Automation platforms like Make have evolved far beyond simple task chaining. They now sit at the core of revenue pipelines, onboarding flows, custo...
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This is exactly why we moved everything to n8n. Self-hosted all the way.
Self-hosting gives control, not immunity.
n8n solves a big part of the problem, but it still needs proper monitoring, backups, and capacity planning. The real win is owning execution, not just switching tools.
Curious about your move to self-hosted n8n - was it primarily about uptime control, data residency, cost, or something else?
I'm building a data pipeline platform and debating the self-hosted vs managed-only question. n8n seems to have nailed the hybrid approach. Trying to understand which problems actually push teams to want that option.
Good question. In practice it’s rarely just one factor.
For most teams I’ve seen, uptime is the trigger, but not the core reason. An outage exposes something deeper: loss of control over execution, recovery, and failure modes. That’s usually when people start looking at self-hosted options.
Data residency and compliance matter in regulated environments, but they’re often secondary. Cost almost never drives the initial decision either. Managed SaaS is usually cheaper until you hit scale or complexity.
What actually pushes teams toward a hybrid model is ownership. Who owns failure, recovery, observability, and long-term behavior once workflows become business-critical? Self-hosted execution gives predictability and control there, while managed tools remain useful for speed and experimentation.
One important nuance with n8n specifically is licensing. The self-hosted version is not “do whatever you want” open source. Teams need to be careful when embedding it into commercial products, offering it as part of a service, or reselling automation capabilities. I’ve seen founders underestimate that risk early on.
n8n gets traction because it doesn’t force an ideological choice, but the license does mean you should be deliberate about how and where you use it. For many teams it’s a great execution layer, as long as legal and commercial boundaries are clear.
For a data pipeline product, I’d think less in terms of self-hosted vs managed, and more in terms of who owns failure, recovery, data flow, and licensing constraints at scale. That’s usually where the real trade-offs surface.
Cannot agree more, its what I try and tell people when they ask "managed vs self-hosted" the answer depends on the the current state of the product and if you've got the resources to handle it.
I got lucky and was able to play with N8N at work a bit cool tool, I actually used their workflow viewer as inspiration for the dataflow pipeline visualization for Flywheel.
We’ve been using Make for years without major issues. Isn’t this a bit overblown?
Not really. Make is solid most of the time.
The issue isn’t frequency, it’s impact. If one incident can freeze revenue-critical workflows, the architecture deserves scrutiny. Reliability is about failure tolerance, not uptime statistics.
Make.com going down just reminds everyone that no-code is great… until it isn’t 😅
😁
It’s great until it’s down and there’s no equally fast fix for the instant generation. Tougher even is that you can’t always jump in and patch with a redirect.
How does this affect AI agents specifically? Aren’t they more flexible?
They’re more flexible in decision-making, not execution.
If an agent can think but can’t act because the execution layer is down, it’s stuck. AI increases the need for resilient infrastructure, it doesn’t reduce it.
Sounds nice, but redundancy is expensive. Not every startup can afford this.
Agreed. Not everything needs redundancy.
The mistake is treating all workflows the same. Most teams only need fallback for a small subset. The cost comes from not knowing which ones matter.