MonX v2 watches every server, network device, cloud resource, and LLM call — then uses AI to tell you why something broke, down to the file and line, and what to do about it.
SELECT on orders.status running 340×/sec — triggering the circuit breaker on api-gateway.
Full-stack observability from kernel TCP events to cloud bills — with AI that closes the loop from alert to fix.
Correlates distributed traces and logs by traceId, spanId, and time window, then asks AI to explain the root cause — with the specific service, file, and query involved. Not just "CPU spike", but why.
Each hypothesis maps to a ranked catalog of FixRecommendations with before/after code diffs, numbered steps, expected outcomes, risk badges, and a rollback plan — ready to send for approval.
Full state machine — pending → approved → in progress → completed/rolled back. Every transition requires a named approver and comment. Full audit trail on every action, enforced valid transitions only.
Track every LLM call (Sonnet, GPT-4o, Gemini): token usage, latency p50/p95/p99, cost per model, error rate, and anomaly detection (latency spike, cost surge, error surge) across all your AI workloads.
Kernel-level TCP event capture builds a live dependency graph with EMA-smoothed latency on every edge. DFS finds the highest-latency critical path. Click any node or edge for protocol, error rate, and connection details.
Multi-cloud resource health, metrics and alert lifecycle across AWS, Azure, and GCP resources. Connect with IAM credentials without local agents.
CPU, memory, disk, network, and process-level data streamed in as it happens — not on a five-minute poll.
Poll firewalls (FortiGate, Cisco), switches, APs, WAN links, and UPS. Track bandwidth, port status, session counts, and ping latency across all your network kit.
Every agent authenticates with a tenant-scoped key. Isolate dashboards, seats, alerting rules, and API access per client — nothing ever crosses tenant lines.
Instead of waking someone at 3am to read logs, MonX correlates the evidence and asks AI to explain exactly what broke, why, and how to fix it.
Traditional monitoring tells you that CPU spiked on Container X. MonX tells you Container X is spiking due to an unindexed database query on /api/user line 42.
orders.status
executing 340×/sec. This caused
api-gateway's circuit breaker to open,
cascading to notification-service.
No agents to compile, no config files to hand-edit. One command, one CSV, or one push from the dashboard.
Run the one-line installer for your OS, or upload a CSV to push it to every server in the fleet. Works on-prem, in VMs, and in containers.
The agent authenticates with your tenant key and starts streaming metrics, traces, and logs — usually inside a minute. SNMP polling starts automatically for network devices.
When something goes wrong, MonX correlates the evidence, AI explains it, and the fix queue opens for your team to approve. Signal, not noise.
The same installer pattern works whether you're bringing up a single staging box or standing up a production fleet — or connecting to your AWS, Azure, and GCP accounts.
MonX tracks resources across AWS, Azure, and GCP — health status, metric bars, monthly cost estimates, and an alert lifecycle with AI-powered explanations for each issue.
EC2 instances, RDS databases, Lambda functions — health, CPU, cost, and alerts in one view.
Virtual Machines, SQL Database, AKS clusters — DTU, node count, and cost tracked automatically.
Compute Engine, Cloud Storage, and more — storage size, request rate, and health monitoring.
IAM Role Delegation: We provide a pre-configured CloudFormation template that creates a read-only role trusting MonitorX, secured by a unique External ID to prevent unauthorized access.
App Registrations: Create a Service Principal in Microsoft Entra ID and assign it a Reader role at the subscription level. Bind the Client ID, Tenant ID, and Client Secret key.
Service Account Keys: Set up a GCP Service Account, assign it the read-only Viewer role, download the credentials JSON key, and upload it to connect GCP assets.
Every plan includes all platform installers and AI usage quota. Team members are role-based and capped at 6 users per tenant (custom arrangements for larger teams can be made at extra cost).
For small setups getting started with AI-assisted monitoring.
For teams running production fleets that need full AIOps.
For large-scale, multi-cloud environments with heavy AI workloads.
AI features are powered by state-of-the-art models (RCA explanations and per-alert explanations) to help you resolve issues instantly. Prices are set at a fixed monthly rate — no per-call metering or surprise bills.
Subscriptions can be cancelled at any time from your billing profile. Your active subscription will remain active until the end of your current billing cycle, with no further recurring charges.
Credits included within monthly cost usage limits do not roll over to the next month. Additional credits bought will roll over 1 month.
Telemetry collection and AI insights are subject to fair use limits. Abuse or excessive concurrent API requests may result in temporary rate limits to ensure system stability.
Because MonitorX is a cloud service with instant resource provisioning and API allocation, we offer no returns or refunds on all checkouts and top-ups.
Real-time monitoring, autonomous root-cause analysis, and human-approved remediation. Free to start, deployed in minutes.