Performance Improvement (Tuning & Capacity)

What We Do

Performance bottleneck identification and analysis
ABAP program optimization and code review
Database tuning (indexes, statistics, parameters)
Operating system and hardware optimization
Memory management and buffer tuning
Batch job scheduling and optimization
Capacity planning and growth forecasting
Performance monitoring setup and alerting

Why It Matters

SAP system performance directly impacts business operations:

User Productivity: Slow transactions waste employee time and reduce efficiency
Business Processes: Long-running batch jobs delay critical operations like order processing
Customer Experience: Portal and e-commerce performance affects customer satisfaction
Infrastructure Costs: Poor performance often leads to over-provisioning hardware
System Stability: Resource exhaustion causes system crashes and outages
Growth Capacity: Performance constraints limit business expansion

How We Do It

Step 1: Performance Baseline & Analysis

Collect current performance metrics (response times, throughput, resource utilization)
Review SAP transaction ST03N for workload analysis
Analyze database statistics and expensive SQL statements
Review system logs for errors, warnings, and resource bottlenecks
Identify peak usage periods and resource constraints
Interview users about specific performance complaints
Advanced monitoring solutions with 50+ metrics including system component status, HANA performance, network traffic, system errors, background job data, backup status, memory usage, CPU load
Real-time monitoring with cloud-based 24/7 access

Step 2: Bottleneck Identification

We systematically analyze performance across all layers:

ABAP Layer

Identify expensive ABAP programs and transactions
Review custom code for inefficient database access patterns
Analyze memory consumption and internal table usage
Check for missing or unused indexes

Database Layer

Identify expensive SQL statements and missing indexes
Review database statistics freshness and accuracy
Analyze table fragmentation and reorganization needs
Check database buffer hit ratios and cache effectiveness

Operating System & Hardware

Review CPU, memory, disk I/O, and network utilization
Identify resource contention and scheduling issues
Analyze swap usage and memory pressure
Check for hardware errors or degraded components

Step 3: Optimization Recommendations

Prioritize improvements by impact and effort
Provide specific tuning recommendations with expected benefit
Document configuration changes with before/after values
Identify quick wins vs. longer-term improvements
Estimate resource requirements for implementation

Step 4: Implementation & Validation

Test changes in non-production environment first
Implement tuning changes during maintenance windows
Monitor system behavior after each change
Measure performance improvement against baseline
Document all changes made and results achieved

Step 5: Capacity Planning

Analyze historical growth trends (users, data volume, transactions)
Forecast future resource requirements
Identify when capacity thresholds will be reached
Recommend infrastructure upgrades or scaling actions
Establish ongoing monitoring and alerting

Common Performance Issues & Solutions

Slow Transactions

Symptoms: Long response times for interactive transactions

Common Causes:

Missing database indexes
Inefficient ABAP code
Network latency
Undersized SAP buffers

Solutions: Index creation, code optimization, buffer tuning

Long-Running Batch Jobs

Symptoms: Batch jobs exceed maintenance window

Common Causes:

Inefficient SQL queries
Large data volumes
Sequential processing
Resource contention

Solutions: SQL tuning, parallel processing, job scheduling optimization

Memory Issues

Symptoms: System crashes, swap usage, allocation failures

Common Causes:

Undersized memory configuration
Memory leaks in custom code
Inefficient internal table usage
Too many work processes

Solutions: Memory parameter tuning, code fixes, process optimization

Database Bottlenecks

Symptoms: High database time, lock waits, I/O delays

Common Causes:

Outdated database statistics
Table fragmentation
Slow disk subsystem
Locking conflicts

Solutions: Statistics update, reorganization, I/O optimization, lock analysis

Deliverables

Performance Baseline Report: Current metrics and resource utilization
Bottleneck Analysis: Detailed findings by system layer with evidence
Optimization Recommendations: Prioritized list with expected impact
Configuration Changes: Specific parameter tuning with before/after values
Code Review Findings: ABAP programs requiring optimization
Index Recommendations: Missing or unused indexes to add/remove
Capacity Forecast: Growth projections and upgrade timeline
Monitoring Setup: Alerts and dashboards for ongoing tracking
Post-Optimization Report: Measured improvements and remaining opportunities

Advanced Monitoring Solutions

We leverage advanced monitoring technology to provide comprehensive visibility:

Key Benefits

Automation: Advanced technology with error-free monitoring
Visibility: Metrics that illuminate the SAP BASIS layer
Cost: Up to 85% advantage in monitoring costs
Global Access: Cloud-based 24/7 access for all SAP users and BASIS teams

Technical Capabilities

Monitors 50+ metrics including system component status, HANA performance, network traffic, system errors, background job data, backup status, memory usage, CPU load
No installation required, no agent deployment needed
Works within SAP standards using service users and database users
Runs on its own database structure without creating extra load
Fed by standard SAP functions, tables and CCMS content

Expected Outcomes

Metric	Typical Improvement	Measurement Method
Transaction Response Time	20-50% reduction	SAP ST03N workload analysis
Batch Job Duration	30-60% reduction	Job log comparison before/after
Database Time	40-70% reduction	ST03N database time percentage
CPU Utilization	10-30% reduction	OS monitoring tools
Memory Efficiency	15-40% improvement	Reduced swap, better buffer hit ratios

Note: Actual improvements depend on current state and specific bottlenecks. Results measured against baseline and validated in production.