P $2,997–$4,997 · fixed SLA · 7–14 days

Scale your n8n instance — queue mode, Redis workers, Postgres tuning, execution pruning, load tested.

Automations built to last.

You hit the ceiling. Workflows are slow. Postgres is growing. Executions time out under load. The single-process n8n instance that worked at 5k executions/month is choking at 50k.

I set up queue mode with Redis, split monolith workflows into parallelized sub-workflows, tune Postgres for your workload, configure execution pruning, and hand you a load-test report proving the improvement.

Async. Written. No call. You send instance access. I send a scaled architecture with before-and-after benchmarks.

NDA-friendly · Fixed-price · Money-back guarantee

Send instance details Request a sample report

FIG · Instance scaling architecture

Fit

Who this is for

Companies hitting performance walls at 50k+ executions per month. Workflows are slow, the database is growing unbounded, executions are timing out, and you've started seeing “worker timed out” or memory errors in the logs.

You know you need queue mode but don't know how to set it up without breaking existing workflows. Or you've tried enabling it and something went wrong.

Or you're planning to 10x your workflow volume (new product launch, migration from another tool, onboarding enterprise clients) and want the infrastructure scaled before the traffic arrives.

This is for operators who've outgrown single-server n8n and need a production-grade horizontal scaling setup — not a tutorial that stops at “add EXECUTIONS_MODE=queue to your .env”.

Deliverable

What you receive

A fully scaled n8n architecture, deployed on your infrastructure, with before-and-after proof that it works.

Queue mode setup — Redis instance configured, n8n main + worker process separation, environment variables locked
Worker node deployment — separate worker containers or processes, scaled to your volume needs
Execution pruning strategy + configuration — retention windows set per workflow criticality, dead data cleared
Postgres performance tuning — shared_buffers, work_mem, effective_cache_size, connection pooling (PgBouncer if needed)
Workflow splitting for parallelism — monolith workflows refactored into sub-workflows for parallel execution
Load test report — before-and-after benchmarks showing throughput, p95 latency, and failure rates under load
Updated runbook covering the scaled architecture — how to add workers, how to debug queue issues, how to recover
Monitoring updates for the new worker topology — per-worker health checks, queue depth alerts, Redis memory alerts

Scope exclusions

What's NOT included

Multi-region or multi-datacenter high availability. This is single-region horizontal scaling.
Kubernetes orchestration. If you need K8s, that's a custom scope — send the brief and I'll quote it separately.
Application-level rewrite of workflow logic. I split monoliths into sub-workflows for parallelism, but I don't redesign your business logic.
Hosting infrastructure costs. You pay for servers, Redis, and any managed services. I configure them.
Ongoing monitoring operations. For monthly oversight see SKU I — Retainer.
Database migrations or schema changes to your application database (only n8n's internal Postgres is tuned).
n8n version upgrades as part of this engagement. If you're on an old version, upgrade first (or bundle with this scope).

Process

How it works

01

You buy.

$2,997 for single-server queue mode / $4,997 for multi-worker horizontal scaling. Fund the milestone via Upwork or direct invoice.
02

You send instance access + context.

SSH access to the current server (or Docker host). Current docker-compose or deployment config. Approximate monthly execution volume. Which workflows are slowest.
03

I run baseline benchmarks.

Load test the current setup to establish a before measurement — throughput, p95 latency, failure rate under concurrent load.
04

I deploy the scaled architecture.

Queue mode, Redis, worker processes, Postgres tuning, execution pruning, monitoring updates. No mid-flight calls — one written question if a blocker surfaces.
05

I run post-scaling benchmarks and deliver.

Same load test against the new architecture. Before-and-after report. Updated runbook. You validate the improvement and accept.

Pricing

Scope	Price	Timeline
Single-server queue mode — Redis + worker process on same host, Postgres tuning, pruning	$2,997	7 days
Multi-worker horizontal scaling — separate worker nodes, load balancing, full benchmark report	$4,997	14 days

Fixed price. The load-test report is included in both tiers. The difference is architectural complexity — same host vs. distributed workers.

Not sure which you need? Send your monthly execution count and workflow complexity. I'll recommend the right tier in the scope confirmation.

Questions

FAQ

What execution volume triggers the need for queue mode?

Generally 30k–50k executions/month on a single 4-vCPU server. Below that, single-process mode with Postgres tuning and pruning is usually sufficient. Above that, queue mode prevents the main process from becoming a bottleneck.

Will my existing workflows break when switching to queue mode?

No — if done correctly. The risk is in credentials, environment variables, and file-system dependencies that don't transfer cleanly to worker processes. I audit every workflow for these dependencies before flipping the switch.

Do I need a separate Redis server?

For the single-server tier, Redis runs on the same host. For multi-worker scaling, a dedicated Redis instance (or managed Redis like ElastiCache) is recommended. Infrastructure cost is yours; I configure it.

What does Postgres tuning actually change?

shared_buffers (25% of RAM instead of the 128MB default), work_mem (scaled to query complexity), effective_cache_size, maintenance_work_mem, connection pooling via PgBouncer if connection count exceeds 100. Plus: vacuum schedule tuning for execution tables.

Can you scale n8n Cloud instances?

n8n Cloud manages its own infrastructure. This SKU is for self-hosted instances where you control the server configuration. If you're on Cloud and hitting limits, I can advise on whether to stay or migrate — but the scaling work itself requires self-hosted.

What if I'm on Kubernetes already?

K8s-based scaling is a custom scope. Send the brief describing your current K8s setup (helm chart? custom manifests? managed n8n operator?) and I'll quote it separately.

How do you load test without disrupting production?

Baseline benchmarks run against a staging replica of your instance. If no staging exists, I test during off-peak hours with synthetic payloads that mirror your real workflow patterns but don't trigger side effects.

What happens if the scaling doesn't improve performance?

The load-test report shows before-and-after numbers. If the scaled architecture doesn't demonstrate measurable improvement on the metrics we agreed in scope (throughput, latency, failure rate), you reject the deliverable and the milestone refunds.

Ready to scale ?

NDA-friendly · Fixed-price · Money-back guarantee

Async. Written. Before-and-after benchmarks. 7–14 days.

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syed@noorflows.com · async only · UTC+5