disaster recovery for sap hana with suse linux
DESCRIPTION
SAP HANA typical implementations today Outlook for the next 12-18 months Disaster Recovery capabilities of SAP HANA Complete automation of Disaster Recovery for SAP HANA with SUSE Linux High Availability Speakers: Dan Lahl (VP Database Product, SAP), Markus Guertler (Senior SAP Architect, SUSE)TRANSCRIPT
Disaster Recovery forSAP HANA
with SUSE Linux
Dan Lahl, SAPVP Database Products
Markus Guertler, SUSESenior Architect SAP Linux Lab
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
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 5
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
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 6
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
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 99
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.
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 1010
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 )
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 1111
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
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 14Customer
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
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 16Customer
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
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 17Customer
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
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 19Customer
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
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 20Customer
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
OS: DNS, hostnames, virt. IPs
Primary(active)
Name Server
Index server
Secondary
Name Server
Index server
HA
Sol
utio
n P
artn
er
Clients Application Servers
HA
Sol
utio
n P
artn
er
Transferby
HANAdatabase
kernelInternalDisks
DataDisks
LogDisks
InternalDisksData
Disks
LogDisks
DataDisks
LogDisks
PRD
QA/DEV
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 21Customer
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
Secondary(active, data pre-loaded)
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
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 23Customer
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
Clients Application Servers
HA
Sol
utio
n P
artn
er
DataVolumes
LogVolume
DataVolumes
LogVolume
DataVolumes
LogVolume
DataVolumes
LogVolume
DataVolumes
LogVolume
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 24Customer
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.
Disaster Recovery Options SAP HANA System Replication4
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 26Customer
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
Data Center 2Data Center 1
OS: Mounts
DataVolumes
LogVolume
OS: DNS, hostnames, virt. IPs
Primary(active)
Name Serve
r
Index serve
r
Name Serve
r
Index serve
r
Name Serve
r
Index serve
r
Secondary(active, data pre-loaded)
Name Server
Index server
Name Server
Index server
Name Server
Index server
HA
Sol
utio
n P
artn
er
Clients Application Servers
HA
Sol
utio
n P
artn
er
DataVolumes
LogVolume
DataVolumes
LogVolume
DataVolumes
LogVolume
Transferby
HANAdatabase
kernel
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 27Customer
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):
https://scn.sap.com/docs/DOC-47702
Data Center 2Data Center 1
OS: Mounts
DataVolumes
LogVolumes
OS: DNS, hostnames, virt. IPs
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
Clients Application Servers
HA
Sol
utio
n P
artn
er
DataVolumes
LogVolumes
DataVolumes
LogVolumes
DataVolumes
LogVolumes
Transferby
HANAdatabase
kernel
DataVolumes
LogVolume
DataVolumes
LogVolume
PRD
QA/DEV
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 28Customer
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
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
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
SAP HANA SR and SUSE Linux Enterprise High Availability Extension ClusterHANA Single Box
Pacemaker
System Replication
node 1 node 2
SAP HANAPR1[primary]
SAP HANAPR1primary
SystemPR1
SystemPR1
vIP
SAP HANA SR and SUSE Linux Enterprise High Availability Extension ClusterHANA Single Box
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 HANAPR1secondary
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/
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+49 911 740 53 0 (Worldwide)www.suse.com
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Appendix
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 48
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 49
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
Further options for System Replication
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 51Customer
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
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 52Customer
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
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 54Customer
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
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 55Customer
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
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 56Customer
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.
Roadmap
© 2014 SAP AG or an SAP affiliate company. All rights reserved. 58Customer
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)