XRAY VU Observability engineers the telemetry and monitoring foundations that give engineering teams genuine situational awareness. From SLO definition through distributed tracing and alert intelligence, we make the invisible legible — and keep it that way.
Foundation
Observability is not a product you buy — it's a discipline you build. It rests on three data types that, when properly collected and correlated, give you a complete picture of system behavior.
Time-series numerical data representing system state over time. The foundation of dashboards, alerts, and SLO tracking.
Event records with rich context. The narrative layer that explains what happened — when metrics show something went wrong.
Request flow data across distributed systems. The only way to understand latency and failure in microservice architectures.
Service Offerings
From stack design through ongoing maturity improvement, XRAY VU Observability covers the full spectrum.
Design of the full observability data pipeline — collection, transport, storage, and visualization. Right-sized for your scale, budget, and team's operational capacity.
Work with engineering and product leadership to define Service Level Objectives grounded in user experience, with SLIs that actually measure what matters and error budgets that drive real prioritization.
Audit and redesign of alert rules to eliminate noise while ensuring coverage. Alert routing, escalation policy, and on-call process design. The goal: every alert that fires is actionable.
Opinionated, purpose-built dashboards for engineering teams, on-call responders, and executive stakeholders. Each layer shows what its audience needs — no more, no less.
End-to-end instrumentation of microservice architectures using OpenTelemetry. Trace collection, storage, and UI configuration with Grafana Tempo or Jaeger.
APM implementation covering request rates, error rates, latency distributions, and saturation metrics. Real user monitoring strategy and synthetic probe design.
Log architecture using Grafana Loki or ELK stack. Structured logging standards implementation, log sampling strategy, and retention policy design for cost and compliance balance.
Evaluation of your current observability posture against a structured maturity model. Gap analysis, prioritized improvement roadmap, and quick-win identification.
Structured runbooks linked to alert definitions. Incident management process design with tooling integration (PagerDuty, OpsGenie, Slack workflows) and postmortem framework.
Technology Stack
We're technology-agnostic — we recommend based on your environment, scale, and team capability, not our preferred vendor.
| Category | Primary Options | Selection Criteria |
|---|---|---|
| Metrics Storage | Prometheus, VictoriaMetrics, Mimir, Thanos | Retention requirements, cardinality, HA needs, cost |
| Visualization | Grafana, Kibana, DataDog, New Relic | Team familiarity, dashboard complexity, alerting integration |
| Log Aggregation | Grafana Loki, Elasticsearch, OpenSearch | Query patterns, retention volume, budget, existing stack |
| Tracing Backend | Grafana Tempo, Jaeger, Zipkin, DataDog APM | Service count, sampling rate, storage cost |
| Instrumentation | OpenTelemetry SDKs, Prometheus client libs | Language ecosystem, vendor lock-in tolerance |
| Collectors | OTel Collector, Prometheus Exporters, Vector | Data fan-out requirements, transformation needs |
| Alerting | Prometheus Alertmanager, Grafana Alerting | Routing complexity, integration requirements |
| On-Call | PagerDuty, OpsGenie, Grafana OnCall | Team size, schedule complexity, cost |
SLO Engineering
Service Level Objectives are the single most powerful alignment tool between engineering and business stakeholders — when they're defined correctly.
Identify the critical user journeys that SLOs should protect — not system components, but user experiences.
Select indicators that actually measure user experience: availability, latency at P95/P99, error rate, and correctness where applicable.
Set targets based on historical data, user tolerance, and business risk — not aspirational round numbers that no one believes.
Define what happens when error budget is consumed: feature freeze, architecture review, or incident post-mortem requirement.
Derive alert rules from SLO burn rate — not threshold crossings. Alerts fire when budget is being consumed too fast, not when a metric exceeds an arbitrary value.
Monthly SLO report cadence with trend analysis, error budget summary, and reliability investment recommendations for leadership.
Our Position
Observability is the prerequisite for everything else. You cannot secure what you cannot see. You cannot scale what you cannot measure. You cannot respond to incidents you don't know about. XRAY VU treats observability as the foundation layer — not a nice-to-have that gets addressed after features ship. The organizations we work with share this view, or they come to share it quickly.
Engage Observability
Whether you're starting from zero or improving a mature stack, we can help. Start with an observability maturity assessment.