPro™ through @vibespro/public-api, and Nx prevents anything else.

3) Bridge the boundary with “anti-corruption” mapping If SEA™ and VibesPro™ have different concepts (they will), don’t force one to speak the other’s internal model.

SEA™ has its own types

VibesPro™ has its own types

Integration uses DTOs at the boundary

Adoption indicator: you can refactor VibesPro™ internals without touching SEA™, unless the DTO contract changes.

Transaction boundaries: the thing that bites people Once data ownership is separate, you cannot rely on “one DB transaction” across both contexts.

You have two sane patterns:

Pattern 1: “Sync call + eventual consistency” SEA™ issues a command to VibesPro™ (in-process call today)

VibesPro™ writes to its DB and emits an event

SEA™ listens to the event and updates SEA™ state

Observable success: if SEA™ crashes mid-flow, replaying events repairs state.

Pattern 2: “Outbox + inbox” If you want high reliability:

VibesPro™ writes changes + an “outbox event” in the same transaction

A worker publishes outbox → message bus (or in-process event dispatcher)

SEA™ processes with idempotency keys

Observable success: no “ghost writes” and no missed notifications under load/restarts.

If you’re early-stage, start with Pattern 1 (in-process events), but keep the contracts shaped so you can upgrade to outbox later.

Nx enforcement so this doesn’t degrade into spaghetti Tagging scope:sea, scope:vibespro

layer:domain, layer:app, layer:ports, layer:adapters, layer:public, layer:shell

Rules (the important ones) scope:sea can depend on scope:vibespro only if layer:public

layer:domain depends on nothing except maybe shared primitives

layer:app depends on domain + ports

adapters depend inward, never outward

Adoption indicator: an illegal import fails lint/CI immediately.

How this deploys (still “library/internal module”) Even if everything is in one repo and one deployment artifact:

SEA™ runs as a process (API/worker)

VibesPro™ runs as an in-process module

VibesPro™ still uses its own DB/schema/role/migrations

Communication is direct calls + event dispatch (not HTTP), but contract-shaped so you can swap to HTTP later

Key point: “blackbox” here is enforced by module boundaries + DB permissions, not by network hops.

A practical “default blueprint” for you Given your direction, I’d do:

Dissolve GovernedSpeed™ into SEA™ kernel (domain/app/ports), keep only what’s needed.

Dissolve VibesPro™ into SEA™ workspace but keep it as a bounded context:

libs/vibespro/* layered

libs/vibespro/public-api is the only dependency surface

separate DB role/schema at minimum

Add LibreChat or Zed as UI shells:

They talk to SEA™ API (SEA™ becomes “capability gateway”)

UI is replaceable; core is stable

Common pitfalls (so we avoid them) Shared DB tables “temporarily” → becomes permanent coupling.

Symptom: SEA™ features require VibesPro™ migrations.

Leaking domain objects across boundary

Symptom: SEA™ starts depending on VibesPro™ internal invariants.

Cross-context transactions

Symptom: “sometimes state is inconsistent” bugs after retries/timeouts.

No contract versioning

Symptom: refactor breaks other side unexpectedly.

One decision point Which data boundary do you want first for VibesPro™?

A/B (separate DB or separate database): strongest, slightly more ops

C (same DB, separate schema + separate DB role): fast and still enforceable

Does C match your current constraint (speed while still being “real” separation), or are you ready for A/B right away?

You said: same DB server, separate database, Outbox + inbox ChatGPT said: Perfect — same DB server, separate database + outbox/inbox is the “grown-up monolith” pattern: tight dev ergonomics, hard data boundary, and reliable cross-context messaging.

Here’s the concrete shape we should implement for SEA™ ↔ VibesPro™ when VibesPro™ is an internal module (in-process) but data-owned and contracted like a service.

Database boundary: same server, separate database What that means operationally One Postgres server (same cluster/host).

Two databases:

sea_db

vibespro_db

Separate DB users/roles:

sea_app can only access sea_db

vibespro_app can only access vibespro_db

Separate migration pipelines (even if both are driven by Nx targets).

Observable success: SEA™ code cannot accidentally join VibesPro™ tables because it literally cannot connect to vibespro_db using SEA™ creds.

Messaging boundary: Outbox + Inbox We’re going to treat “SEA™ calls VibesPro™” as either:

command (sync) call that returns quickly, and still produces events reliably, or

async command by writing a message into an outbox table.

Given you explicitly want outbox+inbox, the simplest reliable approach is:

Each bounded context has its own Outbox table in its own database.

Each bounded context has its own Inbox table in its own database.

A small “relay” worker (can run in SEA™ process or as separate worker) moves events from each outbox → bus (or direct to inbox).

Two transport choices (both compatible with outbox/inbox) Option A: In-DB relay (no external broker) Relay reads outbox in vibespro_db, writes into SEA™ inbox in sea_db and vice versa. ✅ simplest infra, still reliable ⚠️ relay needs access to both DBs (use a dedicated relay role)

Option B: Real broker (Kafka/Rabbit/SQS/NATS) Relay publishes outbox → broker; consumers write to inbox. ✅ scales, clearer ops ⚠️ more infrastructure now

If you’re early and want “reliable but minimal moving parts,” start with Option A and keep the interfaces shaped so we can swap to Option B later.

Concrete table contracts Outbox table (per context, in its own DB) outbox_events

id (uuid, PK)

aggregate_type (text)

aggregate_id (text/uuid)

event_type (text) — e.g. VibeCreated.v1

event_version (int) — or bake into event_type

payload (jsonb)

occurred_at (timestamptz)

trace_id (text, nullable)

causation_id (uuid, nullable) — links to triggering message

correlation_id (uuid, nullable)

published_at (timestamptz, nullable)

publish_attempts (int default 0)

publish_error (text, nullable)

Indexes:

(published_at) where published_at is null (fast “next batch” query)

(occurred_at)

Success signal: events exist even if the app crashes after committing state.

Inbox table (per context, in its own DB) inbox_messages

message_id (uuid, PK) — same as event id

event_type (text)

received_at (timestamptz)

processed_at (timestamptz, nullable)

process_attempts (int default 0)

last_error (text, nullable)

Idempotency rule: message is processed at most once because the PK prevents duplicates.

Success signal: replaying the same event doesn’t duplicate side effects.

The lifecycle: write model + outbox in one transaction Example: VibesPro™ handles a command In vibespro_db transaction:

mutate VibesPro™ state (tables)

insert one or more rows in outbox_events

Commit.

Relay publishes (or copies) outbox events.

Failure mode & symptom: If you publish directly without outbox and crash, you’ll see “state updated but SEA™ never heard.” Outbox eliminates that.

Relay mechanics (Option A: DB-to-DB) A dedicated worker does:

Publish step Connect to vibespro_db

SELECT … FROM outbox_events WHERE published_at IS NULL ORDER BY occurred_at LIMIT N FOR UPDATE SKIP LOCKED

For each event:

connect to sea_db

INSERT INTO inbox_messages(message_id, event_type, received_at, …) VALUES (…) ON CONFLICT DO NOTHING

mark published_at = now() in vibespro_db

Why SKIP LOCKED: lets you run multiple relay instances safely.

Diagnostics:

If outbox grows and published_at stays null → relay is down or failing.

If inbox fills but processed_at stays null → consumer is failing.

Consumer mechanics: Inbox worker inside each context SEA™ has a worker loop:

fetch unprocessed inbox rows in sea_db with FOR UPDATE SKIP LOCKED

dispatch handler based on event_type

commit processed_at

Important: handler must be idempotent. The inbox prevents duplicates, but you’ll still retry failures.

Versioning & contracts Use an explicit event naming convention:

VibeCreated.v1

VibeScored.v1

Rules:

Never change meaning of .v1 once emitted.

Add .v2 when payload changes incompatibly.

Keep handlers for older versions until drained.

Observable success: you can deploy SEA™ first or VibesPro™ first without breaking the pipeline.

Nx workspace implications (so boundaries stay real) Even though VibesPro™ is “internal module,” treat it like a service:

libs/vibespro/public-api (DTOs + event types + command interfaces)

libs/vibespro/domain, libs/vibespro/app, libs/vibespro/ports, libs/vibespro/adapters

apps/vibespro-worker (optional) — runs relay/publish or VibesPro™’s inbox consumer

apps/sea-worker — runs SEA™ inbox consumer and/or relay

Boundary enforcement to add:

SEA™ can import libs/vibespro/public-api only

Separate database configs and migration targets per context

What we should build next (in order) DB layout + roles

create sea_db, vibespro_db

create sea_app, vibespro_app, and optionally relay_app with access to both DBs (only if using DB-to-DB relay)

Schema + migrations

add outbox_events to both DBs

add inbox_messages to both DBs

Event contract package

centralize event type strings + payload schemas in libs/vibespro/public-api and libs/sea/public-api (or a shared “contracts” lib if you want)

Relay worker

implement the outbox polling + inbox insert + mark published loop

Inbox consumers

one per context

Observability

metrics: outbox backlog, inbox backlog, processing latency, failure counts

logs keyed by correlation_id/trace_id

One decision point before we cut code For the relay transport, do you want:

DB-to-DB relay (no broker) to start (fastest path), or

Broker-backed from day 1?

You already chose outbox/inbox; this is just the “middle hop.” If you pick DB-to-DB now, we can still switch later without rewriting domain code—only the relay.

If you want, I can also open your uploaded zips (SEA™ + VibesPro™ + GovernedSpeed™) and propose the exact Nx package layout + target names + boundary rules that fit your existing structure.

You said: i like NATS ChatGPT said: Nice — NATS + JetStream is a strong fit for the outbox/inbox pattern because it gives you:

At-least-once delivery with explicit acks + redelivery on the consumer side. NATS Docs

Publisher-side deduplication via the Nats-Msg-Id header (idempotent publish) — which is the closest thing to “exactly-once publish” you’ll get in practice. NATS Docs +2 NATS Docs +2

Clean request/reply support when you want synchronous “RPC-like” interactions. NATS Docs +1

Below is the concrete architecture I’d implement for SEA™ + VibesPro™ given your choices: same DB server, separate DBs, outbox+inbox, NATS JetStream.

The end-state wiring Databases (hard data boundary) Postgres server/cluster: shared

Databases:

sea_db

vibespro_db

Roles:

sea_app → only sea_db

vibespro_app → only vibespro_db

relay_publisher (optional) → can read outbox tables from both DBs

Success indicator: SEA™ can’t query VibesPro™ data even if a dev tries.

Messaging: Outbox → NATS JetStream → Inbox Tables (per bounded context) In sea_db:

outbox_events

inbox_messages

In vibespro_db:

outbox_events

inbox_messages

NATS subjects + streams Use JetStream streams for persistence and replay:

Stream: SEA_EVENTS

Subjects: sea.> and/or vibespro.> (you decide if one shared stream or per-domain streams)

Example subjects:

vibespro.event.vibe_created.v1

vibespro.event.vibe_scored.v1

sea.event.policy_violation_detected.v1

Rule: subjects are your public contract surface. Version them intentionally.

Publisher side (the “outbox publisher”) Step-by-step App writes its state + inserts an outbox_events row in one DB transaction.

A publisher worker polls outbox rows where published_at IS NULL.

For each row, publish to JetStream with:

Subject = event type mapping

Payload = JSON (or protobuf if you prefer)

Header Nats-Msg-Id = outbox_event_id (UUID string)

JetStream will deduplicate publishes that share the same message ID within its dedupe window / config. NATS Docs +2 NATS Docs +2

When publish succeeds, mark published_at.

Observable success: if the publisher crashes after publishing but before marking published_at, it will republish later — and JetStream dedupe prevents duplicate stream entries (within the dedupe window), while consumers still remain idempotent via inbox. NATS Docs +1

Failure diagnostic: if published_at backlog grows, publisher is down or failing.

Consumer side (the “inbox consumer”) Step-by-step JetStream durable consumer receives message.

Consumer writes an inbox_messages row keyed by message_id (the outbox id / Nats-Msg-Id).

If insert conflicts, it’s a duplicate → skip work.

Process handler (idempotent).

Mark processed_at.

Ack message.

JetStream consumers track delivery + acknowledgements and will redeliver messages that aren’t acked. NATS Docs

Observable success: kill the consumer mid-processing and you’ll see redelivery; duplicates won’t cause duplicate side effects because inbox PK blocks it.

Common pitfall: ordering assumptions. Redeliveries can make things appear out of order; if strict ordering matters, you’ll design for it (e.g., per-aggregate subjects, or constrain concurrency). GitHub

“Exactly once” reality check (and how we get as close as possible) With outbox+inbox, you get:

Exactly-once side effects in your DB (because inbox makes processing idempotent).

At-least-once delivery from JetStream (by design, via acks/redelivery). NATS Docs

Effectively exactly-once publish within the dedupe window when you use Nats-Msg-Id. NATS Docs +2 NATS Docs +2

That combination is the standard “reliable messaging” setup.

Where this fits your “library/internal module” choice Even if VibesPro™ is in the same Nx workspace and linked as libs:

SEA™ calls VibesPro™ use-cases in-process for immediate synchronous needs (optional)

Cross-context state sync happens via events (outbox → NATS → inbox)

That preserves:

conceptual ownership (SEA™ can’t touch VibesPro™ internals)

data ownership (separate DB)

operational flexibility (you can later deploy VibesPro™ separately; NATS contract stays)

Minimal subject + contract conventions (practical defaults) Subjects: {context}.event.{name}.v{n} (all lowercase)

Message headers:

Nats-Msg-Id: UUID (from outbox row id) for dedupe NATS Docs +1

X-Correlation-Id, X-Causation-Id (your own headers; avoid Nats- prefix reserved space) NATS Docs

One decision point (so we don’t overbuild) Do you want one shared stream (e.g., EVENTS with subjects sea.> and vibespro.>) or one stream per context?

Shared stream: simpler ops, easier global replay

Per-context streams: tighter retention + isolation, cleaner governance

If you’re not sure, default to shared stream early.

If you want, next step is I’ll translate this into an Nx implementation plan: targets for outbox-publisher, inbox-consumer, and the contracts libs — and show the exact interfaces that keep SEA™ dependent only on libs/vibespro/public-api.

You said: per-context streams ChatGPT said: Per-context streams is a great choice. It gives you clear ownership, retention tuning per domain, and fewer “oops we blew up the global stream” incidents.

Here’s the concrete setup for SEA™ + VibesPro™ with NATS JetStream + outbox/inbox + separate Postgres databases.

1) JetStream layout: one stream per bounded context Streams VIBESPRO_EVENTS (owned by VibesPro™)

subjects: vibespro.event.> (subjects are the “topics”; streams are storage) NATS Docs +1

SEA_EVENTS (owned by SEA™)

subjects: sea.event.>

This matches JetStream’s model: streams define storage, consumers define delivery. NATS Docs

Subject conventions (contract surface) Use: {context}.event.{snake_case_name}.v{n}

Examples:

vibespro.event.vibe_created.v1

vibespro.event.vibe_scored.v1

sea.event.governance_decision_recorded.v1

Rule: never change meaning of .v1. Create .v2 on breaking changes.

2) Outbox → JetStream publish: idempotent publish with Nats-Msg-Id JetStream supports message deduplication when you set the Nats-Msg-Id header; it ignores duplicates of the same ID within a configurable window. NATS Docs +1

Do this:

outbox row id (UUID) becomes the publish msg-id

publish with header: Nats-Msg-Id: NATS Docs +1

keep stream dedupe window reasonably sized (docs caution against very large windows; default is small) Synadia

Also: Nats- is a reserved header namespace—use your own prefix for correlation headers. NATS Docs

Observable success

If the publisher crashes after publishing but before marking published_at, it can republish safely; JetStream dedupe prevents multiple stored copies (within the dupe window). NATS Docs +1

3) JetStream → Inbox consume: durable consumer + explicit acks Consumers track delivery/acks and will redeliver if a message isn’t acked. NATS Docs +1

Consumer pattern For each context, run an inbox writer/processor:

SEA™ subscribes (as a durable consumer) to VIBESPRO_EVENTS subjects it cares about.

VibesPro™ subscribes to SEA_EVENTS subjects it cares about.

Ack policy: explicit acks (the standard for reliable processing; redelivery occurs when unacked). NATS Docs +1

Inbox idempotency

Inbox table PK = message_id (same UUID as outbox id / msg id)

On receive: insert inbox row ON CONFLICT DO NOTHING

conflict = duplicate delivery → skip side effects

Process then mark processed_at, then ack

Failure diagnostics

If JetStream consumer backlog grows → consumer down or slow

If inbox fills but processed_at stays null → handler errors

If you see repeated deliveries → acks aren’t happening (or ack wait too short)

4) Retention + scaling knobs per stream Because streams are per-context, you can tune:

retention/limits and discard behavior (discard old vs refuse new) NATS Docs +1

consumer delivery attempts (max deliveries) NATS Docs

Pitfall to avoid: ordering assumptions. Redeliveries can show up on a different instance; strict ordering is not guaranteed under failures unless you design for it. NATS Docs +1

If you need “order per aggregate,” shard subjects like:

vibespro.event.vibe_scored.v1. and constrain concurrency per shard (optional, only if you truly need it).

5) Database boundary: same Postgres server, separate databases Keep:

sea_db (SEA™ owns tables + inbox/outbox)

vibespro_db (VibesPro™ owns tables + inbox/outbox)

Apps use separate DB credentials. This prevents accidental cross-context joins by construction.

6) How this fits the “library/internal module” choice Even if VibesPro™ code is in the SEA™ Nx workspace:

Conceptual boundary: SEA™ imports only libs/vibespro/public-api

Data boundary: separate DB

Messaging boundary: per-context streams + inbox/outbox

This means you can later deploy VibesPro™ as its own service without changing the integration style—only the packaging.

7) The next concrete step we should implement Create JetStream streams:

VIBESPRO_EVENTS ← subjects vibespro.event.>

SEA_EVENTS ← subjects sea.event.>

Add outbox publisher worker per context:

polls local DB outbox

publishes to its own stream subject(s) with Nats-Msg-Id

Add inbox consumer worker per context:

consumes from the other context’s stream subjects of interest

writes inbox row, processes, acks

Add Nx boundary rules so SEA™ can’t import VibesPro™ internals.

One decision point (small but important) Do you want consumers pull-based (worker pulls batches) or push-based (server pushes to subscriber)?

Pull-based is usually easier to reason about for work-queue style processing and backpressure.

Push-based can be simpler for low-throughput event fanout.

If you tell me which runtime you’re on (Node/Rust/Python) for the workers, I’ll recommend the most reliable mode for that client library and give you a concrete worker skeleton.

You said: i like pull base, i’m not sure what you mean about which runtime i’m on but i’m leaning towards rust for it’s memory saftey and speed. note SEA™ is polyglot ChatGPT said: “Runtime” here just means: what language/process is running the outbox publisher + inbox consumer workers (Node? Python? Rust? etc.). If you’re leaning Rust, that’s a solid choice for the infrastructure-y parts (JetStream pull consumer loops, backpressure, retries, idempotency), and it plays well with a polyglot SEA™ because it’s a clean “adapter/runtime shell” around your bounded contexts.

Below is a concrete pull-based design in Rust that fits: per-context streams + outbox/inbox + separate DBs.

The pull-based shape with JetStream With pull-based JetStream, your worker does this loop:

Fetch a batch of messages from a durable consumer (pull)

For each message:

write to Inbox with PK = message id (dedupe)

run handler (idempotent)

mark processed

ACK the message

Repeat with backoff when no messages

Observable success: you can stop the worker mid-batch and messages reappear later (redelivery), but your inbox PK prevents duplicate side effects.

Rust as the “messaging runtime” in a polyglot SEA™ Think of it as: Rust owns the transport + reliability loop, while your domain logic stays polyglot.

You have two good patterns:

Pattern A: Rust worker runs handlers directly Best if your handlers are already in Rust or you want them to be.

Lowest latency, simplest operations.

Pattern B: Rust worker is a “message pump” and calls language-specific handlers Rust does NATS + inbox/outbox reliably.

It invokes handlers via:

local HTTP on localhost (if same pod)

gRPC

or a lightweight command execution boundary (rarely worth it)

Adoption indicator: even if handlers crash, your inbox/outbox guarantees the message isn’t “lost”; it just retries.

Given SEA™ is polyglot and you’re still evolving, Pattern B is often the pragmatic move: Rust for reliability core, handlers can remain wherever they are today.

Concrete worker responsibilities 1) Outbox Publisher (per context) Poll outbox_events in that context’s DB (sea_db or vibespro_db)

Publish to that context’s stream subject

Set Nats-Msg-Id = outbox_event_id (UUID string)

Mark published_at

Success signal: outbox backlog trends toward zero; reboots don’t duplicate events (and even if they do, consumers dedupe via inbox).

2) Inbox Consumer (per context, pull-based) Pull from other context’s stream durable consumer

On each message:

Extract message_id (prefer: header Nats-Msg-Id; fallback: JetStream message metadata sequence + subject if needed)

INSERT INTO inbox_messages(message_id, …) ON CONFLICT DO NOTHING

conflict → duplicate delivery → ACK and continue

Run handler

Mark processed_at

ACK

Success signal: redeliveries don’t create duplicated rows or duplicated side effects.

Rust tooling that works well (practical choices) NATS: async-nats (JetStream supported)

Postgres: sqlx (good async + compile-time checked queries if you want)

Runtime: tokio

Observability: tracing + tracing-subscriber

Config: config or figment

Failure diagnostics you’ll actually use:

outbox_unpublished_count

inbox_unprocessed_count

jetstream_consumer_num_pending

handler_failures_total

message_processing_latency_ms

Pull consumer settings that prevent pain These are the knobs that most often cause “why is this redelivering constantly?”

Ack policy: explicit

Ack wait: must exceed worst-case handler time (plus some buffer)

Symptom of too small: same message keeps showing up while still processing

Max deliver: finite, with DLQ strategy

Symptom if missing: poison message loops forever

Max ack pending / concurrency: cap it so you don’t overload DB/handler

Symptom if too high: DB connection pool starvation, timeouts, huge retry storms

For early stability: start with low concurrency (like 10–50 messages in flight) and increase once metrics look clean.

How “per-context streams” + “pull-based” maps to processes A clean baseline deployment (even if all code lives in one Nx workspace):

SEA™ context sea-api (whatever language)

sea-outbox-publisher (Rust)

sea-inbox-consumer (Rust) — consuming from VIBESPRO_EVENTS for subjects SEA™ cares about

VibesPro™ context vibespro-api (whatever language)

vibespro-outbox-publisher (Rust)

vibespro-inbox-consumer (Rust) — consuming from SEA_EVENTS

You can combine publisher+consumer into one “worker” per context if you prefer fewer processes.

Observable success: you can deploy SEA™ + VibesPro™ independently and the integration still works because it’s contract-driven via subjects and message schemas.

Common pitfalls and their symptoms Pitfall: treating “pull” like “read and forget” If you don’t ack correctly, JetStream will redeliver.

Symptom: duplicates even though handler succeeded

Fix: only ACK after inbox insert + successful handler commit

Pitfall: missing idempotency on side effects Inbox prevents reprocessing, but your handler must still be safe under retries.

Symptom: “sometimes we double-charge / double-create”

Fix: every write keyed by deterministic id (message_id / correlation_id), or conditional UPSERTs

Pitfall: schema drift in payloads Symptom: handler panics/deserialization errors after deploy

Fix: version subjects (.v1, .v2) and keep old handler until drained

What I’d do given “Rust + polyglot + pull-based” Make Rust the standardized “messaging substrate” across SEA™.

Every bounded context gets:

a Rust outbox publisher

a Rust inbox consumer

Domain logic stays where it is for now.

Over time, you can migrate hot paths into Rust if it’s worth it—but you don’t have to.

That gives you reliability and uniform ops without forcing a single-language rewrite.

Quick check so we don’t build the wrong thing When you say “SEA™ is polyglot,” are your backend services currently mostly:

Node/TypeScript?

Python?

Rust already?

a mix?

Not asking for preference—this determines whether the Rust consumer should call handlers over HTTP/gRPC (Pattern B) or whether we should put the handler logic directly in the Rust worker (Pattern A). If you answer with the current mix, I’ll recommend one and outline the exact worker-to-handler contract (including request/response shapes and retry semantics).

You said: a mix but frontend is mainly typescript, backend mainly python i also have some rust componants ChatGPT said: Got it: frontend mostly TS, backend mostly Python, with some Rust already. That’s the perfect setup for:

Rust = the standardized messaging substrate (JetStream pull consumers + outbox publishers + retries/backpressure)

Python = the domain/use-case handlers (where most of your logic already lives)

TS = UI and any “thin gateway” APIs

So we’ll do pull-based JetStream in Rust, and have Rust invoke Python handlers in a controlled way.

The cleanest pattern for your mix: Rust workers + Python handler APIs Why this wins Rust excels at “never fall over” loops: batching, acks, timeouts, reconnects, memory safety.

Python owns the business logic, and doesn’t need to be rewritten.

The boundary is explicit: events → handler contracts, not “random imports.”

Observable success: you can restart Python handlers independently; Rust keeps pulling/acking correctly; duplicates never create double side effects.

Concrete runtime topology per bounded context (SEA™ and VibesPro™) For each context, run 2 workers (can be 1 process if you prefer):

Outbox Publisher (Rust)

Reads outbox_events from that context’s DB (sea_db or vibespro_db)

Publishes to that context’s stream (SEA_EVENTS or VIBESPRO_EVENTS)

Uses Nats-Msg-Id = outbox_event_id for publish dedupe

Marks published_at

Inbox Consumer (Rust, pull-based)

Pulls from the other context’s stream subjects it subscribes to

Writes inbox_messages into local DB (idempotency key = message id)

Invokes Python handler

Marks processed_at

ACKs JetStream message

And separately: 3) Handler Service (Python, per context)

A small HTTP (or gRPC) service with endpoints like:

POST /handle/{event_type}

Runs domain use-cases and writes to its own DB

Returns success/failure so Rust can decide ack vs retry

The key contract between Rust and Python Recommended: HTTP on localhost (simple and reliable) Rust calls Python like:

POST http://127.0.0.1:/handle

Body includes:

event_type

event_version

message_id (UUID)

occurred_at

payload

correlation_id, causation_id

Handler response contract (important for retries) Python returns one of:

200 OK → processed successfully (Rust marks processed_at, ACK)

409 Conflict → already processed / idempotent duplicate (Rust can mark processed and ACK)

422 Unprocessable Entity → “poison message” (schema mismatch, invalid data). Rust should ACK and dead-letter (or park it), not retry forever.

5xx / timeout → transient failure. Rust should not ACK, let JetStream redeliver, and increment attempt counters.

Observable success: you can deliberately crash the Python handler, watch retries/redelivery happen, then restore it and see the backlog drain without duplicates.

Pull-based consumer settings that match this setup Start conservative:

Durable consumer per subscriber (e.g., sea-consumes-vibespro)

Explicit acks

Ack wait: set > worst-case handler time (e.g., 60–120s to start)

Symptom if too small: same message shows up again while still processing

Max deliver: finite (e.g., 10–20)

After max deliver, route to a dead-letter subject/stream

Max in-flight / concurrency: cap (e.g., 10–50)

Symptom if too high: DB pool exhaustion, timeouts, cascading retries

Where “separate database” matters in code Because you chose same DB server, separate database:

SEA™ Python handlers connect only to sea_db

VibesPro™ Python handlers connect only to vibespro_db

This prevents accidental coupling at the most dangerous layer (data).

If SEA™ needs some VibesPro™ info, it gets it via:

events (preferred), or

explicit capability calls via @vibespro/public-api (in-process), but never via shared DB reads.

How Nx fits without becoming a mess Even though the runtime split is “Rust infra + Python domain,” Nx can still be the orchestrator:

apps/sea-worker-rs (Rust: publisher+consumer)

apps/sea-handlers-py (Python: handler service)

apps/vibespro-worker-rs

apps/vibespro-handlers-py

And enforce boundaries so:

SEA™ TS/Python code can only use libs/vibespro/public-api (DTOs/contracts)

No imports from VibesPro™ internals

No cross-db connections

Failure modes you’ll want to design for now Poison event (bad payload / incompatible version)

Symptom: same message fails every time

Fix: handler returns 422, Rust sends to DLQ and ACKs

Transient handler outage

Symptom: redeliveries + growing pending count

Fix: don’t ACK; JetStream redelivers; Rust backoff prevents storms

Duplicate publish / duplicate delivery

Symptom: same event appears twice

Fix: Inbox PK blocks double-processing; Nats-Msg-Id reduces duplicate storage

Slow handlers

Symptom: ack wait exceeded, duplicates while still working

Fix: increase ack wait and/or lower concurrency

The one decision point to lock in now For Rust → Python invocation, do you want:

HTTP localhost (fastest to implement, easiest to debug), or

gRPC (stricter contracts, better tooling for schemas, a bit more work)

Given you’re moving fast and polyglot, I’d start with HTTP + JSON, but version your event types (*.v1) and keep schemas in a shared “contracts” package so you can upgrade cleanly.

If you tell me whether you’re already using FastAPI (or similar) for Python services, I’ll sketch the exact handler endpoint shape + the Rust worker loop responsibilities (what to ack when, how to DLQ) in a way that matches your stack.

You said: im using fastapi for python ChatGPT said: Cool — FastAPI is exactly what we want here: it makes the Rust pull-consumer → Python handler boundary simple, debuggable, and versionable.

Below is a concrete, reliable pattern that matches your choices:

Per-context streams (SEA_EVENTS, VIBESPRO_EVENTS)

Pull-based JetStream consumers (explicit ack)

Outbox + Inbox (exactly-once effects, at-least-once delivery)

Rust workers (publisher + consumer)

FastAPI handler services (domain logic)

I’ll keep it implementable and show the “what to ACK when” rules.

1) JetStream contract basics we’ll rely on JetStream supports publisher dedupe using the Nats-Msg-Id header. NATS Docs +2 NATS Docs +2

JetStream consumers provide at-least-once with delivery tracking + acks. NATS Docs +1

Pull consumers fetch in batches and let the client control flow. NATS Docs +1

Nats- is a reserved header namespace; use your own prefix for correlation headers. NATS Docs +1

2) The precise “ACK rules” (this is the whole game) For each JetStream message:

Write inbox row (idempotency)

If inbox insert is a duplicate → ACK immediately (we already processed it)

Call FastAPI handler

If handler succeeds and DB commit succeeded → mark processed + ACK

If handler fails transiently (timeout/5xx) → DON’T ACK (let JetStream redeliver)

If handler says “poison” (422 / schema mismatch) → ACK + dead-letter (don’t retry forever)

JetStream will redeliver unacked messages; that’s your free retry mechanism. NATS Docs +1

3) FastAPI handler API (simple, versioned, and retry-aware) One endpoint per bounded context Run a “handler service” per context (SEA™ handlers, VibesPro™ handlers). Minimal contract:

POST /handle

Request body (JSON):

{ “message_id”: “uuid”, “subject”: “vibespro.event.vibe_created.v1”, “event_type”: “vibe_created”, “event_version”: 1, “occurred_at”: “2025-12-28T17:00:00Z”, “correlation_id”: “uuid”, “causation_id”: “uuid”, “payload”: { “…” : “…” } } Response codes (drives Rust ack logic):

200 OK: processed successfully

409 Conflict: already processed (idempotent duplicate)

422 Unprocessable Entity: poison message (bad payload/version) → dead-letter

503 / 500: transient failure → retry via redelivery

Observable success: you can see retries by watching 5xx/timeout cases reappear.

Why one endpoint instead of /handle/{event_type}? It keeps routing stable while event types evolve; handler selection happens in Python based on subject or event_type+version.

4) Inbox/outbox tables (per context DB) Inbox (in sea_db and vibespro_db) inbox_messages:

message_id uuid PK

subject text

received_at timestamptz

processed_at timestamptz null

attempts int default 0

last_error text null

Idempotency: the PK enforces “process once.”

Outbox (in sea_db and vibespro_db) outbox_events:

id uuid PK

subject text

payload jsonb

occurred_at timestamptz

published_at timestamptz null

publish_attempts int default 0

publish_error text null

5) Rust: pull consumer + FastAPI call (architecture, not a wall of code) Pull consumer loop (per subscription) durable consumer name: e.g. sea__from_vibespro

filter subject: vibespro.event.> (or narrower)

loop:

fetch(batch=N, expires=…)

for each msg:

get message_id from header Nats-Msg-Id (required)

insert inbox row (ON CONFLICT DO NOTHING)

if duplicate → ACK

call FastAPI /handle with request body

update inbox processed_at / attempts / last_error

ACK only on success/duplicate/poison

Outbox publisher loop (per context) poll unpublished outbox rows

publish to that context’s stream subject

set header Nats-Msg-Id = outbox.id for dedupe NATS Docs +1

mark published_at

Note: dedupe is within a window (“rolling period”), so you still keep inbox idempotency as the real safety net. NATS Docs +2 NATS Docs +2

6) Pull-based tuning defaults (good starting point) batch size: 50

concurrency: 10–25 in-flight messages

ack wait: 60–120s initially (must exceed worst-case handler time)

max deliver: 10–20, then dead-letter

dead-letter subject: {context}.dlq.> (in the same stream as the sender context, or a separate *_DLQ stream)

Symptoms & fixes

repeated redelivery while processing → ack wait too short or handler too slow

DB timeouts → concurrency too high or pool too small

poison loops → missing 422→DLQ path

7) How this fits your Nx polyglot workspace Even if everything “lives inside SEA™,” we keep operational clarity:

apps/sea-handlers (FastAPI)

apps/sea-mq-worker (Rust: consumes VIBESPRO_EVENTS, publishes SEA_EVENTS)

apps/vibespro-handlers (FastAPI)

apps/vibespro-mq-worker (Rust: consumes SEA_EVENTS, publishes VIBESPRO_EVENTS)

And a contracts package:

libs/contracts (or libs/vibespro/public-api + libs/sea/public-api)

event subjects, payload schemas, versioning rules

One decision point (so I can make this concrete) For the Rust worker calling FastAPI, do you want the Python handler service:

Co-located (same pod/container group) and called via http://127.0.0.1:PORT

Networked service (K8s service name, auth between them)

If you’re early, (1) is simpler and keeps auth out of the critical path. If you tell me which you’re aiming for (even loosely), I’ll lay out the exact deployment wiring (env vars, ports, health checks) and the failure behavior you’ll see when things go wrong.

You said: 1 ChatGPT said: Great — co-located FastAPI handler on 127.0.0.1 is the cleanest way to start. It lets the Rust JetStream worker do reliable pulling/acking without introducing auth/service-discovery complexity in the critical path.

Here’s the concrete wiring (what runs, what talks to what, what env vars you set, and how it fails).

The deployment unit (per bounded context) For SEA™ (repeat same pattern for VibesPro™):

Same pod / same docker-compose service group:

sea-handlers (Python/FastAPI) — listens on 127.0.0.1:7001

sea-mq-worker (Rust) — connects to NATS, Postgres (sea_db), calls http://127.0.0.1:7001/handle

Why this works Localhost is stable and fast.

If Python dies, Rust sees connection errors and simply doesn’t ACK, so JetStream redelivers later.

You can restart either container independently.

Observable success: kill the FastAPI container → pending messages rise; restore it → backlog drains without duplicates.

Required environment variables Rust worker (sea-mq-worker) NATS_URL=nats://nats:4222 (or whatever your NATS service is)

DB_URL=postgres://sea_app:…@postgres:5432/sea_db

HANDLER_URL=http://127.0.0.1:7001/handle

CONSUME_STREAM=VIBESPRO_EVENTS

CONSUME_SUBJECT=vibespro.event.> (or narrower)

DURABLE_NAME=sea__from_vibespro

PUBLISH_STREAM=SEA_EVENTS (usually implied by subject binding, but keep explicit in config)

PUBLISH_PREFIX=sea.event. (optional convenience)

Tuning knobs (start conservative):

BATCH_SIZE=50

MAX_INFLIGHT=25

ACK_WAIT_SECS=120

MAX_DELIVER=20

DLQ_SUBJECT=sea.dlq.vibespro (or per-event DLQ mapping)

FastAPI (sea-handlers) DB_URL=postgres://sea_app:…@postgres:5432/sea_db

BIND_HOST=127.0.0.1

PORT=7001

Networking note: why 127.0.0.1 is correct only if This is the one “gotcha”:

In Kubernetes, two containers in the same Pod share the same network namespace → 127.0.0.1 works.

In docker-compose, two separate services do not share localhost → you must either:

run them as one service with a process supervisor (not ideal), or

call by service name (http://sea-handlers:7001) instead of localhost.

So: localhost implies “same pod” (or same container).

Does this match your deployment constraint today (K8s pod style), or are you currently using docker-compose services? If you’re unsure, the safe default assumption is you’ll end up in “same pod.”

Health checks that actually catch the right failures FastAPI container Liveness: GET /health/live → returns 200 if process is alive

Readiness: GET /health/ready → checks DB connectivity (and migrations applied)

Rust worker container Liveness: a simple endpoint /health/live (or just “process running”)

Readiness: NATS + DB connectivity established (and JetStream consumer exists)

Failure symptom mapping

FastAPI not ready → Rust starts but will fail handler calls; that’s fine, but you’ll see growing pending.

Rust not ready → no consumption; pending grows, outbox grows.

The ACK/Retry/DLQ rules (tight and operational) When Rust pulls a message:

Extract message_id (require Nats-Msg-Id; treat missing as poison)

Insert into inbox_messages(message_id …)

conflict → ACK immediately

Call FastAPI /handle

Based on response:

200 → mark processed → ACK

409 → mark processed (optional) → ACK

422 → publish to DLQ_SUBJECT + mark failed → ACK

timeout / 5xx → increment attempts + store error → DON’T ACK (redelivery)

Observable success: poison events don’t loop forever; transient outages auto-heal.

Startup ordering and “wait-for” Don’t try to strictly order startup. Instead:

Rust worker retries connections to:

NATS

Postgres

Handler URL

Rust does not ACK until it completes a handler cycle.

Symptoms if you get this wrong

If you ACK before handler commit: you’ll lose side effects.

If you never ACK duplicates: you’ll get redelivery storms.

Minimal port plan Pick consistent ports so you don’t hate yourself later:

SEA™ handlers: 7001

VibesPro™ handlers: 7002

(Optional) metrics:

Rust worker metrics: 9101, 9102

What I’d implement first SEA™ side only end-to-end:

SEA_EVENTS stream

VIBESPRO_EVENTS stream (even if no producer yet)

SEA™ Rust consumer pulls from VIBESPRO_EVENTS and successfully calls SEA™ FastAPI (use a test subject/message)

Add outbox publisher in SEA™ and confirm publish dedupe with Nats-Msg-Id

Mirror the same for VibesPro™

Quick check (so the localhost assumption holds) Are you planning to run this in Kubernetes pods (or something pod-like) soon? If yes, we’re aligned. If you’re staying in docker-compose for a while, we can still do the same pattern but the “co-located” URL becomes http://sea-handlers:7001/handle instead of 127.0.0.1.

DEVELOPER MODE

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