◆ Elasticsearch

Clean up Elasticsearch indexes

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 taskClean up the old log data in the 'app-logs-prod' index, deleting anything older than 90 days to…+
Clean up the old log data in the 'app-logs-prod' index, deleting anything older than 90 days to free up disk space by Friday morning.
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 run the index cleanup on 'app-logs-prod', can you suggest a more efficient way to…+
Before I run the index cleanup on 'app-logs-prod', can you suggest a more efficient way to manage log retention for our production environment? The current manual process feels brittle and prone to missing older data, and I'm worried about hitting disk limits again.
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 'app-logs-prod' index just hit 95% disk utilization, and I'm getting alerts. I need to free…+
The 'app-logs-prod' index just hit 95% disk utilization, and I'm getting alerts.
The 'app-logs-prod' index just hit 95% disk utilization, and I'm getting alerts. I need to free up space immediately, but I'm not sure if deleting the oldest 90 days will be enough or if I'll delete data that the compliance team needs for an audit. What's the fastest, safest way to get us below 80% without risking crucial data?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternWe keep running into disk space issues with our log indexes every few months, leading to…+
We keep running into disk space issues with our log indexes every few months.
We keep running into disk space issues with our log indexes every few months, leading to frantic cleanup efforts. This eats up engineering time and creates stress. What habit should I change to proactively manage log retention and prevent these recurring emergencies?
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 Elasticsearch'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.