Archive for the ‘VMware’ Category

Could DINO Be The Future Of vSphere NUMA Scheduler?

December 24, 2012 3 comments


DINO the future of vSphere NUMA scheduler uh!220px-Dino_Harikalar_Diyari_Flintstones_06029_nevit
First thing first, DINO is not Dino… Dino is one of the  The Flintstones’s fictional characters.
Flintstones. Meet the Flintstones. They’re the modern stone age family.
From the town of Bedrock, They’re a page right out of history…yabba dabba doo time!
All right, all right. DINO is not Dino. So what is DINO? I leave this for later.
For now let’s focus on NUMA design and vSphere NUMA Scheduler.

So what is NUMA?

Wikipedia says: “Non-Uniform Memory Access (NUMA) is a computer memory design used in multiprocessing, where the memory access time depends on the memory location relative to a processor. Under NUMA, a processor can access its own local memory faster than non-local memory, that is, memory local to another processor or memory shared between processors. NUMA architectures logically follow in scaling from symmetric multiprocessing (SMP) architectures”

NUMA is often contrasted with Uniform Memory Access (UMA) which is a shared memory architecture used in parallel computers. All the processors in the UMA model share the physical memory uniformly. In a UMA architecture, access time to a memory location is independent of which processor makes the request or which memory chip contains the transferred data. Read more at Wikipedia.

Figure 1 shows a classic SMP system where there is usually a single pool of memory also referred as an Uniform Memory Access (UMA). That is memory access is equal for all processors. Contention-aware algorithms works well here.

Figure 1 : SMP system - Uniform Memory Access (UMA)

Figure 1 : SMP system – Uniform Memory Access (UMA)

The main drawback of the UMA architecture is that it doesn’t follow in scaling from symmetric multiprocessing (SMP) architectures where many processors must compete for bandwidth on the same system bus. That’s why server vendors added NUMA design on top of SMP design. The first commercial implementation of a NUMA-based Unix system was the Symmetrical Multi Processing XPS-100 family of servers, designed by Dan Gielan of VAST Corporation for Honeywell Information Systems Italy (HISI). In 1991 Honeywell’s computer division was sold to Groupe Bull. How interesting is that!

Figure 2 shows a classic SMP system with Distributed Shared Memory (DSM). In a DSM system there are multiple pools of memory and the latency to access memory depends on the relative position of the processor and memory. This is also referred to a Non-Uniform Memory Access or NUMA.

Figure 2 : SMP system - Distributed Shared Memory (DSM) - Non-Uniform Memory Access (NUMA)

Figure 2 : SMP system – Distributed Shared Memory (DSM) – Non-Uniform Memory Access (NUMA)

Major benefit; each processor has local memory with the lowest latency. On the opposite remote memory access is slower.  Intel says that latency can go up to 70% and bandwidth as less than half of local access bandwidth.
But the biggest downside of DSM is that it only works well if the operating system is “NUMA-aware” and can efficiently place memory and processes. The OS scheduler and memory allocator play a critical role here.

vSphere is NUMA aware as long as the BIOS reports it. That is as long as the BIOS builds a System Resource Allocation Table (SRAT), so the ESX/ESXi host detects the system as NUMA and applies NUMA optimizations. If you enable node interleaving (also known as interleaved memory), the BIOS does not build an SRAT, so the ESX/ESXi host does not detect the system as NUMA. Does that mean that vSphere doesn’t do any optimization if you haven’t enabled NUMA in the BIOS? I guess it doesn’t since the scheduler doesn’t know the relationship between processor and local memory. That information is only given by the SRAT as I understand it.

What are vSphere NUMA optimizations I’m referring to?

Before we deep dive vSphere NUMA optimizations, first let’s define a Home Node. A Home Node is one of the system’s NUMA nodes containing processors and local memory, as indicated by the System Resource Allocation Table (SRAT).

They are two main vSphere NUMA optimization algorithms and settings you find in the vSphere NUMA Scheduler:

  1. Home Nodes and Initial Placement. When a virtual machine is powered on, ESX/ESXi assigns it a home node in a round robin fashion. To work around imbalanced systems when virtual machines are stopped or become idle, there is a second set of algorithms and settings called,
  2. Dynamic Load Balancing and Page Migration. ESX/ESXi combines the traditional initial placement approach with a dynamic rebalancing algorithm. Periodically (every two seconds by default), the system examines the loads of the various nodes and determines if it should rebalance the load by moving a virtual machine from one node to another. This calculation takes into account:
    1. the resource settings for virtual machines and
    2. resource pools to improve performance without violating fairness or resource entitlements.

To get a detailed description of the algorithms and settings used by ESX/ESXi to maximize application performance while still maintaining resource guarantees, visit

vSphere  NUMA Scheduler has put in place pretty smart algorithms and settings when it comes to initial placement and memory management. I was wondering could it be better?
For instance, by managing contention for shared resources that occurs when memory-intensive threads are co-scheduled on cores that share parts of the memory hierarchy, such as last-level caches and memory controllers.


Sergey Blagodurov from Simon, Sergey Zhuravlev, Mohammad Dashti and Alexandra Fedorova, all from Simon Fraser University, have published a very interesting technical paper at about limitation of current NUMA design and a proposition of a new approach they called DINO which stands for Distributed Intensity NUMA Online.

Those guys have discovered that state-of-the-art contention management algorithms fail to be effective on NUMA systems and may even hurt performance relative to a default OS scheduler.

Contention-aware algorithms focused primarily on UMA (Uniform Memory Access) systems, where there are multiple shared last-level caches (LLC), but only a single memory node equipped with the single memory controller, and memory can be accessed with the same latency from any core.

Remember that unlike on UMA systems, thread migrations are not cheap on NUMA systems because you also have to move the memory of the thread. So their approach to the problem is a mechanism that ensure that superfluous thread, those that are not likely to reduce contention, are not migrated in a NUMA system.

Existing contention aware algorithms perform NUMA-agnostic migration, and so a thread may end up running on a node remote from its memory. Actual vSphere NUMA scheduler is mitigating this issue by detecting when most of a VM’s memory is in a remote node and eventually load balancing and migrating memory as long as it doesn’t cause CPU contention to occur in that NUMA node.

Could DINO Be The Future Of vSphere NUMA Scheduler?

DINO organizes threads into broad classes according to their miss rates, and to perform migrations only when threads change their class, while trying to preserve thread-core affinities whenever possible. VMware vSphere NUMA optimizations would benefit from this by adding DINO approach to the existing optimization code by eventually migrate  memory based on threads and their miss rates as well.

In vSphere 5.x VMware introduced vNUMA. It presents the physical NUMA typology to the guest operating system. vNUMA is enabled by default on VMs greater than 8 way but you can change this by modifying the numa.vcpu.min setting. Is this an attempt to hand over the critical NUMA scheduler job to the guest OS hoping it does a better job? I would say that it may seems a good approach but at the cost of losing control. In a shared environment such a VMware environment, the virtual machine monitor should be in control, always.


I’m not within the secret of Gods. I don’t have access to VMware developers and codes. Thus what I’m being saying here is based on a series of elements, readings, articles, vendor architecture documents that I have compiled and read through while preparing Santa Christmas Eve with an enhanced version of eggnog in my mug. Therefore I may be wrong, off-target, totally inaccurate in my conclusion…

If you have another point of view, piece of information I don’t have. If I missed something in my thought process just post a comment. I’ll be very happy to read from you!

Source: vmware,,,

Letter To Santa

December 21, 2012 Leave a comment

Dear Santa, I’ve been terrific at virtualising low hanging fruit over the past years. I have reduced costs while increasing availability, reliability and performance for my applications. I’m a prodigy, I’m a super-hero!

Now my CIO asked me to realize the same wonder with our business mission-critical applications!

Those applications are massive man! They require a lot of resources and they need mainframe-style availability and performance.

Only monster vm’s can cope with the load and I need even bigger monster servers to hold them up!

Please Santa, I need you to get me some MONSTER BULLION’s

Monster Bullion

Monster Bullion

Bull’s BCS Architecture – Deep Dive – Part 4

December 3, 2012 Leave a comment

Following on from part 1part 2 and part 3 here is … part 4 of this deep dive series on the Bull’s BCS Architecture.

In the previous post I focussed on Intel RAS features that Bull’s BCS Architecture is leveraging to make the memory more reliable and available.

In part 4, I will cover additional features leverage by Bull’s specific server architecture.  Some of these features address directly customers who require the level of reliability, availability and serviceability they could only find in expensive mainframe systems.


Reliability addresses the ability of a system or a component to perform its required functions.

Dual Path IO HBAs

Each bullion module provides the ability to connect up to 3 HBA’s per IO Hub aka IOH which is an Intel component that provides the interface between the IO components such PCIe buses and the Intel QPI based processors. Those 3 HBA’s can then be mirrored inside the same bullion module to the HBA’s attached to a second IO Hub.  This teaming gives you a fault tolerant IO connectivity and associated with VMware’s Native Multipathing Plugin (MPP), you load balance the IO across the members of the teaming.

Four-Socket Two IOH Topology - Courtesy of Intel

Four-Socket Two Boxboro IOH Topology – Courtesy of Intel


Availability of a system is typically measured as a factor of its reliability – as reliability increases, so does availability.

Active/Passive Power-supplies

The bullion servers are equipped with two 1600W power supplies, which are 80+ Platinum level certified. They provide a full N+N redundancy for maximum availability.

For its mainframe systems, Bull  has developed a patented solution based on an active/passive power supply principles. This patented solution provides the highest efficiency rate possible, regardless the requirements and still provide a maximum uptime possible.

This technology from mainframe systems is now available on the bullion.

What is it exactly? The unique active/passive power supply solution provides an embedded fault resiliency against the most common electrical outages: micro-outages.

Rather than having to rely on heavy and expensive UPS systems bullion servers are equipped with an ultra-capacitor which provides the ability to switch from the active to the passive power supply in case of failure, as well as being protected against micro outages.

The ultra-capacitor provides a 300ms autonomy, sufficient to switch-over or to avoid application un-availability during micro-outages.

Bullion' s Ultra-Capacitor - Courtesy of Bull

Bullion’ s Ultra-Capacitor – Courtesy of Bull

The passive PSU rotates and it is frequently tested with failover and failback runs to guarantee its availability in case of a failure of the active PSU.

Bull announces a global consumption of 20-30% below competition.


It refers to the ability of technical support personnel to install, configure, and monitor computer products, identify exceptions or faults, debug or isolate faults to root cause analysis, and provide hardware or software maintenance in pursuit of solving a problem and restoring the product into service.

Empower Maintainability

To ease the replacement of the most frequently failing motorized components, such as the ventilators, power-supplies and disk-drives which are responsible for over 80% of hardware failures, with no impact whatsoever in the production on bullion servers since they is always a redundant part available to take over the failed one.

Replacing these components are now part of the Customer Replaceable Units (CRU’s). This program empowers you to repair your own machine. Other server vendors have the same policy actually. In situations where a computer failure can be attributed to an easily replaceable part ( a CRU), Bull sends you the new part. You simply swap swap the old part for the new one, no tools required. It is simple and a major advantage: really fast service for you and reduced support and maintenance fees.

Increase Availability

On the other side, there are components replaceable only by Support. They are part of the Field Replaceable Units (FRU).

To avoid downtime for the customer, and under the correct conditions, some FRUs can be excluded from the system at boot time: PSUs, processors, cores, QPI links, XQPI links, PCIe boards, embedded Ethernet controllers are among the elements which can be excluded at boot time and minimize downtime during serviceability.

RAS Monitoring

Each bullion module contains an embedded  Baseboard Management Controller (BMC) for monitoring and administration functions. This embedded controller runs the Server Hardware Console (SHC).

Bullion servers offer the following built-in functions:

  • SHC access to all of the module components by standard out-of-band (non-functional) paths – the I2C and SMBus interfaces.
  • A dedicated network to interconnect all of the SHCs of a server without affecting the customer’s network.
  • Dynamic communications between the SHC and the BIOS.

The SHC provides this information to vCenter or any other industry standard System Management solution, with support for IPMI, SNMP and other industry standard interfaces.

’nuff said with Bull’s BCS Architecture. It’s time to witness the power of the beast, it’s time to see the greenness of the monster. it’s time to meet the monster bullion ™ – Stay tuned!

Source: Bull, Intel, Wikipedia

Bull’s BCS Architecture – Deep Dive – Part 3

November 21, 2012 3 comments

The last couple of posts about Bull’s BCS Architecture have been quite intense and I hope I’ve met the technical details you were expecting.

Here are the links to the entire deep dive series so far:

Now I want to talk about another feature that Bull’s BCS Architecture is leveraging: Intel RAS

What is RAS and what is its purpose?

Today’s crucial business challenges require the handling of unrecoverable hardware errors, while delivering uninterrupted application and transaction services to end users. Modern approaches strive to handle  unrecoverable errors throughout the complete application stack, from the underlying hardware to the application software itself.

RAS Flow - Courtesy of Intel

RAS Flow – Courtesy of Intel

Such solutions involve three components:

  1. reliability, how the solution preserves data integrity,
  2. availability, how it guarantees uninterrupted operation with minimal degradation,
  3. serviceability, how it simplifies proactively and reactively dealing with failed or potentially failed components.

This post  covers only the memory management mechanisms providing reliability and availability. Next post will cover other mechanisms.

Memory Management mechanisms

Memory errors are among the most  common hardware causes of machine crashes in production sites with large-scale systems.

Google® Inc. researchers conducted a  two-year study of memory errors in  Google’s server fleet (see Google Inc.,  “DRAM Errors in the Wild: A Large-Scale  Field Study”).

Researchers observed more than 8 percent of DIMMS and about one-third of the machines in the study were affected by correctable errors per year.

At the same time the annual percentage of detected uncorrected errors was 1.3 percent per machine and 0.22 percent per DIMM.

Capacity of memory module has increased – following Moore’s law – over the last two decades. In the 80′s you could buy 2MB memory modules, 20 years later, 32GB memory modules hit the market. That is a 16,000x improvement.

One of the unique reliability and availability features of the bullion is its RAM memory management and memory protection. From basic ECC  up to Memory Mirroring, memory protection mechanisms can guarantee up to 100% memory reliability on the bullion.

Let’s have a look at  some of those memory protection mechanisms available in the bullion:

ECC memory

Over and above traditional memory correction mechanisms, such as ECC memory, which maintains a memory system effectively free from single-bit errors.

Double device Data Correction (DDDC)

Bullion provides much more sophisticated mechanisms such as Double device Data Correction (DDDC), which corrects dual recoverable errors.

Double Device Data Correction - DDDC - Courtesy of Bull

Double Device Data Correction – DDDC – Courtesy of Bull

DIMM & Rank Sparing

The commonly available DIMM Sparing is now being enhanced to provide Rank Sparing. With Rank Sparing of dual rank DIMM’s, only 12.5% is being used to enhance the reliability of the memory system. If the level of ECC corrected errors becomes too high, it fails over the spares. Note that DIMM and Rank Sparing does not protect against uncorrectable memory errors.

DIMM Sparing- Rank Sparing - Courtesy of Bull

DIMM Sparing- Rank Sparing – Courtesy of Bull

MCA Recovery

In a virtualized environment, the Virtual Machine Manager (VMM) shares the silicon platform’s resources with each virtual machine (VM) running an OS and applications.

In systems without MCA recovery, an uncorrectable data error would cause the entire system and all of its virtual machines to crash, disrupting multiple applications.

With MCA recovery, when an uncorrectable data error is detected, the system can isolate the error to only the affected VM. Here the hardware notifies the VMM (Support for VMware vSphere 5.x), which then attempts to retire the failing memory page(s) and notify affected VMs and components.

If the failed page is in free memory then the page is retired and marked for replacement, and operation can return to normal. Otherwise, for each affected VM, if the VM can recover from the error it will continue operation; otherwise the VMM restarts the VM.

In all cases, once VM processing is done, the page is retired and marked, and operation returns to normal.

It is possible for the VM to notify its guest OS and have the OS take appropriate recovery actions, and even notify applications higher up in the software stack so that they take application-level recovery actions.

Here is a video demoing the MCA Recovery (MCAR) with VMware vSphere 5.0

Here is a diagram of MCA recovery process:

Software-Assisted MCA Recovery Process - Courtesy of Intel

Software-Assisted MCA Recovery Process – Courtesy of Intel

MCA Recovery is cool but the main drawback it does not offer 100% memory reliability. The scrubbing process that goes through all memory pages to detect the unrecoverable error takes some time, and a few CPU cycles too.

If you’re fortunate enough the MCA Recovery detects the error and reports to the VMM (VMware vSphere 5.x) otherwise you end up most probably with a purple screen of death.

Mirroring Mode

For 100% memory reliability, bullion use memory lockstep. Data are written simultaneously in two different memory modules in lockstep mode. It is the best memory protection mechanism for both reliability and availability as it protects against both correctable and uncorrectable memory errors. On four memory channel systems such the bullion, you cut your available number of DIMM slots by 1/2.

The bullion can hold up to 4TB of memory, which is surprisingly the double of the memory maximum of VMware vSphere 5.1 tolerates so far ;)

Memory Mirroring

Memory Mirroring – Courtesy of Bull

Mirroring mode offers 100% memory reliability and availability but it cost an arm, well two arms and maybe a leg as well… Memory performance drops as well by as much as 50%.

I’ve gone through a small subset of the many many features available to RAS. Here below a full list of Intel Xeon processor E7 family advanced RAS features.

Intel Xeon processor E7 family advanced RAS features - Courtesy of Intel

Intel Xeon processor E7 family advanced RAS features – Courtesy of Intel

I’ve setup a little poll about the memory protection mechanism you rely on in your production environments. Thank you for your time to answer!

Next post I will address some other RAS features available into the bullion. Stay tuned!

Source: Bull, Intel, Wikipedia

Bull’s BCS Architecture – Deep Dive – Part 2

November 8, 2012 2 comments

In Bull’s BCS Architecture – Deep Dive – Part 1 I have listed BCS’s two key functionalities: CPU caching and the resilient eXternal Node-Controller fabric.

Now let’s deep dive in  to these two key functionalities. Bear with it is quite technical.

Enhanced system performance with CPU Caching

CPU caching provides significant benefits for system performance:

  • Minimizes inter-processor coherency communication and reduces latency to local memory. Processors in each 4-socket module have access to the smart CPU cache state stored in the eXternal Node Controller, thus eliminating the overhead requesting and receiving updates from all other processors.
  • Dynamic routing of traffic.
    When an inter-node-controller link is overused, Bull’s dynamic routing design  avoids performance bottleneck by routing traffic through the least-used path. The system uses all available lanes and maintains full bandwidth.

BCS Chip Design – Courtesy of Bull

With the Bull BCS architecture, through CPU caching and coherency snoop responses consume only 5 to 10% of the Intel QPI bandwidth and that of the switch fabric. Bull implementation provides local memory access latency comparable to regular 4-socket systems and 44% lower latency compared to 8-socket ‘gluesless’ systems.

Via the eXtended QPI (XQPI) network a Bull 4-socket  module communicates with the other 3x modules as it was a single 16-socket system. Therefore all accesses to local memory have the bandwidth and latency of a regular 4-socket system. Actually each BCS has an embedded directory of 144 SRAM’s of 20 Mb each for a total memory of 72 MB.

Adding to that, the BCS provides 2x MORE eXtended QPI links to interconnect additional 4-socket modules where a 8-socket ‘glueless’ system only offers 4 Intel QPI links. those links are utilized more efficiently as well. By recording when a cache in a remote 4-socket module has a copy of a memory line, the BCS eXternal Node-Controller can respond on behalf of all remote caches to each source snoop. This removes snoop traffic from consuming bandwidth AND reduces memory latency.

Enhanced reliability with Resilient System Fabric

Bull BCS Architecture extends the advanced reliability of the Intel Xeon processors E7-4800 series with a resilient eXtended-QPI (X-QPI) fabric. The BCS X-QPI fabric enables:

  • No more hops to reach the information inside any of the other processor caches.
  • Redundant data paths. Should a failure of a X-QPI link occur, automatically a redundant X-QPI link takes over.
  • Rapid recovery with an improved error logging and diagnostics information.
Bullion Multi Modules BCS Design

Bullion Multi-Modules BCS Design – Courtesy of Bull

What about RAS features?

Bull designed the BCS with RAS features (Reliability, Availability and Serviceability) consistent with Intel’s QPI RAS features.

The point-to-point links – that you find in QPI, Scalable Memory Interconnect (SMI)  and BCS fabric – that connect the chips in the bullion system have many RAS features in common including:

  • Cyclic Redundancy Checksum (CRC)
  • Link Level Retry (LLR)
  • Link Width Reduction (LWR)
  • Link Retrain

All the link resiliency features above apply to both Intel QPI/SMI and the X-QPI fabric (BCS). They are transparent to the hypervisor. The system remains operational.

XQPI cabling for a 16 sockets bullion

XQPI Cabling for a 16 Sockets bullion – Courtesy of Bull

In part 3 I will write about how Bull improves memory reliability by forwarding memory error detections right into the VMware hypervisor to avoid purple screen of death. This is not science fiction! It is available in a shop near you :)

Source: Bull, Intel


Bull’s BCS Architecture – Deep Dive – Part 1

October 29, 2012 5 comments

Before going further, let’s put here a list of related posts. Although not required, I encourage you to go through them all before reading the following post.

OK now let’s deep dive this BCS technology. I ended up my previous post by saying that Bull’s BCS solves scale-up issues without compromising performance. Here a graph showing what that does mean.

Bullion measured performance vs the maximum theoretical performance – Specint_rate 2006 – Courtesy of Bull

Bull’s BCS eXternal Node-Controller technology scales up almost linearly compared to the ‘glueless’ architecture. What’s the secret sauce behind this  awesome technology?

BCS Architecture

The BCS enables two key functionalities: CPU caching and the resilient eXternal Node-Controller fabric. These features server to reduce communication and coordination overhead and provide availability features consistent with Intel Xeon E7-4800 series processor.

BCS meets the most demanding requirements of today’s business-critical and mission-critical applications.

Detailed 4 Sockets Xeon E7 Novascale bullion Architecture – Courtesy of Bull

As shown in the above figure, a BCS chip sits on a SIB board that is plugged in the main board. When running in a single node mode, a DSIB (Dummy SIB) board is required.

BCS Architecture - 4 Nodes - 16 Sockets

BCS Architecture – 4 Nodes – 16 Sockets

As shown in the above figure, BCS Architecture scales to 16 processors supporting up to 160 processor cores and up to 320 logical processors (Intel HT). Memory wise, BCS Architecture supports up to 256x DDR3 DIMM slots for a maximum of 4TB of memory using 16GB DIMMs. IO wise, there are up to 24 IO slots available.

BCS key technical characteristics:

  • ASIC chip of 18x18mm with 9 metal layers
  • 90nm technology
  • 321 millions transistors
  • 1837 (~43×43) ball connectors
  • 6 QPI (~fibers) and 3×2 XQPI links
  • High speed serial interfaces up to 8GT/s
  • power-concsious design with selective power-down capabilities
  • Aggregated data transfer rate of 230GB/s that is 9 ports x 25.6 GB/s
  • Up to 300Gb/s bandwidth

BCS Chip Design – Courtesy of Bull

Each BCS module groups the processor sockets into a single “QPI island” of four directly connected CPU sockets. This direct connection provides the lowest latencies. Each node controller stores information about all data located in the processors caches. This key functionality is called “CPU caching“. This is just awesome!

More on this key functionality in the second part. Stay tuned!

Source: Bull,


Scale-Out And Scale-Up Architectures – The Business-Critical Application Point Of View

October 17, 2012 2 comments

This post is the first in a series of articles focusing on a great piece of hardware you may have seen in action at VMware Barcelona 2012 in the Solutions Exchange hall.

By the end of 2012 over 50% of the applications running on x86 platforms will be virtualized. However, currently only 20% of mission-critical applications have so far been virtualized.

Is it because IT departments do not trust virtualization platforms? Do they find virtualization platforms not stable enough to hold mission-critical applications?
Over the last decade, VMware has shown that virtualization is reality and actually virtualized applications are often more stable when running on trustworthy VMware platforms.

So if it is not a stability or trust issue, what’s the reason IT departments haven’t yet virtualized the last bit?


Scale-out aka scale horizontally means to add more nodes to the infrastructure, such as adding a new host to a VMware cluster.

As computer prices drop and performance continue to increase, low cost ‘commodity’ systems are the perfect fit for scale-out approach and can be configured in large clusters to aggregate compute power.

For the last seven years designing VMware virtual environments have been preaching for a scale-out approach. One could argue with that approach and as always it depends. Pro’s are low commodity hardware price and usually few virtual machines per host are impacted whenever the commodity hardware fails. On the other side, con’s are such design requires more VMware licensing, more datacenter footprint too and usually those low cost ‘commodity’ systems have small reservoir of resources.


To scale up aka to scale vertically means adding resources to a single host. Typically adding CPUs and memory to a single computer.

Usually that kind of host are beefier. They support 4-socket processors with up to 512GB of memory. Eventually you can see even beefier systems which support up to 8-socket processors and 1TB of memory. Some of us have been lucky enough to witness systems supporting up to 16-socket processors and 4TB of memory. No this is not a mainframe or such but x86 architecture based systems.

Moving to the so-called second wave of virtualization, that is providing the agility of virtualization to the business-critical applications are placing today’s Enterprise VMware clusters under enormous stress. Challenges are:

  • Inadequate scaling of computer capabilities. Support of high demanding workloads is an issue with resource limited low cost ‘commodity’ systems.
  • Insufficient reliability. Commodity hardware or hardware using ‘commodity’ components can be seen as less reliable. Reliability can be addressed with features I will talk about in the next articles.
  • Increase management complexity and operating cost. It is easier to manage 100 hosts than 1000, and from that statement, managing 10 hosts is even easier than 100. Same goes for OPEX, 10 hosts cost much less to operate than 1000 hosts.

A scale-up approach fits perfectly business-critical applications requiring huge resources. Monster VM hellooo! Those power-hungry business-critical applications such large databases, huge ERP systems, big data analytics, JAVA based applications, etc. will directly benefit from a scale-up approach.

With the introduction of VMware vSphere 5, the amount of resources available on a single VM increased fourfold compared to previous version as shown on the picture below.

And lately with the release of VMware vSphere 5.1 the monster VM beefed up one more time.

For a vSphere 5.1 Monster VM to do any work the hypervisor will have to find and schedule 64 physical CPU cores. There are very few systems out there able to hold 64 cores and even less systems capable of doing 16-socket processors, 160 cores…  Here is a hint, it starts with a B…

…To be continued!

Cluster Profiles

November 28, 2011 4 comments

This is the English version of a blog post from Raphael Schitz at

Raphael is very smart guy, vExpert fellow and PowerCLI guru. Recently he came up with a great idea, which turned into a great blog post and a powerful script available for free. All credits go to Raphael.

No need to remind you the benefits of Host Profiles in terms of configuration consistency and correctness across the datacenter. With PXE Manager and PowerCLI, you could free yourself from the hassle of deployment and with Host Profiles’ help you automate and monitor host configuration management (These features were greatly improved in vSphere 5).

Unfortunately Cluster configuration management hasn’t improved at the same pace and remains tedious with no visibility into changes. You configure properly your Cluster settings and 6 months later, after a few maintenance windows and some changes e.g. Admission Control set to disable and DRS set to Partially Automated, you find yourself in a situation where a broken Blade powers off VM’s which are unable to restart on other hosts in the Cluster because someone forgot to re-enable HA. We have experienced this situation but hopefully our latest PowerCLI script will help us to change once for all those bad habits and behaviors: Meet Manage-ClusterProfile

Manage-ClusterProfile was developed for three simple tasks:

  • export Cluster configuration and settings to a cluster profile file.
  • compare Cluster configuration and settings with a cluster profile file.
  • import a cluster profile file to an existing Cluster.

The cluster profile file, which is a xml file, contains the entire configuration and settings of a Cluster (HA, DRS, DPM, rules, swapfile, etc…) and therefore allows a detailed comparison of similarities and differences.

Optionally you can send an email to vAdmins for instance.

The import function addresses only Cluster’s own configuration and settings. For instance, Affinity Rules or any other VM’s settings (e.g. HA/DRS/DPM customization) are not imported.

The script has the following input parameters:

  • ManagedCluster [name of the Cluster]
  • Action [import|export|check]
  • ProfilePath [directory for export|path to xml cluster profile file for import and check]
  • SendMail [1 for enable]
  • ForceImport [1 for enable]

To summarize this blog post,  this script will allow you to create new Clusters by importing cluster profile templates with all your predefined configuration and settings tailored to your own criterias.  Also ran as a scheduled task, this script will allow you to track changes and stay compliance. Of course when you make changes to your Cluster, you will have to export them to a cluster profile file that you use to track changes.

As usual do not hesitate to share your feedback and suggestions in the comment area :)

Enjoy !

Download Manage-ClusterProfile

Categories: ESXi, PowerCLI, VMware, vSphere