What is Site Reliability Engineering?

Site reliability engineering (SRE) treats operations as a software problem. Rather than reacting to outages, SRE teams define measurable reliability targets (SLOs), track them with real user-facing indicators, and spend an explicit error budget to balance shipping speed against stability. The discipline spans observability, on-call and incident response, capacity planning, and automating away repetitive toil. Through our site reliability engineering services, growing companies get Google-style reliability practice without building a dedicated SRE org first — reliability becomes a number you manage, not a hope you hold.

Key Benefits

Why SRE Matters for San Francisco Businesses

The Bay Area failure mode isn't moving too slowly — it's shipping so fast that production becomes fragile. A launch that goes viral, an AI feature that triples inference load overnight, a marketplace promo that spikes both sides of the platform at once — all classic San Francisco reliability problems. SRE gives fast-moving teams a control system: error budgets decide when to ship and when to stabilize, and a rehearsed incident process turns 2 a.m. chaos into a 20-minute fix. Teams that want delivery modernized too pair this with our DevOps consulting in San Francisco.

Higher uptime & SLO adherence

99.9%+ targets defined per service and tracked from the user's point of view — the uptime story your enterprise prospects ask about in security review.

Faster incident response

Runbooks, severity levels, and a 24×7 rotation shrink MTTR — and blameless postmortems make sure each incident buys you permanent resilience.

Lower toil via automation

Terraform and GitOps replace manual ops, so your small team's hours go into product — not into pushing deploys and rotating certificates by hand.

Predictable scaling & costs

Autoscaling tuned to real traffic and GPU capacity planned ahead of model launches — growth without burn-rate surprises on your AWS bill.

Keep shipping fast — we'll keep it up

Get an SRE assessment of your platform: SLO readiness, observability gaps, on-call load, and where your next scaling cliff is hiding.

Book an SRE Assessment

What Our SRE Services Include

SLOs, SLIs & error budgets

We define SLOs around what your users actually feel — API latency percentiles, signup success, inference response times — and wire up automated SLI measurement against them. The error budget policy is written down and agreed with engineering leadership, so "can we ship this today?" gets answered by a burn-rate dashboard instead of a debate.

Observability: Prometheus, Grafana, New Relic

Startups usually have too many dashboards and too few answers. We consolidate metrics, logs, and traces into an observability stack built on Prometheus, Grafana, and New Relic (we're a New Relic partner), with alerts tuned to page on user pain only. Our monitoring and observability services also cover cost-aware telemetry — because observability bills can quietly rival compute at scale.

Incident response & on-call (24×7)

Most Bay Area startups can't staff a sane on-call rotation without burning out their best engineers. We can. Backed by our 24×7 support team, we take the pager around the clock, respond by runbook, and escalate to your team only when product context is genuinely needed. Every incident ends with a documented timeline and a blameless postmortem that feeds the backlog.

Kubernetes & infrastructure reliability

We productionize EKS clusters for scale-ups: autoscaling that reacts before users notice, pod disruption budgets, safe rollout strategies, and — for AI workloads — GPU node groups with capacity planned ahead of launches, not scrambled after them. Whether you're on us-west-1 or us-west-2, we design multi-AZ so a zone failure is a graph blip, not a status-page post.

Toil reduction & automation (Terraform, GitOps)

Anything an engineer does by hand twice, we automate: infrastructure in Terraform, deployments through GitOps, environment spin-ups on demand, certificate and secret rotation on schedule. For a startup, the payoff is compounding — the ops workload stays flat while the product and traffic grow.

Capacity planning & performance/cost tuning

We load-test before launches and right-size continuously afterward — instance families, storage tiers, autoscaling floors, even the us-west-1 vs us-west-2 placement question, since region choice alone can move your AWS bill. Reliability targets and cloud spend get planned as one budget, so headroom is a decision rather than an accident.