What happens if one API source is slow or down?

That source retries automatically. The rest of the run continues in parallel, it does not wait on the slowest source.

How is this different from a cron job?

A cron job runs a script and hopes. This workflow retries failures automatically, validates data before it loads, and notifies your team the moment something actually breaks.

Can I change the schedule?

Yes, the trigger cadence is a single setting, nightly, hourly, or whatever fits your data.

What happens to records that fail validation?

They get flagged instead of silently dropped or silently loaded bad, so you can see exactly what did not make it through.

ETL Automation

The cron job breaks at 2am. Nobody notices until the dashboard is wrong at 9.

Unmeshed runs your nightly data pull, cleanup, and warehouse load as one governed workflow instead of a cron job and a shell script duct taped together. When something fails, it retries automatically and tells someone, instead of failing silently until a report looks off.

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What Changes

The job still needs to run every night. The question is whether anyone finds out when it does not.

This workflow is fully deterministic, no model, no judgment call, just the same pull, clean, and load sequence applied every night.

Before

A cron job and a shell script, held together by whoever set it up two years ago

A failed API call partway through means a partial, silently wrong load

Nobody finds out until someone notices the dashboard looks off

Debugging means SSHing into a box and reading through log files by hand

After

One workflow runs the pull, clean, and load as a single governed process

A failed step retries automatically before anyone has to look at it

A real failure notifies your team immediately, not the next time someone checks a report

Every run is logged and readable, no SSH required

Trigger

Runs on Schedule, Not on Someone Remembering

The workflow kicks off on a schedule, no one has to remember to run it, and no one has to notice it did not.

RULE
Fire on a fixed schedule, nightly or whatever cadence fits (#init_run)
RULE
No manual trigger required
RULE
Every run gets a run ID before anything else happens

Trigger Path

Scheduled Trigger

# init_run

Assign Run ID

no manual trigger

Extract Path

Begin Extract

fan out, in parallel

Source 1

# fetch_api_source_1

Source 2

# fetch_api_source_2

Source 3

# fetch_api_source_3

Sources Fetched

Extract

Pull from Every Source in Parallel

Data gets pulled from each API source at the same time instead of one after another, so a slow source does not hold up the rest of the run.

RULE
Fetch from multiple APIs in parallel (#fetch_api_source_1, #fetch_api_source_2, #fetch_api_source_3)
RULE
A failed fetch retries automatically before failing the run (retry-3x)
RULE
Partial failures are visible, not silent

Transform

Clean Before It Ever Touches the Warehouse

Raw data gets cleaned and normalized in this step, so what lands in the warehouse is consistent, not whatever shape each source happened to send.

RULE
Normalize fields and formats across every source (#merge_and_validate)
RULE
Flag records that fail validation instead of silently dropping them
RULE
Branch on validation result (#switch_validation): clean vs has failures

Transform Path

Normalize & Validate

# merge_and_validate

Clean

# switch_validation

Has Failures

flagged, not dropped

Load and Notify Path

Load Warehouse

# load_warehouse

Notify Team

# slack_alert_failure, optional

No Failure

nothing to report

Mark Run Complete

# mark_run_complete

Load and Notify

The Warehouse Gets It, Then Your Team Does

Clean data loads into the warehouse. If anything failed along the way, the team gets notified immediately instead of finding out from a bad dashboard the next morning.

RULE
Load into the warehouse as the final step (#load_warehouse)
RULE
Notify the team immediately on failure, optional step (#slack_alert_failure)
RULE
Mark the run complete either way (#mark_run_complete)

What This Template Is Built to Do

A failed step retries automatically before anyone has to notice. A real failure gets flagged immediately, not discovered in tomorrow's dashboard.

Nightly or custom

Scheduling cadence

Parallel fetch

Across every API source

Full run history

Every night, readable after the fact

Connects to Your Stack

Runs on the sources and warehouse you already use.

Any REST or GraphQL APIBigQueryPostgresMySQLMongoDBSlackMS TeamsGitHub

Python

JavaScript

Go+100 more

Inside the Workflow

Four pieces, one workflow.

Scheduled trigger

Runs on its own, no one has to remember. Fires on a fixed cadence, no manual kickoff required.

Parallel extraction

A slow source does not hold up the rest of the run. Every source fetches at the same time.

Automatic retries

Transient failures resolve themselves, before anyone has to look at it.

Immediate failure alerts

Your team finds out the moment something breaks, not the next morning from a bad dashboard.

Why It Holds Up in Production

Built to fail loudly instead of quietly.

Retry on extraction

A flaky API does not fail the whole run.

Validation before load

Bad records get flagged, not silently loaded.

Immediate alerts

Failures notify your team in real time.

Full run history

Every night's run is logged and readable, no log file spelunking.

Frequently asked questions

Still have questions? Talk to us.

Stop finding out your pipeline broke from a bad dashboard.

Connect your API sources, your warehouse, and Slack, and this runs every night without anyone babysitting a cron job.

Try Free Template Here

Free tier, no credit card required