Disaster Recovery for SAP HANA with SUSE Linux

Disaster Recovery forSAP HANA

with SUSE Linux

Dan Lahl, SAPVP Database Products

[email protected]

Markus Guertler, SUSESenior Architect SAP Linux Lab

[email protected]

mailto:[email protected]

mailto:[email protected]

Agenda

• SAP HANA typical implementations

• Outlook for the next 12 – 18 months

• Disaster Recovery Capabilities of SAP HANA

• Automate SAP HANA System Replication

• Setup and Implementation

• Outlook: Scale Out Scenario

• Our Community

For decades, a complex landscape of core, yet disparate, technologies have been cobbled together to solve business problems

HOLDING YOU BACK

DATA STORAGE & RETRIEVAL ANALYSIS FORECASTING

SENSING & UNDERSTANDING

REAL-TIME SHARING

These technologies are critical to success but the infrastructure is

© 2014 SAP AG or an SAP affiliate company. All rights reserved. 4

SAP HANA(DRAM)

An innovative data management and

application approach for transactions, analytics and custom development using

an in-memory platform

One in-memory atomic copy of data for Transactions + Analysis

Eliminate unnecessary complexity and latency Less hardware to manage Accelerate through innovation and simplification

Re-think Applications with SAP HANA in-memory computingDon’t just Speed Up IT, rather transform your applications and business

Transact

ETL

Analyze

ETL

Accelerate

Cache

3 copies of data in different data models Inherent data latency Poor innovation leading to wastage

Separated Transactions + Analysis + Acceleration processes

“In-memory computing will have a long-term, disruptive impact by radically reducing overall total cost of ownership – lower power, cooling, floor space, resources and fewer servers.”

VS


Any AppsAny App Server

SAP Business Suite and BW ABAP App Server

JSONR Open ConnectivityMDXSQL

SAP HANA Platform

SAP HANA Platform – More than just a database

SAP HANA platform converges Database, Data Processing and Application Platform capabilities & provides Libraries for predictive, planning, text, spatial, and business analytics so businesses can operate in real-time.

Adm

inistration

Extended Application Services

Integration Services

Deployment:

Database Services

De

velo

pm

en

t

OLTP | OLAP | Search | Text Analysis |Predictive | Events | Spatial | Rules | Planning | Calculators

Processing Engine

Application Function Libraries & Data ModelsPredictive Analysis Libraries | Business Function Libraries | Data Models & Stored Procedures

Data Virtualization | Replication | ETL/ELT | Mobile Synch | Streaming

App Server| UI Integration Services | Web Server

On-Premise | Hybrid | On-Demand

Supports any Device


Renovate existing systems while enabling future breakthroughs

Operational Analytics

Big Data Warehousing

Predictive, Spatial & Text Analytics

REAL-TIME ANALYTICS

SAP HANA PLATFORM

Database & Data Processing

Services

Application Platform Services

Integration & Data Virtualization

Services

Mission-Critical Deployment

Services (Appliance, Cloud)

Sense & Respond

Planning & Optimization

Consumer Engagement

REAL-TIME APPLICATIONS

SAP BusinessSuite

& SAP BusinessOne

30+ HANA Apps, Accelerators

& RDS

StartUp & ISV Apps

Operational Datamarts

EDW on HANA (BWonH)

Industry Platforms

(Healthcare)

Use this title slide only with an image

See how Unilever uses SAP HANA to transform supply chain decision making processes.

Hear about itelligence’s easy and smooth migration process with SAP HANA and SAP

HANA Enterprise Cloud.

Hear how Joskin is accelerating global expansion with SAP Business Suite powered by

SAP HANA.

Hear how automotive supplier Faurecia validated SAP HANA in a proof of concept to do

complex MRP runs much faster

Hear how Usha is using SAP ERP powered by SAP HANA to expand manufacturing capacity

and margins.

City of Boston uses SAP HANA to improve citizens’ experience.

MOLSON Coors Transforms Reporting with SAP HANA

Learn how Centerpoint Energy utilized SAP HANA to build three game changing applications

for Centerpoint and its customers.

Hear how NCT is using HANA to provide better treatments and outcomes for cancer patients

http://www.youtube.com/embed/u-MQo3UwnLY/?autoplay=1&rel=0&feature=youtu.be

http://www.youtube.com/embed/7_X79rBPNCY/?autoplay=1&rel=0&feature=youtu.be

http://www.youtube.com/embed/3XZE8hx4EK0/?autoplay=1&rel=0&feature=youtu.be

http://www.youtube.com/embed/Pd-YL1GvFHs/?autoplay=1&rel=0&feature=youtu.be

http://www.youtube.com/embed/9dAm9EFwk-E/?autoplay=1&rel=0&feature=youtu.be

http://www.youtube.com/embed/0gepYGx0Yvg/?autoplay=1&rel=0&feature=youtu.be

http://www.youtube.com/embed/TBZAsh4L6xs/?autoplay=1&rel=0&feature=youtu.be

http://www.youtube.com/embed/Ggr2EhoYMkI/?autoplay=1&rel=0&feature=youtu.be

http://www.youtube.com/embed/cNyoHje7O4o/?autoplay=1&rel=0&feature=youtu.be


CenterPoint Call Center Predictive Analytics Engine (PAE)‘Likeliness for the Customer’s Call’

Customer VisionProgram

The CRM PAE was developed to understand the ‘likeliness of the customer’s call’ and empower the Call Center Agents to analyze ~40 business scenarios (High Bill, Disconnect, Outages, Pay my Bill, etc) by predicting why the customer might be calling – potentially reducing the Agent’s Call Handling Time (AHT).

PAE analyzes data across 7 systems, for ‘Super 8’ processes (40 sub-processes- High Bill/ Re-connect/ Outage/Move-in Move-out/Street Light Enquiry / Home Service Plus and more), fetches 116 dynamic data points to generate 55 dynamic messages within 5 seconds of the call, and recommends agents with a likely reason for the customer’s call.

HANA has significantly improved the performance of PAE, with run times reduced from 90 seconds to just one second—a 9,000% improvement in many cases. Output of PAE is also shared across IVR, WEB and Power Alert Services

The PAE process dramatically reduces the average 14 clicks to 2 clicks and thereby reduces the handling time (AHT) and improves customer satisfaction. What’s more, the system can now use the HANA-supplied data to proactively communicate with customers or deflect a call.


CenterPoint ‘High Volume’ Customer Segmentation for Marketing’

Customer VisionProgram

• Using CRM segment builder helps teams develop more personalized, targeted campaigns based on analytics, helping ensure that the right message is sent to the right customer through the right channel.

• CenterPoint’s marketing team couldn’t easily identify key audiences to contact, create targeted communications or analyze the results of their marketing programs, compromising the success of their efforts.

• For the first time, our teams now are using the same single source of truth to discuss and report sales opportunities, activities, marketing campaigns, marketing effectiveness and results using Segment builder on HANA, we provide CNP Marketing with relevant information that they can act upon and help us build more productive relationships with customers.

Using HANA, Marketing is able to create targeted campaigns with up to date information in minutes. Used to take weeks (with historical data) and now takes minutes

Segments ~ 5 million customers (~10 Million Business Partners )


CenterPoint Smart Meter AnalyticsForecasting Model Engine

• Prior to FME, Load Studies based upon IDR data were routine from the 1980’s through September 1999 . . . (then dormant)

Jointly, ERCOT Load Research Samples of residential and small commercial customers were discontinued effective JAN 2012.

• Load Studies incorporating SMART METER data significantly improves upon traditional methods

• solid estimates of Unbilled Revenues & weather impacts, timely Load Studies and an improved understanding of changes in usage

• Applications built on SAP HANA to handle BIG DATA (15 minutes Interval data for ~2.2 million premises >10 billion records)

• Speed of analysis on large volumes of data• Insight into their business process information for

better decision making• Manage multiple data sources and deliver a single

version of truth • Platform for driving innovation and advanced analytics

use cases for different business units• Leverage SAP HANA technology such to address the

Big Data challenge and do what was not possible till now

• Empower business users to access data quickly and seamlessly to drive self-service BI and analysis

Use this title slide only with an image

High Availability & Disaster Recovery

Customer

http://www.saphana.com/docs/DOC-2010

© 2014 SAP AG or an SAP affiliate company. All rights reserved. 13Customer

High Availability – Disaster RecoveryOverview

Business Continuity

High Availability

per Data Center

Disaster recovery

between Data Centers

SAP HANA Host Auto-Failover(Scale-Out with Standby)

SAP HANA Storage Replication

SAP HANA System Replication● Performance Optimized

● Cost Optimized

SAP HANA System Replication● Performance Optimized

● Cost Optimized

1

2

3

4


HA & DR Concepts in generalClassification of solutions

RPO RTO

operation resumed…

time

Sync or backup

…system operational

design & prepare detect recover perf. ramp

KPIs:• Recovery Point Objective (RPO) = worst-case data-loss• Recovery Time Objective (RTO) = time to recover from outage

*synchronous solution

Solution Used for Cost RPO RTO Perf. rampBackup & Recovery HA & DR $ high high med

SAP HANA Host Auto-Failover HA $ 0 med long

SAP HANA Storage Replication w/ QA, Dev. DR $$ 0* med long

SAP HANA System Replication HA & DR $$$ 0* low shortSAP HANA System Replication w/ QA, Dev. HA & DR $**/$$ 0* med long

** single host installations

High Availability Options Scale-Out or Host Auto-Failover1


SAP HANA High Availability: Host Auto-Failover

High Availability configuration•N active servers in one cluster•M standby server(s) in one cluster•Shared file system for all servers

Services•Name and index server on all nodes•Statistics server (only on one active server)•Name server active on Standby

Failover•Server X fails•Server N+1 reads indexes from shared storage and connects to logical connection of server X•Storage Connector API ensures remount of necessary disk areas(Note 1900823 - Storage Connector API Attachments)

Sha

red

Sto

rage

SA

N S

tora

ge

Sto

rag

e C

on

nect

or

API

Server 1

Server 2

Server 3

Server 4

Server 5

Server 6

Standby Server

https://service.sap.com/sap/support/notes/1900823


HANA High AvailabilityHost Auto-Failover (standby)

Different implementation of High Availability by HW partners

Using storage solution inside Using internal disk

Name Server

Index Server

StandbyName Server

Index Server

Name Server

Index Server

DataDisks

LogDisks

DataDisks

LogDisks

DataDisks

LogDisks

GPFS

GPFS

Name Serve

r

Index server

Name Serve

r

Index server

Name Serve

r

Index server

Name Serve

r

Index server

Data

Log

Data

Log

Data

Log

Name Serve

r

Index server

Name Serve

r

Index server

Name Serve

r

Index server

Name Serve

r

Index server

Data

Log

Data

Log

Data

Log

Name Serve

r

Index server

Name Serve

r

Index server

Name Serve

r

Index server

Name Serve

r

Index server

Data

Log

Data

Log

Data

Log

High Availability Options SAP HANA System Replication2


SAP HANA High Availability: System ReplicationPerformance Optimized

Performance optimized option

Secondary system completely used for the preparation of a possible take-over

Resources used for data pre-load on Secondary

Take-overs and Performance Ramp shortened maximally

Data Center 1

OS: DNS, hostnames, virt. IPs

Primary(active)

Name Server

Index server

Secondary(active, data pre-loaded)

Name Server

Index server

HA

Sol

utio

n P

artn

er

Clients Application Servers

HA

Sol

utio

n P

artn

er

Transferby

HANAdatabase

kernelInternalDisks

InternalDisks

DataDisks

LogDisks

DataDisks

LogDisks


SAP HANA High Availability: System ReplicationCost Optimized

Cost optimized with

Operating non-prod systems on Secondary

Resources freed (no data pre-load) to be offered to one or more non-prod installations

During take-over the non-prod operation has to be ended

Take-over performance similar to cold start-up

Data Center 1


Primary(active)

Name Server

Index server

Secondary

Name Server

Index server

HA

Sol

utio

n P

artn

er


HA

Sol

utio

n P

artn

er

Transferby

HANAdatabase

kernelInternalDisks

DataDisks

LogDisks

InternalDisksData

Disks

LogDisks

DataDisks

LogDisks

PRD

QA/DEV


SAP HANA High Availability Comparison of minimal setups for available solutions

Master Name Server

Index Server

DataDisks

LogDisks

active standby

Index Server

Name Server

Storage System

Primary(active)

Name Server

Index server


Name Server

Index server

Transferby

HANAdatabase

kernelInternalDisks

InternalDisks

DataDisks

LogDisks

DataDisks

LogDisks

Secondary

Name Server

Index server

DataDisks

LogDisks

DataDisks

LogDisks

PRD

QA/DEV

Performance optimized(data pre-loaded)

or

Cost optimized

Scale-Out 1+1(Host Auto-Failover)

System Replication with both alternatives (1+1)

Disaster Recovery Options SAP HANA Storage Replication3


SAP HANA Disaster Recovery: Storage ReplicationCluster across Data Centers with non-prod on 2nd site

Arrangement usually offered with a strong part of hardware partners involvement Support issues handled

by/routed to HW partners

TCO reduction by combined operation with non-prod on Secondary Needs another disk stack for

non-prod usage load

Cluster management often included and delivered as a whole package

Data Center 2Data Center 1

OS: Mounts

DataVolumes

LogVolume

OS: DNS, hostnames

Primary

Name Serve

r

Index server

Name Serve

r

Index server

Name Serve

r

Index server

Secondary Prod. (inactive), QA&DEV (active)

Name Server

Index server

Name Server

Index server

Name Server

Index server

HA

Sol

utio

n P

artn

er

Sto

rage

M

irror

ing


HA

Sol

utio

n P

artn

er

DataVolumes

LogVolume

DataVolumes

LogVolume

DataVolumes

LogVolume

DataVolumes

LogVolume

DataVolumes

LogVolume


HA & DR solutions from hardware vendors with certified HANA offering – May 2014*

(only China)

Scale Out (BW) S - L M M, L M M S - L M M M

High Availability X X X X X X X X X

DR – Storage Repl.: Async

X X,X X planned

DR – Storage Repl.: Sync

X X X X X X

* For most up to date list please go to the SAP Product Availability Matrix (Westmere) or http://scn.sap.com/docs/DOC-52522 (IvyBridge)

All certified synchronous and asynchronous solutions for SAP HANA Storage Replication are listed in SAP note 1755396.

http://service.sap.com/pam

http://scn.sap.com/docs/DOC-52522


Disaster Recovery Options SAP HANA System Replication4


SAP HANA Disaster Recovery: System ReplicationCluster across Data Centers with DB controlled transfer

Performance optimized option Faster Take-Over Shortened Performance Ramp

(seconds to less minutes) SYNC & ASYNC possible

Several cluster options Some HW Partners offer pre-

packaged options

Step-by-Step Implementation Guide (updated recently to SPS8): https://scn.sap.com/docs/DOC-47

702


OS: Mounts

DataVolumes

LogVolume


Primary(active)

Name Serve

r

Index serve

r

Name Serve

r

Index serve

r

Name Serve

r

Index serve

r


Name Server

Index server

Name Server

Index server

Name Server

Index server

HA

Sol

utio

n P

artn

er


HA

Sol

utio

n P

artn

er

DataVolumes

LogVolume

DataVolumes

LogVolume

DataVolumes

LogVolume

Transferby

HANAdatabase

kernel

https://scn.sap.com/docs/DOC-47702



SAP HANA Disaster Recovery: System ReplicationCluster across Data Centers with non-prod operation on 2nd site

Cost Optimized option

SYNC & ASYNC possible

TCO reduction by combined operation with non-prod on Secondary

Needs another disk stack for non-prod usage load

Step-by-Step Implementation Guide (updated recently to SPS8):



OS: Mounts

DataVolumes

LogVolumes


Primary(active)

Name Serve

r

Index serve

r

Name Serve

r

Index serve

r

Name Serve

r

Index serve

r

Secondary(active,)

Name Server

Index server

Name Server

Index server

Name Server

Index server

HA

Sol

utio

n P

artn

er


HA

Sol

utio

n P

artn

er

DataVolumes

LogVolumes

DataVolumes

LogVolumes

DataVolumes

LogVolumes

Transferby

HANAdatabase

kernel

DataVolumes

LogVolume

DataVolumes

LogVolume

PRD

QA/DEV




SAP HANA in Data CentersCluster Manager with direct SAP HANA System Replication Support

SUSE Cluster Included with “SUSE SLES for SAP Applications” Developed in the SAP Linux Lab Blog: Fail-Safe Operation of SAP HANA®: SUSE Extends Its High-Availability Solution

HP Service Guard Directly available from HP and HP drives the implementation process Link for further information: o Reference Guide: HP ServiceGuard Extensions, March 2014o User Guide: Managing HP ServiceGuard Extensions for SAP for Linux, December 2013

SAP Landscape Virtualization Manager (SAP LVM) Consulting package to create a cluster manager with SAP LVM available

Other cluster managers In pipeline or can be adapted with individual consulting packages

Note: Solution certification is not offered for cluster managersSupport is handled by solution partner directly

http://scn.sap.com/community/hana-in-memory/blog/2014/04/04/fail-safe-operation-of-sap-hana-suse-extends-its-high-availability-solution

http://scn.sap.com/community/hana-in-memory/blog/2014/04/04/fail-safe-operation-of-sap-hana-suse-extends-its-high-availability-solution

http://h20566.www2.hp.com/portal/site/hpsc/template.PAGE/action.process/public/psi/manualsDisplay/?sp4ts.oid=4181640&javax.portlet.action=true&spf_p.tpst=psiContentDisplay&javax.portlet.begCacheTok=com.vignette.cachetoken&spf_p.prp_psiContentDisplay=wsrp-interactionState=docId=emr_na-c04197457%7CdocLocale=en_US&javax.portlet.endCacheTok=com.vignette.cachetoken






High Availability for SAP with SUSE

Around 8 years of experience with High Availability for SAP NetWeaver Systems

Starting around 1 year ago to implement the HANA SR Automation

Solutions are jointly developed between SUSE, SAP, customers and partners in the SAP Linux Lab in Walldorf

HANA in a SUSE® Linux Enterprise High Availability Extension ClusterHANA Single Box – System Replication / Scale-UP

SAP HANA SR and SUSE Linux Enterprise High Availability Extension ClusterHANA Single Box

Pacemaker

System Replication

node 1 node 2

SAP HANAPR1primary

SAP HANAPR1secondary

SystemPR1

SystemPR1

vIP


Pacemaker

System Replication

node 1 node 2

SAP HANAPR1primary


SystemPR1

SystemPR1


Pacemaker

System Replication

node 1 node 2

SAP HANAPR1[primary]

SAP HANAPR1primary

SystemPR1

SystemPR1

vIP


Direction of the system replication will only be changed if the parameter AUTOMATED_REGISTER is been changed to “true”

Pacemaker

System Replication

node 1 node 2


SAP HANAPR1primary

SystemPR1

SystemPR1

vIP

From Concept to Implementation

SAP HANAPrimary

SAP HANASecondary

vIP

SAPHana Master/Slave ResourceMaster Slave

SAPHanaTopology Clone ResourceClone Clone

suse01 suse02

Cluster Communication

Fencing

Setup and Implementation

Install package SAPHanaSR with two resource agents: SAPHanaTopology and SAPHana

Setup Guide SAPHanaSR HAWK Wizard

and

Four Steps to Install and Configure

Install HANA

Configure System Replication

Install and initialize SUSE Cluster

Configure SR Automation using HAWK wizard

SAPHanaSR HAWK WizardTechnical preview included in the shipping.

HANA System Replication in HAWK

The Five Interfaces

HANA Startframework: sapstartsrv / sapcontrol / HDB (calls, output format “GetProcessList”)

HANA-Topology: landscapeHostConfiguration.py (rc, output format)

SR-Topology: hdbnsutil (calls, output format “-sr_state --sapcontrol=1”)

SAP Hostagent: saphostctrl(call, output format “ListInstances”)

SR-Status: hdbsql (now) / systemReplicationStatus.py (future) (now; rc, calls, output format)

Outlook: HANA in a SUSE Linux Enterprise High Availability Extension ClusterHANA Multi Node – System Replication / Scale-OUT

This scenario is currently in development

site 1 site 2

N M

A B

N M

A B

HANADatabase

HANAmemory-preload

A B

SystemReplication

HANA PR1primary

HANA PR1syncmem

resource failover

active / active

Our Community

Developed jointly in the SAP Linux Lab

Integration of the solution in partner products

Upstream open-source project

Scoping, discussing and implementing Scale-Out

You are invited to join our community :-)Visit our booth (#180) or contact us via email [email protected]

HANA SR Automation using SUSE

Reduces complexity- by automating the sr-takeover and IP failover (unbind / bind)

Reduces risk- by having always a consistent picture of the HANA topology

Increases reliability- due to short takeover times

Thank you.

Find our Best Practices at:

www.suse.com/products/sles-for-sap/resource-library/

Corporate HeadquartersMaxfeldstrasse 590409 NurembergGermany

+49 911 740 53 0 (Worldwide)www.suse.com

Join us on:www.opensuse.org

http://www.opensuse.org/

Unpublished Work of SUSE. All Rights Reserved.This work is an unpublished work and contains confidential, proprietary and trade secret information of SUSE. Access to this work is restricted to SUSE employees who have a need to know to perform tasks within the scope of their assignments. No part of this work may be practiced, performed, copied, distributed, revised, modified, translated, abridged, condensed, expanded, collected, or adapted without the prior written consent of SUSE. Any use or exploitation of this work without authorization could subject the perpetrator to criminal and civil liability.

General DisclaimerThis document is not to be construed as a promise by any participating company to develop, deliver, or market a product. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. SUSE makes no representations or warranties with respect to the contents of this document, and specifically disclaims any express or implied warranties of merchantability or fitness for any particular purpose. The development, release, and timing of features or functionality described for SUSE products remains at the sole discretion of SUSE. Further, SUSE reserves the right to revise this document and to make changes to its content, at any time, without obligation to notify any person or entity of such revisions or changes. All SUSE marks referenced in this presentation are trademarks or registered trademarks of Novell, Inc. in the United States and other countries. All third-party trademarks are the property of their respective owners.

Appendix


KAESER: Transforming Operations with SAP® Business Suite powered by SAP HANA®

Company

KAESER KOMPRESSOREN SE

Headquarters

Coburg, Germany

Industry

Industrial machinery and components

Products and Services

Compressed air systems and compressed

air consulting services

Employees

4,400

Revenue

€600 million (2012)

Web Site

www.kaeser.com

Partner

SAP Consulting organization

Objectives

Create an innovative IT environment that supports the move toward a solution-provider business model

Enhance existing business processes and leverage the power of Big Data and predictive maintenance to become more proactive, customer oriented, and competitive

Leverage the SAP HANA® platform to transform and simplify the entire SAP® solution landscape

Technical implementation

Successful migration of the SAP Customer Relationship Management (SAP CRM) application to SAP HANA in just 2.5 months and with just 1.5 days of downtime

Great collaboration with SAP during all phases of the project

Future plans

Launch predictive maintenance capabilities with a custom solution based on SAP CRM powered by SAP HANA to step up customer service

Migrate all SAP Business Suite applications, such as the SAP ERP, SAP Supply Chain Management, and SAP NetWeaver® Business Warehouse applications, to SAP HANA

Deploy SAP CRM powered by SAP HANA in the cloud with other cloud offerings like the SAP JAM social software platform to enable a mobile and social CRM strategy

“We will leverage the full power of SAP HANA to enhance existing business processes, introduce entirely new ones, and reduce total cost of ownership. We are off to a very good start with the smooth and fast migration of SAP CRM to SAP HANA, which will be followed by other SAP Business Suite applications and custom solutions.”

Falko Lameter , CIO, KAESER KOMPRESSOREN SE

SuccessfulSuccessful and smooth production launch of SAP CRM powered by SAP HANA

FasterFive times faster database response times

SimplerSimpler and more agile IT landscape and business processes

SolidFoundation for predictive maintenance

30112 (14/03) This content is approved by the customer and may not be altered under any circumstances.

Public

http://www.kaeser.com/

Further options for System Replication


SAP HANA Zero Downtime maintenanceFeatured by SAP NetWeaver ABAP stack

As an evolution of “Near Zero Downtime Maintenance”, SPS7 now offers

Zero Downtime Maintenance Based on connectivity suspend feature of the SAP NetWeaver ABAP

stack (SAP note 1913302)o DBSL of the database interface decouples transaction management

between ABAP and HANA databaseo This keeps transaction on ABAP layer alive and allows to change

components (software versions) on the layers below on secondary (shadow) HANA instance

Further information also in Step-by-Step Implementation Guide for SAP HANA System Replication: https://scn.sap.com/docs/DOC-47702

Hardware mix (SAP note 1984882 - Using HANA System Replication for Hardware Exchange with minimum Downtime)

Sync/Async mirrored

redo log writing

Transport incremental data

Walldorf

Primary

NameServer

Indexserver

NameServer

Indexserver

NameServer

Indexserver

DataVolumes

LogVolume

DataVolumes

LogVolume

Rot

Secondary

NameServer

Indexserver

NameServer

Indexserver

NameServer

Indexserver

DataVolumes

LogVolume

DataVolumes

LogVolume

SAP HANA Version SAP HANA Version +1

SoftwareUpgrade

Order

SAP NetWeaverABAP Server

DBSL





Data Center Setups with Pre-load OptionMulti Tier System Replication – Cascading Systems

Production Local standbywith data preload

Remote standby systemwith or without preload(mixed usage with non-prod.)

Available with SAP HANA (Three cascading systems with SPS7)

Data Center Data Center

Sync

Async

SAP Business Systems @ SAPSAP HANA Usage in Production


SAP Business Systems @ SAPHANA usage in production

SAP’s financial accounting system runningSAP Business Suite on HANA Scale-Out 2+1 (local High Availability) Secured with SAP HANA System Replication

SAP’s CRM system runningSAP CRM on HANA Scale-out 2+1(local High Availability) Secured with SAP HANA System Replication

SAP’s BW system runningSAP CRM on HANA Scale-Out 8+1(local High Availability) No DR

Distance: about 10 kmRedundant connections: 3

Data Center: St. Leon-Rot

Data Center: Walldorf


SAP’s financial accounting system runningSAP Business Suite on HANA

Technical details

Server Hardware Manufacturer IBM CPU Model 8 CPUs with 10 core , Xeon E7-8870 @2.4GHz Memory 2 x 4096 GB Operating System SUSE Linux Enterprise Server 11.2 Scale-out Scale-out plus standby (2+1) Storage IBM GPFS file system

Restart Restart Time (min)/Takeover 5 – 15 min Performance Ramp 1 h – 1,5 h Loading RowStore 3 min

Business SAP Application SAP Business Suite on HANA Number of named Users 65000 Transactions per day tbc


SAP’s financial accounting system runningSAP Business Suite on HANA

Database DB Version HANA 1.0 Revision 73 DB Usage Custom DR Solution SAP HANA System Replication Replication mode syncmem Distance between Data Centers 10 km Bandwidth for System Replication 10 Gbit Total database size 1,7 TB Column Store size 1460 GB Row Store size 140 GB Avg local log write wait time 210 µs (for avg. log buffer size of 9,5 MB)

Avg remote log write wait time 448 µs (for avg. log buffer size of 9,5 MB)

Delta data shipping throughput 108 MB/sec Log backup (log volume) per day 165 GB Transferred data volume between data centers per day 1,7 TB

Backup Storage IBM GPFS file system backup (local disks) Avg. size of full data backup 1,7 TB Throughput 775 MB/s (2800 GB/h) Avg. runtime of backup (to FS) 41 min Estimated total recovery time 340 min Estimated data recovery time 70 min (~1,7 TB) Estimated log recovery time 270 min (~3,7 TB – log backups of 3 weeks)

[1] In a similar productive SAP system the recovery was done with a three weeks old backup (1,8 TB) and the log backups of these three weeks (7 TB). The data recovery took 70 minutes and the log recovery took 9 hours – makes roughly 10 hours recovery time for this system.

http://help.sap.com/hana_appliance

Roadmap


SAP HANA Disaster RecoveryNews with SAP HANA SPS07 and Beyond

System Replication extension

Multi Tier System Replication allowing first 1:n setups: Three cascading systems in a row

Zero Downtime maintenance Compressed log transfer Basic encryption for internal communication

Planned beyond

System Replication extension oPure Log-based transferoBackup on shadow instanceoOnline Add Host & Remove Host on

SecondaryoActive/Active Operation (r/o reporting on

Sec.)oMore 1:n relationships for shadow

instancesoTime travel via internal snapshots on

shadow instance to handle logical errorsoMore asymmetric options (nm)oTime delay option between sites

Log ShippingoBased on backup files (initial data, sub

sequential log, steady roll forward)

Disaster Recovery for SAP HANA with SUSE Linux

Software

Transcript of Disaster Recovery for SAP HANA with SUSE Linux