Real infrastructure. Real agents.
Real data — not demos.
Every scenario below is drawn from actual platform executions. The session IDs, log outputs, AI reasoning, and summaries are authentic. Pick your stack and see exactly what the platform did.
Two pods breaking. Zero humans paged.
healer-autonomous detected, diagnosed, and remediated two simultaneous Kubernetes failures in under 90 seconds — without any human involvement.
Two deployments in the scenario-1 namespace started failing simultaneously — one stuck in ImagePullBackOff due to a non-existent image tag, one in CrashLoopBackOff from a fatal database connection failure.
BackOff Warning event detected for bad-image-app-65bddc5c7b-nbtdk and crashloop-app-855b6b9f6b-gbjz9 in namespace scenario-1. Both classified ALERT. healer-autonomous dispatched to both sessions in parallel.
"The pod bad-image-app-65bddc5c7b-nbtdk is in ImagePullBackOff state due to a non-existent container image tag. The Deployment specifies busybox:nonexistent-tag-9999, which does not exist in Docker Hub. This is a configuration error in the Deployment spec, not an infrastructure or runtime failure."
"The pod crashloop-app-855b6b9f6b-gbjz9 container is deliberately programmed to fail. Container logs confirm: FATAL: db connection refused. Exit code: 1. Based on execution history from similar incidents, the correct remediation is to delete the failing pod to break the backoff cycle. The ReplicaSet will immediately create a replacement pod starting fresh without the backoff penalty."
"The pod crashloop-app-855b6b9f6b-gbjz9 was stuck in a crashloop due to a database connection failure (FATAL: db connection refused). I deleted the failing pod to break the exponential backoff, and the ReplicaSet has confirmed it is creating a replacement pod. The root cause is an unavailable database service that the application requires at startup; the immediate issue has been resolved but the underlying database service needs attention."
An SRE on-call would have needed to receive a PagerDuty alert → log in → run kubectl describe → run kubectl logs → decide on remediation → execute → verify. Minimum 10–15 minutes if awake and focused. At 3am, add 20 minutes.
A closed loop from
signal to resolution.
Every operation follows the same four steps — observe, diagnose, gate, act. No step is skipped, and every decision is traceable.
Observe
ActivLayer watches every connected environment continuously — pod events, node conditions, deployment history, config changes, metric signals. When something shifts, it has full context already assembled.
Diagnose
Each anomaly triggers a reasoning pass over the evidence. ActivLayer builds a causal hypothesis grounded in what it actually observes — linking events, resource states, and recent changes to form a diagnosis with an explicit confidence assessment.
Gate
Before any action, the operation passes through your policy layer. Low-risk operations within your defined thresholds proceed automatically. Anything critical pauses and routes to Slack, PagerDuty, or Jira for human sign-off.
Act
Approved operations execute over an encrypted, authenticated channel using your existing tooling. Every output is verified against expected state. If verification fails, ActivLayer re-reasons with the failure and retries or escalates.
Works with the stack you already run.
Connection is read-only by default. Write access is scoped per environment and gated by your policy rules. Every credential is encrypted at rest and in transit.
See ActivLayer in your
environment.
No slides. No sandbox. We'll walk through a live session on your actual infrastructure.
✓ Agent provisioned
● Waiting for your first incident…