Ops Pillar · Service Ops

End-to-end service observability, unified.

Service Ops brings logs, traces, alerts and APM together in one intelligence layer, so every service, dependency and request is understood from a single place, and every signal is ready for Sentinel AI to act on.

Request a Demo All Ops Pillars

Service health
Dependency topology
Distributed tracing
Log analytics
ML-powered insights

Service healthOperations console

User satisfactionHealthyStable

Avg response timeLowImproving

Requests / minSteadyLive

Success rateHighHealthy

ML-powered insights

Latency anomaly detected

A microservice is running well above its service average latency.

Traffic shift

Traffic on a service moved sharply versus the start of the window.

Optimization opportunity

High-traffic services above average latency are candidates to tune.

What is Service Ops

One place to see every service, from request to database.

Most teams stitch service health together from separate tools for metrics, tracing, logging and alerting. Service Ops integrates logs, traces, alerts and APM for all services into a single, correlated view. See how each service is performing, how services depend on one another, and where a request slows down, then hand a clean, correlated picture to Sentinel AI to investigate and resolve.

Service health & performance

Real-time health across every service.

The operations console tracks the signals that matter, user satisfaction, response time, throughput and success rate, in real time, and surfaces degraded services the moment they drift. ML-powered insights flag anomalies, traffic shifts and optimization opportunities with a clear impact level so teams know where to look first.

Live performance trends across all services
Automatic detection of degraded services
Anomaly, traffic and optimization insights, ranked by impact

Operations consoleLast 30 mins

User satisfactionHealthyStable

Avg response timeLowImproving

Requests / minSteadyLive

Success rateHighHealthy

Dependency topology

See how services connect, and where it breaks.

An interactive topology maps every service and the calls between them, colour-coded by health. Follow traffic across the graph, spot the service dragging a whole path down, and understand blast radius before you act, not after.

Live service dependency map with health status
Traffic flow and path latency across services
Instant blast-radius view for any incident

Service topologyLive

HealthyWarningCriticalExternal

gatewayapischedulerauthdbcache

Distributed tracing & logs

Trace a request end to end, then jump to the logs.

Follow any request across services with span-level tracing, filter by endpoint, status, customer or user, and pinpoint exactly where time is spent. From any trace, pivot straight into the correlated logs, with advanced search, error-rate tracking and live tail, so root cause is one click away.

Span-level waterfall with error and duration breakdown
Filter traces by customer, user, endpoint or status
One-click trace-to-log correlation with live search

Trace explorer6 spans · 0 err

Alerts & service catalog

Every service, endpoint and alert in one catalog.

Drill into any service for its instances, endpoints, slow queries, traces and logs in one place. A severity-based alert timeline keeps incidents, notifications and anomalies together, filterable by entity, severity and status, so nothing important gets lost in the noise.

Per-service instances, endpoints and slow queries
Severity-based alert timeline across all signals
Playbooks, synopsis and an AI assistant built in

Alert timelineAll severities

05Real-world use cases

Built for the incidents you already have

These are not demo scenarios. Each one is a situation an operations team meets weekly, and each ends the same way: the investigation starts at the evidence, not a login screen, and finishes with a decision someone can defend.

Latency regression after a release

Correlates the anomaly against deployment and topology, then isolates the offending span.

Rollback decided in minutes

A customer reports one slow journey

Filter traces by customer or endpoint, then pivot into the matching logs.

Answered with evidence

Alerts nobody acts on

A severity-based timeline groups incidents and anomalies by entity.

Signal separated from noise

Change risk before the window opens

Blast-radius view of any service and everything downstream.

Fewer self-inflicted outages

06Business perspective

What it is worth outside the NOC

Unified service observability is an engineering capability with a business ledger. The entries that matter are customer impact, licence spend, key-person risk and auditability, and Service Ops moves all four.

Shorter customer impact

Degradation is scoped and fixed before it becomes an outage.

Lower tool spend

One layer over existing APM, log and alerting licences.

Less key-person risk

The dependency map replaces knowledge held by two people.

Audit-ready by default

Every investigation and remediation captured with citations.

07The numbers

The cost of the hunt, summed honestly

Worked example for a several-hundred-engineer estate. Every figure shows the sum it came from; during a pilot we substitute your own inputs.

Engineer hours on investigation

5,760 hrs

40 incidents/mo × 4 hrs × 3 engineers × 12

That is standing headcount

3.2 FTE

5,760 hrs / 1,800 productive hrs per FTE-year

Annual cost of the hunt

$490k

5,760 hrs × $85/hr fully loaded

Released if diagnosis halves

$245k

Modelled at 50% reduction, not a measured result

Service Ops sees. Sentinel acts.

Service Ops does more than show you what is happening. Every correlated signal, health, topology, traces, logs and alerts, feeds Sentinel AI, the intelligence component at the core of Opstral. Sentinel runs the OIAO loop over your service data and resolves issues through governed, reversible Action Tickets.

Sherlock closes the root-cause loop and ProcBot executes the fix, every step explained with citations and fully audited.

Observe
Service Ops normalizes and correlates logs, traces, alerts and APM across every service.
Investigate
Sentinel AI finds root cause across the dependency graph and picks the right procedure.
Act
ProcBot executes the approved MOP through a reversible, audited Action Ticket.
Optimize
Sherlock validates the fix and feeds the learning back to sharpen the next response.

See Service Ops on your own services.

Book a walkthrough and see unified service observability, dependency topology and autonomous resolution on a stack that looks like yours.

Request a Demo Meet Sentinel AI

Ops Pillar · Service Ops

End-to-end service observability, unified.

Request a Demo All Ops Pillars

Service health
Dependency topology
Distributed tracing
Log analytics
ML-powered insights

Service healthOperations console

User satisfactionHealthyStable

Avg response timeLowImproving

Requests / minSteadyLive

Success rateHighHealthy

ML-powered insights

Latency anomaly detected

A microservice is running well above its service average latency.

Traffic shift

Traffic on a service moved sharply versus the start of the window.

Optimization opportunity

High-traffic services above average latency are candidates to tune.

What is Service Ops

One place to see every service, from request to database.

Service health & performance

Real-time health across every service.

Live performance trends across all services
Automatic detection of degraded services
Anomaly, traffic and optimization insights, ranked by impact

Operations consoleLast 30 mins

User satisfactionHealthyStable

Avg response timeLowImproving

Requests / minSteadyLive

Success rateHighHealthy

Dependency topology

See how services connect, and where it breaks.

Live service dependency map with health status
Traffic flow and path latency across services
Instant blast-radius view for any incident

Service topologyLive

HealthyWarningCriticalExternal

gatewayapischedulerauthdbcache

Distributed tracing & logs

Trace a request end to end, then jump to the logs.

Span-level waterfall with error and duration breakdown
Filter traces by customer, user, endpoint or status
One-click trace-to-log correlation with live search

Trace explorer6 spans · 0 err

Alerts & service catalog

Every service, endpoint and alert in one catalog.

Per-service instances, endpoints and slow queries
Severity-based alert timeline across all signals
Playbooks, synopsis and an AI assistant built in

Alert timelineAll severities

05Real-world use cases

Built for the incidents you already have

Latency regression after a release

Correlates the anomaly against deployment and topology, then isolates the offending span.

Rollback decided in minutes

A customer reports one slow journey

Filter traces by customer or endpoint, then pivot into the matching logs.

Answered with evidence

Alerts nobody acts on

A severity-based timeline groups incidents and anomalies by entity.

Signal separated from noise

Change risk before the window opens

Blast-radius view of any service and everything downstream.

Fewer self-inflicted outages

06Business perspective

What it is worth outside the NOC

Shorter customer impact

Degradation is scoped and fixed before it becomes an outage.

Lower tool spend

One layer over existing APM, log and alerting licences.

Less key-person risk

The dependency map replaces knowledge held by two people.

Audit-ready by default

Every investigation and remediation captured with citations.

07The numbers

The cost of the hunt, summed honestly

Worked example for a several-hundred-engineer estate. Every figure shows the sum it came from; during a pilot we substitute your own inputs.

Engineer hours on investigation

5,760 hrs

40 incidents/mo × 4 hrs × 3 engineers × 12

That is standing headcount

3.2 FTE

5,760 hrs / 1,800 productive hrs per FTE-year

Annual cost of the hunt

$490k

5,760 hrs × $85/hr fully loaded

Released if diagnosis halves

$245k

Modelled at 50% reduction, not a measured result

Service Ops sees. Sentinel acts.

Sherlock closes the root-cause loop and ProcBot executes the fix, every step explained with citations and fully audited.

Observe
Service Ops normalizes and correlates logs, traces, alerts and APM across every service.
Investigate
Sentinel AI finds root cause across the dependency graph and picks the right procedure.
Act
ProcBot executes the approved MOP through a reversible, audited Action Ticket.
Optimize
Sherlock validates the fix and feeds the learning back to sharpen the next response.

See Service Ops on your own services.

Book a walkthrough and see unified service observability, dependency topology and autonomous resolution on a stack that looks like yours.

Request a Demo Meet Sentinel AI