Observability for faster diagnosis
Unify metrics, logs, traces, alerting, and service views so engineers can move from symptom to cause without losing time across fragmented tools.
Deployment blueprint
What teams get on day one
Unified signal collection
Capture core metrics, structured logs, and distributed traces within one operational model so teams stop chasing context across vendors.
Searchable log aggregation
Pull service and infrastructure logs into one indexed system with filters that help responders isolate relevant events fast.
Request path tracing
Follow latency and failure propagation through microservices to understand where breakdowns really begin.
1 pane
metrics, logs, traces
MTTR
reduction focused
Live
alert pipelines
Custom
service dashboards
Core capabilities
Purpose-built for modern engineering teams
Unified signal collection
Capture core metrics, structured logs, and distributed traces within one operational model so teams stop chasing context across vendors.
Searchable log aggregation
Pull service and infrastructure logs into one indexed system with filters that help responders isolate relevant events fast.
Request path tracing
Follow latency and failure propagation through microservices to understand where breakdowns really begin.
Operator-grade dashboards
Build focused views for service health, infrastructure posture, or business-critical flows instead of relying on generic charts.
Alerting with less noise
Tune alerts around symptoms that matter, route them intelligently, and reduce fatigue caused by repetitive low-signal pages.
Application performance context
Connect runtime behavior to code-level or service-level insights so engineering teams can act on issues with better precision.
Delivery flow
How teams adopt observability
The platform is designed to reduce setup friction, standardize delivery, and give every team a clear operating model from day one.
Connect services and infrastructure
Instrument the workloads that matter and establish shared naming so teams can navigate signals consistently.
Model health around key journeys
Build dashboards and alert rules around user-facing flows, dependencies, and platform risk instead of single metrics in isolation.
Use telemetry during incidents and reviews
Investigate live failures quickly, then carry the same evidence into retrospectives and platform improvement work.
Use cases
High-impact scenarios teams run on VxCloud
Microservice outage diagnosis
Correlate trace spikes, log errors, and infrastructure pressure to identify the true root cause of cascading failures.
Reliability engineering programs
Create service health baselines and SLO-oriented dashboards that keep reliability work grounded in measurable outcomes.
Performance regression tracking
Spot latency shifts after releases and tie them back to code, dependency, or capacity changes before customers complain.
Integrates with your existing stack
Bring current tooling forward instead of rebuilding workflows. Standard integrations are available immediately, with deeper automation on top.
Operator outcome
Teams get a sharper developer loop, stronger governance, and a cleaner production handoff without adding separate point tools to manage.
Build the next workflow on top of Observability
Start in minutes with VxCloud-managed infrastructure, AI-assisted setup, and a production-ready baseline your team can extend safely.