VictorOps (now Splunk On-Call)
About VictorOps (now Splunk On-Call)
VictorOps sends metadata-rich notifications to devices and allows responders to act, resolve, reroute or snooze alerts from native mobile apps. The product automates time-sensitive actions such as escalations, war rooms and post incident reviews. It automates on-call scheduling, including rotations, overrides and escalation policies.
Used for
- Automating escalations, war rooms and post incident reviews
- Identifying similar incidents using historical insights and audit trails
- Selecting responders with relevant expertise
- Accessing reports on incident frequency and MTTA/MTTR
From VictorOps (now Splunk On-Call)'s own website, read 2026-10-23. How we build listings.
How to evaluate AIOps & Incident Management
This is how the CIOPages Research Team evaluates this category. It is not an assessment of VictorOps (now Splunk On-Call). The category covers two kinds of product, so both frameworks are here. Most buyers need one of them.
Incident Management & On-Call
25%
Alerting & On-Call Reliability
Does the page actually arrive? Multi-channel delivery (push, SMS, phone, email) with carrier redundancy, escalation if unacknowledged, on-call schedule and rotation math, override and coverage-gap handling, and the resilience of the notification pipeline itself — this is the one job that cannot fail
20%
Alert Noise Reduction & Correlation
Event grouping and de-duplication, intelligent correlation across signals, suppression and maintenance windows, dynamic routing by service ownership, and whether the platform measurably lowers pages-per-incident rather than just forwarding every alert your monitoring emits
20%
Incident Response & Comms Orchestration
Chat-native (Slack/Teams) war-room automation, roles and severity workflows, automatic timeline capture, stakeholder and status-page updates, runbook/automation actions, and how little manual coordination an incident commander has to do under pressure
15%
Post-Incident Learning & Analytics
Blameless retro/postmortem templates, auto-drafted timelines and summaries, action-item tracking to closure, MTTA/MTTR and on-call-load reporting, recurring-incident and follow-up trend analysis — the loop that actually reduces recurrence
10%
Integration & Ecosystem Fit
Depth of connectors to your monitoring/observability, ITSM, CI/CD, and chat; bidirectional ticket sync; webhook and API coverage for automation; and how naturally it slots into the tools your responders already live in rather than demanding a new home base
10%
AI / AI-SRE Capability
Autonomous triage and investigation agents, AI root-cause hypotheses and likely-culprit-commit detection, auto-generated summaries and retros, and scheduling/override agents — weighing genuine, evaluable assistance against demo-ware, and checking what data the AI is trained on and where it runs
IT Operations Management (ITOM)
25%
Event Correlation & Noise Reduction
Deduplication and flap suppression, cross-source correlation (topology-based, time-based, text/ML-based), how an alert storm collapses into a single situation, transparency of the correlation logic (open-box vs. black-box), and the realistic false-positive and missed-incident rate on YOUR event volume
20%
Discovery, Topology & CMDB
Agent and agentless discovery breadth (cloud, on-prem, network, containers, mainframe), automated service mapping and dependency graphs, how the topology is kept current as infrastructure churns, and whether correlation depends on a CMDB you must maintain or a graph the platform builds itself
20%
AIOps Depth: Root Cause & Remediation
Probable-root-cause identification and how it is explained, causal vs. purely statistical inference, anomaly and early-warning detection, closed-loop and agentic remediation, and how models behave on noisy, incomplete production data rather than curated demo streams
15%
Integration & Tool Coverage
Breadth of inbound monitoring/observability connectors, bidirectional ITSM and incident-tool integration (ServiceNow, Jira, PagerDuty), ChatOps/collaboration hooks, open APIs and webhooks, and whether the platform plays as an overlay or expects to own the stack
10%
Scale & Performance on Real Telemetry
Sustained events-per-second ingest, query and correlation latency at peak, multi-tenant and multi-region operation, data retention and cost at your volume, and graceful behavior during the event surge of a major incident — exactly when the platform matters most
10%
Operations, Workflow & Automation
Operator and NOC ergonomics, runbook and workflow automation, on-call and escalation routing, service-health and SLA reporting for business owners, role-based access, and audit logging of automated actions
Other AIOps & Incident Management Vendors
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Quick Facts
www.splunk.com/en_us/products/on-call.htmlCategoryObservability & Monitoring
SubcategoryAIOps & Incident Management
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