· productivity  · 6 min read

5 Controversial Automations to Avoid in Make (and Why)

Avoid the common Make patterns that create cost, fragility, and scaling headaches. Learn five controversial automations to avoid, the risks they create, and practical, expert alternatives that scale reliably.

Avoid the common Make patterns that create cost, fragility, and scaling headaches. Learn five controversial automations to avoid, the risks they create, and practical, expert alternatives that scale reliably.

Introduction - what you’ll get from this post

You’ll finish this article with five concrete automation patterns to stop using in Make today - and with clear, practical replacements you can implement this week. Save operations. Reduce failures. Make scenarios that scale.

I’ll be direct. Some habits you picked up while prototyping work fine for a demo. They fail badly in production. Short loops, monolithic scenarios, blind bulk writes - they all come from looking for speed and convenience. They end up costing money, time, and reputation. Read on to learn why, how they break, and what to do instead.

Why this matters up front

Make charges by operations and run complexity. Tight polling, retries, and expensive scenario runs are not just theoretical problems - they increase your bill and your MTTR (mean time to recovery). See Make’s pricing and operation model for details: https://www.make.com/en/pricing

Controversial Automation #1 - Tight polling loops (short-interval polling instead of webhooks)

Why people do it

  • It’s simple to implement; many APIs offer no native push/event mechanism.
  • It works immediately during prototyping.

Why it’s controversial (and risky)

  • Wastes operations and increases cost. Every poll counts as an operation.
  • Hammers APIs and can hit provider rate limits or IP blocks.
  • Adds latency unpredictability when combined with backoffs and retries.

Better alternative

  • Use webhooks or event-driven integrations whenever the system supports them. Webhooks push data only when something happens, eliminating needless polls.
  • If you must poll, shift to a delta strategy - request only changes since the last run (incremental sync) and lengthen the interval.
  • Add exponential backoff and jitter to avoid thundering-herd effects.

How to implement in Make

  • Use the Webhooks module - create a webhook receiver scenario and let the external service push events into Make. See Make help on webhooks:
  • For polling-only APIs, implement state using Data Store or a small key-value store to track last processed timestamp or cursor: https://www.make.com/en/help/applications/data-stores

Controversial Automation #2 - Blind bulk updates (update everything “just in case”)

Why people do it

  • Simplicity. One update covers every record and avoids complex logic.
  • Time pressure - “Just push an update and fix failures later.”

Why it’s controversial (and risky)

  • Risk of accidental data corruption or overwriting IDs/fields unintentionally.
  • Hard to roll back. Bulk writes often bypass app-level validations.
  • If the target API rejects partial updates, you can leave systems in inconsistent states.

Better alternative

  • Implement idempotent, incremental updates. Only update fields that actually changed.
  • Use pre-flight checks - fetch the record first, compare, then update only when needed.
  • Batch safely - group smaller batches and validate after each batch.

How to implement in Make

  • Use the ‘Get’/‘Search’ modules to fetch the current record, compare values with the Tools > JSON or Text functions, and then conditionally call the Update module.
  • Preserve original data in a Data Store or backup table before doing large updates so you can roll back.

Controversial Automation #3 - Building monolithic, all-in-one scenarios

Why people do it

  • One scenario looks neat. Everything in one place feels easier to manage.
  • Developers reuse modules instead of duplicating configuration.

Why it’s controversial (and risky)

  • Hard to debug - a failing run needs step-through across a huge logic tree.
  • Poor observability and brittle error handling. A single failure can cascade.
  • Difficult to scale - you can’t run parts independently or distribute load.

Better alternative

  • Split logic into single-responsibility scenarios (micro-scenarios). Each scenario does one clear job.
  • Use routers and webhooks to orchestrate flows, not a thousand if/then branches.
  • Build explicit contracts between scenarios (simple JSON payloads, stable webhook endpoints).

How to implement in Make

Controversial Automation #4 - Waiting by long-running scenario runs or sleep loops

Why people do it

  • Developers block until an external process completes. It’s simpler than redesigning the workflow.
  • They use Sleep/Delay modules or tight retry loops as an easy “wait and poll” approach.

Why it’s controversial (and risky)

  • Long-running runs consume memory/operations and can be killed if they exceed platform limits.
  • Sleep loops still count toward execution time and may increase bill or hit run-time constraints.
  • Race conditions and timeouts become common when external processes are flaky.

Better alternative

  • Use event-driven handoffs - external system pings a webhook when work is done.
  • Convert wait logic into a state machine - store the job state in Data Store and schedule a small polling scenario with an exponential backoff.
  • If you need long-term orchestration, delegate to a proper queue or workflow engine rather than using sleep inside Make.

How to implement in Make

  • Replace Sleep/Delay with two-step flows - 1) kick off work and persist a job record, 2) a scheduled or webhook-triggered scenario picks up when the job completes.
  • For scheduled checks, increase interval and implement backoff to reduce ops. Use Data Store to record attempts and timestamps.

Controversial Automation #5 - Hardcoding credentials, endpoints, and logic inside scenarios

Why people do it

  • Fast to prototype - paste an API key or URL into the module and go.
  • Easier for one-off automations maintained by a single person.

Why it’s controversial (and risky)

  • Security risk - hardcoded secrets are easy to leak and harder to rotate.
  • Poor maintainability - changing an endpoint or key requires editing every module/scenario.
  • No environment separation - same scenario used in dev and prod leads to accidental cross-environment effects.

Better alternative

  • Use Make Connections and built-in credential management for OAuth/API keys instead of literal strings.
  • Centralize configuration - use a single config scenario, Data Store, or a private configuration file (where your team stores secrets securely) and have scenarios read those at runtime.
  • Implement environment-aware flows - tag scenarios for dev/stage/prod and use different webhook endpoints or connections for each.

How to implement in Make

  • Create Connections for services and use them across modules rather than pasting credentials.
  • Store configuration values and small secrets in Data Store or a secure vault your organization approves of, and fetch them at scenario start.
  • Keep environment-specific settings out of the scenario logic; reference them with a single source of truth.

Final checklist - quick, practical rules to apply now

  • Replace tight polling with webhooks where possible. (Use webhooks first.)
  • Avoid blind bulk writes - always diff and update only what changed.
  • Split monoliths into focused scenarios; test each independently.
  • Stop using Sleep loops as orchestration - prefer event-driven or scheduled checks.
  • Remove hardcoded secrets and centralize configuration.

If you fix these five things you’ll see immediate wins: lower operation counts, fewer intermittent failures, faster debugging, and a lower blast radius when things go wrong. Build your automations so they behave like services - observable, testable, and replaceable. Do that, and your Make projects stop being tech debt and start being assets.

References and further reading

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