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Sizing sap s 4 hana using the quick sizer tool
1.
PUBLIC June, 2017 Sebastian Schmitt,
SAP Sizing SAP S/4HANA using the Quick Sizer Tool
2.
2 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Disclaimer This presentation outlines our general product direction and should not be relied on in making a purchase decision. This presentation is not subject to your license agreement or any other agreement with SAP. SAP has no obligation to pursue any course of business outlined in this presentation or to develop or release any functionality mentioned in this presentation. This presentation and SAP's strategy and possible future developments are subject to change and may be changed by SAP at any time for any reason without notice. This document is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. SAP assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP intentionally or grossly negligent.
3.
3 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Sizing Introduction and Basics Sizing Tools and Results Sizing SAP S/4HANA Wrap-up Agenda
4.
4 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ SAP HANA Sizing KPIs – Game Changer Different sizing approach: HANA sizing vs. sizing of traditional DB Memoryis the leading driver for HANA sizing Massive parallelization in analytical scenarios will have an influence on Response Times; hence CPU requirement will get more important for analytical scenarios Mixed transactionaland analyticworkloads now possible with SAP HANA but compete for shared resources Disk is required for data persistence and for logging data Disk sizing depends on type of store which is used Sufficient I/O performance required to enable processes to run with acceptable data throughput and storage system latency. Disk size Disk I/O Compared to anyDB, more CPU power is required to fully benefit from the parallel processing capabilities of HANA for optimal response times CPU Memory sizing is determined by the data footprint in SAP HANA (business and meta data in column and row store) Memory is also used by other components (e.g. HANA caches) and for processing of requests Memory Network sizing typically focuses on the bandwidth and is described in gigabits per second (gbps) Front-end Network Load
5.
5 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Memory: Leading Driver for SAP HANA Sizing The main driver for memory sizing is the table data of the planned SAP HANA system Most tables are located in the highly compressed column store of SAP HANA For working memory of the database and temporary calculations, almost the same size as for table datais required additionally A SAP HANA database includes further memory areas, such as code, stack, caches, operating system and other system files. These areas are typically small compared to a typical database
6.
6 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Approaches to SAP HANA Sizing General Information: Different Memory Areas in SAP HANA Relevant memory parts 1. The memory area allocated for table data, either row store or column store. 2. Subsequently, the buffer for dynamic and temporary computations is assumed to be equal to the table data size 3. “Offset” refers to space required for code and stack, caches and services and the operating system. Note: Used memory consists of temporary memory parts and table data, either in row store or in column store. HANA code and stack is also included, but usually negligible. Operating System HANA caches and services (code and stack included) HANA Table data (row store and column store) Temporary memory Pool Sizing “offset” Results of sizing reports Room to grow Depends on node size ~50 GB Table footprint (measured) Equal to table footprint (assumed) Sizes
7.
7 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ What are SAPS? SAP Application Performance Standard (SAPS) is a hardware-independent measurement unit that describes the throughput of hardware in an SAP environment. Laptop 1 processor Quad-core Approx. 10,000 SAPS Commodity server 2 processors 40 cores Approx. 90,000 SAPS High-end server 16 processors 244 cores Approx. 500,000 SAPS Definition of SAPS: Derived from Sales & Distribution (SD) Standard Application Benchmark 100 SAPS = 2,000 fully-processed order line items per hour For more information on SAPS, see www.sap.com/benchmark → Measuring in SAPS
8.
8 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Three-Party Collaboration Model Contributions Certified benchmarks scalable hardware Different configurations together with technology partners Service level agreements Final responsibility for sizing at customer site Expectations from benchmarking & sizing Optimal performance Suggestion for HW config. Contributions Responsetime requirements Throughput requirements Provides business input Contributions Development and provision of benchmark toolkits Regression testing for new releases Standard sizing guidelines Sizing verification processes Hardware Vendors Customer SAP SizingRecommendation CPU (SAPS) Memory (GB) Database space (GB) Disk I/O operations per sec Frontend bandwidth mbps Sizing is the joint responsibility of customer (LoB), SAP and HW Vendor. But: The main responsibility have the HW Vendor. They have to make sure that the SAP software runs smoothly at customersiteand that customers don’t run intoperformance or TCO issues due to under or over-sizedHW Examples: Custom coding Different businesses require different sizings Different applications need different amounts of CPUs Additional needs might come from additional not sized usages
9.
9 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Sizing Introduction and Basics Sizing Tools and Results Sizing SAP S/4HANA Wrap-up Agenda
10.
10 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ General Available Sizing Page (www.sap.com/sizing) Guidelines Access Sizing Guidelines Access Sizing-related Materials Tools Access Quick Sizer * Sizing Decision tree Others Training opportunities FAQs * Requires login credentials
11.
11 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Initial Calculation Method Educated guess Questionnaire without formulas For structured questions T-Shirt Sizing Simple algorithms with many assumptions Formulas Simple or more complex Standard Sizing Methods and Tools QuickSizer Supports user- based and throughput-based sizing
12.
12 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Example: Quick Sizer, SAP’s Online Sizing Tool Structured sizing questionnaires Input for – Greenfield sizing – GoingLive Check Hardware vendor contact list Available online since 1996 NewSpecialQuickSizerversionforSAP HANAavailable (since 09/2014) Free of charge As of 2016: avg. 35,000 new projects per year Characteristics Facts & Figures Scope SAP Key applications – SAP S/4HANA – SAP Business Suite and Industries – SAP NetWeaver® – etc. Sizing by users and/or by throughput
13.
13 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Sizing Introduction and Basics Sizing Tools and Results Sizing SAP S/4HANA Wrap-up Agenda
14.
14 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ SAP HANA Sizing – In a Nutshell Customer Interested in SAP S/4HANA New SAP HANA system (Greenfield Sizing) Existing SAP system migrated to HANA (Migration Sizing) Use HANA Quick Sizer Use Migration Reports Connect with hardware vendor and check for sample configuration or get started with SAP CAL Find deployment options: Appliances, SAP Tailored Datacenter Integration (TDI), Cloud via SAP Cloud Appliance Library (CAL)
15.
Greenfield Sizing
16.
16 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Greenfield Sizing for SAP S/4HANA For greenfield sizing for SAP S/4HANA, use HANA version of Quick Sizer Please note: The basics of the calculations are the same in HANA QS and in the Classic QS, e.g. the think times of the different user types (low, medium, high) are the same
17.
17 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Data Aging Data aging is a business data management concept for reducing the memory footprint in SAP HANA Only operationally relevant (“hot”/current) data is loaded into main memory of SAP HANA Other (“cold”/historical) data remains primarily stored on disk, not affecting hot data performance, yet cold data remains accessible via SQL on request
18.
18 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ HANA Quick Sizer News Data Aging in HANA Quick Sizer Since February 2016, a dataaging logichas been implementedin QuickSizer. There are two residenceperiods. One for memory (aging period)and one for disk(archiving period) There are aging objects available, if the aging column (residence time in memory) is changeable. Per default the aging period has been set to 24 months There are no aging objects available, if the aging column (residence time in memory) is empty and highlighted in blue. Since March 2017: Introduction of ‘What if analysis for the retention times (disk/memory)’
19.
19 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Example What-If Analysis Data Aging Option 1: HANAMemory Result – 4,2TB for S/4HANAServer (24 monthresidence time in memory) Option 2: HANAMemory Result – 8,9TB for S/4HANAServer(no data aging)
20.
20 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Quick Sizer News Sizing Principles for SAP Fiori Frontend Server (FES) SAP Fiori Launchpad (FLP) Logon is the most influencingsizing factor Determine Your FLP Logon Scenario for FES Sizing The total resource consumption has two parts, the one on the SAP Fiori Frontend Server, and the other one on the SAP S/4HANA Backend For Fiori Frontend Server Sizing, please use the SAP Fiori Frontend Server Sizing” in the Quick Sizer and estimate the maximal number of FLP logons per hour at peak time Please Don‘t Forget to Size the Backend for Your Application Areas
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21 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Quick Sizer News HANA Disk I/O SAP HANA requires adequate I/O performance to support processes such as Savepoint writing Delta merges Database startup times Storage systems running with SAP HANA must provide sufficient I/O performance to enable processes to run with acceptable data throughput and storage system latency.
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22 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Sizing SAP S/4HANA Embedded Analytics The goal of sizing for Sizing SAP S/4HANA Embedded Analytics is: To determine how many CPU Cores/Threads and memory are required for the processing of target number of parallel queries And at the same time achieving the average target response time. Get the latest version of the Sizing Excel Questionnaire:
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23 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Example Analytical Fiori Applications Please note: HANA is designed for OLTP+OLAP. OLTP workloads can be sized with the Quick Sizer, whereas Analytical Fiori Applications (OLAP) have to be sized additionally.
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24 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Example Analytical Fiori Applications Result Input Be Careful: The SAPS out of the analytics sizing are very “peaky SAPS”, which are needed to get the best possible response times Customers have to be asked, whether this load may be shifted to low load phases Customers have to decide, whether this optimal response times justify systems, which have X times more CPU power compared to what is needed just for the usual throughput out of the usual sizing. Customers and hardware partners have to find a balance between optimal response time on the one side and minimized costs for hardware on the other side (also higher response times might be acceptable for the business of the customer)
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Migration Sizing
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26 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Sizing Report for SAP S/4HANA Report /SDF/HDB_SIZING Described in SAP Note 1872170 – Suite on HANA sizing report Scope Runs on SAP_BASIS 620 and higher Is suitable for sizing of all Business Suite products (ERP, CRM, SCM, SRM, etc.) Not suitable for BW (Refer to SAP Note 1736976 – Sizing Report for SAP Business Warehouse on HANA) Functionality Estimates the maximum memory consumption of the database, if migrated to SAP HANA Is independent of the source database provider Considers distribution of tables to row and column store Considers differences for secondary indexes Considers compression of legacy database
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27 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ SAP Simple Finance Sizing for Migration Sizings The current version of the report is also valid for sizing of HANA 2.0. The report can also be used for different sizing scenario such as SAP Suite on HANA, SAP S/4HANA Finance, SAP S/4HANA. 1872170 – Suite on HANA sizing report
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28 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Algorithm of Sizing Report /SDF/HDB_SIZING 1 • The totalnumberof entriesof each tables is read from the database statistics 2 • A random sample of data is readfrom every tables in the system 3 • Out of this sample, the report calculates the averagenumberof bytes per column 4 • Out of the average size per column and the total record count, the uncompressed size of a columnis calculated 5 • To the uncompressed size an average compressionfactoris applied to get the estimated size in HANA. Example: A typical column “mandt” has type c and values such as ‘100’, ‘000’, ‘066’. The report will calculate an average size of 6 bytes for this column. Example: Column “mandt” has an average size of 6 bytes and the tables has 100 records. Total uncompressed size of the column is 600 bytes. The size estimation for keys (primary, secondary keys, etc.) is more complex (and more accurate) but uses the same metrics (avg. size per column and record count)
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29 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Results of Sizing Report /SDF/HDB_SIZING The sizing report for SAP ERP on SAP HANA includes the sizing projections, based on the actual table sizes in the legacy system as well as an estimation of how much the memory footprint can be reduced using functionalities that HANA will enable.
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30 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ How to Interpret the Results of the Sizing Report Column store and row store estimations have good enough accuracy (10-20%). Still, do not forget it is an estimation. Work Space (temporary memory) estimation uses a simple formula (data size in memory) * 2. Based on experiences, if the work space is bigger than 3TB, it might be oversized. Always check the top tables. Very often, you will find basis tables with deletion/archiving potential such as idoc, workflow, application log tables, etc. See SAP Note 706478 – “Preventing Basis tables from increasing considerably” for more details. The total estimated memory requirement given by the report should not be considered as the final memory sizing result. Take into account that: – Not all the server physical memory will be available to HANA (OS and other processes are run too). – There should be enough space left for future data growth or functional extension The sizing report takes a snapshot. Any growth between that date and the go-live date should be considered.
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31 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Memory Sizing Report News (1872170 – Business Suite on HANA and S/4HANA sizing report) Data aging estimationfor Workflowdocument Added to already existing data aging estimation for Application log, Change documents and iDocs. The addition of this objects completes the full coverage of “service objects”. Sizing of upgrade shadowinstances Integration in S/4HANA readiness check
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32 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Memory Sizing Report News Outlook Improve sizing of the “Work Space” (or temporary memory) Add more data aging objects to the report (especially, estimation of saving on “application objects”) Other planned enhancements Integrate IOPS Sizing Reflect further simplifications in data model
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Deployment Options
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35 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Active-Active Read Enabled Loadbalance read-intensive operations between a primary and secondary instanceof SAP HANAwith the active/ active-readenabledmode. Currently „out of the box“ about 60 Apps are Active-active read enabled. Customer build queries – Usage of generic analytical clients that use analytical CDS views – Own Smart Business Apps (and respective adjustment of the Tile configuration) – Own purely reading Apps (and respective adjustment of the App Descriptor) Sizing: Beware that in case of a fail over the complete load is on one instance For resource intensive operations available resources are used
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36 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ SAP HANA Multitenant Database Containers (MDC) MultitenantDatabase Containersprovide strong isolation capabilities – Each tenant database has its own database admin and end users, database catalog, repository, persistence, backups, traces and logs – Tenants Memory and CPU consumption can be configured independently – Integration with SAP HANA data center operation procedures, housekeeping, backups (full and/or on tenant level), etc. MultitenantDatabase Containersshare one SID and Revision – Shared installation of database system software and therefore better usage of hardware – Tenant databases are identified by name or port – SAP HANA system replication covers whole system (Sys. DB and tenants) – Additive sizing for all tenant database Targeting MCOS-likeon premise and SAPCloudPlatformscenarios with a reasonable number of tenantdatabases per system. Application SAP HANA System Application System DB Tenant DB Tenant DB
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37 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Newest Adaptions in Quick Sizer and its Sizing / Configuration Impact Introduction of Data Aging in Quick Sizer Introduction of sizing forAnalytical Applications HANAQuickSizer calculatesCPU and memoryindependently DataAgingcan reducethe memoryfootprintsignificantly Impacton CPU requirementsby applyingtheC2M ratio: Reduced memory footprint will also lead to reduced CPU requirements. But: Data aging should not reduce the required CPU resources for OLTP load Increased risk of CPU under-sizing with wrongly perceived C2M* To getthebestpossible responsetimes,theCPU requirementscan increase significantly Impacton CPU requirementsby applyingtheC2M ratio: The calculation of CPU requirement based on the memory footprint might not reflect correctly the additional CPU requirements for OLAP workloads. Increased risk of CPU under-sizing with wrongly perceived C2M* TheratiobetweenCPU and memorydiffers significantly amongsttheavailablesizing elements Impacton CPU requirementsby applyingtheC2M ratio: The calculation of CPU requirements based on the memory footprint doesn’t take these differences into account Risk of CPU over-sizing Risk of CPU under-sizing with wrongly perceived C2M* (e.g. systems with high DB load) * Please note that the CPU requirements based on the C2M ratio are minimum CPU values. This is often misunderstood by customers
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38 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Distribution: User-based Sizing Elements vs. C2M Ratio Expected shifts through Data Aging effects Expected shifts through Sizing of Analytical Apps Quick Sizer projects with higher CPU results as projected by the C2M ratio
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39 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ Deployment Options Virtualization – SAP Note1788665 Infrastructure as a Service(IaaS) – Certified and SupportedSAP HANA Directory Physical server – Certified and SupportedSAP HANA Directory
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41 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ www.sap.com/sizing – Access to Quick Sizer* – Access to sizing guidelines, for example, SAP HANA accelerators SAP Support Portal – SAP Note 1872170 – SAP S/4HANA memory sizing – SAP Note 1793345 – Sizing for Suite on HANA – SAP Note 1736976 – Sizing Report for BW on HANA – SAP Note 1514966 – SAP HANA 1.0: Sizing SAP In-Memory Database HANA Sizing – General Introduction to Sizing on SAP HANA video HANA Quick Sizer (for greenfield sizing) & SAP SoH Migration Sizing Greenfield Sizing with SAP Quick Sizer demo video Sizing information and tools Sources of published sizing documentation * Requires login credentials
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42 PUBLIC © 2017 SAP
SE or an SAP affiliate company. All rights reserved. ǀ 7 Key Points to Take Home Sizing means translating business requirements into hardware requirements The success of the sizing exercise almost entirely depends on the quality of the data Sizing involves very different people and teams within an organization Expert sizing is recommended for custom development The HANA sizing approach is different from the sizing of traditional databases Initial Sizing for HANA should be done with Quick Sizer Migration sizing of an existing system to SAP S/4HANA should be done following SAP Note 1872170
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Thank you. Contact information: Sebastian
Schmitt Product Management Performance & Scalability SAP SE Email: sebastian.schmitt@sap.com
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