Multi-dimensional filter engine for observability dashboards that lets NOC and SRE teams build hierarchical metric views across instance groups, regions, and service tiers with a single saved filter c
An engineer manually cycling through flat filters during an incident is a safety problem, not just an annoyance, and no incumbent has fixed the multi-level pivot UX
Built for NOC engineers and SREs managing complex infrastructure who need flexible real-time metric filtering across categorical hierarchies..
Monitoring tools optimize for data ingestion and alerting, leaving dashboard navigation as an afterthought, so a composable filter layer that works as a plugin across Grafana, Datadog, and others wins by portability
“Pulse is used primarily by our NOC to review current load as well as historical loads. Real-time high-resolution metric monitoring. Data can be collected and vi…”
The receipts — real demand
“Pulse is used primarily by our NOC to review current load as well as historical loads. Real-time high-resolution metric monitoring. Data can be collected and viewed at 1-second resolution. ... Pulse lacks the ability to have multi-level filters for viewing data. You can only build a dashboard containing particular metrics then you can change what instances are displayed on those charts. It would be nice to be able to…”
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demand score 6.4 — the receipts are below
Why this is a gap
Surfaced from a high-intensity complaint with clear willingness to pay and a specific, reachable audience.
The market
NOC engineers and SREs managing high-cardinality infrastructure metrics who need flexible real-time filtering across metric hierarchies. No search volume, but pain signal shows active monitoring workload at 1-second resolution with complex categorical data.
Competition & the opening
Grafana, Datadog, New Relic, Prometheus dashboards offer metric filtering. The gap: none provide hierarchical categorical filtering (e.g., filter by region > service > host > metric_type) as a first-class UI primitive; users build nested queries or accept flat search.
What's hard to build
Hierarchical filtering on high-cardinality data (millions of metric combinations) requires efficient indexing and query planning. Real-time 1-second resolution means sub-100ms query latency is non-negotiable. Streaming architecture must handle metric explosion without cardinality blowup in the index.
Why now
NOC teams managing large-scale infrastructure lack intuitive multi-level filtering in existing monitoring tools; observability platforms leave this UX gap open.
How you'd monetize
$499-2000/mo B2B SaaS per team