U.S. patent application number 13/340461 was filed with the patent office on 2013-07-04 for dynamic throttling of access to computing resources in multi-tenant systems.
The applicant listed for this patent is Bryan Cantrill, Brendan Gregg, Gerald A. Jelinek, William D. Pijewski. Invention is credited to Bryan Cantrill, Brendan Gregg, Gerald A. Jelinek, William D. Pijewski.
Application Number | 20130173803 13/340461 |
Document ID | / |
Family ID | 48578241 |
Filed Date | 2013-07-04 |
United States Patent
Application |
20130173803 |
Kind Code |
A1 |
Pijewski; William D. ; et
al. |
July 4, 2013 |
DYNAMIC THROTTLING OF ACCESS TO COMPUTING RESOURCES IN MULTI-TENANT
SYSTEMS
Abstract
Systems, methods, and media for method for managing requests for
computing resources are provided herein. Methods may include
dynamically throttling requests for computing resources generated
by one or more tenants within a multi-tenant system, such as a
cloud. In some embodiments, the present technology may dynamically
throttle I/O operations for a physical storage media that is
accessible by the tenants of the cloud. The present technology may
dynamically throttle I/O operations to ensure fair access to the
physical storage media for each tenant within the cloud.
Inventors: |
Pijewski; William D.; (San
Francisco, CA) ; Jelinek; Gerald A.; (Colorado
Springs, CO) ; Gregg; Brendan; (Walnut Creek, CA)
; Cantrill; Bryan; (Piedmont, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Pijewski; William D.
Jelinek; Gerald A.
Gregg; Brendan
Cantrill; Bryan |
San Francisco
Colorado Springs
Walnut Creek
Piedmont |
CA
CO
CA
CA |
US
US
US
US |
|
|
Family ID: |
48578241 |
Appl. No.: |
13/340461 |
Filed: |
December 29, 2011 |
Current U.S.
Class: |
709/226 |
Current CPC
Class: |
G06F 3/067 20130101;
Y02D 10/00 20180101; Y02D 10/22 20180101; G06F 2209/504 20130101;
G06F 9/5072 20130101; G06F 2209/5021 20130101 |
Class at
Publication: |
709/226 |
International
Class: |
G06F 15/16 20060101
G06F015/16 |
Claims
1. A method for managing requests for computing resources, the
method comprising: dynamically throttling requests for computing
resources generated by one or more tenants within a multi-tenant
system, the requests being directed to a computing resource, the
requests of a tenant being selectively throttled based upon a
comparison of a utilization metric and priority for the tenant and
automatically updating the utilization metric for a tenant by
continually calculating, for a given a time span, the utilization
metric by multiplying an aggregate number of read requests for a
tenant over the time span by an average read latency relative to
the computing resource, plus the product of a number of write
requests and an average write latency relative to the computing
resource, wherein the aggregate numbers of read and write requests
both include decayed requests, wherein decayed requests are
requests from a tenant that occurred prior to current requests
relative to the time span, wherein current requests include the
most recent requests generated by the tenant, further wherein the
decayed requests comprise a weight that is less than a weight of
current requests.
2-3. (canceled)
4. The method according to claim 1, wherein the utilization metric
is calculated on an exponential decay basis.
5. The method according to claim 1, wherein automatically updating
further includes automatically comparing the updated utilization
metric for a tenant to the priority for the tenant and increasing
or decreasing the selective throttling of the requests by a
predetermined amount based upon the comparison.
6. The method according to claim 1, further comprising assigning a
priority to each tenant of the multi-tenant system, wherein the
priority includes an amount of requests that may be performed by
the tenant within a time span.
7. The method according to claim 1, wherein the amount of
throttling that is applied to a tenant is based upon a difference
between the utilization metric and the priority value of the
tenant, an increase in the difference between the utilization
metric and the priority corresponding to an increase in a delay
imposed upon the requests of the tenant, wherein the priority is a
value representing a number of I/O requests allotted for the
utilization metric.
8. The method according to claim 1, wherein the priority for a
tenant may be based upon a pricing structure.
9. The method according to claim 1, wherein the computing resource
comprises a physical storage media that can process a predetermined
number of I/O requests within a given timespan.
10. The method according to claim 1, further comprising
interleaving requests from unthrottled tenants to the computing
resource.
11. (canceled)
12. A system for managing requests for computing resources, the
system comprising: a processor that executes computer-readable
instructions; a memory for storing executable instructions that
include an operating system that has a file system; and a
throttling module that manages requests for computing resources by
dynamically throttling requests for computing resources generated
by one or more tenants within a multi-tenant system, the requests
being directed to a computing resource that receives fluctuating
quantities of requests from the multi-tenant system, the requests
of a tenant being selectively throttled based upon a comparison of
a utilization metric and priority for the tenant; and a metric
generator that automatically updates the utilization metric for a
tenant by continually calculating, for a given a time span, the
utilization metric by multiplying an aggregate number of read
requests for a tenant over the time span by an average read latency
relative to the computing resource, plus the product of a number of
write requests and an average write latency relative to the
computing resource, wherein the aggregate numbers of read and write
requests both include decayed requests, wherein decayed requests
are requests from a tenant that occurred prior to current requests
relative to the time span, wherein current requests include the
most recent requests generated by the tenant, further wherein the
decayed requests comprise a weight that is less than a weight of
current requests.
13-14. (canceled)
15. The system according to claim 12, wherein the metric generator
calculates the utilization metric for a tenant on an exponential
decay basis.
16. The system according to claim 12, wherein the metric generator
further automatically updates the utilization metric by
automatically comparing the updated utilization metric for a tenant
to the priority for the tenant and increasing or decreasing the
selective throttling of the requests by a predetermined amount
based upon the comparison.
17. The system according to claim 12, further comprising a priority
module that assigns a priority to each tenant of the multi-tenant
system, wherein the priority includes an amount of requests that
may be performed by the tenant within a time span.
18. The system according to claim 12, wherein the throttling module
selectively varies the amount of throttling that is applied to a
tenant is based upon a difference between the utilization metric
and the priority of the tenant, wherein the priority is a value
representing a number of I/O requests allotted for the utilization
metric.
19. The system according to claim 12, wherein the utilization
metric for a tenant is stored in kernel memory of the file
system.
20. The system according to claim 12, further comprising an
interleaving module that interleaves requests from unthrottled
tenants to the computing resource.
21. A non-transitory computer readable storage media having a
program embodied thereon, the program being executable by a
processor to perform a method for managing requests for computing
resources, the method comprising: dynamically throttling requests
for computing resources generated by one or more tenants within a
multi-tenant system, the requests being directed to a computing
resource that receives fluctuating quantities of requests from the
multi-tenant system, the requests of a tenant being selectively
throttled based upon a comparison of a utilization metric and
priority for the tenant; and automatically updating the utilization
metric for a tenant by continually calculating, for a given a time
span, the utilization metric by multiplying an aggregate number of
read requests for a tenant over the time span by an average read
latency relative to the computing resource, plus the product of a
number of write requests and an average write latency relative to
the computing resource, wherein the aggregate numbers of read and
write requests both include decayed requests, wherein decayed
requests are requests from a tenant that occurred prior to current
requests relative to the time span, wherein current requests
include the most recent requests generated by the tenant, further
wherein the decayed requests comprise a weight that is less than a
weight of current requests.
22. The method according to claim 1, wherein the dynamic throttling
of a request comprises delaying the request with respect to an
unthrottled request.
Description
FIELD OF THE TECHNOLOGY
[0001] Embodiments of the disclosure relate to the management of
cloud-based computing environments. Systems, methods, and media
provided herein may be utilized to dynamically throttle access to
computing resources in multi-tenant systems such as a cloud or an
enterprise computing environment.
BACKGROUND OF THE DISCLOSURE
[0002] A cloud is a resource that typically combines the
computational power of a large grouping of processors and/or that
combines the storage capacity of a large grouping of computer
memories or storage devices. For example, systems that provide a
cloud resource may be utilized exclusively by their owners, such as
Google.TM. or Yahoo!.TM., or such systems may be accessible to
outside users who deploy applications within the computing
infrastructure to obtain the benefit of large computational or
storage resources. The cloud may be formed, for example, by a
network of servers with each server providing processor and/or
storage resources.
[0003] The cloud may be formed, for example, by a network of web
servers, with each web server (or at least a plurality thereof)
providing processor and/or storage resources. These servers may
manage workloads provided by multiple users (e.g., cloud resource
customers or other users). Typically, each user places workload
demands upon the cloud that vary in real-time, sometimes
dramatically. The nature and extent of these variations may depend
on the type of business associated with the user.
SUMMARY OF THE DISCLOSURE
[0004] According to some embodiments, the present technology may be
directed to methods for managing requests for computing resources
by dynamically throttling requests for computing resources
generated by one or more tenants within a multi-tenant system, the
requests being directed to a computing resource, the requests of a
tenant being selectively throttled based upon a comparison of a
utilization metric and priority for the tenant.
[0005] According to other embodiments, the present technology may
be directed to methods for managing requests for computing
resources by dynamically throttling requests for computing
resources generated by one or more tenants within a multi-tenant
system, the requests being directed to a computing resource that
receives fluctuating quantities of requests from the multi-tenant
system, wherein the one or more tenants that are selectively
throttled are determined by comparing a raw number of requests
generated each tenant and selecting one or more of tenants with the
greatest amount of requests relative to the other tenants.
[0006] According to additional embodiments, the present technology
may be directed to systems for managing requests for computing
resources. These systems may include: (a) a processor that executes
computer-readable instructions; (b) a memory for storing executable
instructions that include an operating system that has a
filesystem; and (c) a throttling module that manages requests for
computing resources by dynamically throttling requests for
computing resources generated by one or more tenants within a
multi-tenant system, the requests being directed to a computing
resource that receives fluctuating quantities of requests from the
multi-tenant system, the requests of a tenant being selectively
throttled based upon a comparison of a utilization metric and
priority for the tenant.
[0007] According to additional embodiments, the present technology
may be directed to computer readable storage media for managing
requests for computing resources. The method may include
dynamically throttling requests for computing resources generated
by one or more tenants within a multi-tenant system, the requests
being directed to a computing resource that receives fluctuating
quantities of requests from the multi-tenant system, the requests
of a tenant being selectively throttled based upon a comparison of
a utilization metric and priority for the tenant.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] The accompanying drawings, where like reference numerals
refer to identical or functionally similar elements throughout the
separate views, together with the detailed description below, are
incorporated in and form part of the specification, and serve to
further illustrate embodiments of concepts that include the claimed
disclosure, and explain various principles and advantages of those
embodiments.
[0009] The methods and systems disclosed herein have been
represented where appropriate by conventional symbols in the
drawings, showing only those specific details that are pertinent to
understanding the embodiments of the present disclosure so as not
to obscure the disclosure with details that will be readily
apparent to those of ordinary skill in the art having the benefit
of the description herein.
[0010] FIG. 1 illustrates an exemplary system for practicing
aspects of the present technology;
[0011] FIG. 2 illustrates an throttling kernel that manages
requests for computing resources;
[0012] FIG. 3 is a flowchart of an exemplary method for managing
requests for computing resources; and
[0013] FIG. 4 illustrates an exemplary computing system that may be
used to implement embodiments according to the present
technology.
DETAILED DESCRIPTION
[0014] In the following description, for purposes of explanation,
numerous specific details are set forth in order to provide a
thorough understanding of the disclosure. It will be apparent,
however, to one skilled in the art, that the disclosure may be
practiced without these specific details. In other instances,
structures and devices are shown at block diagram form only in
order to avoid obscuring the disclosure.
[0015] Generally speaking, the present technology may control
access to a computing resource(s) that is subject to an
unknown/unpredictable number of requests (e.g., workload). In some
instances, these computing resources are physical components that
are constrained by a finite number of possible requests that they
may process within a given time frame. For example, a physical
storage media may only be able to process up to a thousand read
and/or write requests per second.
[0016] In some embodiments, the present technology may be utilized
in multi-tenant systems. Multi-tenant systems may impose dynamic
and drastically varying workloads on computing resources of a
cloud. An exemplary computing resource may include a physical
storage medium such as a hard disk. Workload imposed on the
computing resource may include I/O operations (e.g., read and write
operations) and/or network bandwidth usage. Because physical
systems such as hard disks have finite operational constraints
(e.g., maximum amount of I/O requests that can be fulfilled in a
given timespan), monopolization of these resources by one or more
tenants in a multi-tenant system may lead to pathological latency
issues for the other tenants as they must wait for the computing
resource. Such latency issues will diminish the overall performance
of the other tenants.
[0017] To address these issues, the present technology may
dynamically limit the workload from a tenant applied to the
computing resource based upon the number of tenants providing such
workloads to the computing resource for processing. Workloads may
be understood to include I/O (e.g., input/output, read/write)
operations for a computing resource such as a physical storage
media, but may also include any quantifiable request that is based
upon the process that is executed by the computing resource.
[0018] More specifically, when designing a cloud computing
platform, a cloud provider may desire to mitigate any performance
vagaries due to multi-tenant effects. As stated previously, a cloud
computing environment may include a physical machine or plurality
of machines that provision a plurality of tenants (e.g., zones) for
customers. Groups of tenants are often referred to as multi-tenancy
environment.
[0019] The terms multi-tenant may be understood to include not only
cloud environments, but also other configurations of computing
devices/resources, such as an enterprise system that may have both
primary and secondary computing resources. The present technology
may ensure that primary resources have adequate access to computing
resources such as databases or other storage media, while
preserving the ability for secondary computing devices to access
the storage media on a throttled basis, if necessary.
[0020] Because the workload imposed upon a computing resource by
each tenant may not be consistent and uniformly distributed, bursts
of activity (increases in workload) may affect the performance of
other tenants. These tenants may be virtual machines utilizing the
system's computing resources, or single applications running on
that system. For example, when one tenant monopolizes the available
I/O operations of a physical storage media, other tenants may be
required to wait for unacceptable periods of time to access the
physical storage media.
[0021] One way to avoid these multi-tenant effects is to
overprovision the cloud to handle spikes in activity (e.g., provide
additional physical storage media), but that approach may leave
machines or components of the cloud underutilized and may undermine
the economics of cloud computing.
[0022] The present technology may employ a software virtualized
solution within a cloud platform, wherein each tenant is a
container built into the underlying operating system of the cloud.
The present technology may provision a tenant (also known as a
zone) for each customer, and this architecture grants the system
additional flexibility when allocating resources to individual
tenants. The present technology may observe the activity of all
tenants, and can coordinate with the kernel of the cloud to
optimize resource management between tenants.
[0023] Generally speaking, the four basic computing resources that
may require provisioning with a cloud include CPU, memory, I/O, and
network bandwidth. For many customer workloads, network bandwidth
may occasionally present a bottleneck, and such bottlenecking may
increase as applications become more and more distributed.
[0024] I/O contention can also be major factor that negatively
impacts customers. For example, on one machine, a single tenant can
issue a stream of I/O operations, usually synchronous writes, which
disrupt I/O operations for all other tenants. This problem is
further exacerbated by filesystem management functionalities, which
may buffer asynchronous writes for a single transaction group.
These asynchronous writes may include a set of data blocks which
are atomically flushed to disk. The process of flushing a
transaction group may occupy all or a significant portion of a
computing device's (e.g., a storage media) I/O bandwidth, thereby
preventing pending read operations by other tenants.
[0025] According to some embodiments, the present technology may
employ an I/O throttling functionality to remedy I/O contention.
The I/O throttling functionality may be generally described as
having two components. The first component may monitor and account
for each tenant's I/O operations. A second component may throttle
each tenant's operations when it exceeds a fair share of disk I/O.
When the throttle detects that a tenant is consuming more than is
appropriate, each read or write system call is delayed by up to 200
microseconds, which may be sufficient to allow other tenants to
interleave I/O requests during those delays. I/O throttling
functionality may calculate an I/O utilization metric for each
tenant, as will be described in greater detail below. It will be
understood that while some embodiments of the present technology
may implement a delay of up to 200 milliseconds, the actual delay
imposed by the system may include any duration desired.
[0026] The present technology may prioritize I/O access amongst the
tenants, such that certain tenants may be granted prioritized
access to the I/O component. These types of prioritizations may be
referred to as a "priority," If desired, each tenant may be
provisioned with a utilization metric and the I/O throttling
functionality may monitor I/O utilization across the zones and
compare I/O utilization for each tenant to its utilization metric.
If a zone has a higher-than-average I/O utilization (compared to
their utilization metric), the I/O throttling functionality may
throttle or temporarily suspend I/O requests from the tenant to the
I/O device. That is, each I/O request may be delayed up to 200
microseconds, depending on the severity of the inequity between the
various tenants.
[0027] Additionally, the delay applied to the I/O requests may be
increased and/or decreased in a stepwise fashion, based upon a
velocity of the I/O requests for the tenant. These and other
advantages of the present technology will be described in greater
detail with reference to the collective figures.
[0028] FIG. 1 illustrates an exemplary system 100 for practicing
aspects of the present technology. The system 100 may include a
multi-tenant system 105 that may include a cloud-based computing
environment. As stated above, a cloud-based computing environment
is a resource that typically combines the computational power of a
large grouping of processors and/or that combines the storage
capacity of a large grouping of computer memories or storage
devices. For example, systems that provide a cloud resource may be
utilized exclusively by their owners, such as Google.TM. or
Yahoo!.TM.; or such systems may be accessible to outside users who
deploy applications within the computing infrastructure to obtain
the benefit of large computational or storage resources.
[0029] The cloud may be formed, for example, by a network of web
servers, with each web server (or at least a plurality thereof)
providing processor and/or storage resources. These servers may
manage workloads provided by multiple users (e.g., cloud resource
customers or other users). Typically, each user places workload
demands upon the cloud that vary in real-time, sometimes
dramatically. The nature and extent of these variations typically
depend on the type of business associated with the user.
[0030] In some embodiments, the cloud includes a plurality of
tenants 110A-N (e.g., zones), where each tenant may represent a
virtual computing system for a customer. Each tenant may be
configured to perform one or more computing operations such as
hosting a web page, enabling a web-based application, facilitating
data storage, and so forth.
[0031] In other embodiments, the multi-tenant system 105 may
include a distributed group of computing devices such as web
servers that do not share computing resources or workload.
Additionally, the multi-tenant system 105 may include a single
computing device that has been provisioned with a plurality of
programs that each produce instances of event data.
[0032] The multi-tenant system 105 may provide the tenants 110A-N
with a plurality of computing resources, which may be either
virtual or physical components. For the purposes of brevity, the
following description may specifically describe a computing
resource 130 that includes a physical storage media such as a hard
disk. Again, the computing resource 130 may include physical
devices that have operational constraints that can be defined in
terms of a finite quantity. For example, an upper limit for the
amount of I/O requests that can be handled by the computing
resource 130 over a given period of time.
[0033] Customers or system administrators may utilize client
devices 115 to access their tenant within the system 105.
Additionally, the individual parts of the system 100 may be
communicatively coupled with one another via a network connection
120. The network connection may include any number or combination
of private and/or public communications media, such as the
Internet.
[0034] The filesystem of the multi-tenant system 105 may be
provisioned with a throttling layer or "kernel 200," which will be
described in greater detail with regard to FIG. 2. The throttling
kernel 200 may also be embodied as a standalone application that is
executable on the multi-tenant system 105. The throttling kernel
200 may be executed to selectively throttle requests for computing
resources generated by one or more tenants within a multi-tenant
system 105. It will be understood that the requests may be directed
to a computing resource that receives fluctuating quantities of
requests from the multi-tenant system. Furthermore, the requests
generated by a tenant may be selectively throttled based upon a
comparison of a utilization metric and priority for the tenant.
[0035] According to some embodiments, the throttling kernel 200 may
comprise a priority module 205, a tenant monitor module 210, a
metric generator 215, an analytics module 220, a throttling module
225, and an interleaving module 230. It is noteworthy that the
throttling kernel 200 may include additional or fewer modules,
engines, or components, and still fall within the scope of the
present technology. As used herein, the term "module" may also
refer to any of an application-specific integrated circuit (ASIC),
an electronic circuit, a processor (shared, dedicated, or group)
that executes one or more software or firmware programs, a
combinational logic circuit, and/or other suitable components that
provide the described functionality.
[0036] Prior to throttling request of tenants within the
multi-tenant system, a system administrator may interact with the
throttling kernel 200 to establish guidelines that govern the
behavior of the throttling kernel 200. For a particular computing
resource such as a physical storage media that may be accessed by
the tenants 110A-N, the system administrator may determine
threshold request levels that represent the physical constraints of
the computing resource. For example, the system administrator may
estimate that the maximum number of I/O requests that a physical
storage media may handle within a one second period of time is
approximately 1,000.
[0037] It will be understood that while the throttling kernel 200
may be utilized to manage requests provided by tenants to any
number of computing resources, for the purposes of brevity, the
following descriptions will be limited to a computing resources
such as a physical storage medium (e.g., hard disk).
[0038] Based upon this threshold information, in some instances,
the priority module 205 may be executed to generate a global
priority value for each tenant 110A-N within the system 105. The
global priority value defines an acceptable number of requests
relative to other tenants that may be generated by each tenant and
provided to the hard disk. The relative global priority values of
tenants determines their relative access to the computing resource,
such as a hard disk. The use of global priority values will be
discussed in greater detail infra.
[0039] In other embodiments, the priority module 205 may generate a
tenant specific priority value for each tenant in the multi-tenant
system. A tenant specific priority value may be generated by a
pricing schedule provided by the multi-tenant system operator. For
example, a customer may obtain higher priority by purchasing
additional computing resources from the operator. In other cases,
increased priority may be obtained by customers purchasing multiple
tenants, or other price-based methods that would be known to one of
ordinary skill in the art.
[0040] The priority module 205 may also distribute available
requests across the tenants relative to a weighting of tenants that
is based upon their respective priority values. That is, a tenant
with greater priority may receive a greater percentage of the
available requests for the computing resource.
[0041] In some instances, the priority module 205 may not consider
a priority for a tenant that has not generated an I/O request or
other access to a computing resource within a given timespan.
Moreover, these tenants are not considered when comparing global
priorities to determine preferential access to the computing
resource. Such provisioning ensures that the computing resource is
not idle and is being utilized to its fullest potential.
[0042] Once priorities have been established for the tenants, the
tenant monitor module 210 may be executed to monitor the I/O
requests generated by each of the tenants. These I/O requests
represent workload that will be placed upon the computing resource
when transmitted to the resource. For example, the I/O requests may
include read and write requests for the physical disk that were
generated by the tenants. The tenant monitor module 210 may obtain
raw request numbers for each tenant within the system. By way of
non-limiting example, the tenant monitor module 210 may continually
obtain raw data from a tenant that includes all I/O requests that
were generated by the tenant in the last two seconds.
[0043] Once the raw data has been gathered, the metric generator
215 may be executed to calculate utilization metrics for each of
the tenants. Utilization metrics are generated by processing the
raw data for a tenant. In some embodiments, the metric generator
215 takes the raw request data generated during a timespan to
generate an automatically updated utilization metric. The metric is
generated by multiplying an aggregate number of read requests for a
tenant over the timespan by an average read latency relative to the
computing resource, plus the product of the number of write
requests and the average write latency relative to the computing
resource.
[0044] It will be understood that the utilization metric has been
referred to as an "automatically updated" metric because the metric
generator continually receives raw data from the tenant and updates
the utilization metric to continually measure the I/O requests
generated by a tenant in near real-time. That is, I/O requests for
a tenant are typically a fluctuating and variable quantity. Tenant
may have periods of high or sustained I/O request generation and
may also have periods of relatively little or not I/O request
generation. Monitoring and automatically processing the I/O
requests generated by the tenants ensure that access to the
computing resource may be fairly distributed across the tenants as
their I/O requests fluctuate.
[0045] The metric generator 215 may weight the raw data based upon
temporal aspects of the raw data. For example, new I/O requests may
be given greater weight than relatively older I/O requests.
Therefore, in some instances, the metric generator 215 may
calculate an exponentially decayed average which may be included in
the aggregate numbers of read and write requests. It is noteworthy
that this average may include I/O requests from a tenant that
occurred prior to current I/O requests relative to the timespan of
interest. Current I/O requests include the most recent requests
generated by the tenant.
[0046] The analytics module 220 may be executed to compare the
current utilization metric for a tenant to the priority established
for the tenant. The analytics module 220 may repeat the comparison
for each tenant in the system. If the utilization metric for a
tenant exceeds its priority, the throttling module 225 may be
executed to throttle the tenant. Throttling may include imposing a
delay in communication or transmission of I/O requests to the
computing resource. The delay may be based upon the severity of the
overuse of the computing resource by the tenant. That is, the
greater the difference between the utilization metric and the
priority, the more delay may be imposed upon the tenant. The exact
amount of the delay is configurable, but an exemplary delay may
include a delay time of approximately zero to 200 milliseconds in
duration.
[0047] Because the utilization metric for a tenant may be
continually or automatically updated, the delay duration imposed
upon the tenant may be increased or decreased in a stepwise manner.
For example, if the analytics module 220 determines that a tenant
is exceeding its allotted I/O request quota (e.g., priority), the
tenant may be throttled by imposing a delay duration to the
transmission of its requests to the computing resource. Subsequent
updating of the utilization module some time later may indicate
that the tenant is still exceeding its priority. Therefore the
throttling module 225 may increase the delay duration by another
ten milliseconds. The throttling module 225 may also decrease the
delay duration in a stepwise fashion as the difference between the
utilization metric and the priority begins to recede. The ten
millisecond step up or down is a configurable amount, and is just
an reference amount for this example.
[0048] The ability of the throttling kernel 200 to selectively
throttle I/O request of the tenants ensures that access to
computing resources is allotted fairly across the tenants,
according to priority. Furthermore, these types of short
millisecond delay durations will not create deleterious performance
issues for the tenants.
[0049] Upon throttling of a tenant, the interleaving module 230 may
be executed to transmit I/O requests for the other tenants to the
computing resource during the duration of the delay imposed against
the tenant that exceeded their priority. That is, I/O requests
generated by other tenants may be interleaved in between I/O
requests generated by the tenant that has exceeded its utilization.
This functionality is particularly important when a tenant has a
relatively high priority relative to the other tenants, or a tenant
is alone capable of monopolizing access to the computing device,
for example, by large transfers of write requests to a storage
media.
[0050] As mentioned above, in some embodiments, the throttling
kernel 200 may employ a global priority to each tenant within the
multi-tenant system. The analytics module 220 may compare the raw
request data for each tenant to the global priority value and
throttle tenants that generate requests for the computing resource
that exceed the global priority. In other embodiments, the
throttling kernel 200 may simply compare raw request numbers for
each of the tenants relative to one another and selectively
throttle tenants as their raw request numbers increase or decrease
over time.
[0051] FIG. 3 illustrates a flowchart of an exemplary method for
managing requests for computing resources. It will be understood
that the computing resource may be subject to a workload imposed
thereon by a plurality of tenants, such as tenants within a
multi-tenant system (e.g., a cloud). The method may include a step
305 of establishing a priority for each tenant within the
multi-tenant system.
[0052] The method may then include a step 310 of gathering raw
request data for each tenant along with a step 315 of processing
the raw request data to generate an automatically updating
utilization metric for each tenant that includes calculations
performed on the raw data over a given timespan. As stated before,
the utilization metric may be weighted using an exponentially
decayed average.
[0053] The method may also include a step 320 of comparing the
utilization metric for a tenant to the priority for the tenant
along with a step 325 of dynamically throttling requests generated
by the tenant based upon the comparison. Again, as mentioned
previously, the duration of delay applied to the requests of a
tenant may be selectively varied as the utilization metric changes
over time.
[0054] FIG. 4 illustrates an exemplary computing system 400 that
may be used to implement an embodiment of the present technology.
One or more aspects of the computing system 400 may be implemented
within any of multi-tenant system 105, client device 115, and/or
computing resource 130. The computing system 400 of FIG. 4 includes
one or more processors 410 and memory 420. Main a memory store 420
stores, in part, instructions and data for execution by processor
410. Main a memory store 420 can store the executable code when the
system 400 is in operation. The system 400 of FIG. 4 may further
include a mass storage device 430, portable storage medium drive(s)
440, output devices 450, user input devices 460, a graphics display
440, and other peripheral devices 480.
[0055] The components shown in FIG. 4 are depicted as being
connected via a single bus 490. The components may be connected
through one or more data transport means. Processor unit 410 and
main a memory store 420 may be connected via a local microprocessor
bus, and the mass storage device 430, peripheral device(s) 480,
portable storage device 440, and display system 470 may be
connected via one or more input/output (I/O) buses.
[0056] Mass storage device 430, which may be implemented with a
magnetic disk drive or an optical disk drive, is a non-volatile
storage device for storing data and instructions for use by
processor unit 410. Mass storage device 430 can store the system
software for implementing embodiments of the present technology for
purposes of loading that software into main a memory store 410.
[0057] Portable storage device 440 operates in conjunction with a
portable non-volatile storage medium, such as a floppy disk,
compact disk or digital video disc, to input and output data and
code to and from the computing system 400 of FIG. 4. The system
software for implementing embodiments of the present technology may
be stored on such a portable medium and input to the computing
system 400 via the portable storage device 440.
[0058] Input devices 460 provide a portion of a user interface.
Input devices 460 may include an alphanumeric keypad, such as a
keyboard, for inputting alphanumeric and other information, or a
pointing device, such as a mouse, a trackball, stylus, or cursor
direction keys. Additionally, the system 400 as shown in FIG. 4
includes output devices 450. Suitable output devices include
speakers, printers, network interfaces, and monitors.
[0059] Display system 470 may include a liquid crystal display
(LCD) or other suitable display device. Display system 470 receives
textual and graphical information, and processes the information
for output to the display device.
[0060] Peripherals 480 may include any type of computer support
device to add additional functionality to the computing system.
Peripheral device(s) 480 may include a modem or a router.
[0061] The components contained in the computing system 400 of FIG.
4 are those typically found in computing systems that may be
suitable for use with embodiments of the present technology and are
intended to represent a broad category of such computer components
that are well known in the art. Thus, the computing system 400 of
FIG. 4 can be a personal computer, hand held computing system,
telephone, mobile computing system, workstation, server,
minicomputer, mainframe computer, or any other computing system.
The computer can also include different bus configurations,
networked platforms, multi-processor platforms, etc. Various
operating systems can be used including UNIX, Linux, Windows, Mac
OS, Palm OS, and other suitable operating systems.
[0062] Some of the above-described functions may be composed of
instructions that are stored on storage media (e.g.,
computer-readable medium). The instructions may be retrieved and
executed by the processor. Some examples of storage media are
memory devices, tapes, disks, SSDs (solid-state drives), and the
like. The instructions are operational when executed by the
processor to direct the processor to operate in accord with the
technology. Those skilled in the art are familiar with
instructions, processor(s), and storage media.
[0063] It is noteworthy that any hardware platform suitable for
performing the processing described herein is suitable for use with
the technology. The terms "computer-readable storage medium" and
"computer-readable storage media" as used herein refer to any
medium or media that participate in providing instructions to a CPU
for execution. Such media can take many forms, including, but not
limited to, non-volatile media, volatile media and transmission
media. Non-volatile media include, for example, optical or magnetic
disks, such as a fixed disk. Volatile media include dynamic memory,
such as system RAM. Transmission media include coaxial cables,
copper wire and fiber optics, among others, including the wires
that comprise one embodiment of a bus. Transmission media can also
take the form of acoustic or light waves, such as those generated
during radio frequency (RF) and infrared (IR) data communications.
Common forms of computer-readable media include, for example, a
floppy disk, a flexible disk, a hard disk, magnetic tape, any other
magnetic medium, a CD-ROM disk, digital video disk (DVD), any other
optical medium, any other physical medium with patterns of marks or
holes, a RAM, a PROM, an EPROM, an EEPROM, a FLASHEPROM, any other
memory chip or data exchange adapter, a carrier wave, or any other
medium from which a computer can read.
[0064] The above description is illustrative and not restrictive.
Many variations of the technology will become apparent to those of
skill in the art upon review of this disclosure. The scope of the
technology should, therefore, be determined not with reference to
the above description, but instead should be determined with
reference to the appended claims along with their full scope of
equivalents.
[0065] In the foregoing specification, the invention is described
with reference to specific embodiments thereof, but those skilled
in the art will recognize that the invention is not limited
thereto. Various features and aspects of the above-described
invention can be used individually or jointly. Further, the
invention can be utilized in any number of environments and
applications beyond those described herein without departing from
the broader spirit and scope of the specification. The
specification and drawings are, accordingly, to be regarded as
illustrative rather than restrictive. It will be recognized that
the terms "comprising," "including," and "having," as used herein,
are specifically intended to be read as open-ended terms of
art.
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