Hey everyone,
I’m thinking about self-hosting n8n on a DigitalOcean droplet. I’m looking at their $6/month plan and wondering how many workflows it can handle without issues.
Does anyone have experience running n8n on this kind of setup? I’d love to know roughly how many simple, medium, and complex workflows it can manage smoothly.
Also, has anyone noticed any performance differences between simple and complex workflows on this type of server?
Thanks in advance for any insights!
I’ve been running n8n on a $6 DigitalOcean droplet for about a year now, and it’s been a pretty solid experience. In my setup, I’ve found that it comfortably handles around 15-18 simple workflows, 8-10 medium complexity ones, and about 3-5 complex workflows without major issues.
One thing I’ve noticed is that the performance can vary quite a bit depending on the specific tasks you’re running. API-heavy workflows tend to be more taxing on the system compared to simple data manipulations. I’ve also found that scheduling workflows to run at different times helps distribute the load and keeps things running smoothly.
If you’re planning to scale up in the future, you might want to consider setting up monitoring tools to keep an eye on your resource usage. It’s helped me identify bottlenecks and optimize my workflows. Overall, for small to medium automation needs, the $6 droplet is a cost-effective solution, but be prepared to upgrade if your needs grow significantly.
yo, ive been usin a $6 DO droplet for n8n too. handles bout 15-20 simple workflows ez. medium ones, maybe 8-10. complex stuff? stick to 3-4 max.
simple ones run quick, but complex workflows can lag a bit. watch ur RAM usage tho, it can spike with data-heavy tasks. overall, its decent for smaller setups.
I’ve been running n8n on a $6 DigitalOcean droplet for about 6 months now. In my experience, it handles around 20-25 simple workflows without breaking a sweat. For medium complexity, I’d say 10-15 is the sweet spot. Complex workflows with lots of data processing or API calls? I wouldn’t push it beyond 5-7.
Performance-wise, there’s definitely a noticeable difference between simple and complex workflows. Simple ones execute almost instantly, while complex workflows can take a few seconds, especially if they involve large data sets or multiple external integrations.
One tip: keep an eye on your droplet’s resources. I’ve found that memory usage can spike with certain types of workflows, particularly those involving heavy data manipulation. Overall, though, it’s a solid setup for small to medium automation needs.