Observability: Next

AI-First. Agentic. Controlled.

Distill
Detect
Explain

Qotes icon

“Increasingly complex systems and ballooning telemetry volumes have made observability costs and processes an operational challenge for many organizations. Concepts like controllability aim to address these issues and necessarily evolve how we think about observability by focusing on actively governing, shaping, and optimizing telemetry rather than just collecting it.”

Kelly Fitzpatrick, Senior Analyst at RedMonk

Distill

Telemetry data is noisy. To find the needle in the haystack requires distilling telemetry down to its essential elements. Distillation – classically, the process of purifying a liquid to extract the essence from raw input – filters and clarifies telemetry through a series of agentic layers, concentrating the signal, not the noise – powering AI-first observability.

Filter out noise
De-duplicate redundant telemetry
Enrich to add context for troubleshooting
Extract essential sentiments

Detect

Boil up precise answers by setting local baselines at the edge and detecting changes and variations. Localize patterns that indicate potential problems or symptoms that can be correlated into known failures as data passes up the layers and distillation chain. Retain a history for triage and post-mortems.

Learn local baselines at the edge
Identify unusual behaviors and deviations
Correlate related telemetry patterns

Explain

AI-first observability surfaces incident summaries in plain English. Visually support and verify conclusions with related hotspots, sentiments, and log snippets that help rapidly identify and validate the root cause. Assist problem exploration with guided context, groupings, and localization of potential issues.

Boil up root cause hypotheses with context
Troubleshoot faster with timeline of what changed and where
Proactive alerting and notifications
Kubernetes context aware

ControlTheory Integrations

Any Source, Any Destination

ControlTheory integrates with all your existing telemetry sources and observability endpoints – optimizing and controlling hundreds of different logs, metrics, traces, and profiles and delivering to your favorite dashboards. Learn more about our integrations…

AI-First Observability and Control

SREs, DevOps

Find problems faster and stop digging through piles of unnecessary log data.

Root cause hypotheses with context
No Dashboard Diving
Just Answers

Engineers

Get to the root cause of issues and start fixing what’s broken – get context and validation.

Incident summaries in plain English
Timeline of what changed and where
Pinpoint app versus K8s issues

Cloud Security

Detect suspicious patterns early. If we see something, we say something.

Anomalous behavior detection
Misconfiguration & exposure detection
Reduce false positives