You cannot fix what you cannot see. Our observability testing practice validates your entire telemetry pipeline — metrics, logs, and distributed traces — ensuring your monitoring stack delivers accurate, timely, and actionable signals. We test that your dashboards, alerts, and APM instrumentation work as designed before incidents reach your customers.
We validate every layer of your observability stack — confirming that metrics are accurate, logs are structured, traces propagate correctly, and alerts fire when and only when they should.
Validate that your Prometheus, StatsD, or cloud-native metrics collectors accurately capture, aggregate, and expose the right values — no missing counters, no silent data drops.
Test log ingestion pipelines (Fluentd, Logstash, Vector) for completeness, structured formatting, correct severity mapping, and zero data loss under high throughput.
Verify trace propagation across microservices using OpenTelemetry and Jaeger — confirming span context is correctly injected, sampled, and correlated end-to-end.
Replay synthetic and historical failure conditions against your alerting rules to confirm they fire at the right thresholds — eliminating false positives, alert fatigue, and missed fires.
Audit your application performance management instrumentation — validating that every critical transaction, database query, and external call is correctly traced and measured.
Verify that Grafana dashboards and SLO/SLI calculations reflect ground truth — testing panel queries, time-range accuracy, and error budget burn rate calculations against known data.
We work across the full observability toolchain — from instrumentation libraries and collectors to storage backends, visualisation layers, and alert routing platforms.
Our five-phase methodology moves from understanding your system's observable surface area to a continuously validated, production-grade telemetry pipeline that your teams genuinely rely on.
We inventory your current instrumentation, alert rules, dashboards, and log pipelines — mapping coverage gaps to service criticality and SLA obligations.
We define what signals to validate across metrics, logs, and traces — designing synthetic injection scenarios, alert replay playbooks, and tracing validation test cases.
Engineers inject synthetic spans, fire test events, and replay failure conditions — validating that every metric, log line, and trace propagates accurately through your entire stack.
Every alerting rule is tested for correct threshold, labelling, and routing. Dashboard queries are verified against known datasets to confirm accuracy across all time ranges.
We deliver a telemetry coverage report with prioritised gaps, lead remediation efforts alongside your engineers, and wire observability assertions into your CI/CD pipeline.
Uninstrumented code paths and mis-configured alert rules mean incidents can run undetected for hours. Observability testing ensures your monitoring catches what matters.
Dashboards built on inaccurate metrics create false confidence. Telemetry pipeline testing validates data fidelity so engineering and leadership can trust what they see.
Every minute between a failure occurring and your team knowing about it costs money. Validated alerting and tracing slashes Mean Time to Detect and Mean Time to Resolve.
In distributed systems, a single broken trace propagation means losing the thread across dozens of services. Distributed tracing validation is essential in cloud-native architectures.
Our telemetry specialists join your squads to instrument, validate, and continuously improve your observability coverage — sprint by sprint, not just at release.
We integrate observability checks into your CI/CD pipeline — automatically asserting that new code ships with correct instrumentation before it reaches production.
Detailed reports mapping instrumentation gaps to service criticality, with prioritised remediation roadmaps accepted by SRE teams, architects, and compliance auditors.
We test metrics, logs, and traces together — not in silos — validating the correlations between pillars that make observability genuinely useful during incidents.
We generate synthetic failure conditions, transactions, and spans to test your monitoring stack end-to-end without waiting for real incidents to reveal coverage gaps.
We audit every alerting rule for precision and recall — removing noisy, redundant, or mis-scoped alerts that erode on-call trust and cause real incidents to be ignored.
Deep hands-on experience with OTel SDK instrumentation, collector pipelines, and exporter configuration — ensuring your telemetry is vendor-portable and standards-compliant.
We test that your SLI calculations are mathematically correct and your error budget dashboards accurately reflect reality — giving SREs reliable data for release decisions.
High-cardinality metric labels inflate storage costs and degrade query performance. We identify and remediate cardinality issues before they become a billing crisis.
Book a free observability audit with our engineers. We'll map your telemetry coverage gaps, identify blind spots in your alerting, and deliver a prioritised remediation plan — at no cost.