IT consultant/freelance reviewer – Independent consultant – SearchStorage
Let’s clear up some misconceptions about storage. First, cloud
storage isn’t always hosted on a public service, such as AWS and
Microsoft Azure. And second, virtualization and virtualized data storage
don’t just refer to virtual servers or desktop systems hosted on VMware
ESX or Microsoft Hyper-V. These two misconceptions are related, because
one true thing about cloud storage is that it is virtualized.
To a certain extent, all storage is virtualized.
Even the most basic block-based hardware system — a single hard disk
— is mapped by the storage controller attached to the hard disk. This
translates the physical hardware blocks, sectors and tracks on the hard
drive’s physical disks into a virtual set of blocks, sectors and tracks
that the motherboard and storage controller use to communicate with the
Likewise, file-based storage creates an SMB or NFS volume containing
files and metadata, even though the underlying file system might be
different from the one presented by the storage system. Many file
servers use more modern file systems, such as ZFS, instead of SMB or NFS, and then translate. Others use CIFS
or NFS and present the volume as both. That way, an SMB volume can be
presented as an NFS volume and vice versa. This is also a type of
virtualized data storage.
The truth about virtualized data storage
Storage virtualization refers to storage that isn’t directly accessible to the storage consumer. It can be a server, server instance, client system or other system that needs storage. Nearly all storage in the data center and public and private clouds is virtualized.
One true thing about cloud storage is that it is virtualized.
Even iSCSI volumes and Fibre Channel LUNs
that appear to be block devices and theoretically identical to an
internal hard disk can be considered virtualized. They’re generally RAID
volumes, which mean that several physical disks are presented as one or
more virtual disks. In addition, software features, such as tiering,
snapshots and replication, require a virtualization layer between the
physical storage and the consumer. Deduplication, compression and object
storage layers add additional layers of virtualized data storage.
Virtualization can be useful. A volume that appears to an application or end user as a single contiguous directory tree may include files hosted on different storage tiers, some on local hard disks and others on low-cost cloud storage tiers. This results in high-performance storage at the lowest possible cost, because virtualized data storage lets files that haven’t been accessed for a while be moved to inexpensive storage.
is often assumed to be storage in the public cloud, like Amazon S3,
Google Cloud Platform and Microsoft Azure. However, many vendors offer
some form of cloud storage, ranging from backup vendors, such as
Barracuda and Zetta; to Oracle, Salesforce and other cloud application
vendors; to alternatives to the big three, such as DigitalOcean and
Data center cloud products also make storage easily available to applications, whether or not they’re running locally. Dell EMC, Hewlett Packard Enterprise, Hitachi Vantara and NetApp all offer these capabilities. Some of these products are proprietary, some are single-purpose and some are based on open source standards, such as Ceph.
Freelance trainer, consultant and blogger specializing in server and desktop virtualization
There are multiple ways to approach a hyper-converged infrastructure deployment, some of which give IT a little more control.
When we talk about building a hyper-converged infrastructure (HCI),
the mental image is usually deploying some physical appliances using
high-density servers and spending a few minutes with some wizard-driven
software. But buying hyper-converged infrastructure appliances is just
one way to do it.
As an IT professional, you can also deploy software-only HCI
on your own servers. Or you can start from scratch and engineer your
own infrastructure using a selection of hardware and software. The
further you move away from the appliance model, however, the more you must take responsibility for the engineering of your deployment and problem resolution.
Hyper-converged infrastructure appliances wrap up all their
components into a single order of code. The vendor does all of the
component selection and the engineering to ensure that everything works
together and performs optimally.
Usually, the hyper-converged appliance
has its own bootstrap mechanism that deploys and configures the
hypervisor and software with minimal input from IT. For many customers,
this ease of use is a big reason for deploying HCI, making it possible
to largely ignore the virtualization infrastructure and focus instead on
the VMs it delivers.
One of the big reasons for selecting a software-only hyper-converged
infrastructure is that it offers hardware choice. You may have a
relationship with a preferred server vendor and need to use its
hardware. Or you may simply want an unusual combination of server
Another example is that you may want a lower cost, single-socket
server option, particularly if you are deploying to a lot of remote or
branch offices. If you are deploying to retail locations, you may need
servers that will fit into a shallow communications cabinet rather than a
data center depth rack.
Once you select your hardware, you are responsible for the consequences of those choices.
Once you select your hardware, you are responsible for the consequences of those choices. If you choose the wrong network interface card
or a Serial-Attached SCSI host bus adapter, you may find support is
problematic, or performance may not match your expectations.
As with software-only HCI, you are taking responsibility for this
decision and its consequences. You can probably buy support for the
hypervisor and the SDS, but what about potential interoperability issues
between the layers? What is the service level for resolving performance
Building a platform from scratch instead of buying preconfigured hyper-converged infrastructure appliances is only sensible if you have your own full support team providing 24/7 coverage.
Freelance trainer, consultant and blogger specializing in server and desktop virtualization.
Converged and hyper-converged infrastructures have similar names, but
they take very different approaches and solve different types of
Converged infrastructure (CI) helps remove risk from a large
virtualization deployment. Hyper-converged infrastructure (HCI)
represents a rethinking of VM delivery, and it aims to simplify
operation of a virtualization platform. Either converged or
hyper-converged infrastructure appliances can deliver a faster time to
value than assembling a virtualization platform from disparate
components, but their resulting platforms will have different
Converged infrastructure appliances
A converged infrastructure appliance is pre-configured to run a
certain number of VMs, and it’s ready to be connected to an existing data center network
and power supply from the time it’s built. Vendors build these
appliances with components that include a storage array, some servers,
network switches and all the required cables and connectors. Vendors
assemble and test all of these components before delivering them to
customers, and they control every aspect of the build, down to the
certified firmware and driver levels for each part.
A small converged infrastructure appliance can take up just half a
data center rack, and the largest might be five full racks. Usually,
deployment involves professional services from the vendor, and every
update requires more professional services. The aim of CI is to take the
risk out of deploying a virtualization platform by having the vendor
design and support the same platform across multiple customers. It is
usually not designed to scale in place; for more capacity, organizations
must buy additional complete converged infrastructure appliances.
Hyper-converged infrastructure appliances are built around a single
x86 server, and a group of appliances are configured together as a
cluster that organizations can expand and contract by adding or removing
The first consideration when choosing converged or hyper-converged infrastructure is scale.
HCI puts an emphasis on simplified VM management. It usually also
includes some sort of backup capability and often a disaster recovery
(DR) function. (Many hyper-converged products integrate with the public cloud for backup and DR.)
A significant feature of hyper-converged infrastructure appliances
is that in-house IT professionals, rather than vendors’ professional
services staff, can complete most functions, from initial deployment to adding nodes to the entire update process.
Converged or hyper-converged?
The first consideration when choosing converged or hyper-converged
infrastructure is scale. A half rack of CI appliances will run 100 or
more VMs, whereas five racks will run thousands of VMs. CI is not for
small offices or small businesses. It’s suited for enterprises.
The second aspect is that CI is about reducing risk,
even if that increases cost. All of the professional services that
surround CI are areas where the vendor is paid to reduce the customer’s
risk. Organizations buy CI for guaranteed outcomes, so they tend to be
in risk-averse industries, such as banking, insurance, government and
Hyper-converged infrastructure appliances are popular with
organizations that do not want to think about the hardware or software
underneath their VMs. These organizations want to manage a fleet of VMs
with minimal effort because the value is in the applications inside
those VMs, rather than the servers or hypervisors on which they run. HCI
is ideally suited for scale-out workloads, such as VDI, or for nonproduction uses, such as test and development.
Some hyper-converged infrastructure appliances operate with just one or two nodes at a site. This makes them suitable for remote or branch office deployments, particularly where there are a large number of branches, such as in a retail chain. HCI’s built-in data protection is popular in these scenarios because it reduces the risk of data loss at the branch and, in some cases, allows one branch to provide DR capacity for another.
Modern IT equipment can handle more workloads in a
smaller footprint, but this benefit also creates challenges for some
A hyperscale cloud provider with full knowledge of its average workload can easily architect a dense compute platform.
This is especially true when that average workload is actually millions
of different workloads across a massive user base — which is the case
for cloud providers like Amazon Web Services (AWS) and Microsoft Azure
— or is a predictable set of workloads, such as those that run at
Netflix, Facebook or Twitter. A single, logical platform that uses a
massive amount of compute, storage and network nodes is fairly easy to
create for these providers, since it’s a cookie-cutter approach; when
AWS needs to add extra resources, there is very little
However, it is more challenging for an organization with
its own dedicated IT platform to support high-density data centers. For
example, an organization won’t usually run thousands of servers as a
single, logical platform that supports all workloads. Instead, there
will most likely be a one-application-per-server or cluster model,
virtualized servers that carry one or more workloads and private clouds
that carry different workloads with dynamic resource sharing.
HCI vendors engineer server, storage and networking
components to work together and offer adequate cooling at the lowest
cost, which enables organizations to support high-density data centers
in a shorter period of time. However, there are still challenges with
power, cooling and workload capabilities.
Power and cooling challenges
are fairly easy to address. Standard power distribution systems can
support most HCI systems in a data center facility. But if you want to
build a platform that supports high-performance computing (HPC),
where power densities might exceed existing distribution capabilities,
you’ll face concerns. Decide whether expanded power and cooling
capabilities in the facility are a worthwhile investment or if a
colocation facility can meet these new demands.
It’s more difficult to address complex workload
capabilities. If you have applications that are directly applied to a
platform, hard partition the resources allocated to them, and like in
traditional IT models, carefully plan to allow enough space for peak
When you work with applications that are applied to
VMs, remember that each VM is a self-contained entity that carries a
full stack of resource-hungry services. Containers share a lot of the same services
as a VM, so allow for a greater number of containers to run on a given
platform rather than VMs that carry out the same function.
So, just how many VMs or containers should you run on a given HCI
platform? Be wary of figures given out by vendors, as the workloads they
use to gather those numbers are often generalized and basic. For
example, HCI vendors that sell a system focused on virtual desktop
infrastructure might state that upwards of 200 desktops can run on their
system. But that might only be true when desktops don’t have more than
one OS and when users don’t need to log into them at the same time every
Look for vendors who run HCI systems as a proof of concept, allowing
you to put your own workloads onto their platform and apply synthetic
loads to gauge how many real-world VMs or containers the platform can
If you choose to build your own highly dense platform, employ
experienced systems architects who can ensure that the interdependencies
among compute, storage and network resources are carefully balanced and
work well together. People with such skills are difficult to find,
though — another reason why, outside of HPC, HCI is a better bet for
high-density data centers than the build-it-yourself approach.
There are many factors to consider in the midst of a server
selection. For example, VM and container consolidation, as well as
visualization and scientific computing, each affect the decision. In
part two of our purchasing guide, we’ll discuss other important factors
on server purchases for your enterprise.
Enhanced server security plays a role in server purchases
Although server purchases aren’t based solely on security
capabilities, there is a proliferation of protection, detection and
recovery features to consider for most enterprise tasks. Modern security
features now extend well beyond traditional Trusted Platform Modules.
For example, secure servers can offer protection through a hardware-based root of trust, which uses hardware validation of server management platforms,
such as an integrated Dell Remote Access Controller, and server
firmware as the system boots. Validation typically includes
cryptographic signatures to ensure that only valid firmware and drivers
are running on the server. Similarly, firmware and driver updates are
usually cryptographically signed to verify their authenticity or source.
You can execute validations periodically even though the system might
not reboot for months. Native data encryption is increasingly available
at the server processor level to protect data in flight and at rest.
An increasing number of systems can detect unauthorized or unexpected changes in system firmware
images and firmware configurations, enforcing a system lockdown to
prevent such changes and alerting administrators when change attempts
occur at the firmware level. Servers frequently include persistent event
logging, which includes an indelible record of all activity.
And servers benefit from various recovery capabilities. For example, automatic BIOS/firmware recovery can restore firmware to a known good state after the system detects any flaw or compromise in the firmware code base. Some systems can apply similar restoration to the OS by detecting possible malicious activity and restoring the OS to a known good state as well. And system erasure features can be used to wipe all hardware configuration settings of the server, including BIOS data, diagnostic data, management configuration states, nonvolatile cache and internal SD cards. System erasure can be particularly important before redeploying the server or removing it from service.
For data servers, focus on network I/O
or data servers, can take many shapes and sizes depending on the needs
of each specific business. The actual compute resources needed in a data
server are typically light. For example, file servers rarely process
data or make computations that demand extensive processor or memory
capacity. Web servers may include more resources if the system will also
be running code or back-end applications, such as databases. If the
organization plans to employ virtualization to consolidate multiple data
servers onto a single physical box, the processor and memory
requirements will need a closer look.
However, the emphasis for data servers is more frequently focused on
network I/O, which can be critical for accessing shared/centralized
storage resources and exchanging files or web content with many
simultaneous users — network bottlenecks are commonplace. If the data
server will employ internal storage, the choice of disk types and
capacity can have a significant influence on storage access performance
and resilience. Data servers can deploy a fast 10 Gigabit Ethernet port
or multiple 1 GbE ports, which you can trunk together for more speed and
As just one example, a modestly configured Dell EMC PowerEdge
R430 rack server offers two processor sockets, 16 GB of memory, four 1
GbE ports and a 1 TB 7.2K rpm Serial Advance Technology Attachment
(SATA) 6 Gbps disk drive by default. However, you can select the R430
chassis to accept varied disk configurations with up to 10 hot-pluggable
Serial-Attached SCSI, SATA, nearline SAS or solid-state drives if the
business chooses to place storage in the server itself. You can also
enhance network performance through a choice of Peripheral Component
Interconnect Express network adapters or storage host bus adapters.
Systems versus CPUs
Many data centers are shrinking as virtualization, fast networking
and other technologies allow fewer servers to host more workloads. The
quandary for server purchases then becomes server count versus CPU
count. Is it better to have more servers or more resources within fewer
servers? Packing more capability into fewer boxes can reduce overall
capital expenses, data center floor space and power and cooling demands.
But hosting more workloads on fewer boxes can also increase risk to the
business because more workloads are affected if the server fails or requires routine maintenance.
Clustering, snapshot restoration and other techniques can help to guard
against hardware failures, but a business still needs to establish a
comfortable balance between server count and server capability, regardless of how the servers are used.
What server features do you look for?
This is the second article of a two-part series on server selection.
The process of purchasing a server is relatively straightforward, but
working out the details of a hardware service contract tends to require
significantly more effort.
The need for a support contract is often overlooked because many in IT assume the hardware warranty protects the company if any problems occur. Although a warranty offers some assurances, it is often inadequate on its own.
For example, suppose a server’s system board fails, but it is covered
under warranty. Each vendor has its own way of handling this type of
issue. Typically, the administrator would need to ship the system board
to the vendor before it sends a replacement. In contrast, a support
contract can provide same-day service for the replacement and
professional installation by a certified technician.
Map out the company’s needs
Prior to negotiating a hardware service contract, consider what
matters most to the organization. Why obtain a support agreement in the
first place? Does the organization require immediate access to hardware
parts during a critical outage? Does the IT staff lack the technical
skills to handle hardware-level repairs? Make sure that any service-level agreements the organization must adhere to are part of the equation.
Keep these factors in mind during discussions with a support vendor,
and make sure you address three key areas in a hardware service
Pin down terms to avoid a lengthy outage
First, negotiate the response time. When a critical issue hits the
data center, there should be no doubt about the availability of the
Most rapid response support contracts are expensive because they
might require the provider to hire extra staff members. One way to
reduce this cost is to negotiate a two-tier response time. For example,
the contract might require the provider to respond within 48 hours for
noncritical outages, but also to have a tech on site within an hour for
any outages the organization deems critical.
Prior to negotiating a hardware service contract, consider what matters most to the organization.
Second, lock down the availability of replacement hardware. It’s
pointless to have a contract that requires the provider to respond to a
critical outage within an hour if it takes the needed parts a week to
At one time, organizations relied almost exclusively on physical
servers, and the server’s operating system was tied to its specific
hardware configuration. Backups could not restore to dissimilar
hardware. To account for this, most service agreements required
providers to have exact duplicates of the organization’s hardware so it
could swap out an entire server if necessary.
Server virtualization makes this less of an issue, but the provider’s inventory remains an important consideration. During an outage,
an organization needs to get back online as quickly as possible. As
such, a good contract for hardware service should require the support
vendor to maintain an inventory of spare parts that match your server
hardware. It is also a good idea to make sure the agreement provides
loaner servers if the service vendor does not have the required parts
The hardware support agreement should address the quantity of repair
parts the vendor needs to keep in stock. Multiple servers can break at
the same time. The support contract should eliminate any chance a
cascading failure would leave the company vulnerable.
Third, consider adding warranty handling to the hardware service
contract. This is less critical than the other items, but it is worth
considering. Because some of the hardware is covered under warranty,
ideally, the support provider should handle the warranty claims.
If a system board fails, then the service vendor should replace that system board with a spare, file a warranty claim and ship the failed part to the manufacturer. This offers the dual benefit of a quick system recovery and frees the IT department from dealing with warranties.
When the time comes to buy server hardware, there are a lot of
factors to consider, such as the number of processors, the available
memory and the total storage capacity. Buyers should closely evaluate
eight important features when comparing the servers available from the
These eight features cover the basic components to look for to buy
server hardware, but they don’t represent all the features that buyers
should consider. Decision-makers at every organization must determine
exactly what they need to support their existing and future workloads,
keeping in mind the differences between rack, blade and mainframe computers.
Companies should view these eight features as the starting point to
identify their requirements and evaluate the available products and
should expand their research as necessary to ensure they’re addressing
One of the most important components to consider when buying server
hardware is the processor that carries out the data computations. Also
referred to the central processing unit (CPU), the processor does all
the heavy lifting when it comes to running programs and sifting through
data. Most servers run multiple processors, usually with one per socket.
However, a processor can also be made up of multiple cores to support
usually translate to better performance, but the number of cores is not
the only factor to consider. Buyers should also consider the processor
speed — CPU clock speed — and available cache, as well as the total
number of sockets, as these can differ significantly from one processor
to the next.
For example, the NEC Express5800/D120h blade server supports up to
two processors from the Intel Xeon Scalable product family. One of the
most robust of these processors offers 26 cores, 35.75 MB of cache and a
2.0 GHz clock speed.
Compare that to the Dell PowerEdge M830 blade server, which uses
Xeon E5-4600 v4 processors. The most robust of these offers 22 cores, 55
MB of cache and a 2.20 GHz clock speed. The Dell server also supports
up to four processors rather than two.
With extensive research into the server market, TechTarget editors
have focused this series of articles on server vendors with
considerable market presence and that offer at least one product among
blade, rack and mainframe types. Our research included Gartner,
Forrester and TechTarget surveys.
Adequate server memory is essential to a high-performing system, and
the more memory that is available, the better the workloads are likely
to perform. However, other factors can also contribute to performance,
such as the memory’s speed and quality. Most server memory is made up of
dual in-line memory module integrated circuit boards with some type of
Companies should view these eight features as the starting point to
identify their requirements and evaluate the available products and
should expand their research as necessary to ensure they’re addressing
Server memory might also include fault-tolerant capabilities or
other features that enhance reliability. One of the most common
capabilities is error-correcting code (ECC), a method to detect and
correct common single-bit errors. When evaluating server hardware
memory, you should look at the entire offering, keeping in mind the
types of workloads and applications you run.
For example, Fujitsu’s mainframe computers in the BS2000 SE series
support up to 1.5 TB of memory. However, IBM’s ZR1 mainframe, which is
part of the z14 family, supports up to 8 TB of memory. The ZR1 also
provides up to 8 TB of available redundant array of independent memory
to improve transaction response times, a pre-emptive dynamic RAM feature
to isolate and recover from failures quickly, and ECC technologies to
detect and correct bit errors.
Servers vary greatly in the amount and types of internal storage
that they support, in part because workflows and applications also vary.
For example, a server hosting a relational database management system
will have different requirements than one hosting a web application. In
addition, the use of external storage, such as storage area networks
(SANs), can also impact internal storage requirements.
When you buy server hardware, be sure to evaluate each prospective
server to ensure it can meet your storage needs. Today, most servers
support both solid-state drives (SSDs) and hard disk drives (HDDs). But
buyers should certainly verify this support, as well as the server’s
supported drive technologies, such as Serial-Attached SCSI (SAS), Serial
Advanced Technology Attachment (SATA) or non-volatile memory express
(NVMe). Other considerations should include drive speeds, capacities,
endurance and support for redundant array of independent disks (RAID).
For example, Oracle’s X7-2 rack server can support up to eight
2.5-inch HDDs or SSDs, either SAS or NVMe, and multiple RAID
configurations. Compare that to the Inspur TS860G3 rack server, which
can handle up to 16 drives, either SSDs or HDDs, and support both SAS
and SATA. However, the Inspur server does not support NVMe, which means
the SSDs might not perform as well.
A server’s ability to connect to networks, peripherals, storage and
other components is essential to its effectiveness within the data
center. The server needs the necessary connectors and drivers to ensure
that it can properly communicate with other entities and process various
workloads. Buyers need to determine exactly what type of connectivity
is necessary and, from there, examine the server’s specs to verify
whether it will meet those requirements.
Servers differ widely in this regard, so buyers should look for
specifics such as the number and speed of the Ethernet connectors, the
number and type of USB ports, the availability of management interfaces,
the types of protocols available, support for SANs and other storage
systems, as well as whatever other components are necessary to
Acer’s rack server Altos R380 F3 is a good example of what
connectivity features to look for when you buy server hardware. It
includes two Ethernet ports, either 1 GB or 10 GB, an RJ-45 management
port, three USB 3.0 ports, one USB 2.0 port, and a video port. In
addition, the server offers up to seven Peripheral Component
Interconnect Express (PCIe) 3.0 slots and one PCIe 1.0 slot.
Servers offer hot swapping capabilities to varying degrees. Hot
swapping refers to the ability to replace or add a component without
needing to shut down the system.
The term hot plugging sometimes refers to hot swapping, although, in
theory, hot plugging capabilities are limited to being able to add
components but not replace them without shutting down the system.
Because of the confusion around these terms, it is best to verify how
each vendor uses them.
One of the most common hot swappable components is the disk drive.
For example, the Cisco UCS B480 M5 blade server supports hot swappable
drives, as does the Huawei FusionServer CH242 V5 blade server and the
Intel R2224WFQZS rack server.
With blade systems, the hot swapping capabilities are often within
the chassis itself. One example is the chassis used for the Lenovo
ThinkSystem SN850 blade server, which provides hot swapping capabilities
for the fans and power supplies, in addition to the server’s disk
drives. However, these types of capabilities are not limited to blade
servers. The Acer Altos R380 F3 system also supports hot swappable fans
and power supplies even though it is a rack server.
Redundancy is important to ensure a server’s continued operation in
the event of a component failure. Most servers provide some level of
redundancy, often for the hard drives, power supplies and fans. The Asus
RS720-E9-RS12-E rack server, for example, offers redundant power
supplies and the HPE ProLiant DL380 Gen10 rack server offers redundant
As with its hot swapping capabilities, the redundancy available to
blade servers is often located within the chassis. For instance, the
chassis that support the Dell PowerEdge M830 blade server and Supermicro
SBI-6129P-T3N blade server both provide redundant power supplies.
However, the Dell chassis also offers redundant cooling components, and the server itself provides redundant embedded hypervisors.
Admins must manage a server
effectively to ensure its continued operation while delivering optimal
performance. Most servers provide at least some management capabilities.
For example, many servers support the Intelligent Platform
Management Interface (IPMI), a specification developed by Dell, Hewlett
Packard, Intel and NEC to monitor and manage server systems. Not
surprisingly, the servers offered by these companies, such as the Dell
PowerEdge M830, HPE ProLiant DL380 Gen10, Intel Server System R2224WFQZS
and NEC Express5800/B120g-h, are IPMI-compliant.
But servers are certainly not limited to IPMI capabilities. For
example, the Acer Altos R380 F3 rack server comes with the Acer Smart
Server Manager; the Asus RS720-E9-RS12-E rack server comes with the ASUS
Control Center; and the Cisco Unified Computing System (UCS) B480 M5
blade server comes with Cisco Intersight, Cisco UCS Manager, Cisco UCS
Central Software, Cisco UCS Director and Cisco UCS Performance Manager.
Blade systems usually provide some type of module to manage the
individual blades. For instance, Huawei’s FusionServer CH242 V5 blade
system includes the Intelligent Baseboard Management System module to
monitor the compute node’s operating status and support remote management.
Not surprisingly, systems such as Fujitsu’s BS2000 mainframes
provide a variety of management capabilities. For example, each BS2000
system includes a management unit that works in conjunction with the SE
Manager to offer a centralized interface from which to administer the
entire server environment.
And IBM’s ZR1 mainframe includes the IBM Hardware Management Console
(HMC) 2.14, the IBM Dynamic Partition Manager and an optimized z/OS
platform for IBM Open Data Analytics.
Another important factor to consider is the server’s security
features. As with other features, servers can vary significantly in
what they offer, with each vendor taking a different approach to
securing their systems.
For example, the Lenovo ThinkSystem SN850 blade server provides an
integrated Trusted Platform Module 2.0 chip to store the RSA encryption
keys used for hardware authentication. The server also supports Secure
Boot, Intel Execute Disable Bit (EDB) functionality and Intel Trusted
Another example is the Oracle Server X7-2 rack server, which comes
with the Oracle Integrated Lights Out Manager 4.x, a cloud-ready service
processor for monitoring and managing system and chassis functions. On
the other hand, the Huawei FusionServer CH242 V5 blade server supports
the Advanced Encryption Standard — New Instructions, as well as Intel’s
EDB feature and Trusted Execution Technology.
IBM’s ZR1 mainframe is also strong when it comes to security. The server includes on-chip cryptographic coprocessors and the Central Processor Assist for Cryptographic Function (CPACF), which includes the new Crypto Express6S feature to enable pervasive encryption and support a secure cloud strategy. The CPACF is standard on every core. The platform also includes IBM Secure Service Containers to securely deploy container-based applications.
The field of data storage is massive and continues to grow as the years go by. Naturally, this leads to a large number of questions that need to be answered. Our Ask the Expert articles enlist top experts and analysts to tackle common data storage questions readers have about different storage technologies and developments.
While storage technology has grown more complex, reader interest
often points toward basic concerns. In 2018, expert answers covering
RAID levels, storage infrastructure comparisons and units of capacity measurement
garnered the most interest. Of course, while these data storage
questions lean toward the basics, they have clearly been affected by the
changes in the storage market.
Below, we’ve compiled the top five most-read Ask the Expert articles
of 2018. Symbolic of the ever-evolving, but consistent, storage market,
all five pieces have been updated to reflect modern changes to evergreen
Memory and storage: What’s the difference?
Memory and storage, while connected, aren’t synonymous. Both refer
to internal data storage space on a computer, and the major difference
between the two lies in the state of the data when the storage system is
off. However, as storage technology evolves, the line between memory and storage
is beginning to blur. It’s no wonder that this was one of the most
prominent data storage questions readers were searching for this year.
RAID levels explained
While RAID is a storage standby, it continues to grow and change as storage requirements do. The benefits of RAID
include improved performance and higher availability, along with
relatively low costs. RAID today is broken into three separate
categories: standard, nonstandard and nested. Numbered 0 to 6, standard
RAID levels represent the original basic RAID, while nonstandard levels
and nested RAID cover RAID levels set for particular open source
projects and combinations of RAID levels.
Looking for a refresher on the state of RAID levels? You’re not
alone. In this expert answer, we break down RAID levels and benefits and
how they’re used today.
Terabytes, petabytes, exabytes and more
Long gone are the days when a 1 TB drive was an unimaginably large amount of storage space.
It only makes sense that, as storage capacities grow, units of
measurement must grow as well. Long gone are the days when a 1 TB drive
was an unimaginably large amount of storage space. “What is bigger than a terabyte?”
is no longer a theoretical storage question, and while these large
amounts of data may yet have practical commercial uses, it won’t be long
before they are put into wider use.
What is bigger than a terabyte? Well, there’s a petabyte (1,024 TB), an exabyte (1,048,576 TB), a zettabyte (1,073,741,824 TB) and more. You get the gist.
NFS vs. CIFS/SMB
Both NFS and CIFS/SMB were designed to work with any OS, but in
Linux and SMB in Windows, NFS reigns supreme. Once a heated debate, NFS and CIFS/SMB
have taken on similar characteristics over time and are supported by
most enterprise storage systems. Perhaps it’s because of these
similarities that “What is the difference between NFS and CIFS/SMB?” was
one of the more prominent data storage questions asked in 2018.
Regardless, readers will now find that, despite their lengthy
history of facing off, the two protocols are now more similar than
they’ve ever been.
Network storage showdown: SAN vs. NAS
SAN and NAS are staples in the field, so what data storage questions could you possibly have about them? Well, while the technologies are established, the nuances and uses continue to change with the world around them. The differences and benefits of SAN and NAS aren’t the same as they used to be and will continue to change. In this expert answer, we explore how the two architectures compare, the advantages and disadvantages of each, and where they’re headed in the future.
Revenue was up 37.7% year-on-year overall, marking the third quarter out as the fifth consecutive quarter of double-digit growth the worldwide server market has enjoyed in recent times. Meanwhile, shipment volumes were up 18.3% on the previous year and totalled 3.2 million units.
Sebastian Lagana, research manager of infrastructure platforms and technologies at IDC, said the figures are indicative of how high the demand is for datacentre hardware from the cloud and internet giants at present.
“The worldwide server market once again generated strong revenue and unit shipment growth due to an ongoing enterprise refresh cycle and continued demand from cloud service providers,” said Lagana.
“Enterprise infrastructure requirements from resource intensive next-generation applications support increasingly rich configurations, ensuring average selling prices [ASPs] remain elevated against the year-ago quarter. At the same time, hyperscalers continue to upgrade and expand their datacentre capabilities.”
The market’s record quarter appears to have been primarily driven by the growth in volume server shipments, as the revenue generated by this category of hardware was up 40.2% on the previous year and hit $20bn.
IDC has directly attributed the surge in demand for volume units to the datacentre refresh and build-out activities of the hyperscale cloud and internet service provider community in previous quarters.
The main beneficiaries of this trend tend to be the original design manufacturers (ODM), who saw their share of the server market creep up by 2.5% to 26.8% from third quarter 2017. This group of suppliers also grew their collectively revenue by 51.9% during the past 12 months.
While the ODM community collectively holds the biggest share of the server market, Dell is name-checked by IDC as the server market leader with 17.5% revenue share, and quarterly revenue of $4.09bn, which is up 33.3% on the previous year.
The company was founded in 2009 by Dheeraj Pandey, Mohit Aron and Ajeet Singh, and it is based in San Jose, Calif.
Nutanix appliances converge storage, compute and virtualization into one box. Initially targeting VMware customers, Nutanix branched out after VMware released its own Virtual SAN hyper-converged platform. The vendor’s products now support Microsoft Hyper-V and KVM hypervisors, as well as VMware vSphere and Nutanix’s own KVM-based Acropolis hypervisor (AHV).
Nutanix branded appliances consist of the vendor’s software stack packaged on Super Micro servers. Original equipment manufacturer (OEM) partners Dell and Lenovo rebrand Nutanix software on their x86 servers, and Nutanix channel partners package the vendor’s software on Cisco and Hewlett Packard Enterprise (HPE) servers. IBM also has an OEM deal with Nutanix to sell its software on Power servers.
Nutanix came out of stealth in 2011 with Complete Cluster, one of the first hyper-converged storage products on the market. In June 2013, Complete Cluster was rebranded as the Virtual Computing Platform, and two new configurations with smaller and larger capacities were added to the line.
In its first two years, company revenue surpassed $100 million. In June 2014, Nutanix entered into an OEM deal with Dell that allowed Nutanix software to be sold on Dell PowerEdge servers.
In December 2015, Nutanix filed for an initial public offering, reporting revenue of $241.1 million for the year. Though the IPO took nine months to complete, Nutanix revenue grew 125% to $166.8 million in its first quarter as a public company. However, losses were also high at $162.2 million.
This video from Nutanix explains the company’s approach to the enterprise cloud.
In 2017, Nutanix leadership focused its business model on the company’s software. While the vendor will still sell appliances, it intends to continue selling software on any vendor’s x86 hardware and to count revenue only from its software business.
In June 2017, Nutanix announced a partnership with Google that enables customers to deploy and manage workloads across Google Cloud Platform and its in-house hyper-converged infrastructure (HCI) through a single interface.
Major products and their important features
Despite a push to focus primarily on being a software company, Nutanix products include both software and turnkey appliances. Here are some of the vendor’s major products and services:
The Nutanix Virtual Computing Platform ships with VMware ESX or Red Hat KVM and includes hard disk drives and solid-state drives. It also provides storage features, such as tiering, compression and deduplication.
Nutanix Enterprise Cloud converges server, storage, virtualization and networking into one software-defined platform. The Enterprise Cloud Platform is scalable, and it’s available as a turnkey appliance or a software-only platform.
Nutanix Calm, part of the Nutanix Enterprise Cloud Platform, handles application automation and lifecycle management across public and private clouds.
Xi Cloud Services are an extension of the Nutanix Enterprise Cloud Platform. Xi Cloud Services deliver a public cloud environment that can be automatically configured and provisioned. The Xi Disaster Recovery Service enables centralized DR management, one-click failover and nondisruptive disaster recovery (DR) testing.
Nutanix X-Ray is the vendor’s automated testing and benchmarking tool. X-Ray can simulate the effects of system failures, software upgrades and other common scenarios to enable better DR planning.
Nutanix Acropolis software includes its hypervisor, file and block storage services, data protection, and network and security features. Acropolis is available in Starter, Pro and Ultimate editions, which vary based on the size of the deployment and the number of workloads.
Nutanix Prism software uses machine learning technology to help manage, monitor and analyze the vendor’s hyper-converged infrastructure.
Although Nutanix was the first hyper-converged vendor to make a big splash in the market, it is far from alone now.
Dell EMC not only sells Nutanix software in its XC Series on PowerEdge servers, but it competes with Nutanix with a vSAN-based VxRail appliance from VMware — which it owns. In mid-2017, Dell EMC passed Nutanix as the hyper-converged market leader, according to research firm IDC.
HPE and Cisco made acquisitions in 2017 to bolster their HCI products. HPE acquired early Nutanix competitor SimpliVity for $650 million, and it now sells SimpliVity software on ProLiant servers. While Nutanix software supports HPE servers, HPE has no relationship with Nutanix, and it recommends its own SimpliVity software on ProLiant servers.
Storage vendor NetApp entered the HCI market in 2017, using its SolidFire Element OS as the basis of the all-flash NetApp HCI product. NetApp HCI is technically considered a disaggregated, software-defined architecture, but it can be deployed for use cases similar to HCI and uses the same high-density unit appliance as Nutanix and other HCI vendors.
Nutanix’s Google partnership puts it in competition with Amazon Web Services, which has partnered with VMware to target an enterprise market with on-premises workloads. Lenovo, which partners with Nutanix and other HCI software vendors, also sells hyper-converged appliances.
Other HCI competitors include smaller companies, such as Maxta, Pivot3 and Scale Computing.
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