HANA‑Aware AutoScaler & Cost Guard for S/4 Workloads
8/10
Demand Score
Unpredictable dialog/batch load causes user-visible slowdowns and surprise cloud bills during closes or promotions.
7/10
Blue Ocean
Competition Level
$4k-12k
Price/Month
Predicted customer spend
14 days
Time to MVP
Difficulty: Hard
The Problem
A workload-aware scaling orchestrator purpose-built for SAP stacks. It taps sapcontrol/CCMS, SM50/SM66 queues, ST03N, and HANA memory/column-store stats to predict demand and scale app servers, enqueu
🔗 Validated by Real User Complaints
This problem has been verified through 3 real user complaints:
Competitor Landscape
- AWS Auto Scaling
- Azure Autoscale
- Google Managed Instance Groups
- IBM Turbonomic
- Dynatrace Workload Rightsizing
- Spot by NetApp
Must-Have Features for MVP
ABAP work-process and queue-aware scaling policies
Batch and fiscal calendar lookahead for pre-scaling
HANA memory/CPU signature detection to protect row/column stores
Blue‑green app server orchestration with health checks
Guardrail policies (batch windows, minimums, SLA thresholds)
Reserved/spot/committed-use optimization with risk caps
Latency SLOs with ‘stabilize capacity’ kill‑switch
Savings and SLO dashboard with anomaly alerts
Synthetic load rehearsal to test scaling rules safely
⚠️ Potential Challenges
- Accessing SAP runtime metrics securely (sapcontrol/CCMS)
- Coordinating with Basis change windows
- Hyperscaler quota and instance warm-up times
- Validating HANA tiering impacts on licensing/cost
Risk Level: Minimal
🎯 Keys to Success
- ≥99% of hours within defined dialog response SLO
- 15–30% reduction in monthly compute spend
- Zero unplanned downtime attributable to scaling events
- <5 minutes to recover SLO after demand spikes
- Accurate forecast vs. actual capacity within 10%
Ready to Build This?
This hard-difficulty project could be your next micro-SaaS success.