Real-time operational visibility, portable architecture, and a common view for SRE, DevOps, and engineering leadership.
EyeNode by DDOSCOM brings metrics, logs, traces, and continuous profiles into a shared operational context.
OpenTelemetry
Use this documentation to plan an EyeNode by DDOSCOM integration, define telemetry contracts, and consult configuration reference material. Start with the overview, then continue with the SDK or pipeline your team already uses.
View the solution architectureIdentify the services, nodes, containers, and production code that must contribute metrics, logs, traces, or continuous profiles. This inventory reduces context gaps during investigation.
Align resource, service, and deployment attributes across signals. Consistent context makes it possible to relate alert, transaction, event, and code without manual reconstruction.
EyeNode organizes standards-based telemetry within a consistent operational context. Your team reuses existing instrumentation knowledge and workflows, reducing technical rework and integration time.
Confirm that signals can be queried together before relying on them for incident response. This validation shortens triage when degradation appears.
EyeNode uses an open standards-based architecture compatible with OpenTelemetry. It unifies observability data without requiring a proprietary format, enabling interoperability and reducing the operational cost of changing your observability strategy.
Reuse existing instrumentation knowledge and workflows that produce standards-based telemetry. Before introducing an SDK, confirm its supported language, version, attribute semantics, and exporter in its documentation; do not assume undocumented compatibility.
Retain identifiers and attributes that let you follow a request across services, associate the timestamped event, and relate the continuous profile to production code. Correlation connects the alert, transaction, event, and exact line of code, reduces tool switching, and accelerates MTTR.
Telemetry is not tied to a proprietary EyeNode schema. You retain the ability to move data across compatible platforms, reducing migration risk and protecting your technology investment.
detect anomalies and show system health so teams can prioritize alerts by impact and begin triage with evidence.
record detailed, timestamped events to reconstruct what happened, validate changes, and reduce manual searching during an incident.
follow the end-to-end path of each request across microservices to locate the affected transaction, its dependencies, and the point of degradation with less triage.
continuously analyze CPU and memory consumption alongside production code execution to isolate bottlenecks down to the exact line without restarting services. This preserves diagnostic continuity and accelerates remediation.
connect your stack in minutes without additional agents. EyeNode reads signals directly from your clusters and cloud services. Integration respects your existing configuration and does not require rewriting deployment pipelines.
document service owner, environment, deployment version, and resource attributes. This discipline makes it easier to separate symptoms, dependencies, and likely causes with less triage.
do not make proprietary formats a requirement of instrumentation. Keep open formats to protect data portability and reduce rework if the observability strategy changes.
validate a verifiable sequence: alert in the metric → transaction in the trace → timestamped event in the log → exact line of code in the continuous profile. The team eliminates manual tool switching, isolates the root cause, and accelerates MTTR.
