Cloud Reliability & Operations

Site reliability engineering you can count on.

Uptime that holds, incidents that get resolved quickly, and systems built to recover when something breaks.

What Is Cloud Reliability and Operations?

Your systems need to perform reliably every day.

Cloud reliability and operations combines SRE, observability, incident management, performance, disaster recovery, and resilience to keep systems available and help teams respond when something fails.

The goal is simple: reduce disruption, recover faster, and build systems that are prepared for failure.

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What Downtime Costs

  • $300K+

    Hourly cost of downtime reported by more than 90% of mid-size and large enterprises.

    ITIC, Hourly Cost of Downtime Survey

  • $600B

    Annual losses across the Global 2000 from unplanned outages, up from $400 billion two years earlier.

    Splunk, 2026

  • 20%

    Respondents reported their most recent major outage cost more than $1 million.

    Uptime Institute, 2026

Signs You Need Reliability Engineering

  • Your Systems Lack Clear Reliability Targets
  • Incidents Take Hours to Resolve
  • Your Team Is Overwhelmed by Alerts
  • Critical Knowledge Lives With a Few People
  • Your Disaster Recovery Plan Hasn't Been Tested

What Cloud Reliability & Operations Covers

Service level objectives defined against user-facing outcomes, error budgets established, and engineering effort directed by what the measurements show rather than by assumption.

How We Build Reliability

Cloud Reliability & Operations runs the Evolve stage of The Pivot.

Where the underlying architecture limit's achievable reliability, that work runs through Cloud Transformation & Migration or Legacy Modernization.

  • 01

    Discover

    Current availability, incident history and existing instrumentation assessed, with failure patterns identified.

    Output: a reliability baseline with gaps documented.

  • 02

    Define

    Service level objectives and error budgets agreed against user-facing outcomes and business tolerance.

    Output: measurable reliability targets.

  • 03

    Design

    Observability architecture, alerting strategy, incident process and recovery objectives.

    Output: an operational design for review.

  • 04

    Build

    Instrumentation, alerting and automation implemented, prioritized by the failure modes with highest impact.

    Output: observability and response operating in production.

  • 05

    Launch

    On-call structure, runbooks and escalation paths transitioned to the teams that will operate them.

    Output: an operational model your team runs.

  • 06

    Evolve

    Availability, incident frequency and recovery time measured against baseline, with postmortem actions tracked.

What You Walk Away With

  • Defined reliability targets
  • Clear system visibility
  • Actionable alerts
  • Faster incident response
  • Tested recovery procedures
  • Operational runbooks
  • Continuous improvement practices

Our Technology Landscape

  • Observability

    • Datadog
    • Grafana
    • Prometheus
    • New Relic
    • OpenTelemetry
    • Honeycomb
  • Logging and tracing

    • Elastic
    • Loki
    • Jaeger
    • CloudWatch
  • Incident management

    • PagerDuty
    • Opsgenie
    • incident.io
  • Infrastructure and automation

    • Terraform
    • Kubernetes
    • Ansible
    • AWS
    • Microsoft Azure
    • Google Cloud
  • Resilience

    • Chaos Mesh
    • AWS Fault Injection Service
    • load testing tooling

Common Questions

Monitoring tells you when something is wrong. Observability helps you understand why.

Know Where You Stand.

We assess your reliability gaps, identify the highest-impact risks, and give you a clear plan for what to fix first.

Book a reliability review
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