◆ Elasticsearch

Monitor Elasticsearch performance metrics

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 taskDisplay the CPU utilization and JVM memory usage for all data nodes in the production cluster…+
Display the CPU utilization and JVM memory usage for all data nodes in the production cluster for the last 24 hours.
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 the daily stand-up, give me a quick overview of the production cluster's health.…+
Before the daily stand-up, give me a quick overview of the production cluster's health. Highlight any nodes with unusually high CPU or low disk space, and show me the overall indexing rate compared to yesterday.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentSearches on the 'product_catalog' index are taking over 5 seconds, impacting our e-commerce…+
Searches on the 'product_catalog' index are taking over 5 seconds, impacting our e-commerce site's conversion rates, but no single metric is spiking.
Searches on the 'product_catalog' index are taking over 5 seconds, impacting our e-commerce site's conversion rates, but no single metric is spiking. CPU, memory, and disk I/O look normal across nodes. The product manager is asking for an ETA on a fix. I'm afraid of misdiagnosing the issue. What's the most likely cause of slow search times when basic resource metrics are stable, and what specific metrics should I check next to pinpoint the bottleneck?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI often struggle to quickly identify the root cause of performance issues when multiple metrics…+
I often struggle to quickly identify the root cause of performance issues when multiple metrics are involved or none are obviously spiking.
I often struggle to quickly identify the root cause of performance issues when multiple metrics are involved or none are obviously spiking. It feels like I'm always sifting through dashboards. What habit should I change to more efficiently correlate different performance metrics and pinpoint the actual bottleneck during an incident, instead of just looking at individual graphs?
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.