Module 15: BW/4HANA Monitoring & Housekeeping (BW/4HANA 2.0)
Monitoring and housekeeping are not optional activities in BW/4HANA.
They directly impact:
- System performance
- Data consistency
- Storage costs
- Operational stability
This module covers:
- Load monitoring
- Request management
- PSA handling
- Data aging (intro)
- Housekeeping jobs
1. Load Monitoring
1.1 Why Load Monitoring Matters
Load monitoring ensures:
- Data completeness
- Timely availability
- Early detection of issues
Most BW production issues are detected via monitoring, not complaints.
1.2 Monitoring Tools in BW/4HANA
| Tool | Purpose |
|---|---|
| DTP Monitor | Track data loads |
| Request Monitor | Request lifecycle |
| Process Chain Monitor | End-to-end flows |
| Delta Queue Monitor | Delta health |
1.3 What to Monitor
- Load status (green/yellow/red)
- Runtime trends
- Error patterns
- Delta backlogs
Monitor trends, not just failures.
2. Request Management
2.1 What is a Request?
A request represents:
- One data load execution
- Identifiable by request ID
- Tracked end-to-end
2.2 Request Lifecycle
Created → Loaded → Activated → Available
2.3 Request Deletion & Repair
- Delete old requests
- Repair failed requests
- Reprocess error stack
Keep request volumes manageable to reduce activation overhead.
3. PSA Handling
3.1 What is PSA?
PSA (Persistent Staging Area):
- Stores extracted source data
- Enables reprocessing
- Acts as audit layer
3.2 PSA in BW/4HANA
- PSA is optional
- Often replaced by Staging aDSOs
- Still useful for auditing
Persist PSA only when audit or replay is required.
3.3 PSA Cleanup Strategy
- Retain recent requests
- Delete old PSA data
- Balance audit vs storage
Uncontrolled PSA growth is a silent storage killer.
4. Data Aging (Intro)
4.1 What is Data Aging?
Data aging:
- Moves cold data to cheaper storage
- Keeps hot data accessible
- Reduces memory footprint
4.2 Data Aging in BW/4HANA
- Based on time characteristics
- Aging buckets (hot/warm/cold)
- Transparent to queries
Data aging is storage optimization, not data deletion.
4.3 When to Consider Data Aging
- Very large historical datasets
- Legal retention requirements
- Performance-sensitive systems
5. Housekeeping Jobs
5.1 Common Housekeeping Tasks
| Task | Purpose |
|---|---|
| Delete old requests | Reduce load |
| PSA cleanup | Free storage |
| Change log cleanup | Optimize aDSOs |
| Temp data cleanup | System hygiene |
5.2 Scheduling Housekeeping Jobs
- Run during off-peak hours
- Automate via process chains
- Monitor execution
Housekeeping jobs should be scheduled, not manual.
6. BW/4HANA vs Classic BW (Operations)
| Area | Classic BW | BW/4HANA |
|---|---|---|
| Monitoring | Fragmented | Centralized |
| PSA usage | Mandatory | Optional |
| Storage | Disk-based | In-memory optimized |
| Data aging | Limited | Advanced |
7. Common Operational Mistakes
Never deleting requests
Ignoring PSA growth
Manual housekeeping
No monitoring alerts
8. Interview-Grade Questions
Q1. Why is request management important?
Answer: Requests track data loads and directly affect performance and activation times. Proper management ensures system stability.
Q2. Is PSA mandatory in BW/4HANA?
Answer: No. PSA is optional and often replaced by Staging aDSOs, but can still be used for auditing and reprocessing.
9. Summary
- Monitoring ensures stability
- Requests must be managed
- PSA handling impacts storage
- Data aging optimizes memory
- Housekeeping keeps BW healthy
10. What's Next?
➡️ Module 16: Performance Optimization & Tuning (BW/4HANA)
A BW system without housekeeping is guaranteed to degrade over time.