What is Site Reliability Engineering?
Site Reliability Engineering (SRE) applies software engineering to operations: instead of reacting to outages, you set measurable reliability targets (SLOs), track them with real telemetry, and automate away the manual work that causes most failures. When something does break, structured incident response and blameless postmortems turn the outage into a permanent fix. Our site reliability engineering practice brings this discipline to Seattle teams as an embedded service — engineers, tooling, and process — so reliability improves without pausing your product roadmap. The payoff is fewer 2 a.m. pages, faster recovery when incidents happen, and infrastructure spend that tracks actual demand.
Why SRE Matters for Seattle Businesses
Seattle customers are unusually cloud-literate — they notice degraded latency long before a status page admits it. SRE gives you the instrumentation to see problems first, the error budgets to balance shipping speed against stability, and the automation to survive holiday peaks and game launches without heroics.
Higher uptime & SLO adherence
Reliability targets defined per user journey and enforced with error budgets — so 99.9%+ uptime is measured, reported, and defended.
Faster incident response
Runbooks, alert routing, and practiced escalation cut MTTR — incidents get detected in minutes and resolved before customers open tickets.
Lower toil via automation
Repetitive operational work gets automated with Terraform and GitOps, freeing your engineers for product work instead of firefighting.
Predictable scaling & costs
Capacity planning grounded in real traffic data means peak season is provisioned for in advance — and idle capacity gets trimmed after.
Make reliability your competitive edge in Seattle
Get a reliability assessment of your AWS environment — SLO readiness, observability gaps, and incident process — from engineers who run production 24×7.
Book a Reliability AssessmentWhat Our SRE Services Include
SLOs, SLIs & error budgets
We work with your product and engineering leads to define Service Level Indicators for the journeys that matter — checkout latency, API availability, login success — then set SLOs your business can stand behind. Error budget policies make the speed-versus-stability trade-off explicit: while budget remains, ship fast; when it burns, the data says stabilize. Reliability stops being a debate and becomes a dashboard.
Observability engineering
Metrics, logs, and traces unified across Prometheus, Grafana, and New Relic, with dashboards built around your SLOs rather than raw host graphs. As part of our monitoring and observability services, we tune alerts to page on symptoms users feel — not on every CPU blip — so on-call engineers trust the pager again.
Incident response & on-call (24×7)
Structured incident command with severity definitions, escalation paths, and communication templates, staffed around the clock through our 24×7 DevOps support team. Every incident ends in a blameless postmortem with tracked action items, so the same failure does not page you twice. Your Seattle engineers keep Pacific-hours context; we carry the night.
Kubernetes & infrastructure reliability
Production-grade EKS on us-west-2: pod disruption budgets, topology-aware scheduling, resource requests tuned from live usage, and cluster upgrades executed without downtime. We harden the layers beneath the apps too — networking, DNS, data stores — because most "Kubernetes outages" start somewhere else.
Toil reduction & automation
Anything an engineer does twice by hand becomes a candidate for automation. We codify infrastructure with Terraform, drive changes through GitOps pipelines, and script the recurring operational chores — certificate rotation, failover drills, scaling events — until your team's week is engineering, not ops chores.
Capacity planning & performance tuning
Load testing against realistic traffic models before your peak events, autoscaling policies proven under stress, and performance profiling that finds the slow query before your customers do. The same data drives cost tuning afterward: right-sized instances, storage tiers matched to access patterns, and no paying for capacity January doesn't need.
