◆ Apache Cassandra

Optimize Cassandra database performance

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
See the prompt↓All Apache Cassandra tasks

The same task, four prompts

today's deadline · the next reviewer · the stuck moment · the pattern
AExecute — do the immediate taskIncrease the read and write throughput on the customer activity log table by 15% before…+
Increase the read and write throughput on the customer activity log table by 15% before Friday's peak traffic. We need to handle the new marketing campaign's load without a noticeable slowdown for users.
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 we push the new customer activity log schema to production, review the current indexing…+
Before we push the new customer activity log schema to production, review the current indexing strategy. Identify any queries that might cause hot spots or full table scans with the increased data volume and suggest more efficient compound primary keys.
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 inventory service queries are spiking in latency, and I can't tell if it's the new data…+
We just saw a sudden spike in latency on the inventory service queries after deploying the new data model.
The inventory service queries are spiking in latency, and I can't tell if it's the new data model's partitioning or a sudden increase in requests from the front end. The CEO is already asking why the product pages are slow. What's the fastest way to diagnose the root cause and get us back to acceptable performance?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternEvery time we roll out a major feature, I spend the next week firefighting performance…+
I keep ending up in reactive performance firefighting mode after every major release.
Every time we roll out a major feature, I spend the next week firefighting performance regressions. I'm losing credibility with the product team because I can't predict these issues. What habit should I change to proactively catch these performance bottlenecks before they hit production?
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 Cassandra'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.