Go from raw logs to AI post-mortems in seconds.
ObservabilityOS ingests structured logs, automatically scrubs PII, detects latency and error anomalies using statistical Z-scores, and generates GPT-4/Claude root-cause post-mortems. Stop grepping at 2 AM.
Integrates directly with your development stack
See the intelligence live
Datadog shows you everything and explains nothing. We show you what matters and explain it in plain English. Interact with our live mockup below.
Microservice Health Registry
Environment: productionauth-service
Handles JWT validation & sessions
payment-service
Stripe billing integrations
api-gateway
Proxy routing & rate-limiting
notification-service
Slack & email alerts dispatch
Traditional Monitoring is Broken
Modern software systems emit gigabytes of logs, but finding the exact commit that broke production remains a manual, stressful scavenger hunt.
Alert Fatigue
Legacy systems spam your channels with 1,000+ alerts representing minor CPU fluctuations, burying critical product database failures under endless noise.
Dashboard Overload
Grafana and Datadog provide 100+ generic graph configurations. But when an incident occurs, you still have to manually trace timelines to find the root cause.
The 2 AM Log Crawl
When a service crashes, engineers spend hours typing log grep queries in terminals, attempting to link random timeout lines back to the latest GitHub release.
How ObservabilityOS works
An intelligent, automated workflow that processes raw logs and returns actionable resolutions.
Ingest Logs
Integrate our zero-dependency SDK in one line or connect your Docker containers. Telemetry is scrubbed of sensitive PII locally before shipping.
Detect Anomalies
Statistical Z-score algorithms analyze error ratios and latency response times in real-time, immediately isolating anomalies from normal traffic patterns.
AI Analyzes
Our LLM processing pipeline ingests structured logs, environment variables, and GitHub commit diffs to compile a full-context root cause description.
Get Actionable Report
Receive a detailed Slack/Discord incident alert mapping out exactly what code broke, why, and providing a direct rollback button.
Enterprise Capabilities. Startup Simplicity.
ObservabilityOS is built with high-throughput ingestion and AI analytics to help modern engineering teams deploy code with complete confidence.
AI Incident Reports
Benefit: Instant diagnostic summaries instead of raw log greps.
Outcome: Lower Mean Time to Resolution (MTTR) by 80%.
Anomaly Detection
Benefit: Zero threshold configurations. Adapts to weekly traffic trends.
Outcome: No alert spam or false positives.
SDK Ingestion
Benefit: Non-blocking API calls. Zero-dependency node installation.
Outcome: 100% app safety with background batch queue operations.
Real-Time SSE Monitoring
Benefit: Live system telemetry flows without page refreshes.
Outcome: Immediate confirmation of system hotfixes.
Multi-channel Webhooks
Benefit: Slack, Discord, and Teams integration out of the box.
Outcome: Alerts delivered directly to your shared developer workspace.
Root Cause Analysis
Benefit: Automatic correlation between deploy times and error spikes.
Outcome: Pinpoint the exact line of code that introduced the bug.
Incident Collaboration
Benefit: Shared threads and runbooks inside the dashboard.
Outcome: Developers work together on resolution instead of silos.
No-Config Dashboards
Benefit: Dashboards are autogenerated from log metadata.
Outcome: No time wasted building, tweaking, or correcting charts.
API & CSV Logs Export
Benefit: Fast structured JSON logs queries via Lucene index.
Outcome: Easily load telemetry inside scripts or export for compliance.
Integrated in under 5 minutes
A zero-dependency, local-scrubbing SDK for your favorite runtime. Copy the snippet below and start sending telemetry in seconds.
// Install SDK
// npm install observability-os
import { Observability } from "observability-os";
const obs = new Observability({
apiKey: process.env.OBS_API_KEY,
serviceName: "payment-service",
environment: "production",
});
// Logs are automatically buffered and scrubbed of PII
obs.info("Payment processed successfully", {
userId: "user_98234",
amount: 49.00,
gateway: "stripe"
});ObservabilityOS vs Legacy Monitoring
Why developers choose ObservabilityOS over traditional monitoring stacks.
| Feature Comparison | ObservabilityOS | Traditional Monitoring |
|---|---|---|
| Setup Time | 1 Minute (One-line SDK / Sidecar) | Days of config, YAML setups & agent configurations |
| Root-Cause Pinpointing | Automated AI Post-mortems | Manual timeline correlations & log grep queries |
| Alert Signal-to-Noise | 98% noise reduction via rolling Z-score | High spam (static CPU alerts waking teams at 3 AM) |
| PII Data Protection | Local SDK scrubbing (scrubber.ts) | Forwarded blindly (security compliance hazards) |
| OpenTelemetry support | Native compliance (HTTP OTLP Ingest) | Requires complex exporter pipelines |
| Pricing Predictability | Flat $29/mo (no host/seat limits) | Complex matrices (charges per host, metric, & seat) |
Works with your existing toolchain
ObservabilityOS integrates seamlessly into standard backend systems, cloud clusters, and chat workspaces.
What developers are saying
Modern teams have replaced complex Grafana setup tasks with ObservabilityOS.
“ObservabilityOS changed our developer workflow overnight. When our payments microservice began timeouts, the AI flagged the exact database release commit before our pagerDuty call went off. Our MTTR dropped from 45 minutes to 30 seconds.”
Jason Sanders
CTO @ PaymentsFlow
“We migrated our Express APIs from Datadog in 10 minutes. The in-memory SDK queue configuration means our endpoint request latency did not spike at all. The automatic Z-score algorithm filters out 99% of noisy telemetry alerts.”
Alex Mercer
Lead DevOps @ CloudVibe
“The secure PII scrubbing engine (scrubber.ts) is standard compliance gold. We audit logs for client authorization headers and tokens before writing logs to any storage. ObservabilityOS handles all recursive redaction automatically.”
Hannah Kim
Head of Security @ MedVault
Simple, developer-first pricing
No host-counting or per-seat fees. Choose a plan that aligns with your logging throughput requirements.
Free Developer
Side projects & local testing.
- 1 service monitored
- 500MB logs / month
- 7-day data retention
- Basic statistical anomaly checking
- Multi-channel alerts
- AI incident root cause
Pro Cloud
Solo founders & small teams in production.
- Up to 10 services monitored
- 10GB logs / month
- 30-day secure data retention
- Slack, Discord & Teams alerts
- AI SRE Analyst incident diagnostics
- 1 team member seat
Self-Host OSS
Run on your own infrastructure.
- Unlimited services monitored
- Unlimited logs / month
- Unlimited data retention
- Community z-score anomaly checker
- Self-service Docker/Compose setup
- GitHub community support
Usage-based add-ons: Log overages at $0.10/GB above plan limit · Additional AI analysis credits at $20 / 100 credits · Extra seats at $30/seat/mo · 20% off with annual billing.
Frequently Asked Questions
Everything you need to know about log shipping, data scrubbing, billing, and AI post-mortems.
Deploy in under 5 minutes.
Join teams resolving system errors 10x faster. Create your free account today, install our SDK, and let the AI map your production health automatically.