◆ Elasticsearch

Build Kibana dashboards

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 taskCreate a new Kibana dashboard showing CPU and memory usage for our production servers over the…+
Create a new Kibana dashboard showing CPU and memory usage for our production servers over the last 6 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 I present this new operations dashboard to the executive team, make it more impactful.…+
Before I present this new operations dashboard to the executive team, make it more impactful. Emphasize the key performance indicators at the top, ensure the visualizations are easy to interpret for non-technical users, and highlight any potential bottlenecks or areas of concern.
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 product manager just requested a new dashboard to visualize conversion funnels, but our…+
The product manager wants a new dashboard showing conversion funnels, but our current data model in Elasticsearch doesn't easily support the exact sequence of events they need.
The product manager just requested a new dashboard to visualize conversion funnels, but our current data model doesn't easily support tracking the exact sequence of events they need. I'm afraid of over-promising or building something inaccurate. What's the best way to approach this – can I adjust the existing data, or do I need to push back on the request and suggest an alternative visualization that's feasible?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI keep building one-off Kibana dashboards for specific requests that quickly become stale or…+
I keep building one-off Kibana dashboards for specific requests that then become stale or unused, but I'm still maintaining them.
I keep building one-off Kibana dashboards for specific requests that quickly become stale or unused, yet I'm still technically maintaining them. This clutters our environment and wastes my time. What habit should I change to create more sustainable and valuable dashboards, perhaps by standardizing templates or implementing a lifecycle for reviewing and archiving unused ones?
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.