Reality Check: Server Insights
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HP & Red Hat team up bringing cost effective scale-out storage via ProLiant Gen8 Servers

Guest blog written by Richard Bland, HP Global HPC Storage
While once considered a niche solution, scale-out storage has now emerged as a compelling approach to
big data storage. Just as cost-effective scale-out server architectures have revolutionized computing infrastructure, scale-out storage offers many of the same benefits for storage. 

Red Hat Summit officially kicked off today - 6/23. Here’s the news…

Authored by: David Kling. Keynote Summaries, Jim Whitehurst, (CEO Red Hat) started things off with a RH version of creating value for customers… a good compliment to HP’s Better business outcomes. He focused on 3 reasons why SW is not optimized: SW biz models with too many features (bloat), Complexity & IT Project failure.

Catching up on the Red Hat Summit activity in Boston this week?

Authored by: David Kling The big start for the Red Hat Summit will be begin today in Boston (6/23), but here’s a re-cap of the Red Hat Partner Conference and Advisory Council from Tuesday 6/22:

Scaling up your virtualization solution on 8-socket HP ProLiant Servers

These days, when wearing my “Linux planner” hat, and with Virtualization being the “phrase that pays”, I’m often asked to help provide guidance on how to best take advantage of the technology included in our 8-socket HP ProLiant server offerings for Linux based virtualization solutions like Red Hat Enterprise Virtualization or Suse Linux Enterprise Server Xen (there’s a plethora of information out there about VMware ESX/ESXi 3.5.x and vSphere 4.0, so I’m not going to talk about that, this time around.)


The problem I’ve had, until recently, was providing actual – objective - data as a means to help illustrate my points.  For instance, I could not clearly illustrate how a snoop filter on the CPU interconnect can improve the linearity of the workload scalability in a virtualized environment (see Fig. 1).


Fig. 1: Average response time with pinned vs. un-pinned processors


 Fig. 1: Average response time with pinned vs. un-pinned processors


I was unable to demonstrate benefits of the NUMA aware scheduler that the Linux kernel uses and how it does improve performance. (In figures 2 and 3, it’s represented by the improvement in average response times from the web-servers included in the workload) when your workloads run with memory interleaving disabled in the system BIOS – see Fig. 2. Unless, for support reasons, your application vendor explicitly tells you otherwise.


Fig. 2: Average Response Times - Non-interleaved Memory Config


Fig. 2: Average Response Times - Non-interleaved Memory Config


Fig. 3: Average Response Times - Interleaved memory


Fig. 3: Average Response Times - Interleaved memory


I also used to have a hard time explaining how and why to tune the Linux kernel for these systems. For instance, I only suspected how little (none) tuning of the host platform is required in order to drive pretty significant numbers of guests  (98) in these environments - see Fig. 4. But, if you engage in some very minor tuning activities of the network stack, how those very same workload performance results can be extended even further (to 256 guests) – see Fig. 5:


Fig. 4: The system has not been tuned beyond it's "out of the box" state.


Fig. 4: The system has not been tuned beyond it's "out of the box" state.


Fig. 5: System is tuned and exhibiting linear scalability to 256 KVM guests


Fig. 5: System is tuned and exhibiting linear scalability to 256 KVM guests


As part of a joint documentation effort with Red Hat, all of the data collected has been brought together in a Reference Architecture document  - “Scaling RHEL 5.4 + KVM up to 256 Guests" available for free from Red Hat’s website.


We obviously picked the guest density to prove a point about the platform, however it’s worth mentioning that 256 guests does not represent the upper bound for the platform. It only represents where we thought the density went (far) beyond what is reasonable to expect in a production environment this day in age.


Contributed by Thomas Sjolshagen (Strategic Planner for Linux and Virtualization on scale-up x86 servers)

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About the Author(s)
  • I am part of the embedded software management team doing UEFI, HP RESTful API & Scripting tools (STK, PowerShell, HP RESTful Interface Tool), etc
  • I am part of ISS Product Marketing, currently managing couple of dual processor ProLiant servers.
  • More than 25 years in the IT industry developing and managing marketing programs. Focused in emerging technologies like Virtualization, cloud and big data.
  • Delisa Johnson currently leads successful, corporate events for HP Servers and is established as the go-to person for business unit communications regarding launches, executive meetings, wins and business updates.
  • I work within EMEA HP Servers Central Team as a launch manager for new products and general communications manager for EMEA HP Server specific information. I also tweet @ServerSavvyElla
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  • I’ll be blogging about the latest news and enhancements as it relates to HP Moonshot.
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