VMWorld 2015 Session Recap
I’m almost fully recovered from VMWorld, which was probably one of my busiest and most enjoyable VMWorld’s I’ve had in my 6 plus years at VMware because of the interaction with attendees, customers, and partners. I’ll be doing a series of Post-VMWorld Blogs focused on my SAP HANA Software-Defined Data Centers sessions but my first blog will cover the misconceptions associated with sizing SAP HANA databases on vSphere. There are many good reasons to upgrade to vSphere 6.0, going beyond the 1TB monster virtual machine limit in vSphere 5.5 when deploying SAP HANA databases is not necessarily one of them.
SAP HANA is no longer just an in-memory database, it is now a data management platform. It is NOT confined by the size of available memory since the SAP HANA warm data can be stored on disk in a columnar format and accessed transparently by applications.
What this means is the 1TB monster virtual machine maximum in vSphere 5.5 is an artificial barrier. SAP HANA multi-terabyte size databases can be easily virtualized with vSphere 5.5 using Dynamic Tiering, Near-Line Storage, and other memory management techniques SAP has introduced to the SAP HANA Platform to optimize and reduces HANA’s in-memory footprint.
SAP HANA Dynamic Tiering (DT)
SAP HANA Dynamic Tiering was introduced last year in Support Pack Stack (SPS) 09 for use with BW, Dynamic Tiering allows customers to seamlessly manager their SAP HANA disk based “Warm Data” on an Extended Storage Host, essentially placing data which does not need to be in-memory on disk. The guidance SAP gives when using the SAP HANA Dynamic Tiering option for SPS 09 is up to 20% of in-memory data can reside on the Extended Storage (ES) Host, for SPS 10 up to 40% can reside on the ES Host, and in the future up to 70% of the SAP HANA data can reside on the ES Host. So in the future the majority of SAP HANA data which was once in-memory can reside on-disk.
Near-Line Storage (NLS)
In addition to the reduction of the SAP HANA in-memory footprint DT affords customers, Near-Line Storage should be considered as well. With NLS, data is moved outside of the SAP HANA database proper to disk and classified as “Cold”, due to its infrequent accessed and can only be accessed read only. SAP provides examples showing NLS can reduce the HANA database in-memory requirements by several Terabytes (link below).
It is also important to note that both the DT Extended Storage Host and NLS solutions do not require certified servers or storage, so not only has SAP given customers the ability to run SAP HANA in a reduced memory footprint, customers can run on standard x86 hardware as well.
There is a white paper authored by Priti Mishra, Staff Engineer, Performance Engineering VMware, which is an excellent read for anyone considering DT or NLS options. “Distributed Query Processing in SAP IQ on VMware vSphere and Virtual SAN”
Importance of the VMware Software Defined Data Center
To their credit SAP has taken a leadership role with HANA’s in-memory columnar database computing capabilities and as HANA has evolved the sizing and hardware requirements have evolved as well. Rapid change and evolving requirements are givens in technology; the VMware Software Defined Data Center provides a flexible and agile architecture to effectively react to change by recasting compute, network, and storage resources, in a centrally managed manner.
As a concrete example of the flexibility VMware’s Platform provides, Figure 1. illustrates the evolution of SAP HANA from SPS 07 to SPS 09. For customers who would like to take advantage of SAP HANA’s multi-temperature data management techniques but initially deployed SAP HANA on SPS 07 (all in-memory); through virtualization customers can reclaim and recast memory, storage, and network resources in their virtual HANA landscape to reflect the latest architectural advances and memory management techniques in SPS 10.
Figure 1. SAP HANA Platform: Evolving Hardware Requirements
Since SAP HANA can now run in a reduced memory footprint, customers who licensed HANA to be all in-memory can use virtualization to reclaim memory and deploy additional virtual databases and make HANA pervasive in their landscapes.
As a general rule, in any rapidly changing environment The VMware Software-Defined Data Center provides an agile platform which can accommodate change and also protect against capital hardware investments that may not be necessary in the future (certified vs. standard x86 hardware). For that matter, the cloud is a good option to deploy any rapidly changing application/database in places like VMware vCloud Air, Virtustream, or Secure-24 just to mention a few.
Virtual SAP HANA Back on track
After speaking with session attendees, customers, and partners, at VMworld about SAP HANA’s Multi-temperature management capabilities, I was happy to hear they will not be delaying their virtual HANA deployments due to the vSphere 6.0 roadmap certification timeline. As I said earlier, the 1TB monster virtual machine maximum in vSphere 5.5 is an artificial barrier. It really is a worthwhile exercise to take a closer look at the temperature of your data, age of your data, and your access requirements in order to take full advantage of all the tools and features SAP provides their customers.
I was also encouraged to hear from many session attendees that my presentation at VMWorld brought the SDDC from concept closer to reality by demonstrating actual mission critical database/application use cases. My future post VMWorld blogs will focus on how I deconstructed the SAP HANA Networks Requirements document and transformed that into a virtual network design using VMware NSX from my desktop. I’ll also cover Software Defined Storage, essentially translating SAP’s Multi-Temperature Storage Options into VMware Virtual Volumes and Storage Containers.
“SAP HANA SPS10- SAP HANA Dynamic Tiering”; (SAP Product Management)
“Distributed Query Processing in SAP IQ on VMware vSphere and Virtual SAN”; Priti Mishra, Performance Engineering VMware
Blog: Bob Goldsand; “SAP HANA Dynamic Tiering and the VMware Software Defined Data Center”