Eco4Cloud announces EcoInterCloud, which extends their workload consolidation algorithm to intelligently manage workloads across multiple datacenters. EcoInterCloud aims to improve efficiency, resiliency, and policy-driven optimizations for "intercloud" architectures. It utilizes a hierarchical two-layer architecture to exchange information and distribute virtual machines between geographically distributed datacenters while allowing for independent optimization within each datacenter. EcoInterCloud delivers benefits like reduced costs, improved service quality, load balancing, and reduced inter-datacenter traffic.

1. Eco4Cloud – global leader in intelligent workload management solutions
for virtualized data centers and the cloud– today announces
EcoI nterCloud. EcoInterCloud extends Eco4Cloud’s native intra-
datacenter workload consolidation algorithm and award‑winning solutions
to work across multiple datacenters and improve efficiency, resiliency and
policy‑driven optimizations within so called intercloud architectures.
The potential improvements provided by cloud technologies are often
overlooked, as 451 Research articulates in its “Eco4Cloud Floats the
Concept of the EcoInterCloud for Datacenter IT Efficiency” Impact report,
and the notion of intercloud is set to drive the next stage in Cloud
adoption. Intercloud in fact is meant as a set of hybrid cloud architectures
which enable and automate the seamless mobility of workloads within and
between multiple cloud instances. Intercloud is clearly enjoying a growing
popularity and has already become an arena for competitive differentiation
among heavyweight industry leaders such as Cisco, HP, VMware, IBM and
others who are touting their respective strategies and architectural
frameworks in this space.
Eco4Cloud sees intercloud as ideal to maximize the native technical and
business benefits of its innovative and award‑winning workload
management technology, significantly contributing to the level of
intelligence by which bidirectional workload mobility is managed and
–ideally– automated in policy‑driven intercloud implementations.
Eco4Cloud has in fact identified a number of drivers for its EcoInterCloud
architecture and solutions:
Host Thin Provisioning: autonomically provisioning only the
number of physical servers and cores that applications need at any
given time, by dynamically consolidating workloads and switching
on/ off physical cores in real-time hence maximizing the utilization of
available computing resources (i.e., CPU, RAM) and power managing
or decommissioning the remainder. With EcoInterCloud this capability
is now applied to multiple geographically distributed facilities and
clouds.
Cost reduction: EcoInterCloud can be used to bidirectionally shift
workloads between facilities depending on a variety of policy‑set
criteria, such as to max out the utilization of available capacity, to
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2. providers as workloads can also be shifted between sites at different
times of the day or night (a process also known as “follow the
moon”) based on related cost and/ or convenience.
SLA and Quality of Service Managem ent: organizations that
manage multiple datacenters may want to ensure workloads are
proportionally balanced across sites in order to improve the
responsiveness of specific sites and reduce the impact on physical
infrastructure such as power and cooling systems. In fact the
workload must be distributed without overloading any individual site.
This in fact may affect the quality of the service, which on the other
hand may be improved by intelligently combining applications (i.e.,
VMs) having complementary characteristics (e.g., CPU-bound with
RAM-bound applications).
Load Balancing: in a multi-DC/ Cloud environment –especially if
managed by the same organization– it may be crucial to properly
balance the load distributed across different sites, as a better balance
may help improve the responsiveness of the individual sites,
decrease the impact on physical infrastructure –e.g., in terms of
cooling and power distribution–, and help prevent overload
conditions.
I nter-DC traffic reduction: Eco4Cloud’s EcoInterCloud architecture
can also be functional to intelligently determining which workloads
should remain within a specific facility rather than being migrated to
another site, as in fact not all workloads are equally portable
–especially those associated with large data sets– and the amount of
inter-DC bandwidth and/ or latency could also be a limiting factor to
consider. So, in some cases it is more efficient to assign a VM to the
local data center instead of moving it to a remote data center
depending on many factors, among which the amount of data used
by the VM, the available inter-DC bandwidth and the type of
applications hosted by the VMs. For example, choosing a local data
center is more convenient if the VM hosts a database server as
opposed to a web service just because of the intrinsic characteristics
of the respective VMs.
All of these drivers may have different relevance and priority for individual
data centers or Companies, and EcoInterCloud enables the intelligent
combination of choice delivering efficiency and flexibility combined. In fact,
the efficiencies and optimizations which EcoInterCloud introduces to an
intercloud environment deliver value on multiple fronts, effectively being
based on a novel and distinct degree of additional architectural intelligence
by which intercloud implementations can operate. These functional values
are further enriched by the inherent and differentiating attributes of
Eco4Cloud’s algorithm, i.e.: unlimited scalability, technology platform
independence, real‑time adaptation, unified management.
"EcoInterCloud truly raises the bar of the architectural intelligence and
differentiated value of intercloud solutions, delivering tangible benefits to
end users and Cloud providers alike. Eco4Cloud keeps innovating in one of
the hottest spaces of IT, contributing to the evolution of cloud
architectures and we’re thrilled for the opportunity ahead," said Roberto
Mircoli, CEO of Eco4Cloud.
"The potential datacenter efficiency improvements provided by cloud
technologies are often overlooked due to the disconnect between IT and
facilities management. Eco4Cloud appears to be taking a lead in this area
with EcoInterCloud and courting some of the right potential partners.
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3. orchestration," said Andrew Donoghue, European Research Manager, 451
Research.
EcoI nterCloud Architecture
The EcoInterCloud architecture for the efficient and autonomic
management of the workload in a multi-DC/ Cloud scenario is hierarchical
and composed of two layers:
an upper‑layer to exchange information among the different sites and
drive the distribution of Virtual Machines (VMs) among the
geographically distributed data centers
1.
a lower‑layer to manage the workload within individual data centers.2.
This 2‑layers architecture allows most of the intelligence to be maintained
within the individual data centers (i.e., the lower‑layer), which can then
implement their workload optimization policies independently of the
orchestration taking place at the upper‑layer.
In addition to decentralization, a key attribute which results from
EcoInterCloud’s 2‑layers architecture is its modularity: each layer can in
fact tune and customize its respective algorithms and related workload
mobility decisions independently, pursuing different optimization strategies
with no impact, implications or dependencies on/ from the other layers.
This whitepaper co‑authored by Eco4Cloud and European excellence
centers such as the Institute for High Performance Computing and
Networking of the Italian National Research Council (CNR) and the
Department of Electronics and Telecommunications at Politecnico di Torino
frames EcoInterCloud and its scientific foundations:
I nter‑Cloud W orkload Optim ization – A Scalable Hierarchical
Approach
More on EcoInterCloud: www.eco4cloud.com/ ecointercloud
Published Wednesday, February 11, 2015 12: 58 PM by David Marshall
Filed under: Cloud
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