Grid Computing:
Addressing Today’s Business Issues.
A Viewpoint by Deloitte Consulting LLP
Grid Computing:
The Next Step
Addressing Today’s Business Issues
with Grid
During the 1990s, productivity growth
accelerated and has remained historically high
due to a number of factors, including
developments in information technology and
business processes. This boom in IT has
helped lead to productivity gains and new
market opportunities for the world’s major
economies. Some have gone so far as to refer
to this boom as a technology revolution but,
in fact, it seems to be more of an evolution.
And, the evolution continues as organizations
look again to IT to address issues of efficiency,
speed, and cost savings for supporting
infrastructure. Grid computing could be the
next step in dramatically improving IT
operations and leveraging existing capability
to support the enterprise.
Ask any group of IT professionals what grid
computing is and the benefits it provides and
you will get a wide range of definitions and
opinions. Everyone is in agreement that, for
IT to realize its great promise of streamlining
business processes, it needs to provide
business solutions of greater flexibility and
speed with an eye toward optimizing
resources. To quote an old axiom, IT needs to
lead the way in helping businesses do “more
with less.”
Many organizations are moving in this
direction and away from a hardware-based,
or a supply-side, perspective. Demand-side
solutions are needed, that is, better
alignment between business and IT. Grid
computing offers the flexibility to direct
computing resources to support the business,
making underutilized capacity available to
process critical business transactions and to
support new IT enabled business solutions.
Defining Grid Computing
At its most basic, grid computing can be
defined as a virtual environment in which an
application no longer is reliant on a single, selfcontained system, but rather has access to the
computing resources it needs, as those
resources are needed. Grid environments are
collections of dispersed resources that can be
shared to help address specific business
requirements. Grid computing is often
compared to our electrical grid. We take what
is needed, and only what is needed, to perform
a specific task, be it providing light, listening to
music, or drying our hair in the morning. The
rest is there to be utilized by others.
Grid is frequently compared to other
technologies, or even considered to be similar
to them.
Technology
Similarities
Differences
Virtualization
A grid enables components to be
viewed as a similarly available pool
of resources. Work can be performed
on any of them in a like manner
Virtualization is usually on a single
system or a set of similar components
managed to change overall unit size.
Unlike virtualization, a grid pulls
together heterogeneous components
from anywhere, even globally, to form
an IT service delivery pool
Clusters
Clusters and grids bring computing
resources together to solve a single
problem and can have single
management tools for all the
components
Clusters are typically made up of
components of similar hardware and
software while grids are made of
disparate hardware possibly separated
by vast distances and running different
operating environments
Peer-to-peer
Both can share files and
communicate directly with one
another, sometimes through the
implementation of a central broker
Grids can use many-to-many
relationships to share a variety of
resources other than just files
The web
A grid keeps all the complexity
hidden. It connects dissimilar
resources to each other and enables
a single unified view of the
environment
A grid allows machines work together
and collaborate rather than just talk to
each other
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Grid Computing: The Next Step
The value comes from working more efficiently, optimizing existing
resources, and delivering on your service promises now, rather than
hours from now.
While compute-grids (the sharing of CPUs) are
most commonly thought of as the definition of
“grid,” there are actually many more
implementations of grid technologies.
Information grids, for example, provide
virtualized, federated, and consolidated views
of enterprise information while other grids exist
that share memory and network resources—
even this is not a comprehensive list.
For the purposes of assessing the highest
impact on business, we’ll limit our discussion
to computational grids.
The Value of Grid
Imagine a server requiring many minutes or
even hours, at full capacity, to perform a
particularly complex and critical calculation in
which the results are needed right away. Now
imagine that server being able to access the
idle capacity of another server that is not
operating at its peak. Add in the computing
capability of dozens, hundreds, or even
thousands of machines and you can see the
real value of grid computing—providing the
ability to do things that could not previously
have been considered and in less time.
The value is not in doing the one small piece
more efficiently, it’s the net result of the
overall workflow that can deliver a real
business difference. As organizations evaluate
the business lifecycle and identify the
component processes that are part of their
automated support systems, those
component processes—each with its own
workload attributes—represent functions or
services that deliver end value to the business.
By applying grid technology to some or many
of those components, the overall time to
completion can be shortened. All of these
“little” items add up. They have an upstream
and downstream correlation and impact other
processes.
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In our experience, grid clients have found that
by taking typically long-running processes,
cutting the delivery time through grid
computing, and transforming these processes
into real-time transactions, new revenue could
be generated. Conversely, clients in other
situations discovered that no matter how
much hardware is thrown at the problem,
they were not achieving the desired results in
a timely fashion. The latter would be an
example of a typical “supply-side” solution.
Grid computing is a “demand-side”
solution—addressing the business
environment’s demand for greater computing
power and speed. Such improvements enable
business transformation without
reengineering the overall process. This is the
real “ah ha” that leading companies discover
with grid computing. They realize it’s much
more than driving up server utilizations—
although that might have been the starting
point. The value comes from working more
efficiently, optimizing existing resources, and
delivering on your service promises now,
rather than hours from now. Bottom line: the
analysis to identify these opportunities is fairly
easy to perform in a few days to a couple of
weeks with the right participants, and the
benefits can continue for years to come.
The “Other” Workload Pattern
There are two main types of business process
patterns that grid computing technology
supports. These business process patterns are
typically components or subcomponents of a
larger workload.
“Parallel execution” is the first of the two
workload patterns—the one that most people
think of—when considering grid. In reality
this is only about 20 percent of where grid
technology can provide value.
The other workload pattern is “high
concurrency.” High concurrency patterns are
typical request/respond processes where
multiple requests for similar functions or
services are made. Examples might include an
application server environment, a
publish/subscribe (pub/sub) environment, or
an enterprise server environment. Eighty
percent of observed grid implementations are
of this pattern but initial grid projects rarely
consider these operations as applicable to
grid-enablement.
“Parallel execution” is one-to-many, i.e.,
one request results in many tasks that get
spread out and executed over a broad
environment. The workload is fairly
predictable. Every hour, every day, every
week, every month, a business process is
performed and resources are consumed
while performing a particular analysis,
running a report, doing a batch job, or
running other processes of this nature.
These workloads can be real-time or batch
with a typical work pattern of load,
execute, read, and write. They are
measured in seconds and frequently time
out over minutes or hours—and sometimes
even longer.
When you apply grid to such parallel
processing models the objective is typically
to collapse execution times and to create a
higher load on resources—to use more of
the available capacity and leave fewer idle
assets.
Grid Computing: The Next Step
Across industries, high performance
computing in the form of parallel processing
is being performed over grids. In financial
services it includes risk analysis, valuations
and simulations; in electronics it includes
semiconductor design; in industrial
manufacturing it’s crash and clash simulation;
in life sciences it’s drug discovery research; in
energy it’s seismic processing and reservoir
simulation; in utilities it’s statement
generation; and in entertainment and media,
it’s graphics processing and rendering over
grid-enabled server infrastructure.
There are many other grid opportunities that
are overlooked. For example, there are
opportunities to apply grid to unstructured
data processing. This may take the form of
PDF rendering, converting XML data into and
out of databases, or creating compressed, or
ZIP, files as part of reducing file size before
network transmission.
Though it’s not typically considered, “high
concurrency” can achieve similar or even
greater benefits from a grid computing
environment. While parallel execution
represents the one-to-many model, high
concurrency is the many-to-one model. Simply
put, high concurrency is multiple requests for
the same or similar service (versus the same
service making many requests). Requesting a
bank balance is such an example. The
requester doesn’t care who else may be
making such a request, just that his or her
request is satisfied in the expected timeframe.
During their request another thousand such
requests might be made, with all having to be
satisfied with the same level of service.
These tasks or services are typically short-lived
and their volume may be very volatile and
unpredictable. They might be milliseconds in
nature but at very high volumes. Thus, it is
important that the service or application not
be loaded every time the request is made.
Loading the application or service with every
request would result in constant
reprovisioning of the service to meet each
request. The related cost, overhead, and
latency can create significant performance
issues. As volumes peak, the situation only
gets worse by multiplying the latency.
Grid computing provides a solution. Grid
nodes can maintain their “state” for a
predefined duration and additional nodes can
be provisioned if loads exceed certain
thresholds. In other words, grid management
tools can ensure that the code required to be
executed remains loaded even if there are no
immediate requests.
In both models (parallel execution and high
concurrency), creating a solution that has
horizontal scalability, as in grid computing,
provides value to the business. Rather than
having to upgrade larger SMP servers at
considerable expense, the grid can grow its
capacity through the addition of lower-cost
servers, such as Blades. As opposed to the
traditional model of shared computing, the
grid processing model allows for
improvements in granular growth, application
scalability, resiliency, and the tying of business
needs to IT performance. Furthermore, this
growth can be obtained through idle
resources or from third-parties.
The objective of looking at any new
technology should be to answer the question,
“how can improvements be made to change
the way the organization processes, services,
bills, and supports its users and their
applications?” Addressing this organizational
issue can determine where grid technology
can most effectively be applied.
Grid is Now
We often hear that grid is not ready for the
production environment. Yet leading
companies are using grid computing in
production today, measured in tens-ofthousands of nodes, or CPUs, and spanning
multiple continents. Even now, grid
environments are on par with traditional
enterprise application servers and growing.
Grid has now become a better alternative to
service execution than traditional application
server environments, largely due to grids’
horizontal scaling, inherent resiliency, and
dynamic alignment to business priorities. The
application server environment requires that
applications execute on specific servers and
therefore necessitate their availability. Growth
is typically through upgrade of the single
servers and management of the workloads is
a labor-intensive activity.
Grid middleware is most often the software
enabler of a grid environment. Some
companies have created custom solutions
that they consider grid solutions. Custom grid
solutions are usually specifically written into
an application to provide grid-like benefits.
These take considerably longer and cost more
to develop and maintain than commercially
available middleware. The one-off nature of
the custom solution may prohibit moving to
an enterprise-wide solution and potential
inclusion in a utility environment. Proceeding
along a strategy of custom developed grid
solutions might maintain technology silos,
perpetuate inefficiencies, and result in
continued pools of unused capacities.
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Grid Computing: The Next Step
Grid middleware typically sits in the
application layer and is not a resource
management play as many consider. There
are many tools in the marketplace today that
perform resource management functions
independently of grid. Grid middleware
provides additional business value when
integrated with resource management tools
enabling further optimization of IT
performance against business rules.
Single application or departmental grid
environments certainly provide value in a
point solution. Building multiple grids in
multiple organizational silos simply maintains
inefficiencies. Only when organizations
broadly share and pool resources, and
consider grid as part of a shared service, can
all the IT and business benefits be achieved.
Enterprise grid deployment strategies are
where the IT leaders are today. Getting serverhuggers to share and getting to an
enterprise-enabled architecture is a political
and emotional battle – not a technical one.
Getting From Here to There
IT organizations have traditionally built out
their infrastructures (and for the most part
still do) from the supply-side up (providing
hardware and software on which to run
applications), without fully considering the
application environment. The IT organization
tries to improve on this today through server
consolidations that expand utilization by
focusing on tools that partition the hardware
into more granular components. By
implementing a “service-contract view,”
organizations can realize the benefits of a
more holistic approach from the demand-side
(under what rules and schedules the business
processes need to complete).
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Different users have different needs at
different times of the day (or month, or year)
and ask for different tasks to be executed.
They might be one-to-many, or many-to-one,
or both. IT needs to take that demand and
apply the business rules to ensure the needed
supply is available. This will ensure that supply
is matched to the demand based on the
rules—on who someone is, what they are,
and what resources they need. No longer
would the limitations of a user’s hardware
impact performance. In the grid environment
the limitations are the same and they are
imposed by the business.
Designing a comprehensive set of rules helps
put in place a grid service fabric that enables
the creation of a virtual execution platform
tied to the operational needs of the business.
The business requirements no longer would
have technical specifications within them.
Instead, the operational needs would reflect
the business critical success factors. With such
an environmental design, working from
demand-down becomes truly possible.
The rule definition provided by grid
middleware drives real gains in productivity.
Frequently there are critical business
functions, such as front and middle-office in
a financial services company, where IT
(application or infrastructure) is sometimes
viewed as being an obstacle standing in the
way. Really it is IT that is the enabler for a
company to compete effectively, or not,
and it can have a real impact on company
margins. What is needed is simply a way to
supply all the IT as dictated by the business
demand. And the answer, in our experience,
is grid.
Defining the Rules: Service Level
Agreements
SLA definition is an important component in
designing a grid environment. When resources
can be shared by anyone (as opposed to being
dedicated to a single process) identifying the
workflow process limitations, the composition
of the workload, the resource requirements,
and constraints that the workload can take
advantage of becomes critical to ensure the
right activities take place at the right times.
A “processing channel” can be created that is
defined by the business rules, processing rules,
resource rules, and priority rules. They can be
tasks that are time driven, event driven, or ondemand service driven. But the rules need to
be identified and defined to be properly
managed and fulfilled in order to meet the
business requirements.
From the IT supply-side, understanding the
state of the infrastructure, what is being
requested, and the type of IOs necessary to
optimize application performance, resource
utilization, and leverage a shared services
infrastructure is needed. Without the right
analysis and planning, and by just enacting
simple priorities, low-priority tasks might not
be executed at all while high-priority tasks
have access to the entire grid. The appropriate
balance needs to be established that maps to
the priorities of the business.
SLA management in a grid environment is a
very important focus area to provide the ability
to dynamically alter the configuration of the
environment. Grid offers this flexibility. The
“dials” that can be used to tune and adjust
for the demand, based on time of day, day of
the week, or other events, further enhance
performance. A “new” environment and set
of configurations based on provisioning or
changing SLAs can assure that the work is
performed in the proper sequence.
Grid Computing: The Next Step
Think of the possibilities. Business volumes can double in this model
without purchasing more hardware; and when the business volumes
decline the resources work on something else.
The result of this type of analysis, which all
businesses should be performing on a regular
basis, is an understanding that the old
methods of supplying IT services no longer
work in today’s dynamic environment.
The SLAs that are developed need to be about
more than just “availability,” and also should
include business rules and metrics supporting
the needs of the enterprise, such as when
exceptions should be made and what specific
events could cause priorities to change.
For anyone who doubts the value of grid
technologies, this exercise very quickly justifies
and explains why grid computing is not some
future technology but rather a competitive
advantage that must not be postponed.
The Benefits of Hardware
Reprovisioning
Most IT organizations traditionally “over
provision” for peak periods. Some servers
are in place only to handle an annual, limited
set of tasks and are otherwise idle the rest of
the year. When the processing environment
is in silos, the excess capacity issue can be
compounded. Most likely there are redundant
systems at the ready for the “just in case”
need but are idle most of the time. All of
these resources can be used in the grid until
their original purpose or event occurs.
Automated tools can be used to drive up
supply efficiency, improve overall application
performance, and perform with fewer
resources that are on the floor now.
Grid’s management components can make
requests to provisioning tools for additional
resources. When SLAs are approaching the
set limits, and the demand is identified as
growing beyond what is currently available,
additional supply can be provided in order to
fulfill SLAs. Once the workload is completed,
the provisioning tools return the resources
back to a defined state or they can maintain
their current configuration.
This temporary, or on-demand, scaling-out is
only now available as a result of the
combination of defined business rules, the
virtualization aspects of grid, and the current
state of provisioning tools.
Think of the possibilities. Business volumes
can double in this model without purchasing
more hardware; and when the business
volumes decline the resources work on
something else or are returned. Companies
have computing environments with capacities
that are designed to handle volumes seen for
just a few weeks, yet are idle (and being paid
for) 11 months of the year. Many tax
preparation systems and online sales systems
are designed for short-lived, high-volume
resource needs. In addition, grid and
provisioning tools can supply the resources
without the cost overhead.
In the old computing model, such growth
would require not only the hardware expense
but more importantly the larger expense of
the additional system administrators. The grid
management tools available today enable the
SAs to work smarter and at a higher level
with the tools providing the mundane
provisioning and configuration tasks. It’s a
completely new way to look at how to
provide flexible capacity while keeping costs
in-line with current business revenue.
Taking the First Step
Most of the issues and activities presented so
far are focused on understanding the
business and when and how it consumes IT
resources. Ultimately it is from the business
aspects that the greatest benefits are
obtained. To get there, however, the first
steps are very much technology focused.
From an IT perspective implementing a grid
solution can be fairly simple and
straightforward.
The path to grid-enablement is simple in the
micro and should be thoughtfully planed in
the macro. Individual legacy applications can
be grid-enabled in a few hours in one
extreme, to a few months in the other
extreme, when major architectural, platform,
and language changes are parts of the
project. Usually, four to six weeks is the
length of initial grid projects.
Grid-enabling an application is not about
rearchitecting. It’s about altering where
process flow components are executed.
The easiest application to add to a grid is an
application that is already distributed (SOA or
Web Services) and results in achieving value
quickly. Other legacy applications written in
almost any language can also achieve results
quickly based upon language and workflow
patterns. It’s the rare situation where an
entire application is sent across a grid. Only
certain business logic and data services are
extracted and set to a different execution
point for the request and fulfillment of that
service.
But even such obscure environments such as
a SmallTalk CICS transaction running under
zOS or APL running under Solaris have been
initial grid projects that yielded dramatic
business results.
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Grid Computing: The Next Step
Grid computing is all about an evolutionary path from where you
are today to a more dynamic, flexible business model enabled by
new technologies.
Where to Start Looking
Grid Enabling an Enterprise
There are some basic considerations for
selecting the initial applications for a grid
project:
As soon as two or more grid projects have
been completed, the enterprise needs to
begin to break what we call the “serverhugging mentality,” to start crossing
organizational boundaries with IT
components. When the political and
emotional issues associated with this
mentality are addressed, small internal utilities
(obtaining computing capacity from other
than your own resources) can begin to be
achieved on a small scale.
• Applications that run in hours or
transaction tasks taking longer than 30 to
40 milliseconds are a primary
consideration as a candidate to be
processed on the grid. The results can be
dramatic and achieved quickly.
• If an application’s processing volumes are
high, and/or becoming greater, the
application should be considered as a
candidate for running over the grid. In
most cases throwing hardware at the
problem is the traditional solution. Grid
can stop and even reverse that trend very
quickly creating a smaller environment
that produces better results.
• Grid can help address compliance issues
(Sarbanes-Oxley, Basel II, SEC filings) that
are driving large data volumes and
processing to new highs. These need to be
managed in specific timeframes and at
huge expense and grid can help by
guaranteeing the execution at a lower cost.
• Large cost cutting consolidation or
rightsizing efforts can be more effective by
considering the automated workload
management and scheduling that gridmiddleware provides. The data are already
collected on applications and server
location and utilization as part of the cost
cutting and rightsizing efforts, so the grid
efforts can be less costly here than in
other environments. Applying grid
concepts will not only improve the project
results but it will position the organization
to take advantage of more broad resource
sharing, inherent business resiliency, and
readiness for moving to a utility
environment for peak processing needs.
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Imagine if two grid-enabled applications are on
different continents. A “follow-the-moon”
model, i.e., work free of time constraints, can
be created. Enterprises have huge capacities in
“sleeping” servers, the idle resources of the
business line that are closed for the evening,
just waiting to be used. In many cases the
delays caused by increased network latency are
completely overshadowed—sometimes by
orders of magnitude—by the decreases in
elapsed time performance. The consideration
needs to be on the overall performance
improvement and not on a delay increase in a
component function. Does it really matter that
half the execution time of a new global gridenabled two-hour process is network latency
when the original job took 18 hours?
Create a plan that considers all business
applications and when and if they can be put
onto the grid. Analyze the basic business
processes through an application portfolio
review and determine response time and time
to results on current and parallel workloads.
Look at what serial workloads could be
turned into parallel workloads. Investigate
load and throughput measurements—when
and how often do performance peaks and
lulls take place? What do those demands look
like? Look at the supporting workflows and
decompose them to determine bottlenecks
and areas which need to be addressed.
Then look ahead to what the next 12 months
hold from a volumes perspective—after all,
the plan is to address the future demand,
not the problems of the past.
Take a look from the business side. With a
business that wants to grow, IT needs to
provide the necessary support to perform
faster and cheaper. With the creation of an
enterprise virtual resource pool, the
organization will have the ability to do more
and better. In the old model, server size and
cost might have prohibited the creation of
applications needed by the business. Now,
without the physical limitations of servers,
these issues can be addressed.
Identify the what-if business situations and
understand how this demand will be satisfied.
For example, what if business volumes
double? How will that demand be fulfilled? It
may be that fulfilling this demand might not
require the purchase of additional resources.
The Utility Computing Model
By decoupling applications from servers and
creating pools of shared resources, it is now
transparent to applications where they
execute. No longer does an application have
to run on a specific server; it can run on any
appropriate server, regardless of location.
When the multiple groups within an
enterprise start sharing resources and
operating like utilities and customers, the
next logical step is to include third parties as
the providers of computing capacity.
Grid Computing: The Next Step
The current capacity is most likely at a level to
handle some predicted growth above what was
the prior peak load. The hardware, software,
maintenance, and people costs associated with
this capacity are incurred at a fixed rate. It
doesn’t matter if the business demand for this
supply occurs for just four weeks or all year
long, the costs remain fairly fixed.
In the grid computing environment, the 80/20
rule applies very well. Plan an infrastructure
that can handle the capacity needs for 80% of
the business demand. As the need for
additional resources occurs look to third parties
to provide it. This enables costs to be tied to
new business opportunities or revenue growth
and will help maintain profitability. When the
need goes away the infrastructure is not left
with idle resources and expenses. Moving to a
true utility model creates a variable cost model
which is certainly more attractive than the
fixed costs model it replaces. Additionally,
should demand grow beyond the anticipated
peaks, the link to third-party on-demand
capacity providers means seamless processing
of unanticipated volumes.
There are quite a number of providers with
offerings that provide capacity on demand.
Costs can be less than a dollar per CPU hour
in many cases. There are even some
businesses that are looking to establish
relationships with companies in different
industries with mutually exclusive peak
computing needs. By creating a utility with
the right terms between two such companies,
both can achieve substantial financial benefit.
The supplier receives incremental revenue to
offset the fixed costs of their idle resources
and the consumer pays attractive competitive
rates that are less than the total cost of
ownership of the equivalent installed
hardware and software.
Competitive Advantage
Grid computing is not some great panacea
that will solve all the business and IT
challenges that exist. It fits within a certain
area of business workflow processes and does
very well there. Those who have worked with
grid, and are using it in production, are barely
exploiting all the benefits it can provide. Even
for the leaders in this space, recognizing the
broad applicability of follow-on use is not
properly understood.
To achieve the greatest advantage, now is the
time to look at grid for your organization. In a
few short years most organizations will have
grid environments. The benefits can be
realized by implementing early and gaining
the competitive edge now instead of playing
catch-up later.
Grid computing is all about an evolutionary
path from where you are today to a more
dynamic, flexible business model enabled by
new technologies. Grid is a business activity,
not a technology play. Understanding the
difference and creating appropriate projects
will provide the possibility of dramatic
business opportunities.
The grid journey begins with learning and the
enabling of a single application. Then, more
enabled applications are added to the grid.
The definition of policies and practices
establishes orderly and logical sharing. The
results are the dramatic cost reductions that
can be achieved and the increased market
competitiveness that can be gained.
Servers are no longer idle. Business processes
are completed in less time. Transaction
volumes can increase while infrastructure costs
get reduced. Service level agreements are met
and surpassed. The business transforms.
Capacity at this point can come from
anywhere. Maybe it’s not just the least
expensive, but the one that meets the
deadlines set not only by the company but by
the regulators.
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Grid Computing: The Next Step
About the Author
Lucian Lipinsky de Orlov
Deloitte Consulting LLP
Tel: +1 203-905-2679
Email: [email protected]
Lucian Lipinsky de Orlov is a Senior Manager
in Technology Integration at Deloitte
Consulting. He is an expert on grid and utility
computing issues and has assisted clients in
architecting and executing their grid
computing strategies. Mr. Lipinsky de Orlov
has written and spoken internationally on the
business benefits that grid computing can
provide to businesses and how to obtain
those benefits. Mr. Lipinsky de Orlov holds a
bachelor's degree in computer science and
a master’s degree in advanced technology
from Binghamton University.
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