Kibana is an excellent way to search and visualise data in Elasticsearch. If you want dashboards plus autonomous resolution, not a visualisation layer tied to one data store, here is an honest comparison with Ops Singularity.
Kibana is the visualisation and exploration layer of the Elastic Stack: rich dashboards, powerful search over Elasticsearch, and good log and APM views. For exploring and presenting data that already lives in Elasticsearch, it is very good. Teams look for an alternative when they want more than a viewer. Kibana is tied to Elasticsearch as its data store, and it shows you data rather than acting on it, so an incident visible in a Kibana dashboard still needs a human to investigate and fix. When the goal is resolution and freedom from a single backend, the evaluation moves beyond visualisation.
It is worth being precise about what Kibana is and is not. Kibana is a window onto Elasticsearch, not an operations platform. It does not collect data, it does not decide anything, and it cannot act on what it displays. That is entirely by design and perfectly fine when your job is to explore and present data. The mismatch appears only when teams expect their visualisation layer to also reduce toil or resolve incidents, which is a different category of tool. Recognising that distinction is what makes the choice clear.
| Dimension | Kibana | Ops Singularity |
|---|---|---|
| Primary focus | Visualisation and search over Elasticsearch | Unified observability and autonomous, governed resolution |
| Data store | Tied to Elasticsearch | OpenTelemetry-native, open petabyte-scale storage |
| What it does | Dashboards and exploration; a human acts | Detects, investigates and resolves through governed Action Tickets |
| Breadth | Views of the data in Elasticsearch | Ten operational domains, cross-platform correlation |
| From dashboard to fix | You read the dashboard and fix manually | ProcBot executes the fix, Sherlock validates it |
| Deployment | With the Elastic Stack | SaaS, on-premises or fully air-gapped |
Kibana is the better choice if your data already lives in Elasticsearch and your need is powerful search and dashboards over it, with rich exploration for engineers who want to slice the data themselves.
Sentinel AI runs the Observe, Investigate, Act, Optimize loop and executes the fix through ProcBot, so many incidents never need a human at all.
Actions run as reversible, audited Action Tickets with approval gates, so autonomy is something an auditor or a change board can accept.
One intelligence layer across telemetry, service, infrastructure, security, data, cost, process, DevSecOps and the managed estate, deployable on-premises or fully air-gapped.
Yes, its TelemetryOps includes dashboards and exploration, but it is not tied to a single data store and it adds autonomous resolution on top, so dashboards lead to action.
Yes. Teams keep Kibana for Elasticsearch exploration and add Ops Singularity, over OpenTelemetry, to correlate across sources and resolve incidents autonomously.
Bring a real incident. We will show you Sentinel investigate, act and verify end to end, with every action reversible and audited.