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Run · Capability

Know what production is doing
before users have to tell you.

We strengthen the reliability, observability and operational security around live digital products — making important behaviour visible, defining credible reliability targets and putting controls around the systems the business depends on.

Run capabilities
Reliability, Observability & SecurityPart of Run ›
  1. 01SignalsUnderstand what the application, infrastructure and business need to reveal about production behaviour.
  2. 02ReliabilityDefine service expectations, failure modes and recovery around real business consequence.
  3. 03ProtectionStrengthen access, configuration and operational controls around live systems.
  4. 04ResponseDetect issues earlier, investigate faster and learn from incidents so the same surprises happen less often.
Specialist servicesObservability & Reliability EngineeringCloud & Application Security ›

When production is difficult to trust

Reliability problems often exist before anything is technically “down”.

Latency increases. Jobs stop running. Integrations silently fail. Capacity tightens. Errors affect only part of the user journey. Access grows without enough control.

The objective is not to collect more dashboards. It is to make important production behaviour visible enough that teams can act before small problems become business incidents.

  • 01Teams learn about failures from usersMonitoring exists, but the signals do not surface meaningful problems early enough.
  • 02There are too many alerts and too little understandingTeams receive noise without enough context to know what actually requires action.
  • 03Nobody knows what “reliable enough” meansInfrastructure is engineered toward theoretical uptime rather than the actual consequences of failure.
  • 04Operational access and controls have grown inconsistentlyPermissions, secrets, configuration and security practices have accumulated without a clear operating model.

The reliability decisions

Before adding more monitoring, decide what the business actually needs to know and protect.

  1. 01What does failure mean for this product?Which journeys, services, jobs and integrations create meaningful business impact when they slow down or stop?
  2. 02Which signals actually indicate health?What logs, metrics, traces, events and business signals tell us whether the product is behaving normally?
  3. 03What reliability level is appropriate?Where do availability and recovery justify additional engineering effort — and where would it add cost without meaningful value?
  4. 04Who should be able to access what?Which production systems, environments, data and operational actions need explicit access boundaries?
  5. 05What should happen when a meaningful threshold is crossed?Which conditions should alert, escalate, automate or trigger investigation?
  6. 06What should change after an incident?How will incidents produce better monitoring, architecture, controls or operating practices rather than only a closed ticket?

Specialist services

Make production understandable — and strengthen the controls around what matters.

Explore all services ›
01 · ServiceObservability & Reliability EngineeringTurn production signals into operational understanding teams can actually use.We design monitoring, logging, metrics, tracing, alerting and reliability practices around the behaviour that matters — helping teams detect problems earlier, investigate faster and make resilience proportionate to business impact.Typical needs
  • Application monitoring
  • Logs & metrics
  • Distributed tracing
  • SLOs & reliability
  • Incident visibility
02 · ServiceCloud & Application SecurityStrengthen the operational controls around live applications and infrastructure.We improve production security through practical controls around access, secrets, configuration, dependencies and cloud environments — integrated into how systems are actually operated and changed.Typical needs
  • Access controls
  • Secrets management
  • Cloud security
  • Configuration hardening
  • Security monitoring
Explore Cloud & Application Security ›

What you leave with

Production behaviour teams can see, understand and respond to.

The exact outputs depend on the platform, but a Reliability, Observability & Security engagement should leave the environment easier to understand, safer to operate and more deliberate about failure.

  1. 01Meaningful production signalsLogs, metrics, traces and business indicators tied to actual application and user behaviour.
  2. 02Clear reliability expectationsService levels and recovery expectations appropriate to the importance of each part of the system.
  3. 03Actionable alertingAlerts designed around meaningful conditions rather than every technical fluctuation.
  4. 04Stronger operational controlsClearer access, secrets, configuration and production security practices.
  5. 05Credible incident responseDefined detection, escalation, investigation and recovery paths for important failure scenarios.
  6. 06A platform that learns from failureIncidents feed back into monitoring, architecture, automation and operating practices.

Our approach

Observe what matters. Strengthen what failure exposes.

  1. Map the critical behaviourUnderstand applications, journeys, integrations, infrastructure and the consequences of failure.
  2. Define reliability expectationsAgree what needs to remain available, how quickly failure should be detected and what recovery should look like.
  3. Build useful visibilityInstrument logs, metrics, traces, alerts and operational signals around meaningful system behaviour.
  4. Strengthen controls and responseImprove access, security practices, escalation, investigation and recovery around live systems.
  5. Learn and evolveUse incidents, performance trends and operational evidence to continuously improve reliability.

Typical starting points

You do not need a complete reliability programme to start.

Talk to a reliability engineer ›

Clients usually involve us when:

  • Customers discover production problems before the engineering team does.
  • Monitoring exists but alerts are too noisy to trust.
  • We cannot explain why the application is slow or unstable.
  • Nobody knows what uptime or recovery target is actually appropriate.
  • A critical integration or background process can fail silently.
  • Production access and permissions have grown without enough control.
  • We need better logs, metrics or tracing across distributed systems.
  • Incidents keep recurring without producing lasting improvements.

Our perspective

Reliability is not the absence of failure. It is the ability to understand and recover from it.

No useful production system stays perfectly predictable forever. Reliability comes from understanding what matters, seeing problems early, containing their impact and improving the environment after they occur.

  1. 01Business-impact-ledReliability effort follows consequence rather than theoretical perfection.
  2. 02Observable by defaultImportant system behaviour should be visible before somebody has to guess.
  3. 03Security as an operating propertyProtection belongs inside access, configuration, delivery and production practices — not beside them.
  4. 04Failure-informedEvery meaningful incident should leave the platform easier to understand or harder to break the same way again.

AI-first approach

Use AI to shorten investigation — not to invent certainty.

AI can help correlate logs, summarise incidents, identify unusual patterns, search operational history and surface possible causes across complex environments. But operational decisions still need trustworthy evidence and clear human accountability.

AI should help teams find the signal faster — not turn an uncertain suggestion into an automated conclusion.

Explore our AI-first approach ›
  • ContextWhich logs, traces, metrics, configuration and incident history can the capability safely access?
  • EvidenceCan every recommendation be tied back to observable production behaviour?
  • ControlWhich actions can AI suggest, and which production changes must remain explicitly approved?
  • OperationsHow will the AI capability itself be secured, observed and evaluated in production?

Beyond reliability

Healthy is a milestone. Production still has to change.

Reliability, Observability & Security connects directly into the wider Run environment as systems, applications and delivery practices evolve.

Cloud & Platform OperationsOperate the infrastructure and production environment around the signals.Explore Cloud & Operations DevOps & Release OperationsMake production changes safer and easier to understand.Explore DevOps & Releases Application Management & SupportMaintain and improve the applications producing those signals.Explore Application Management Data & IntegrationStrengthen the APIs, data flows and integrations the platform depends on.Explore Data & Integration

FAQ

Common questions about Reliability, Observability & Security.

It can include application and infrastructure monitoring, logging, metrics, distributed tracing, alerting, reliability targets, incident response practices, access controls, secrets management, configuration hardening and operational security. The exact scope depends on which systems matter most and where the current reliability or visibility gaps exist.

Start with what production cannot explain

Something is happening in production. The difficult part should not be finding out what.

Tell us where visibility, reliability or operational control is weak today. We will help determine what needs to be observed, protected and made easier to recover.

Talk to a reliability engineer ›Explore Run ›