Switching from Zapier without breaking everything in production

Table of Contents

1. Fighting the Zapier task cap with Make and n8n combos

Every small team I’ve worked with hits this wall: Zapier runs out of tasks, or your multi-step Zap suddenly reruns a dozen times off one Slack thread bump because someone commented a thumbs-up. You stare at the run history, and Zapier tells you everything is fine. It’s not. That’s when people start looking at Make and n8n.

The combo of Make’s generous free plan (1,000 ops/month) and n8n’s self-hosted flexibility has become my default for anything semi-critical. Make is great for visually building complex paths using HTTP, arrays, routers, etc., but it’s weirdly bad at consistent webhook triggering from tools like Discord. n8n, on the other hand, doesn’t care—it just sees the JSON and rolls with it.

Make’s routers are visually clear but sometimes lag behind webhook triggers by up to 30 seconds
n8n makes it easy to transform payloads inline, but its UI can get laggy with large node graphs
Using webhook.site to capture payloads for Make setups helps debug odd behavior during testing
The Make-to-n8n handoff works cleanest via HTTP module with JSON headers — just don’t forget auth
Tasks in Zapier aren’t equivalent to “Executions” in Make or n8n — watch your usage closely

Zapier recently changed how it counts tasks for multi-package Paths, which broke a working calendar integration mid-meeting. Make & n8n handled the same logic with fewer steps and no surprise usage spikes.

2. Building a Table-driven system using Airtable plus Make

I built a multi-client dashboard system using Airtable a few months back. Mostly worked — until one record’s name included a forward slash. Zapier flopped out hard: couldn’t find the record due to URL-style encoding. Make parsed the incoming value, encoded it right, and pushed it cleanly.

Where this stack shines is using Airtable as the logic database, and Make as the logic runner. The undocumented edge is that Make’s Airtable module doesn’t always grab ‘linked record’ fields unless you manually expand the format. You have to toggle that in the advanced field settings in the module config, which is easy to miss.

Pro tip if you’re pre-filtering in Airtable

Use formula views dynamically—e.g., IF({Status}='Ready', TRUE(), FALSE())—and filter from Make using the View dropdown. It’s WAY faster than scanning every row with a filter module. Also, if you name your fields with emoji (🚀 Launch, ✅ Approved), Make silently strips those during fetch, and nothing throws an error. Fields vanish, and you spend thirty minutes trying to remember whether it was called Launch or 🚀 Launch.

Eventually I built each Make scenario to clone the output into a “Logs” base so I could retrace logic when a push failed due to missing linked records. Lot of time wasted without error messages—but once it clicks, it’s solid.

3. Handling Notion API’s shifting payload structure with Pipedream

Pipedream surprised me. I pushed a test webhook from Notion expecting a standard event structure, but the keys change depending on the block type. Some top-level fields just vanish if a block doesn’t have them. Pipedream’s code steps let you fight back by stuffing defaults for missing values during runtime.

export default defineComponent({
  async run({ steps }) {
    return {
      title: steps.trigger.event.properties?.title?.[0]?.plain_text || "Untitled",
      status: steps.trigger.event.properties?.status?.select?.name || "No status",
    }
  }
})

The catch: sometimes the event payload just… doesn’t core dump anything useful. I’ve seen empty objects with only an ID and a timestamp. It happens when you delete something in Notion and have automations watching “Updated” events. You get a ghost ping.

Pipedream is the only tool I’ve used that logs payload failures with useful metadata and lets you replay with edits, mid-pipeline. I put it in front of my Notion webhooks now, then forward filtered data to either Make or webhook endpoints for Slack pings.

Honestly, the combo of Pipedream + Make is now replacing half my Zaps.

4. Using n8n self-hosted for stable webhook dependencies

Twice now, I’ve had a Zap that depended on a webhook fire twice (back-to-back) even though the payload clearly shows a single event. Not reproducible, no fix offered. Support shrugs. With n8n, I built a tiny anti-replay guard using a Redis key check — fast and safe against Zapier-style dupes.

Self-hosted n8n gives full control, but you need a reverse proxy plus SSL or things break subtly. One time, webhook replies were OK in Postman but quietly failing when called live because I’d misconfigured Cloudflare rules for caching. Turned out n8n expects application/json with exact casing—wrong casing and the execution logs get blank.

There’s also a gotcha: if you update an n8n workflow, saved executions don’t reflect the original version, so reruns can give different outcomes. I now snapshot each workflow version with a timestamp in comments inside the workflow description field so I can trace what logic was live at time of run. Feels janky, but small teams can’t afford silent automations morphing post-hoc.

5. Capturing Slack trigger weirdness using Make plus webhook wrappers

I’ve had at least two Slack-based Zaps auto-deactivate because Zapier thought the app was “not responding”—even though the Slack event was successfully received and parsed. It’s flaky. So now I send Slack events directly to a Make webhook, where I log them in a Notion DB before doing anything else. If Slack misbehaves, I still get the raw event data.

The edge case here: Slack sometimes hides certain button values or metadata depending on user role. An admin clicking a button sends more payload keys than an end-user. That is not in any public Slack docs. Make lets me just dump the raw JSON and work from there. Zapier tries to normalize the payload and fails silently if it doesn’t match expected fields.

One random discovery: If you build a Slack bot that uses modals, and you pipe the submission data into Make, you must use a text field as your user identifier. Trying to use something like user_id from a hidden input field gets dropped by Slack’s payload sanitization.

Being able to debug off raw modal submissions, with timestamped payloads in Notion, has saved me on client rollouts.

6. Pricing anxiety with task-based platforms versus CPU-minute billing

The whole “one task = one run = one action” model is too abstract. Zapier counts looking up a Google Sheet row as a task. Make charges by operations — which is slightly better, until you use a router and accidentally double your count. Pipedream uses compute time. Airtable’s automation run limits reset only on workspace-level quotas. It’s all a mess.

For small teams, the pricing stress comes from two directions:

Zaps that suddenly trigger a dozen times off one event
Backfills or re-runs that blow the monthly limit in an hour

I now tag every automation with a usage annotation field (“light”, “moderate”, “heavy”) and set alerts based on calculation, not tasks. For Make, I run a scenario that logs run counts and ops into a Notion table every 4 hours. For Pipedream, I grep function runtime per event and pipe the totals to a weekly digest. Zapier doesn’t let you get granular enough info unless you scrub through individual task histories manually — which burns more time than it saves.

None of these platforms give financial line-item granularity. You just get billed. That’s painful when you’re bootstrapping or running client automation under a shared plan.

7. When native integrations disappear or change behavior silently

I had a Trello-to-Github Zap that used to pull in card descriptions cleanly as issue bodies. Suddenly, the links stopped rendering right. No warning. Zapier’s integration with Trello had updated and the HTML formatting primitives changed — from markdown to raw preformat.

You can’t roll back integrations. There’s no versioning. This is where n8n and Make are safer—you’re directly using API modules. If Trello changes, you just inspect the new JSON, map the correct field, and move on. For Zapier? You open a support ticket and wait.

Even worse: some Zapier pre-built integrations (like with Typeform) silently throttle trigger speed when you hit form submission volumes over some unlisted cap. I had a client miss 30+ leads before we caught it. We moved the webhook call to go direct-to-Make, with a backup send to Airtable via custom script. No more black box behavior.

Zapier may be stable for most things, but if you’re relying on field mappings inside apps that update often—Trello, Notion, Google Forms—you’ll spend more time triaging breakage than you will building.