Reliability you can measure
Your platform has to absorb load spikes, take frequent deployments and recover when something fails. We apply software engineering to operations so less of that depends on someone being awake, with availability targets up to 99.99% where the business needs it.
What we put in place
SLIs, SLOs and error budgets. 100% uptime is not a useful target. We agree measurable objectives with you, and the error budget tells your developers when they can ship fast and when to slow down.
Less manual toil. Repetitive operational work moves into Terraform, autoscaling, self-healing workloads and automated disaster recovery failover.
Observability. Cloud Trace, OpenTelemetry, structured logging and synthetic user journeys, so you see problems before your users report them.
Blameless postmortems. Incident reviews that find the systemic cause and produce actions that stop it recurring.
Capacity planning and chaos testing. Peak load simulation and controlled failure experiments in staging, so the busy day is not the first real test.
Related
- Managed services: SRE as an ongoing service, alongside our managed SOC and agent reliability work.
- Agent reliability engineering: the same discipline applied to AI agents.
- Hapana: a 99.999% production SLA after moving from AWS to Cloud Run.
Talk to an architect who has done this before.
Bring your current setup and the outcome you need. You will get a view on the approach, the risks and roughly what it costs.
Straight to a senior GCP architect. No SDR, no slide deck.
Not ready to talk? See how we migrated Hapana off AWS →
Or call +61 2 8359 9507 · Hello@aviato.consulting