Agentic Monitoring

    Catch production problems beyond your alerts.

    Tokonoma profiles your services to decide what to monitor. With Agentic Monitoring enabled, it spots unusual behavior, groups related signals, and starts investigations using your team’s expertise and past findings.

    Explore findings and the evidence behind them.

    Detection

    Significant Findings

    3 saved findings
    checkout, payment-serviceGroup 1042 detectorsOct 16, 2026, 2:32 PM UTC2 signals · 0 with closure recorded
    Contributing detectors
    checkout · Errors · checkout-timeouts
    0.4% → 4.2%

    Error rate rose above its recent baseline.

    payment-service · Latency · payment-latency
    120 ms → 1.2 s

    Request latency rose during the same interval.

    Signal closure records a return toward baseline; it does not establish incident resolution.

    Investigation association
    Linked investigation run

    Checkout connection timeouts

    Recorded outcome
    Not recorded
    Started
    Oct 16, 2026, 2:33 PM UTC
    checkoutGroup 1031 detectorOct 16, 2026, 2:18 PM UTC1 signal · 0 with closure recorded
    Contributing detectors
    checkout · Errors · container-restarts
    0 → 6 restarts

    Repeated container restarts were recorded for checkout.

    Signal closure records a return toward baseline; it does not establish incident resolution.

    queue-masterGroup 1021 detectorOct 16, 2026, 1:45 PM UTC1 signal · 1 with closure recorded
    Contributing detectors
    queue-master · Errors · message-processing
    0 → 18 errors

    Rabbit message processing errors were recorded.

    Signal closure records a return toward baseline; it does not establish incident resolution.

    Only signals linked to retained detectors in this scope are shown.

    01

    Learn what to monitor

    When Agentic Monitoring is enabled, Tokonoma profiles your services and entities, discovers available telemetry, and proposes monitors. It checks those proposals against historical data to find useful signals before ongoing monitoring begins.

    02

    Investigate what needs attention

    Related signals are grouped and compared with service context, signal history, and past investigations. With TypeSafe’s Jev enabled, Tokonoma uses that context to distinguish explained recurrences from findings that warrant investigation.

    03

    See the evidence behind a finding

    Review the affected service, supporting evidence, and related occurrences together. Tokonoma also identifies gaps in telemetry and alert coverage that can leave production problems unnoticed.

    Give on-call engineers a head start.

    Try Tokonoma