OpenTelemetry
Open standard for metrics, logs, and traces in polyglot and Kubernetes environments.
We help technical teams detect blind spots, reduce useless alerts and turn telemetry into operational decisions.
Approach
Useful observability is not measured by the number of dashboards. It is measured by how quickly a team understands what is happening, which service is affected and which decision to make.
At Dot and Key we work with technical leadership, platform, SRE and operations teams to organize metrics, logs and traces around concrete questions: user impact, business risk, probable cause, ingestion cost and ownership.
We start from your existing stack, whether it is OpenTelemetry, Elastic, Dynatrace, Grafana, Prometheus or a legacy mix. The goal is not to change tools for the sake of it, but to build a maintainable signal model your team can operate.
Modular engagements to move from accumulated telemetry to actionable observability: assessment, design, implementation and operational enablement.
Four iterative phases with clear deliverables: diagnosis, signal model, validated implementation and continuous improvement of noise, cost and ownership.
Understand architecture, goals, and pain points.
Signal model, SLIs/SLOs, and ingestion architecture.
Instrumentation, dashboards, production validation.
Cardinality, cost, alert noise, team maturity.
Open standards and enterprise platforms, avoiding unnecessary lock-in and prioritizing interoperability, cost and maintainability.
Technology stackOpen standard for metrics, logs, and traces in polyglot and Kubernetes environments.
Elasticsearch, Kibana, ingest pipelines, and Elastic Agent for logs and analysis.
APM, infrastructure, logs, and automated analysis for enterprise environments.
Cloud-native metrics and alerting ecosystem.
Microservices and containers, legacy integrations, distributed teams, regulated environments and platforms with rising telemetry costs.
Common sectors: insurance, transport, digital services and enterprise platforms where reliability, traceability and cost reach leadership conversations. References available under NDA.
Experience on projects alongside leading consultancies and integrators, bringing specialized observability, platform and operations judgement.
View ecosystemClassic monitoring often focuses on infrastructure and static thresholds. Observability correlates metrics, logs and traces to understand user impact and prioritise by symptoms, not resources alone.
No. We are not tied to one tool. We start from your current stack, contracts and maturity, and propose what is most maintainable for your context.
It depends on platform size and agreed scope. A focused assessment is typically completed in a few weeks, with an executive report and prioritised improvement plan.
Yes. We review SLIs/SLOs, alert profiles and operational noise to align notifications with real business impact.
We treat volume, retention, sampling and cardinality as architecture decisions from the design phase, not afterthoughts.
Yes. Projects are mainly remote with European timezone alignment. On-site when required.
AI observability is consulting to instrument and monitor applications with models (Python, OpenTelemetry, OpenLLMetry). Observability with AI is our own agent in development to prioritize and analyze signal on your stack; today we offer PoC and an exploratory conversation.
An initial conversation to review context, blind spots, alerts, ingestion cost and real observability priorities.
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