Observability & Monitoring

Traces, metrics, and logs — correlated, queryable, and owned by you. The observability spine that turns a 3 AM incident into a 9-minute mean time to diagnose instead of a war-room hunt through five vendor consoles.

9 min

Mean time to diagnose after NOC modernization

1 min

Metric resolution for live dashboards

2 years

Metric retention at full resolution

73%

Reduction in duplicate on-call pages

One Signal Plane, Every Layer

Vucos Observability is a unified telemetry plane built on OpenTelemetry. Every service emits distributed traces, metrics, and structured logs that share the same trace IDs, tenant IDs, and session IDs — so a viewer playback error, a DRM license denial, and a billing webhook retry all join up in one query. SLOs, alert rules, and NOC-ready dashboards ship as defaults and are fully customizable; telemetry also flows out to operator-owned stacks like Grafana, Datadog, and Splunk.

Why this matters

Running OTT at scale is a distributed systems problem. A single viewer complaint can touch a dozen services — authentication, entitlement, DRM, origin, CDN, player telemetry, billing, CDN logs — each with its own latency, error, and retry behavior. Without a unified observability layer, on-call engineers spend most of an incident correlating timestamps across tools instead of fixing the issue. MTTR stretches, the same incidents recur, and the NOC treats every spike as new.

Vucos ships observability as a product primitive, not a bolt-on. Trace IDs propagate end to end through ingest, encoding, edge, API, and client. Every metric lives in the same store with minute-level resolution and multi-year retention where it matters. Alert rules ship pre-wired for the failure modes OTT platforms actually hit — not generic CPU and memory alerts.

What the platform exposes

Distributed tracing

OpenTelemetry-native traces that follow a request from the player SDK through edge, API, backend services, and external vendors. W3C trace context, sampled and head-based tracing, and full span attributes.

High-cardinality metrics

Prometheus-compatible metrics with 1-minute resolution and configurable retention. High-cardinality labels (tenant, device, content ID, CDN) remain queryable without pre-aggregation.

Structured logs

JSON-structured logs with trace correlation, tenant scoping, and PII-aware field masking. Searchable through the console or streamed to your SIEM.

SLOs & error budgets

Service Level Objectives for playback startup, rebuffer ratio, API availability, and DRM license latency — with burn-rate alerts, remaining error budget, and weekly review reports.

Alerting & on-call

Native integrations with PagerDuty, Opsgenie, Slack, and Microsoft Teams. Multi-signal alerts reduce paging noise; every alert links back to the traces and logs that fired it.

NOC-ready dashboards

Pre-built dashboards for live event war rooms, regional health, CDN portfolio performance, DRM success rates, and subscriber impact — branded for your NOC screens.

How operators use it

Pay-TV operator

NOC modernization

Replaced a wall of vendor-specific dashboards (encoder, CDN, DRM, billing) with a single operations view. Trace-linked alerts cut mean time to diagnose from 42 to 9 minutes and reduced duplicate pages by 73%.

Sports broadcaster

Live event war room

During major matches, a dedicated war-room dashboard shows concurrent viewers, QoE percentiles by region, CDN split, and revenue at risk — with burn-rate alerts that fire before viewer complaints hit social media.

SVOD service

Incident post-mortem traceability

Every production incident has traces preserved for 90 days, including the exact viewer sessions affected, the upstream cause (e.g. DRM vendor latency), and the revenue impact — so post-mortems become engineering documents instead of speculation.

Technical details

Telemetry standards

OpenTelemetry traces, metrics, logs
W3C Trace Context propagation
Prometheus exposition
OTLP and HTTP export

Retention

Metrics: 2 years at 1-minute resolution
Traces: 7-30 days (configurable)
Logs: 90 days hot, multi-year cold
SLO reports: indefinite

Alert integrations

PagerDuty
Opsgenie
Slack
Microsoft Teams
Webhooks
Email

Export destinations

Grafana
Datadog
Splunk
New Relic
Honeycomb
Elastic / OpenSearch

SLO coverage

Playback startup (p95)
Rebuffer ratio
API availability
DRM license latency
Manifest delivery
Ingest health

Access & security

SSO via SAML and OIDC
Scoped RBAC
Audit log of query & alert changes
PII field masking

Key Takeaways

OpenTelemetry-native traces, metrics, and logs with end-to-end trace IDs
High-cardinality metrics queryable by tenant, device, content, and CDN
SLOs for playback startup, rebuffer, API, and DRM license latency
NOC-ready dashboards for live events, regional health, and CDN portfolio
Native alert routing to PagerDuty, Opsgenie, Slack, and Teams
Export to Grafana, Datadog, Splunk, Honeycomb, and your own stack

Frequently Asked Questions

Do we have to use Vucos's dashboards, or can we keep our own stack?

Both. Vucos ships first-class dashboards for the operations team that wants them on day one, but every signal — traces, metrics, logs — streams out through standard OpenTelemetry and Prometheus endpoints into Grafana, Datadog, Splunk, or any tool you run today. Many operators use Vucos dashboards for OTT-specific views and their existing tool for everything else.

How does trace correlation actually work across vendors?

Trace context propagates using W3C standards through every Vucos service and into third-party vendors that support it (most CDNs, DRM providers, and ad servers now do). When a vendor does not, Vucos captures the outbound request and response with correlating IDs and links them back into the trace graph — so even a vendor black box leaves a visible span.

Are the SLOs fixed or can we define our own?

Fixed defaults ship for the metrics that matter across every OTT service (startup, rebuffer, API availability, DRM license, ingest). Beyond that you define your own: pick any metric, set the target, window, and burn-rate alerts. SLOs are first-class objects with change history and weekly auto-reports.

What's the PII posture on logs and traces?

Fields containing PII are flagged at the schema level and either masked, hashed, or dropped based on tenant policy. Trace attributes have the same treatment. Query access is scoped by RBAC, and every query is audited — especially important for operators in regulated markets or under GDPR/DPA commitments.

Can we page on multi-signal conditions, not just a single metric?

Yes. Alert rules compose across metrics, traces, and log patterns. A classic example: page only when rebuffer ratio exceeds 1%, concurrent viewers are above 100k, and the player SDK error stream shows CDN-specific codes — so the page fires on a real incident rather than a late-night statistical wobble.

How is this different from Vucos Analytics?

Analytics is for business and product signals (ARPU, churn, content ROI, QoE trends) — built for analysts and leadership. Observability is for engineering signals (traces, runtime metrics, error budgets) — built for on-call and the NOC. They share the underlying telemetry but optimize for different audiences and retention horizons.

Ready to learn more?

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