Prompt
query recent and historical metrics fast
Latest observation
Can you clarify what you want to query?
If you mean recent and historical metrics fast, I can help you:
- write a SQL query for time-series metrics
- design a fast aggregation query pattern
- compare recent window vs historical baseline
- optimize for Postgres / MySQL / BigQuery / ClickHouse / Prometheus / Elasticsearch
Please send:
- database/system
- table/schema
- metric name
- time range for “recent” and “historical”
- any grouping you want (by host, service, region, etc.)
Example:
SELECT
date_trunc('hour', ts) AS hour,
avg(value) AS avg_value
FROM metrics
WHERE ts >= now() - interval '7 days'
GROUP BY 1
ORDER BY 1;
If you want, I can also give you a fast template for querying recent + historical metrics right away.
Observation history
How did Obsurfable measure this prompt?
Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.
Which AI systems does Obsurfable collect answers from?
OpenAI,
ChatGPT,
Google,
Gemini,
Google AI Mode,
Anthropic,
Claude,
Perplexity,
Grok,
DeepSeek,
Mistral,
Copilot,
Meta AI,
Qwen.
How can brands improve their AEO?
Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.
Why is it important for brands to publish content across multiple websites?
Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.
Want this interpreted for your brand?
Explorer is the free public corpus. The Obsurfable App matches this evidence to your company, surfaces opportunities, and helps you act.