Site Reliability Engineering (SRE)
Applies SRE practice to production systems defining what reliability means for each service then engineering the automation observability and response habits needed to hit those targets without heroics.
Everything included under this practice line.
Service level objective and indicator design with error budget policy
Observability stack covering metrics logs traces and synthetic monitoring
Incident response process: paging roles comms and blameless postmortems
Runbook automation and toil reduction so recurring alerts get engineered away
Capacity and performance engineering including load testing and headroom modeling
Chaos engineering and game days to verify assumptions before production forces the test
Reliability review of new features before launch so surprises show up in staging
On-call health tracking: alert volume page fatigue and rotation fairness
The stack we reach for.
What the business gets, measured.
- Fewer customer-facing incidents and faster recovery when they happen
- Clear reliability targets aligned to what customers actually experience
- Reduced on-call burnout through toil elimination and cleaner alerting
- Better capacity decisions before the traffic curve punishes them
- Product and engineering share a language for reliability trade-offs
The specialists behind this practice line.
Site reliability engineers embed with the service teams responsible for the systems in scope joined by observability engineers when instrumentation is thin and by performance engineers when capacity is the constraint. Postmortems and SLO reviews are run with the on-call engineers who actually carry the pager so the fixes stick.
Compose several capabilities into one engagement.
Cloud Consulting & Migration (AWS, Azure, GCP)
We plan the target landing zone then move workloads across in waves so nothing goes dark. Lift-and-shift where it makes sense replatform where the payoff is real.
DevOps Consulting
We audit how your team ships today find the actual bottleneck and fix it. Usually it's not the tooling it's the handoff between dev and ops.
CI/CD Pipeline Automation
Pipelines that build test scan and deploy on every merge without a human in the loop. Same pipeline for every service so nobody has to relearn it.
Infrastructure as Code (Terraform)
Every resource in a repo reviewed like application code. No click-ops no drift and no server that only one person knows how to rebuild.
Kubernetes & Container Orchestration
EKS AKS or GKE clusters set up so day-two doesn't become a fire drill. Sane defaults for networking RBAC upgrades and workload isolation.
Platform Engineering
Internal developer platform so product teams ship services without filing tickets. Golden paths for the common cases escape hatches for the rest.
Cloud Cost Optimization
We find the money leaking on idle instances oversized nodes forgotten volumes and egress. Then we set guardrails so it doesn't creep back next quarter.
Disaster Recovery & Business Continuity
RTO and RPO targets you can actually meet backed by restores we test on a schedule. Backups nobody has restored are not backups.
Let's talk
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