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Cardinal

Cardinal

Cardinal provides an agent-first observability backend keeping telemetry in customers' own cloud storage.

San Francisco, CA, US🇺🇸
Founded
2023
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Library

Cardinal - Library

cardinalhq.io·Crawled Oct 9, 2026·

Topics

Publication type

Content origin
Row density

Product

6 pages
  1. Architecture/architecture

    Cardinal UI, mcp-gateway, and Lakerunner all run inside your cloud as one Kubernetes deployment against your S3 bucket, addressed by your IAM. Coding agents…

  2. Continuously Improving Agent UX/agent-ux

    Cardinal's Agent Outcomes surfaces thrashing agent sessions. We reconstruct the workflow, ship a UX fix, and promote it into both the human UI and the MCP…

  3. Enterprise-Grade BYOC/enterprise-byoc

    Cardinal runs in your account against your own object storage and under your IAM. We operate it with you and stay reachable over Slack, email, or a pager.

  4. Kubernetes Monitoring/use-cases/kubernetes

    Cardinal pins kube events onto every chart, unfolds a pod's full topology on a click, and gives agents a governed, read-only view of the cluster.

Blog

6 pages
  1. 200 Million Metric Rows at 2.11 Bytes Each/blog/one-day-of-metrics

    We pulled every metric segment our own production monitoring wrote for a single day and counted. 91,713 time series, 269 million stored rows across five…

  2. How OpenTelemetry and one UI trick changed the way we debug Kubernetes/blog/one-click-from-spike-to-pod

    The chart already knows the cluster, namespace, deployment, and pod. So why are we copying any of that into another tool? A small UI trick — an Infra Map link…

  3. How We Made Object Storage Faster Than ClickHouse for Log Search/blog/object-storage-faster-than-clickhouse-for-log-search

    We ingested ClickHouse's billion-row TextBench corpus through Cardinal's production pipeline and ran the nine queries straight off S3. Cardinal is faster on…

  4. Learn from Experts/blog

    Explore in-depth articles, engineering insights, and practical tutorials designed to level up your agentic workflow skills. Click now to read the latest posts!

Careers & Hiring

1 page
  1. Careers/about/careers

    Help build the observability infrastructure the next generation of AI agents deserve. Founding-engineer and GTM roles at Cardinal: ex-Netflix engineers…

Pricing

1 page
  1. Pricing/pricing

    Transparent pricing for Cardinal. Same product either way — pick where it runs and see the price on the page. No sales call required.

Comparison

1 page
  1. Cardinal vs Datadog, New Relic, Splunk, Grafana Cloud/comparisons

    Side-by-side comparison of Cardinal with the major observability vendors: data ownership, retention, sampling, cardinality, agent runtime, and pricing shape.

About

1 page
  1. About Cardinal/about/company

    Cardinal is an observability data lake and agent runtime, built by the engineers who ran Netflix's observability platform. Full-fidelity telemetry, entirely…

Contact

1 page
  1. Contact/contact

    Reach the Cardinal team for sales demos, support, partnerships, or general questions about the observability data lake and agent runtime.

Homepage

1 page
  1. Homepage/

    A full-fidelity observability data lake built for machine-scale investigation — running entirely in your own cloud.

Privacy

1 page
  1. Transparent & Secure/privacy

    See how we keep your information private with strict security practices while powering advanced AI workflows. Learn more in our privacy policy now!

Terms & Conditions

1 page
  1. Terms & Conditions/terms

    Learn the core policies that guide access to Cardinal’s tools and platform to ensure safe, compliant usage. Get the details. Review our terms now!

Coverage

10 items
  1. cardinalhqgithub.com/cardinalhq

    GitHubRepository owner

  2. How We Made Object Storage Faster Than ClickHouse for Log Searchcardinalhq.io/blog/object-storage-faster-than-clickhouse-for-log-search

    Cardinal ingests ClickHouse’s billion-row TextBench corpus through its production pipeline and runs nine queries directly from S3. The headline presents object storage as faster than ClickHouse for log search, but the provided excerpt ends before giving benchmark results or further details.

    Sep 2026 · cardinalhq.ioNews article

  3. How OpenTelemetry and one UI trick changed the way we debug Kubernetescardinalhq.io/blog/one-click-from-spike-to-pod

    CardinalHQ describes using an Infra Map link to move from a chart to Kubernetes infrastructure context. The chart already identifies the cluster, namespace, deployment, and pod, avoiding the need to copy those details into another tool.

    Sep 2026 · cardinalhq.ioNews article

  4. 200 Million Metric Rows at 2.11 Bytes Eachcardinalhq.io/blog/one-day-of-metrics

    CardinalHQ counts the metric segments written by its production monitoring over a single day, finding 91,713 time series and 269 million stored rows.

    Sep 2026 · cardinalhq.ioNews article