Reliability work often ignores cost until budgets are blown. FinOps teams, meanwhile, push for savings without context on customer experience. The most advanced organizations—Thoughtworks, Google Cloud, and Spotify among them—have started publishing stories about merging SLO and cost management. At Cloudythings we call it FinOps-driven SLOs: treat error budgets and cloud budgets as two sides of the same coin.
Expose cost as a first-class signal
We collect telemetry from:
- Cloud billing APIs (AWS Cost Explorer, GCP Billing, Azure Cost Management) aggregated daily.
- Kubernetes cost tooling (Kubecost, CloudZero meters) attributing spend per namespace/service.
- Feature-level metrics tying user journeys to revenue.
Data lands in a warehouse and powers Looker/Grafana dashboards juxtaposing SLO burn-rate with cost burn-rate.
Define joint guardrails
Together with finance and product, we set:
- Reliability budget: acceptable error budget burn per quarter.
- Cost budget: maximum monthly spend per service or value stream.
- Trade-off policies: e.g., “If reliability is green and cost is red, explore right-sizing; if reliability is red and cost is green, add capacity.”
Policies live in Git and feed automation decisions.
Automate right-sizing with feedback loops
We blend:
- Vertical Pod Autoscaler (VPA) recommendations to adjust requests/limits.
- Karpenter or Cluster Autoscaler policies that scale nodes based on cost-effective spot/on-demand mixes.
- FinOps policies using OPA to block manifest changes that exceed allocated budgets.
Deployment pipelines run cost impact simulations (using Infracost) and annotate PRs with monthly deltas. Engineers see cost consequences before merge.
Embed in SLO reviews
Monthly reliability reviews include a FinOps segment:
- Charts showing error budget burn vs. cost variance.
- Highlights of experiments (e.g., enabling distroless images reduced memory usage by 20%).
- Joint action items—maybe shifting workloads to Graviton/Arm nodes or tuning caching layers.
This aligns with Google’s “cost of reliability” narrative from the SRE workbook: some outages cost more than hardware.
Incentivize through value-stream KPIs
We build dashboards per value stream showing:
- Revenue or customer impact.
- SLO compliance.
- Cloud cost allocated.
Leadership can then prioritize investments where reliability issues hurt revenue or where overprovisioning eats margins. It becomes a business conversation, not a technical debate.
Iterate with experiments
We run experiments like:
- Autoscaling tuning with k6 load tests to find sweet spots.
- Cache TTL adjustments to evaluate cost vs. latency trade-offs.
- Spot instance adoption measured against error budgets.
Results go into a playbook of “approved cost-saving levers” teams can adopt confidently.
FinOps-driven SLOs bridge silos. When cost data and reliability data share the same dashboards, teams make smarter trade-offs—and customers feel the benefits without the finance team panicking.