Track. Simulate. Control.
SLOpilot continuously measures service behavior against your SLOs, simulates infrastructure changes, and selects the action that maintains compliance at minimal cost.
Track Service Behavior Against Your SLOs
SLOpilot measures real service behavior and builds predictive models to forecast SLO compliance — even for conditions your cluster has never seen. Early warnings before breaches occur.
- Behavioral models predict SLO compliance under novel load patterns
- Confidence intervals quantify prediction uncertainty per SLO target
- Alerts trigger on predicted SLO breaches — before they happen
Services Requiring Attention
Click to view forecastRight-Size with Confidence
SLOpilot analyzes historical CPU and memory consumption, assesses whether observed usage data is sufficient and stable, and computes recommended request values calibrated to your workload's actual behavior. Every recommendation passes a data coverage gate and an estimate stability check before it is shown. Workloads that fail either gate are flagged for continued observation rather than premature action.
- Confidence-rated CPU and memory recommendations emerge as usage data accumulates
- HPA-aware for horizontally-scaled workloads — recommendations adapt to actual scaling behavior
- Workloads with insufficient data flagged for continued observation — no premature changes
- Same observation data powers compliance baselines and the What-If Engine — one pipeline, three outputs
Infrastructure Rightsizing
| Deployment | p95 CPU | Current | Recommended | Confidence |
|---|---|---|---|---|
| checkout-api | 210m | 500m | 230m | High |
| payment-svc | 140m | 400m | 160m | High |
| inventory-sync | 95m | 250m | 105m | Medium |
| batch-etl | 380m | 400m | — | Withheld |
Declare Your SLOs. SLOpilot Enforces Them.
Set latency, error rate, or throughput targets on your critical services. SLOpilot constrains all infrastructure actions to these declarations — services without explicit SLOs are right-sized for cost within the fleet's SLO budget.
- Declare latency, error rate, or throughput targets per service
- Unconstrained services optimized for cost — bounded by fleet-wide SLO compliance
- Namespace and time-range filtering for fleet-wide visibility
SLO Configuration
| Service | SLO Type | Threshold | Status |
|---|---|---|---|
| checkout-api | Latency p95 | < 100ms | Active |
| payment-svc | Latency p99 | < 50ms | Active |
| inventory | Throughput | > 1000 rps | Active |
| user-service | — | — | Not set |
| email-worker | — | — | Not set |
Simulate Changes. Predict SLO Impact.
Define resource or traffic changes as inputs. SLOpilot predicts the impact on your declared latency and throughput targets — with confidence intervals that quantify prediction uncertainty.
- Traffic multipliers (2×, 5×, 10×) show SLO headroom under load
- Resource reduction scenarios reveal the SLO-safe cost-cutting threshold
- Compare multiple What-If scenarios side by side
What-If Scenario
| Service | Current | Target | ||||
|---|---|---|---|---|---|---|
| CPU Req | CPU Lim | Replicas | CPU Req | CPU Lim | Replicas | |
| checkout-api | 250m | 500m | 3 | 350m | 700m | 5 |
| payment-svc | 200m | 400m | 2 | 250m | 500m | 3 |
| inventory | 150m | 300m | 2 | 150m | 300m | 2 |
Select and Apply the Lowest-Cost SLO-Compliant Action
Manual approval for full control. Auto-apply for continuous optimization. SLOpilot selects the infrastructure action that minimizes cost while maintaining your declared SLOs.
- Manual mode: review each SLO-validated recommendation, apply with one click
- Auto mode: actions execute continuously within declared SLO constraints
- SLO degradation triggers immediate rollback — no pager required
In manual mode, confidence ratings help you prioritize which recommendations to approve first.
See Compliance & GovernanceAuto-Optimization
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