Reliable production systems that teams can operate.
CodeCones helps engineering teams make reliability measurable and operational. Our site reliability engineering services cover SLIs and SLOs, error-budget governance, observability, incident response, toil automation, resilience testing and capacity planning across cloud-native and hybrid environments.
Representative SRE Engagement Pattern
Baseline
Critical journeys, signals and ownership established at review start
Six services
SLOs, observability, incidents, automation, resilience and capacity
Handover
Runbooks, dashboards, policies and operating responsibilities documented
CodeCones combines SRE consulting services with hands-on implementation. We connect reliability targets, observability, incident response, automation, resilience and capacity work to the ownership model your team can operate.
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SRE turns production operations into a measurable engineering discipline. CodeCones connects user-impact signals, service objectives, incident learning and automation so teams can reduce noise, recover with clearer ownership and invest in reliability where it matters most.
People. Technology. Impact.
CodeCones combines SRE practice design with cloud and platform engineering, so reliability recommendations can become implemented changes rather than reports alone. Engagements are scoped around your operating model, existing tools, risk and ownership boundaries.
Cloud Partner Accreditations
Advisory, implementation, embedded and ongoing models are available only as explicitly agreed. Continuous 24/7 coverage is never implied by default.
How we deliver
A reliability review establishes the evidence, ownership questions and phased plan before implementation depth is agreed.
Production controls
Observability is not a dashboard inventory. It is the system of signals, context and ownership that helps teams understand user impact, diagnose failures and make capacity or reliability decisions. CodeCones documents the capability, scale or cost reason for every material tool change.
Critical journeys, SLIs, SLOs, error budgets and burn-rate alerts connect reliability measurement to user impact and release decisions.
OpenTelemetry, metrics, logs, distributed traces, APM and deployment context are aligned to service ownership, retention and cost controls.
Severity, command, escalation, runbooks, postmortems, rollback paths and tracked remediation create a repeatable response system.
Failure-mode analysis, controlled experiments, performance baselines and capacity validation test recovery assumptions before critical demand.
Client identity systems, least privilege, time-bounded roles, audit logs, approved change paths and documented handover keep operational control explicit.
Operating boundaries
These disciplines work together, but their ownership questions differ. This page owns production reliability; deeper platform build work belongs with our cloud and platform engineering services.
| Discipline | Primary question | Typical ownership |
|---|---|---|
| Site Reliability Engineering | How do we define, measure and improve production reliability? | SLIs and SLOs, error budgets, observability, incidents, toil, resilience and capacity. |
| DevOps | How do development and operations deliver changes safely and frequently? | CI/CD, automation, shared practices and delivery feedback. |
| Platform Engineering | How do we provide developers a consistent self-service path? | Internal platforms, paved roads, templates and environments. |
Own an outcome with an end-to-end product team, or add senior specialists inside your existing delivery team.
Use CodeCones to shape, build, and operate an AI or software product with accountable delivery from discovery and architecture through release, observability, and handover.
Build My ProductEmbed experienced AI, software, data, cloud, or DevOps engineers into an existing team with a defined capability gap, ownership model, and working cadence.
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Industry expertise
Industry scale and outcomes
IDC reports an average annual downtime cost of $970,856 across surveyed organizations. This industry-wide research finding is not a CodeCones client result or a guaranteed outcome. A scoped review establishes the baseline for each engagement.
average annual downtime cost across surveyed organizations, according to IDC research
IDC:Disaster Recovery and Cyber-RecoveryTechnology stack
Technology selection follows the workload, service objectives, existing observability tools, operating model and cost controls. This representative list does not imply that every tool is used on every engagement.
We improve working tools first and recommend replacement only when a documented capability, integration, operating or cost gap justifies it.
FAQs
Direct answers about scope, discipline boundaries, observability, ownership, access, timing and handover.
People. Technology. Impact.
Tell CodeCones which services are business-critical, how incidents and alerts are handled today, and where reliability is blocking delivery or customer trust. We will identify the baseline evidence, ownership questions and most practical first phase for SLOs, observability, incident response and automation.
Outcomes-driven engineering: from discovery to deployment and beyond.
Learn how cloud-native platform engineering connects resilient systems, governance, operational consistency and production readiness at enterprise scale.
See how telemetry, fault detection and capacity forecasting help engineering teams move from reactive operations to measurable production signals.
Get in Touch
Tell us about your critical services, current observability and incident process, reliability targets, cloud environment and access constraints. Our team responds within one business day.
Practical perspectives on AI product development, software engineering, cloud platforms, MLOps, and building effective engineering teams.
