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Monitoring and observability
that show what production is doing before users have to tell you.

We implement metrics, logs, tracing, alerting and operational dashboards so teams can detect issues earlier, investigate them faster and understand how applications, infrastructure and dependencies behave in production.

Monitoring & ObservabilityPart of Cloud, DevOps & Managed Operations ›
  1. 01SignalsIdentify the metrics, logs, traces and events that actually matter.
  2. 02ContextConnect application, infrastructure and dependency behaviour.
  3. 03DetectCreate alerts around meaningful symptoms rather than raw noise.
  4. 04LearnUse production evidence to improve systems and operating practices.

When production visibility becomes the problem

Systems can be technically online — and still be failing in ways users can feel.

Monitoring becomes insufficient when teams know whether infrastructure is “up” but cannot explain slow journeys, partial failures, dependency issues or behaviour across distributed systems.

  1. 01Users discover problems before the technical teamImportant degradation is visible through complaints or support tickets before monitoring surfaces it.
  2. 02Alerts exist, but they create more noise than clarityTeams receive large volumes of notifications without enough context to understand what genuinely requires action.
  3. 03Investigation requires searching several disconnected toolsLogs, infrastructure metrics, application errors and deployment information live separately, slowing diagnosis.
  4. 04Teams know something is wrong but not where it startedDistributed dependencies make it difficult to follow behaviour across applications, services, APIs and infrastructure.

The observability decisions

Before collecting more telemetry, decide what the system needs teams to understand.

  1. 01Which user outcomes matter?What behaviour should indicate that customers or internal users are receiving the expected service?
  2. 02Which signals explain those outcomes?Which metrics, logs, traces, events and business signals are useful enough to collect and retain?
  3. 03What deserves an alert?Which conditions require immediate action, and which belong in analysis rather than interrupting somebody?
  4. 04What context should travel with an incident?What deployment, dependency, infrastructure, user or transaction information helps engineers investigate faster?
  5. 05What should teams be able to trace end to end?Which journeys or transactions need visibility across multiple applications, services or external dependencies?
  6. 06What should production evidence improve?How should incidents, recurring patterns and operational behaviour feed back into engineering priorities?

What Monitoring & Observability can include

Observability connects technical signals into a clearer picture of system behaviour.

  1. 01Metrics & service healthTrack application, infrastructure and business-relevant indicators that reveal system condition over time.
  2. 02Centralised loggingBring application, infrastructure and platform logs together so teams can search and correlate behaviour more effectively.
  3. 03Distributed tracingFollow requests and transactions across services, APIs and dependencies to understand latency and failure paths.
  4. 04Alerting & incident signalsCreate actionable thresholds, anomaly detection and escalation around meaningful production conditions.
  5. 05Operational dashboardsProvide focused views of availability, errors, latency, capacity and other operational signals.
  6. 06Observability instrumentationAdd the application and platform telemetry required to expose behaviour that existing tooling cannot see.

Related reliability & operations areas

Observability provides the evidence other operational disciplines use to improve production systems.

Engagement scope

What we actually do.

  1. 01Observability assessmentReview current monitoring, telemetry, dashboards, alerts and investigation workflows to identify visibility gaps and unnecessary noise.
  2. 02Signal & instrumentation designDefine which metrics, logs, traces and business signals should be generated across applications and infrastructure.
  3. 03Monitoring & telemetry implementationConfigure monitoring platforms, log collection, tracing and application instrumentation across relevant environments.
  4. 04Alert & escalation engineeringDesign alerts around impact, severity and actionable conditions with clearer routing and reduced noise.
  5. 05Dashboard & investigation experienceCreate operational views and correlations that help teams move from symptom to likely cause with less manual searching across tools.
  6. 06Observability improvement & operational adoptionRefine telemetry, dashboards, alerting and investigation practices using real incidents and production behaviour after implementation.

Engagement options

Ways we can improve production visibility with you.

Not sure which starting point fits? We will help you choose.

Talk to an observability specialist ›
  1. Monitoring foundationEstablish core monitoring, logging, dashboards and alerting for a defined application or platform.Useful whenProduction exists but visibility is limited, inconsistent or dependent on manual checking.
  2. Observability modernisationImprove an existing monitoring estate through better instrumentation, tracing, correlation and alert design.Useful whenMany tools and alerts exist but investigation is still slow or noisy.
  3. Embedded observability engineeringWork alongside application, platform or operations teams to continuously improve production telemetry and investigation practices.Useful whenObservability needs to evolve alongside a complex or rapidly changing system.

What you leave with

Production behaviour teams can see, understand and respond to.

The exact outputs depend on the environment, but the engagement should leave teams with clearer signals, better investigation context and less dependence on user reports to discover problems.

  1. 01Defined health signalsA clear set of application, infrastructure and user-impact indicators that matter operationally.
  2. 02Connected telemetryMetrics, logs and traces brought together around important systems and journeys.
  3. 03Actionable alertingAlerts designed around meaningful impact and ownership rather than every technical anomaly.
  4. 04Operational dashboardsFocused views of health, errors, latency, dependencies and capacity for the teams responsible.
  5. 05Faster investigation pathsEnough context to move from symptom to affected component or dependency more efficiently.
  6. 06A stronger production feedback loopOperational evidence feeding into reliability, delivery and application-improvement priorities.

Our approach

Observe what matters. Remove the noise. Make investigation easier.

  1. 01
    Start with user and service healthUnderstand which journeys, transactions and operational outcomes matter most.
  2. 02
    Map the signalsIdentify what metrics, logs, traces and events are needed to explain that behaviour.
  3. 03
    Instrument the gapsAdd telemetry where important behaviour is currently invisible.
  4. 04
    Design for investigationConnect signals, dashboards and alerts so teams can move through incidents with useful context.
  5. 05
    Improve from real incidentsUse production experience to remove noisy alerts, expose missing signals and strengthen observability over time.

Typical starting points

You do not need a complete observability platform to start.

Talk to an observability specialist ›

Clients usually involve us when:

  • Users report incidents before monitoring detects them.
  • Existing alerts generate too much noise.
  • Application, infrastructure and deployment signals live in separate tools and are difficult to correlate.
  • Engineers spend too long searching logs during incidents.
  • Distributed services are difficult to trace end to end.
  • Important customer journeys are not monitored directly.
  • Deployments cause unexpected behaviour that is difficult to correlate.
  • Leadership wants clearer visibility into service health and recurring operational risk.

From visibility to stronger reliability

Seeing the problem is a milestone. Production still has to become better because of what you learned.

Monitoring & Observability can move directly into the capabilities required to reduce recurring failure, improve performance and strengthen ongoing operation.

Performance & ReliabilityUse production evidence to address bottlenecks, resilience gaps and recurring failure modes.Explore Performance & Reliability Managed Application ServicesTurn application signals into ongoing technical health, prioritisation and improvement.Explore Managed Application Services DevOps & CI/CDConnect deployments and release history to production behaviour and failure investigation.Explore DevOps & CI/CD Cloud & InfrastructureImprove capacity and infrastructure behaviour exposed through operational telemetry.Explore Cloud & Infrastructure Cloud & Application SecurityExtend production visibility into security-relevant events, access and suspicious behaviour.Explore Cloud & Application Security

AI-first approach

Use AI to shorten investigation — not to invent certainty from incomplete signals.

AI can help summarise logs, correlate events, identify unusual patterns and surface likely relationships across telemetry. But incident conclusions still need reliable signals, engineering context and explicit validation.

AI should help teams get to the right evidence faster — not replace the evidence itself.

  • SignalIs the telemetry complete and trustworthy enough for AI-assisted interpretation?
  • ContextWhat topology, deployment and dependency information is required to interpret the signals correctly?
  • CorrelationCan AI surface relationships across logs, metrics and traces that would otherwise take longer to find?
  • ControlWhich incident conclusions or remediation actions still require explicit technical validation?

FAQ

Common questions about Monitoring & Observability.

Monitoring checks known indicators and conditions, such as availability, errors or resource utilisation. Observability goes further by giving teams enough telemetry and context to investigate behaviour they did not necessarily predict in advance.

Start with the production behaviour you cannot explain quickly enough

The system is producing signals. Are they telling the team what it needs to know?

Tell us what you monitor today, where investigation slows down and which incidents users still discover first. We will help create clearer production visibility around the system.

Talk to an observability specialist ›Explore Cloud & Operations ›