REMS is an AI-powered Observability platform that sits on your existing open-source stack — turning raw telemetry into autonomous root cause diagnosis, structured incident response, and proactive reliability management.
Every major incident begins the same way: ten engineers, six dashboards, forty-five minutes — and the answer was in the data the entire time.— The pattern across 200+ enterprise SRE teams we've worked with
Your team juggles 5+ disconnected dashboards — Grafana, Loki, Kubernetes, APM — with no shared context. Every incident starts with a scavenger hunt across tabs.
5+ disconnected dashboardsThousands of alerts fire daily. 80% are false positives. Engineers stop trusting signals — which means real incidents get missed, or found far too late.
80% of alerts are noiseWithin 10 minutes of an alert, 5–10 engineers are pulled off productive work. War room convenes. Root cause? Still unknown at minute 25. Business impact compounds.
~45 min average resolutionThe problem isn't that you lack data. You have metrics, logs, and traces. The problem is that the first 15 minutes of every incident are repetitive investigation work that should be automated — but isn't.
The economics and the technology have both shifted. Continuing with the old model isn't a neutral choice — it's an expensive one.
Telemetry volumes are growing faster than budgets. For many enterprises, observability tooling now rivals cloud infrastructure spend — and SaaS per-GB pricing makes it worse at scale.
Senior SREs are among the hardest engineering roles to hire. Yet most of their time is consumed by manual incident triage — repetitive work that burns talent and breeds attrition.
AI can now reliably correlate metrics, logs, and traces across distributed systems in seconds. The gap between human-speed and machine-speed diagnosis is no longer acceptable.
Every observability tool shows you data. REMS is the first platform to combine observability, AI intelligence,
and an execution system — from signal to resolution without manual investigation.
REMS works because it operates in three integrated layers. Each layer is independently powerful — together, they're what enables incident resolution in under 60 seconds.
This isn't just AI bolted onto a monitoring tool. The architecture is fundamentally different: open-source at the foundation, AI intelligence in the middle, and a full execution system on top.
When the three layers work together, this is the measurable result.
Incident response workflows, SLO & error budget management, automated remediation, and runbook execution.
Signal correlation across all systems, autonomous root cause analysis, context and pattern recognition in plain English.
Metrics, logs, and traces via Prometheus, Loki, and Tempo. Unified telemetry. Real-time visibility. 100% your data.
When an alert fires, OLLY traces the signal across your entire stack, eliminates red herrings, and surfaces the root cause with concrete remediation steps — in under 60 seconds. Not anomaly detection. Actual diagnosis.
<60 second RCASLOs are first-class citizens in REMS. Monitor burn rates in real time, get early warnings before you exhaust your error budget, and deploy with deployment gates tied directly to your SLO health.
Real-time burn-rate monitoringA single pane of glass for metrics, logs, traces, and SLOs — correlated in context. Service Explorer maps your entire service topology so you see exactly where problems originate, not just where they surface.
Single pane of glassAI-powered incident war rooms replace ad hoc Slack chaos. Every incident triggers a structured workflow with auto-generated RCA, severity classification, role assignments, and communication templates.
Auto-generated RCAPrometheus metrics, Loki logs, and Tempo traces flow in real time. 100% telemetry — no sampling, no blind spots.
OLLY correlates signals across your entire stack simultaneously — eliminating noise and connecting dots at machine speed.
The exact source is pinpointed and expressed in plain English. Not an anomaly. A diagnosis.
Actionable steps, auto-runbooks, and SLO defense actions are surfaced immediately — ready to execute.
Structured postmortem and RCA documentation logged automatically. No manual paperwork.
The same incident. Two completely different outcomes.
Alert fires. Team scrambles across Grafana, Loki, K8s — 3+ tabs open simultaneously. No shared view.
App pods, CPU, memory all checked. Nothing found. Engineers start a Slack thread. War room forming.
Redis checked manually — latency OK. Still no root cause. 5–10 engineers now fully interrupted.
MinIO bottleneck finally found via manual correlation. Business impact sustained for 40+ minutes.
App latency spike detected — P99 > 5s. OLLY begins cross-system correlation automatically.
Redis cleared as healthy. No anomaly. Candidate eliminated from investigation instantly.
MinIO flagged — GET latency at 4,800ms (normal: 120ms). Storage bottleneck confirmed.
Root cause confirmed. Remediation steps surfaced: scale replicas, trigger runbook. One engineer executes.
| Dimension | REMS by OpsTree | Datadog | New Relic | Dynatrace |
|---|---|---|---|---|
| Pricing | ✓ Infrastructure-based — predictable | Host + ingestion, spikes at scale | Per-GB, grows with data | Host + licensing, expensive |
| Data Sampling | ✓ 100% telemetry — zero blind spots | ✗ Sampling at scale | ✗ Forces sampling | Strong but costly |
| AI / RCA | ✓ Autonomous diagnosis <60 sec | Anomaly alerts only | Anomaly alerts only | Reactive detection |
| SLO Management | ✓ First-class, integrated | Add-on module | Separate product | Separate product |
| Deployment | ✓ On-prem / VPC / Cloud | Cloud SaaS only | Cloud SaaS only | Cloud-centric |
| Data Ownership | ✓ Your infrastructure, always | ✗ Datadog's cloud | ✗ NR servers | ✗ DT cloud |
| Vendor Lock-in | ✓ Zero — CNCF open-source | ✗ High | ✗ High | ✗ High |
| Foundation | ✓ 100% open-source | ✗ Proprietary | ✗ Proprietary | ✗ Proprietary |
OLLY is the AI engine at the center of REMS. It doesn't just detect anomalies — it understands them. Built for enterprises that need to be ahead of failures, not reacting to them.
Three deployments. Three different industries. One consistent pattern — REMS delivers measurable, auditable impact.
33M+ concurrent users, 1TB+ daily logs. Needed predictable costs, faster resolution, and zero tolerance for downtime. Log-to-metrics conversion and AI RCA deployed on open-source foundation.
Delivering mission-critical communications for Fortune 500 companies. Replaced fragmented, reactive monitoring with centralized real-time visibility via OpenTelemetry in 30 days.
75+ countries, 150+ ports and terminals. Required unified intelligence while maintaining regional data residency. On-prem edge monitoring via Prometheus + GitOps-driven deployment.
REMS doesn't just reduce incident resolution time. It changes how your engineering organization operates — permanently.
Mean time to resolution drops from 45 minutes to under 60 seconds. Measured across deployments, not estimated.
AI handles first-responder work. Engineers get notified when action is actually needed — not for every noisy alert.
When toil is automated, senior engineers spend time on reliability improvements — not incident archaeology.
Start where you are. Whether you need observability foundations or are ready for full AI-led incident automation — REMS meets your team at your current maturity level.
Runs on your infrastructure · Zero data lock-in · 100% open-source ·
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