◆ Apache Airflow

Troubleshoot DAGs stuck in 'running' state

This is real work, not a feature someone invented — it comes from real job ads and real questions people asked. Below are four ready AI prompts: get it done, make it easy for the next person to say yes to, work out the right move when you are stuck, and stop it coming back.

4prompts

The same task, four prompts

today's deadline · the next reviewer · the stuck moment · the pattern
AExecute — do the immediate taskCheck the logs for the 'daily_etl_pipeline' DAG run from yesterday morning, specifically…+
Check the logs for the 'daily_etl_pipeline' DAG run from yesterday morning, specifically looking for any tasks that are still marked as 'running' but haven't updated in the last hour. If you find any, try clearing their state to allow a re-run.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
BImprove — make it easier to acceptBefore I dive into the logs for these 'stuck' DAGs, can you give me a quick overview of the…+
Before I dive into the logs for these 'stuck' DAGs, can you give me a quick overview of the most common reasons our DAGs get stuck in a running state? I want to make sure I'm not chasing a red herring and can focus on the likely culprits first.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentThe 'customer_segmentation_refresh' DAG has been 'running' for three hours, but the data in the…+
The 'customer_segmentation_refresh' DAG has been 'running' for three hours, but the data hasn't updated, and I'm getting pings from the marketing team.
The 'customer_segmentation_refresh' DAG has been 'running' for three hours, but the data in the dashboard hasn't updated, and I'm getting pings from the marketing team, who need those segments for their campaign launch tomorrow. I'm afraid of clearing it and losing progress or making things worse, but I also can't just let it hang. What's the most likely reason for this, and what's the safest first step to get it moving or at least diagnose it without breaking anything?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternOur DAGs frequently get stuck in 'running' or 'queued' states, causing us to miss SLAs for…+
Our DAGs frequently get stuck in 'running' or 'queued' states, leading to missed SLAs and frantic troubleshooting.
Our DAGs frequently get stuck in 'running' or 'queued' states, causing us to miss SLAs for reporting and requiring constant manual intervention. It feels like we're always reacting to a problem rather than preventing it. What habit should I change in how we design or monitor our DAGs to reduce these recurring stuck states and improve overall pipeline reliability?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Questions people actually ask

honest answers, no sign-up

Every task here was seen in the real world. Someone doing the job named it, a real job ad asked for it, or a lot of people asked about it online.

If nothing real showed a task, it is not on the page. That is the whole rule.

They are the same job approached four ways, because what you need depends on where you are.

Get it done today. Make it easy for the next person to say yes to. Work out the right move when you are stuck. Learn the pattern so the job stops coming back.

For most of these jobs it can carry the heavy thinking - draft it, sort it, check it, rehearse it with you.

It cannot sit in your chair, take the blame when a number is wrong, or notice what nobody wrote down. Let it do the first 80%. Keep the last 20% that is truly yours.

No. Copy any prompt and paste it into the AI you already use. No account, no score, no wall in the way.

Any of them. The prompts describe the work rather than naming a product, so they are not tied to one assistant.

That is also why they keep working when you switch.

Change it freely. Every prompt is a starting line, not a rule.

Put in your real numbers, your real names and your real deadline. The more you make it yours, the better the answer comes back.

The tasks come from real job ads, published job data and the questions people ask in public forums.

The steps come from Apache Airflow's own documentation, with practitioner sources for the traps the manual does not mention.

Push once. Ask it to sharpen the weakest part and to say what it assumed.

Most wrong answers come from a missing detail rather than a bad prompt - tell it the thing it could not know.