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Hot Topics 2023

SAP HANA NSE Table ACDOCA

NSE Design for table ACDOCA

Requirement: Minimization of main memory usage table ACDOCA

Objective: Optimizing RAM by using NSE

Result: 40%  RAM savings with 3%  performance loss through

Period: 07/2022 - 04/2023


The ACDOCA is one of the largest and fastest growing tables in an S/4HANA system. There are currently still restrictions on the use of ACDOCA in the NSE context by SAP. A customer asked us to test it with different designs - with success! We were able to save 40% of the table size. The customer has been live for several months without any restrictions.

SAP HANA Scale-out S/4HANA

S/4HANA Scale-out

Requirement: PoC for S/4HANA Scale-out

Objective: future architecture with strong growth

Result: pending

Period: 05/2023 - ongoing


A customer sees the current architecture as a limitation in the near future and wants a proof of concept for a possible operation of the S/4 system in the scale-out process. For this we develop the architecture, tests and check the operation for possible limitations.

HANA Workload Management

Effective and efficient use of resources

Requirement: Effective and efficient use of resources

Objective: Map workload without resource extension

Preliminary result: CPU usage from >70% to <50%

Period: 11/2022 - still running


A customer sees the current system stability endangered by the workload. Together, a solution is to be worked out in order to be able to process critical SQLs without restrictions in the event of a bottleneck. The parallelism should be limited depending on the workload.

HANA Downsizing

Downsizing impact analysis

Requirement: Downsizing of Hardware 

Objective:  no loss of performance

Result: 25% RAM + 53% CPU saving at 34,8% performance gain

Period: 04/2023 - 07/2023


By using NSE, the customer's main memory requirements could be dramatically reduced. Now the next step to saving should be taken. A downsizing of the server type used. After migrating a sandbox to the new hardware, the performance could be compared and further SQL optimizations carried out via HANA Capture & Replay.

Workload Management

________________

Industry

energy supplier

________________

Location

Germany

________________

Number of employees

>10.000 employees

________________

Period

since 2023/01 - ongoing

________________

SAP products used

HANA 2.0 SPS05


 

  • Identify bottlenecks
  • Mapping of the workload
  • Set table load/unload priorities
  • increase in performance
  • Reduction of main memory consumption
  • partitioning
  • Health check
  • parameterization
  • Hypercare support
  • Introduction NSE
  • Introduction workload classes

 


________________

Plattorm

SLES15 SP3 / HANA 2.0 SPS05

________________

number of systems

3 SIDs

________________

Resources

6 TB RAM

>400 vCPUs

________________

Result

Saving over 1TB of main memory

Reduction of the CPU at peak times by >54%





  Conversion S/4HANA 2022 FPS2

________________

Industry

metal processing

________________

Location

Germany

________________

Number of employees

>2000 employees

________________

Period

since 2022/04 -

________________

SAP products used

S/4HANA 2022


 

  • Optimization downtime
  • Troubleshooting
  • planning
  • parameterization
  • partitioning
  • Health check
  • Hypercare support

 


________________

Platform

Source: SLES12 SP4 / DB2

Target: SLES15 SP4 / HANA 2.0 SPS05

________________

Number of systems

5 SIDs

________________

Resources

15 TB RAM

>200 vCPUs on VMware





  SAP HANA NSE / NLS

________________

Industry

Retail

________________

Location

Germany

________________

Number of employees

>30.000 employees

________________

Period

2022/04 - 2023/06

________________

SAP products used

BW, IQ


 

  • Analysis of NSE candidates
  • Optimization of resource use
  • KPI definition
  • NSE table level deployment
  • NLS: SAP IQ

 


________________

Platform

IBM Power

________________

HANA Version

HANA 2.0 SPS05

________________

Operating system

SLES12 SP5

________________

Number of systems

3 SIDs

________________

Resources

25 TB RAM

>30 vCPUs on IBM Power

________________

Result

Saving of 8TB RAM



Migration to MS Azure

________________

Industry

Retail

________________

Location

Germany

________________

Number of employees

> 85,000 employees

________________

Period

2022/09 - 2023/04

________________

SAP products used

CAR, MDM, MDG, RMM, PO, TM, EWM, FI, SLT, BO, SolMan

 

  • detailed analysis of on-premises systems
  • Project management with international project teams
  • Isolation of the systems
  • Export of the systems
  • Support for re-implementation after import into MS Azure

 

________________

Operating system

SLES12 SP5

________________

HANA Version

HANA 2.0 SPS05

________________

Number of systems

>85 SIDs

________________

Resources

>3,5 TB RAM

>180 vCPUs on HyperScaler 

PoC: SAP HANA Architecture GeoDB

________________

Industry

forestry

________________

Location

Germany

________________

Number of employees

3,000 employees

________________

Period

since 2023/04

________________

SAP products used

SAP HANA, ESRI

 

  • Architecture / Sizing
  • Workshops regarding HANA functionality
  • HA/DR scenarios
  • Optimization of cross-tenant SQL access
  • Analysis of NSE candidates
  • Optimization of resource use

 

________________

Platform

x86 / VMware

________________

Operating system

SLES15 SP4 

________________

HANA Version

HANA 2.0 SPS05 

________________

Number of systems

1 SIDs

________________

Resources

256 GB RAM

48 vCPUs

Support of the operational SAP Business

________________

Industry

Retail

________________

Location

Germany

________________

Number of employees

>60.000 employees

________________

Period

since 2019/11

________________

SAP products used

ERP, F&R, CAR, SLT, EWM, PI, GK

  • Maintenance
  • Performancetuning
  • Troubleshooting
  • building new SAP systems
  • Integration of new architectures
  • Activation of new HANA features
  • constant sizing checks
  • Health Checks
________________
Platform
x86 / IBM Power
________________
Operating system
SLES12 SP4
________________
Number of systems
>90 SIDs
>120 HDBs
>250 AS
________________
Resources
>100 TB RAM
>500 IBM Power Cores
>400 vCPUs on VMware 

Migration of native applications

________________

Industry

Finance

________________

Location

Germany

________________

Number of employees

> 30,000 employees

________________

Period

from 2020/09

________________

SAP products used

SAP HANA, SDA

  • Migration from SAP ASE
  • sizing
  • DR concept
  • Operating concept
  • scalability
  • NSE
  • Workshops for knowledge transfer of new HANA features
  • Workload Management
  • Usage LDAP
  • Kerberos SSO for HANA Cockpit
  • User / Authorization concept
  • hybrid solution approaches via hyperscaler
________________
Platform
Source: Linux/SAP ASE
Goal: RHEL 7.6 / HANA 2.0 SPS05
________________
Number of systems
>6 SIDs

Design of system architecture

________________

Industry

IT service

________________

Location

Germany

________________

Number of employees

> 900 employees

________________

Period

from 2019/08

________________

SAP products used

ERP, BW, HR, CRM, SLT

  • solution design
  • sizing
  • HA / DR concept
  • scalability
  • Transformation of existing processes
  • Workshops for knowledge transfer of new HANA features
  • S/4HANA planning
  • Performancetuning
  • Troubleshooting
________________
Platform
Source: AIX / DB2 / Oracle
Goal: SLES12 SP3 / HANA 1.0 / 2.0
________________
Number of systems
> 200 SIDs

Use of SAP HANA NSE 

________________

Industry

Retail

________________

Location

Germany

________________

Number of employees

> 170.000 employees

________________

Period

from 2021/04

________________

SAP products used

ERP, S/4HANA, BW

  • Analysis of NSE candidates
  • Optimization of resource use
  • Housekeeping / archiving
  • Partitioning
  • KPI definition
  • SQL optimization
  • NSE use at column, table, index and partition level
  • NLS: SAP IQ
________________
Platform
Source: SLES12 SP5 / HANA 2.0 SPS05

________________
Number of systems
> 200 SIDs
________________
Resources
>50 TB RAM
>500 vCPUs on VMware 
________________
Result
Saving of 60% memory

Fiori Migration + Upgrade

________________

Industry

Insurance

________________

Location

Germany

________________

Number of employees

> 10.000 employees

________________

Period

2021/06 - 2021/08

________________

SAP products used

SAP FIORI FES 2020 FOR S/4HANA

  • Installation HANA
  • configuration OS / HANA
  • Migration
  • Upgrade
  • HyperCare
  • Downtime optimization
  • Troubleshooting
________________
Platform
Quelle: AIX / DB2 / FES 6.0
Ziel: RHEL 7.6 / HANA 2.0 SPS05 / FES 2020
________________
Anzahl Systeme
>5 SIDs

HANA Upgrade

________________

Business

Metal and plastic processing

________________

Location

Germany

________________

Number of employees

> 3500 employees

________________

Period

2021/03 - 2021/12

________________

SAP products used

ERP, BW, CRM, SCM

  • Upgrade HANA 1.0 -> 2.0
  • Solution design
  • Sizing
  • VMware optimizations
  • HA / DR concept
  • Scalability
  • Health checks
  • Workshops for knowledge transfer of new HANA features
  • S / 4HANA planning
  • HANA Performance Tuning
  • Capture & Replay
  • Troubleshooting
  • KPI comparison
  • Use of HANA Plan Stability
  • HyperCare phases
  • LDAP connection
  • HANA authorization design
  • SSL encryption
  • HANA Cockpit (incl. SSO)
________________
Platform
Quelle: SLES12 SP3 / HANA 1.0 SPS12
Ziel: SLES12 SP5 / HANA 2.0 SPS05
________________
Number of systems
> 20 SIDs
________________
Resources
>24 TB RAM
>1000 vCPUs on VMware 

HANA Health Checks

  ________________

Industry

Sanitary area

________________

Location

Swiss

________________

Number of employees

> 12000 employees

________________

Period

since 2021/10

________________

SAP products used

ERP, BW, CRM

  • Architecture
  • Sizing
  • VMware optimizations
  • HA / DR concept
  • Scalability
  • HANA partitioning
  • Workshops for knowledge transfer of new HANA features
  • HANA Performance Tuning
  • Capture & Replay
________________
Platform
Quelle: SLES12 SP3 / HANA 1.0 SPS12
Ziel: SLES12 SP5 / HANA 2.0 SPS05
________________
Number of systems
> 20 SIDs
________________
Resources
>24 TB RAM
>1000 vCPUs on VMware 

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