◆ Elasticsearch

Perform common Elasticsearch maintenance tasks

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 taskI need to free up disk space on the Elasticsearch cluster. Find all indices older than 90 days…+
I need to free up disk space on the Elasticsearch cluster. Find all indices older than 90 days that start with 'logstash-' and delete them. Confirm the deletion before proceeding.
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 deleting old logstash indices, let's make sure we're not losing critical data. Can you…+
Before deleting old logstash indices, let's make sure we're not losing critical data. Can you first identify the top 5 largest indices that are older than 90 days and also list their creation dates, so I can double-check with the compliance team?
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 cluster disk usage is still at 95% after deleting the usual old logstash indices. I'm…+
The disk space on the Elasticsearch cluster is critically low, but deleting old indices hasn't freed up enough space.
The cluster disk usage is still at 95% after deleting the usual old logstash indices. I'm afraid to delete anything else without knowing the impact, especially with the CEO dashboard relying on this data. I can't tell if there's a runaway index or just an unexpected data spike. What's the most likely cause of this persistent high usage, and what's the safest next step to identify and resolve it without disrupting critical services?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI'm constantly reacting to critical disk space alerts on our Elasticsearch cluster, often…+
I keep getting pulled into urgent disk space issues on the Elasticsearch cluster every few weeks.
I'm constantly reacting to critical disk space alerts on our Elasticsearch cluster, often leading to rushed deletions and late-night fixes. This is eating into my development time and causing stress. What habit should I change to proactively manage cluster capacity and prevent these recurring emergencies, instead of just responding to them?
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.