Intelligent Inspection for Operational Risk

What Intelligent Inspection helps you solve

Apply known checks consistently before a weak signal becomes an incident

Capacity pressure, changing error patterns, latency shifts, workload instability, and cost anomalies often appear before a major incident. Repeatable inspection rules help teams look for those signals on a defined schedule and preserve the evidence for review.

01Documented detection typesApply current host, log, application, RUM, Kubernetes, and cloud-billing detection methods.
02Operational evidencePreserve scope, time range, affected dimensions, and the observed change.
03Custom inspection logicUse approved DataFlux Func workflows where team-specific checks are required.

Standardise recurring checks for supported operational data

Configure the documented detection type, scope, filters, notification recipients, and alert strategy. Teams can apply repeatable checks to supported host, log, application, RUM, Kubernetes, and cloud-billing signals instead of relying on an operator to remember each condition.

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Standardise recurring checks for supported operational data

Keep the observed change and affected dimensions available for review

Inspection events should explain the time range, detection dimension, expected range or comparison, and the data that appeared abnormal. This evidence helps an engineer decide whether the finding is actionable without treating an algorithmic result as a guaranteed root cause.

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Extend inspections carefully when a business rule is specific to your team

Use documented DataFlux Func and programmable-detection paths for approved custom checks such as data delay, transaction gaps, interface quality, or operational reports. Validate inputs, permissions, execution frequency, and failure handling before a custom inspection becomes an automated dependency.

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Extend inspections carefully when a business rule is specific to your team

Frequently asked questions

What is Intelligent Inspection?

Intelligent Inspection runs configured detection or inspection logic against supported observability data to surface unusual changes, risks, or recurring conditions for human review.

How is an inspection different from a threshold monitor?

A threshold monitor evaluates an explicit condition. Intelligent detection can compare time-series behaviour with historical patterns or expected ranges for supported rule types. Neither should be described as guaranteed root-cause analysis.

Which data types have documented intelligent detection?

Current Guance documentation lists intelligent detection for hosts, logs, applications, RUM, Kubernetes, and cloud bills. Available metrics, schedules, storage effects, and billing differ by rule type.

Can teams create custom inspections?

Guance provides programmable and DataFlux Func paths for custom logic. Scope the claim to documented APIs, data access, scheduling, credentials, and the team workflow used to review results.

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Resources and further reading

Choose the next step from product documentation, related solutions, and technical guidance.

Turn recurring risk checks into repeatable inspections

Apply known checks consistently before a weak signal becomes an incident

What is Intelligent Inspection?

How is an inspection different from a threshold monitor?

Which data types have documented intelligent detection?

Can teams create custom inspections?

Resources and further reading

Related reading