U.S. patent application number 17/479254 was filed with the patent office on 2022-01-06 for load balancing for ip failover.
The applicant listed for this patent is NetApp Inc.. Invention is credited to Christopher Busick, Rajesh Rajaraman, James Silva, Mohinish Vinnakota.
Application Number | 20220006755 17/479254 |
Document ID | / |
Family ID | |
Filed Date | 2022-01-06 |
United States Patent
Application |
20220006755 |
Kind Code |
A1 |
Busick; Christopher ; et
al. |
January 6, 2022 |
LOAD BALANCING FOR IP FAILOVER
Abstract
Techniques are provided for load balancing for IP failover. A
backend address of a first node is identified as a routing
destination to which a request is to be routed by a load balancer
based upon a load balancer rule mapping a frontend address,
specified by the request as a request destination, to the backend
address of the first node. The request is routed to a primary
network interface of the first node using the backend address. The
first node has a loopback interface with an address matching the
frontend address for routing the request to a destination data
structure based upon the request maintaining the frontend address
as the request destination. Health probes are used by the load
balancer for detecting a failure of the first node in order to
failover to routing requests to a second backend address of a
second node.
Inventors: |
Busick; Christopher;
(Shrewsbury, MA) ; Vinnakota; Mohinish; (Wayland,
MA) ; Silva; James; (Bedford, MA) ; Rajaraman;
Rajesh; (Acton, MA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
NetApp Inc. |
San Jose |
CA |
US |
|
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Appl. No.: |
17/479254 |
Filed: |
September 20, 2021 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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16658280 |
Oct 21, 2019 |
11128573 |
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17479254 |
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International
Class: |
H04L 12/911 20060101
H04L012/911; H04L 12/803 20060101 H04L012/803; H04L 12/721 20060101
H04L012/721; H04L 12/915 20060101 H04L012/915; H04L 12/703 20060101
H04L012/703; H04L 12/801 20060101 H04L012/801; G06F 16/182 20060101
G06F016/182; G06F 16/176 20060101 G06F016/176; G06F 11/07 20060101
G06F011/07; H04L 29/08 20060101 H04L029/08; G06F 9/455 20060101
G06F009/455; G06F 13/42 20060101 G06F013/42; H04L 12/24 20060101
H04L012/24 |
Claims
1. A method comprising: generating a health probe based upon a
health probe definition; identifying a health probe process
executing on a first node; and transmitting the health probe to a
port of the first node for routing through a node management
logical interface to the health probe process executing on the
first node.
2. The method of claim 1, comprising: generating and transmitting
health probes at defined intervals based upon the health probe
definition.
3. The method of claim 1, comprising: determining that the first
node has encountered an issue based upon a failure to receive
acknowledgement of a threshold number of health probes back from
the health probe process.
4. The method of claim 3, comprising: redirecting requests to a
second backend address of a second node based upon a load balancer
rule.
5. The method of claim 4, wherein the load balancer rule specifies
that requests having a frontend address are to be rerouted from
being routed to a first backend address of the first node to being
routed to the second backend address based upon the first node
encountering the issue.
6. The method of claim 5, comprising: migrating a data logical
interface and a destination data structure from the first node to
the second node.
7. The method of claim 4, comprising: receiving an acknowledgement
from the second node to the health probe based upon the second node
listening to the port upon the second node determining that the
first node encountered the issue.
8. The method of claim 5, wherein the load balancer is triggered to
redirect the requests to the second backend address based upon
receiving the acknowledgement from the second node.
9. The method of claim 1, comprising: generating one or more nodes
for processing requests and responding to health probes.
10. The method of claim 9, wherein the one or more nodes may
comprise virtual machines comprising health probe processes.
11. The method of claim 1, comprising: in response to the first
node failing, redirecting requests to a second node.
12. A non-transitory machine readable medium comprising
instructions for performing a method, which when executed by a
machine, causes the machine to: generate a health probe based upon
a health probe definition; identify a health probe process
executing on a first node; and transmit the health probe to a port
of the first node for routing through a node management logical
interface to the health probe process executing on the first
node.
13. The non-transitory machine readable medium of claim 12, wherein
the instructions cause the machine to: generate and transmitting
health probes at defined intervals based upon the health probe
definition.
14. The non-transitory machine readable medium of claim 12, wherein
the instructions cause the machine to: determine that the first
node has encountered an issue based upon a failure to receive
acknowledgement of a threshold number of health probes back from
the health probe process.
15. The non-transitory machine readable medium of claim 14, wherein
the instructions cause the machine to: redirect requests to a
second backend address of a second node based upon a load balancer
rule.
16. The non-transitory machine readable medium of claim 15, wherein
the load balancer rule specifies that requests having a frontend
address are to be rerouted from being routed to a first backend
address of the first node to being routed to the second backend
address based upon the first node encountering the issue.
17. A computing device comprising: a memory comprising
instructions; and a processor coupled to the memory, the processor
configured to execute the instructions to cause the processor to:
generate a health probe based upon a health probe definition;
identify a health probe process executing on a first node; and
transmit the health probe to a port of the first node for routing
through a node management logical interface to the health probe
process executing on the first node.
18. The computing device of claim 17, wherein the instructions
cause the processor to: generate and transmitting health probes at
defined intervals based upon the health probe definition.
19. The computing device of claim 17, wherein the instructions
cause the processor to: determine that the first node has
encountered an issue based upon a failure to receive
acknowledgement of a threshold number of health probes back from
the health probe process.
20. The computing device of claim 19, wherein the instructions
cause the processor to: redirect requests to a second backend
address of a second node based upon a load balancer rule.
Description
RELATED APPLICATION
[0001] This application claims priority to and is a continuation of
U.S. application Ser. No. 16/658,280, filed on Oct. 21, 2019, now
allowed, titled "LOAD BALANCING FOR IP FAILOVER," which claims
priority to U.S. Provisional Patent Application, titled "HIGH
AVAILABILITY FOR CLOUD, SHARED STORAGE WITH LOCKING, AND IP
FAILOVER USING NETWORK LOAD BALANCER", filed on Oct. 20, 2018 and
accorded U.S. Application No.: 62/748,409, which are incorporated
herein by reference.
BACKGROUND
[0002] A computing environment, such as a cloud computing
environment, can be used to host nodes, such as virtual machines,
that provide services to client devices that connect to the
computing environment over a network. The computing environment may
host a load balancer configured to distribute requests from client
devices to various nodes based upon load information. Typically,
load balancers distribute the load of processing requests to a
plurality of nodes to alleviate bottlenecks and improve
performance.
[0003] A service provider that deploys the nodes into the computing
environment (e.g., a storage service provider that uses the cloud
computing environment to host virtual machines to provide storage
services to clients of the storage service provider) may desire to
provide fault tolerance for the clients. If a node that is actively
servicing requests encounters an issue, such as a failure, then the
service provider would want to failover to a partner node that can
then service requests that would otherwise be directed to the
failed node. Failing over from the failed node to the partner node
may involve moving a network interface (e.g., an IP configuration)
of the failed node to the partner node. Unfortunately, this can
take minutes to perform, resulting in client data access
disruption, application timeouts for applications relying on access
to the data, and client data loss. Thus, current failover
capabilities of nodes hosted with these computing environments will
violate recovery time objectives (RTOs) and recovery point
objectives (RPO).
DESCRIPTION OF THE DRAWINGS
[0004] FIG. 1 is a block diagram illustrating an example computing
environment in which an embodiment of the invention may be
implemented.
[0005] FIG. 2 is a block diagram illustrating a network environment
with exemplary node computing devices.
[0006] FIG. 3 is a block diagram illustrating an exemplary node
computing device.
[0007] FIG. 4 is a flow chart illustrating an example method for
load balancing for IP failover.
[0008] FIG. 5A is a block diagram illustrating an example system
for load balancing for IP failover, where a first node is in an
active state and a second node is in a standby state.
[0009] FIG. 5B is a block diagram illustrating an example system
for load balancing for IP failover, where a second node has taken
over for a failed first node.
[0010] FIG. 6 is an example of a computer readable medium in which
an embodiment of the invention may be implemented.
DETAILED DESCRIPTION
[0011] Some examples of the claimed subject matter are now
described with reference to the drawings, where like reference
numerals are generally used to refer to like elements throughout.
In the following description, for purposes of explanation, numerous
specific details are set forth in order to provide an understanding
of the claimed subject matter. It may be evident, however, that the
claimed subject matter may be practiced without these specific
details. Nothing in this detailed description is admitted as prior
art.
[0012] Nodes, such as virtual machines that provide storage
services for client devices, can be configured according to a high
availability configuration where a first node is a primary partner
that actively processes requests from client devices and a second
node is a secondary partner that can takeover for the first node if
the first node fails. Failing over from the first node to the
second node during takeover (failover) may involve migrating an IP
address configuration of the first node to the second node so that
client devices are subsequently routed to the second node instead
of the failed first node after failover. Unfortunately, when the
nodes are hosted within certain computing environments, such as a
cloud computing environment maintained a 3.sup.rd party cloud
service provider different than a provider of the nodes such as a
storage service provider, failover of the IP address configuration
can take minutes. This long failover duration results in client
data access disruption, application timeouts for applications
relying on access to the data, and client data loss. Thus, current
failover capabilities of nodes hosted with these computing
environments will violate recovery time objectives (RTOs) and
recovery point objectives (RPO).
[0013] Accordingly, as provided herein, failover between nodes
hosted within these types of computing environments can be
performed in a relatively short period of time such as in seconds.
This is accomplished by controlling a load balancer with load
balancer rules that are implemented to perform failover between
nodes. Failover can be performed because clients can still send
requests with a same frontend address that is maintained within the
requests as a destination address regardless of whether the load
balancer routes the requests to a first node at a first backend
address during normal operation or a second node at a second
backend address during failover from the first node to the second
node. This is accomplished using the load balancer rules for
mapping the frontend address to the backend addresses, along with
using health probes and health probe definitions for determining
whether a node has failed such that a loopback interface with an
address matching the frontend address should be migrated along with
a destination data structure from the failed first node to the
second node.
[0014] Faster failover between nodes hosted within a cloud
computing environment is also enabled through the use of health
probes. Health probes are transmitted by the load balancer to ports
of the nodes. The health probes are then routed to health probe
processes (e.g., daemons) that will respond with an indication of
whether the nodes are operational (e.g., an acknowledgment will be
sent if a health probe is received and a node is operational,
otherwise, no acknowledgment will be sent which indicates that the
node might not be operational). If the first node encounters an
issue, then the second node can detect this situation (e.g., based
upon a loss of communication over an interconnect over which the
first node and the second node communicate within the cloud
computing environment) and perform a failover.
[0015] During the failover, the second node starts listening to the
port of the first node for health probes in place of the first node
listening on the port for the health probes, and a health probe
process of the second node will respond to the load balancer that
the second node has taken over for the first node. Also, a
destination data structure (e.g., a volume) within which data was
being stored by the first node on behalf of the client devices is
migrated to the second node along with a loopback interface having
an address matching the frontend address used by the client devices
to send requests to the cloud computing environment to access the
destination data structure. Because the loopback interface with the
address matching the frontend address is migrated to the second
node, the client devices can continue to send requests using the
frontend address as the destination address while the load balancer
routes the requests to a second backend address of the second node
instead of to a first backend address of the first node based upon
the load balancer rules indicating that requests with the frontend
address should be routed to the second backend address when the
first node has failed. In this way, failover to the second node can
be performed in a short period of time such as within seconds. This
reduce any client data access disruption, and also allows for
recovery time objectives (RTOs) and recovery point objectives (RPO)
to be met so that client applications relying on access to the data
do not timeout with errors.
[0016] FIG. 1 is a diagram illustrating an example operating
environment 100 in which an embodiment of the techniques described
herein may be implemented. In one example, the techniques described
herein may be implemented within a client device 128, such as a
laptop, a tablet, a personal computer, a mobile device, a server, a
virtual machine, a wearable device, etc. In another example, the
techniques described herein may be implemented within one or more
nodes, such as a first node 130 and/or a second node 132 within a
first cluster 134, a third node 136 within a second cluster 138,
etc. A node may comprise a storage controller, a server, an
on-premise device, a virtual machine, hardware, software, or
combination thereof. The one or more nodes may be configured to
manage the storage and access to data on behalf of the client
device 128 and/or other client devices. In another example, the
techniques described herein may be implemented within a distributed
computing platform 102 such as a cloud computing environment (e.g.,
a cloud storage environment, a multi-tenant platform, a hyperscale
infrastructure comprising scalable server architectures and virtual
networking, etc.) configured to manage the storage and access to
data on behalf of client devices and/or nodes.
[0017] In yet another example, at least some of the techniques
described herein are implemented across one or more of the client
device 128, the one or more nodes, and/or the distributed computing
platform 102. For example, the client device 128 may transmit
operations, such as data operations to read data and write data and
metadata operations (e.g., a create file operation, a rename
directory operation, a resize operation, a set attribute operation,
etc.), over a network 126 to the first node 130 for implementation
by the first node 130 upon storage. The first node 130 may store
data associated with the operations within volumes or other data
objects/structures hosted within locally attached storage, remote
storage hosted by other computing devices accessible over the
network 126, storage provided by the distributed computing platform
102, etc. The first node 130 may replicate the data and/or the
operations to other computing devices, such as to the second node
132, the third node 136, a virtual machine executing within the
distributed computing platform 102, etc., so that one or more
replicas of the data are maintained. For example, the third node
136 may host a destination storage volume that is maintained as a
replica of a source storage volume of the first node 130. Such
replicas can be used for disaster recovery and failover.
[0018] In an embodiment, the techniques described herein are
implemented by a storage operating system or are implemented by a
separate module that interacts with the storage operating system.
The storage operating system may be hosted by the client device,
128, a node, the distributed computing platform 102, or across a
combination thereof. In an example, the storage operating system
may execute within a virtual machine, a hyperscaler, or other
computing environment. The storage operating system may implement a
storage file system to logically organize data within storage
devices as one or more storage objects and provide a
logical/virtual representation of how the storage objects are
organized on the storage devices. A storage object may comprise any
logically definable storage element stored by the storage operating
system (e.g., a volume stored by the first node 130, a cloud object
stored by the distributed computing platform 102, etc.). Each
storage object may be associated with a unique identifier that
uniquely identifies the storage object. For example, a volume may
be associated with a volume identifier uniquely identifying that
volume from other volumes. The storage operating system also
manages client access to the storage objects.
[0019] The storage operating system may implement a file system for
logically organizing data. For example, the storage operating
system may implement a write anywhere file layout for a volume
where modified data for a file may be written to any available
location as opposed to a write-in-place architecture where modified
data is written to the original location, thereby overwriting the
previous data. In an example, the file system may be implemented
through a file system layer that stores data of the storage objects
in an on-disk format representation that is block-based (e.g., data
is stored within 4 kilobyte blocks and inodes are used to identify
files and file attributes such as creation time, access
permissions, size and block location, etc.).
[0020] In an example, deduplication may be implemented by a
deduplication module associated with the storage operating system.
Deduplication is performed to improve storage efficiency. One type
of deduplication is inline deduplication that ensures blocks are
deduplicated before being written to a storage device. Inline
deduplication uses a data structure, such as an incore hash store,
which maps fingerprints of data to data blocks of the storage
device storing the data. Whenever data is to be written to the
storage device, a fingerprint of that data is calculated and the
data structure is looked up using the fingerprint to find
duplicates (e.g., potentially duplicate data already stored within
the storage device). If duplicate data is found, then the duplicate
data is loaded from the storage device and a byte by byte
comparison may be performed to ensure that the duplicate data is an
actual duplicate of the data to be written to the storage device.
If the data to be written is a duplicate of the loaded duplicate
data, then the data to be written to disk is not redundantly stored
to the storage device. Instead, a pointer or other reference is
stored in the storage device in place of the data to be written to
the storage device. The pointer points to the duplicate data
already stored in the storage device. A reference count for the
data may be incremented to indicate that the pointer now references
the data. If at some point the pointer no longer references the
data (e.g., the deduplicated data is deleted and thus no longer
references the data in the storage device), then the reference
count is decremented. In this way, inline deduplication is able to
deduplicate data before the data is written to disk. This improves
the storage efficiency of the storage device.
[0021] Background deduplication is another type of deduplication
that deduplicates data already written to a storage device. Various
types of background deduplication may be implemented. In an example
of background deduplication, data blocks that are duplicated
between files are rearranged within storage units such that one
copy of the data occupies physical storage. References to the
single copy can be inserted into a file system structure such that
all files or containers that contain the data refer to the same
instance of the data. Deduplication can be performed on a data
storage device block basis. In an example, data blocks on a storage
device can be identified using a physical volume block number. The
physical volume block number uniquely identifies a particular block
on the storage device. Additionally, blocks within a file can be
identified by a file block number. The file block number is a
logical block number that indicates the logical position of a block
within a file relative to other blocks in the file. For example,
file block number 0 represents the first block of a file, file
block number 1 represents the second block, etc. File block numbers
can be mapped to a physical volume block number that is the actual
data block on the storage device. During deduplication operations,
blocks in a file that contain the same data are deduplicated by
mapping the file block number for the block to the same physical
volume block number, and maintaining a reference count of the
number of file block numbers that map to the physical volume block
number. For example, assume that file block number 0 and file block
number 5 of a file contain the same data, while file block numbers
1-4 contain unique data. File block numbers 1-4 are mapped to
different physical volume block numbers. File block number 0 and
file block number 5 may be mapped to the same physical volume block
number, thereby reducing storage requirements for the file.
Similarly, blocks in different files that contain the same data can
be mapped to the same physical volume block number. For example, if
file block number 0 of file A contains the same data as file block
number 3 of file B, file block number 0 of file A may be mapped to
the same physical volume block number as file block number 3 of
file B.
[0022] In another example of background deduplication, a changelog
is utilized to track blocks that are written to the storage device.
Background deduplication also maintains a fingerprint database
(e.g., a flat metafile) that tracks all unique block data such as
by tracking a fingerprint and other filesystem metadata associated
with block data. Background deduplication can be periodically
executed or triggered based upon an event such as when the
changelog fills beyond a threshold. As part of background
deduplication, data in both the changelog and the fingerprint
database is sorted based upon fingerprints. This ensures that all
duplicates are sorted next to each other. The duplicates are moved
to a dup file. The unique changelog entries are moved to the
fingerprint database, which will serve as duplicate data for a next
deduplication operation. In order to optimize certain filesystem
operations needed to deduplicate a block, duplicate records in the
dup file are sorted in certain filesystem sematic order (e.g.,
inode number and block number). Next, the duplicate data is loaded
from the storage device and a whole block byte by byte comparison
is performed to make sure duplicate data is an actual duplicate of
the data to be written to the storage device. After, the block in
the changelog is modified to point directly to the duplicate data
as opposed to redundantly storing data of the block.
[0023] In an example, deduplication operations performed by a data
deduplication layer of a node can be leveraged for use on another
node during data replication operations. For example, the first
node 130 may perform deduplication operations to provide for
storage efficiency with respect to data stored on a storage volume.
The benefit of the deduplication operations performed on first node
130 can be provided to the second node 132 with respect to the data
on first node 130 that is replicated to the second node 132. In
some aspects, a data transfer protocol, referred to as the LRSE
(Logical Replication for Storage Efficiency) protocol, can be used
as part of replicating consistency group differences from the first
node 130 to the second node 132. In the LRSE protocol, the second
node 132 maintains a history buffer that keeps track of data blocks
that it has previously received. The history buffer tracks the
physical volume block numbers and file block numbers associated
with the data blocks that have been transferred from first node 130
to the second node 132. A request can be made of the first node 130
to not transfer blocks that have already been transferred. Thus,
the second node 132 can receive deduplicated data from the first
node 130, and will not need to perform deduplication operations on
the deduplicated data replicated from first node 130.
[0024] In an example, the first node 130 may preserve deduplication
of data that is transmitted from first node 130 to the distributed
computing platform 102. For example, the first node 130 may create
an object comprising deduplicated data. The object is transmitted
from the first node 130 to the distributed computing platform 102
for storage. In this way, the object within the distributed
computing platform 102 maintains the data in a deduplicated state.
Furthermore, deduplication may be preserved when deduplicated data
is transmitted/replicated/mirrored between the client device 128,
the first node 130, the distributed computing platform 102, and/or
other nodes or devices.
[0025] In an example, compression may be implemented by a
compression module associated with the storage operating system.
The compression module may utilize various types of compression
techniques to replace longer sequences of data (e.g., frequently
occurring and/or redundant sequences) with shorter sequences, such
as by using Huffman coding, arithmetic coding, compression
dictionaries, etc. For example, an uncompressed portion of a file
may comprise "ggggnnnnnnqqqqqqqqqq", which is compressed to become
"4g6n10q". In this way, the size of the file can be reduced to
improve storage efficiency. Compression may be implemented for
compression groups. A compression group may correspond to a
compressed group of blocks. The compression group may be
represented by virtual volume block numbers. The compression group
may comprise contiguous or non-contiguous blocks.
[0026] Compression may be preserved when compressed data is
transmitted/replicated/mirrored between the client device 128, a
node, the distributed computing platform 102, and/or other nodes or
devices. For example, an object may be create by the first node 130
to comprise compressed data. The object is transmitted from the
first node 130 to the distributed computing platform 102 for
storage. In this way, the object within the distributed computing
platform 102 maintains the data in a compressed state.
[0027] In an example, various types of synchronization may be
implemented by a synchronization module associated with the storage
operating system. In an example, synchronous replication may be
implemented, such as between the first node 130 and the second node
132. It may be appreciated that the synchronization module may
implement synchronous replication between any devices within the
operating environment 100, such as between the first node 130 of
the first cluster 134 and the third node 136 of the second cluster
138.
[0028] During synchronous replication, the first node 130 may
receive a write operation from the client device 128. The write
operation may target a file stored within a volume managed by the
first node 130. The first node 130 replicates the write operation
to create a replicated write operation. The first node 130 locally
implements the write operation upon the file within the volume. The
first node 130 also transmits the replicated write operation to a
synchronous replication target, such as the second node 132 that
maintains a replica volume as a replica of the volume maintained by
the first node 130. The second node 132 will execute the replicated
write operation upon the replica volume so that file within the
volume and the replica volume comprises the same data. After, the
second node 132 will transmit a success message to the first node
130. With synchronous replication, the first node 130 does not
respond with a success message to the client device 128 for the
write operation until both the write operation is executed upon the
volume and the first node 130 receives the success message that the
second node 132 executed the replicated write operation upon the
replica volume.
[0029] In another example, asynchronous replication may be
implemented, such as between the first node 130 and the third node
136. It may be appreciated that the synchronization module may
implement asynchronous replication between any devices within the
operating environment 100, such as between the first node 130 of
the first cluster 134 and the distributed computing platform 102.
In an example, the first node 130 may establish an asynchronous
replication relationship with the third node 136. The first node
130 may capture a baseline snapshot of a first volume as a point in
time representation of the first volume. The first node 130 may
utilize the baseline snapshot to perform a baseline transfer of the
data within the first volume to the third node 136 in order to
create a second volume within the third node 136 comprising data of
the first volume as of the point in time at which the baseline
snapshot was created.
[0030] After the baseline transfer, the first node 130 may
subsequently create snapshots of the first volume over time. As
part of asynchronous replication, an incremental transfer is
performed between the first volume and the second volume. In
particular, a snapshot of the first volume is created. The snapshot
is compared with a prior snapshot that was previously used to
perform the last asynchronous transfer (e.g., the baseline transfer
or a prior incremental transfer) of data to identify a difference
in data of the first volume between the snapshot and the prior
snapshot (e.g., changes to the first volume since the last
asynchronous transfer). Accordingly, the difference in data is
incrementally transferred from the first volume to the second
volume. In this way, the second volume will comprise the same data
as the first volume as of the point in time when the snapshot was
created for performing the incremental transfer. It may be
appreciated that other types of replication may be implemented,
such as semi-sync replication.
[0031] In an embodiment, the first node 130 may store data or a
portion thereof within storage hosted by the distributed computing
platform 102 by transmitting the data within objects to the
distributed computing platform 102. In one example, the first node
130 may locally store frequently accessed data within locally
attached storage. Less frequently accessed data may be transmitted
to the distributed computing platform 102 for storage within a data
storage tier 108. The data storage tier 108 may store data within a
service data store 120, and may store client specific data within
client data stores assigned to such clients such as a client (1)
data store 122 used to store data of a client (1) and a client (N)
data store 124 used to store data of a client (N). The data stores
may be physical storage devices or may be defined as logical
storage, such as a virtual volume, LUNs, or other logical
organizations of data that can be defined across one or more
physical storage devices. In another example, the first node 130
transmits and stores all client data to the distributed computing
platform 102. In yet another example, the client device 128
transmits and stores the data directly to the distributed computing
platform 102 without the use of the first node 130.
[0032] The management of storage and access to data can be
performed by one or more virtual machines (VMs) or other storage
applications that provide software as a service (SaaS) such as
storage software services. In one example, an SVM may be hosted
within the client device 128, within the first node 130, or within
the distributed computing platform 102 such as by the application
server tier 106. In another example, one or more VMs may be hosted
across one or more of the client device 128, the first node 130,
and the distributed computing platform 102. The one or more SMs may
host instances of the storage operating system.
[0033] In an example, the storage operating system may be
implemented for the distributed computing platform 102. The storage
operating system may allow client devices to access data stored
within the distributed computing platform 102 using various types
of protocols, such as a Network File System (NFS) protocol, a
Server Message Block (SMB) protocol and Common Internet File System
(CIFS), and Internet Small Computer Systems Interface (iSCSI),
and/or other protocols. The storage operating system may provide
various storage services, such as disaster recovery (e.g., the
ability to non-disruptively transition client devices from
accessing a primary node that has failed to a secondary node that
is taking over for the failed primary node), backup and archive
function, replication such as asynchronous and/or synchronous
replication, deduplication, compression, high availability storage,
cloning functionality (e.g., the ability to clone a volume, such as
a space efficient flex clone), snapshot functionality (e.g., the
ability to create snapshots and restore data from snapshots), data
tiering (e.g., migrating infrequently accessed data to
slower/cheaper storage), encryption, managing storage across
various platforms such as between on-premise storage systems and
multiple cloud systems, etc.
[0034] In one example of the distributed computing platform 102,
one or more SVMs may be hosted by the application server tier 106.
For example, a server (1) 116 is configured to host SVMs used to
execute applications such as storage applications that manage the
storage of data of the client (1) within the client (1) data store
122. Thus, an SVM executing on the server (1) 116 may receive data
and/or operations from the client device 128 and/or the first node
130 over the network 126. The SVM executes a storage application
and/or an instance of the storage operating system to process the
operations and/or store the data within the client (1) data store
122. The SVM may transmit a response back to the client device 128
and/or the first node 130 over the network 126, such as a success
message or an error message. In this way, the application server
tier 106 may host SVMs, services, and/or other storage applications
using the server (1) 116, the server (N) 118, etc.
[0035] A user interface tier 104 of the distributed computing
platform 102 may provide the client device 128 and/or the first
node 130 with access to user interfaces associated with the storage
and access of data and/or other services provided by the
distributed computing platform 102. In an example, a service user
interface 110 may be accessible from the distributed computing
platform 102 for accessing services subscribed to by clients and/or
nodes, such as data replication services, application hosting
services, data security services, human resource services,
warehouse tracking services, accounting services, etc. For example,
client user interfaces may be provided to corresponding clients,
such as a client (1) user interface 112, a client (N) user
interface 114, etc. The client (1) can access various services and
resources subscribed to by the client (1) through the client (1)
user interface 112, such as access to a web service, a development
environment, a human resource application, a warehouse tracking
application, and/or other services and resources provided by the
application server tier 106, which may use data stored within the
data storage tier 108.
[0036] The client device 128 and/or the first node 130 may
subscribe to certain types and amounts of services and resources
provided by the distributed computing platform 102. For example,
the client device 128 may establish a subscription to have access
to three virtual machines, a certain amount of storage, a certain
type/amount of data redundancy, a certain type/amount of data
security, certain service level agreements (SLAs) and service level
objectives (SLOs), latency guarantees, bandwidth guarantees, access
to execute or host certain applications, etc. Similarly, the first
node 130 can establish a subscription to have access to certain
services and resources of the distributed computing platform
102.
[0037] As shown, a variety of clients, such as the client device
128 and the first node 130, incorporating and/or incorporated into
a variety of computing devices may communicate with the distributed
computing platform 102 through one or more networks, such as the
network 126. For example, a client may incorporate and/or be
incorporated into a client application (e.g., software) implemented
at least in part by one or more of the computing devices.
[0038] Examples of suitable computing devices include personal
computers, server computers, desktop computers, nodes, storage
servers, nodes, laptop computers, notebook computers, tablet
computers or personal digital assistants (PDAs), smart phones, cell
phones, and consumer electronic devices incorporating one or more
computing device components, such as one or more electronic
processors, microprocessors, central processing units (CPU), or
controllers. Examples of suitable networks include networks
utilizing wired and/or wireless communication technologies and
networks operating in accordance with any suitable networking
and/or communication protocol (e.g., the Internet). In use cases
involving the delivery of customer support services, the computing
devices noted represent the endpoint of the customer support
delivery process, i.e., the consumer's device.
[0039] The distributed computing platform 102, such as a
multi-tenant business data processing platform or cloud computing
environment, may include multiple processing tiers, including the
user interface tier 104, the application server tier 106, and a
data storage tier 108. The user interface tier 104 may maintain
multiple user interfaces, including graphical user interfaces
and/or web-based interfaces. The user interfaces may include the
service user interface 110 for a service to provide access to
applications and data for a client (e.g., a "tenant") of the
service, as well as one or more user interfaces that have been
specialized/customized in accordance with user specific
requirements, which may be accessed via one or more APIs.
[0040] The service user interface 110 may include components
enabling a tenant to administer the tenant's participation in the
functions and capabilities provided by the distributed computing
platform 102, such as accessing data, causing execution of specific
data processing operations, etc. Each processing tier may be
implemented with a set of computers, virtualized computing
environments such as a virtual machine or storage virtual server,
and/or computer components including computer servers and
processors, and may perform various functions, methods, processes,
or operations as determined by the execution of a software
application or set of instructions.
[0041] The data storage tier 108 may include one or more data
stores, which may include the service data store 120 and one or
more client data stores. Each client data store may contain
tenant-specific data that is used as part of providing a range of
tenant-specific business and storage services or functions,
including but not limited to ERP, CRM, eCommerce, Human Resources
management, payroll, storage services, etc. Data stores may be
implemented with any suitable data storage technology, including
structured query language (SQL) based relational database
management systems (RDBMS), file systems hosted by operating
systems, object storage, etc.
[0042] In accordance with one embodiment of the invention, the
distributed computing platform 102 may be a multi-tenant and
service platform operated by an entity in order to provide multiple
tenants with a set of business related applications, data storage,
and functionality. These applications and functionality may include
ones that a business uses to manage various aspects of its
operations. For example, the applications and functionality may
include providing web-based access to business information systems,
thereby allowing a user with a browser and an Internet or intranet
connection to view, enter, process, or modify certain types of
business information or any other type of information.
[0043] A clustered network environment 200 that may implement one
or more aspects of the techniques described and illustrated herein
is shown in FIG. 2. The clustered network environment 200 includes
data storage apparatuses 202(1)-202(n) that are coupled over a
cluster or cluster fabric 204 that includes one or more
communication network(s) and facilitates communication between the
data storage apparatuses 202(1)-202(n) (and one or more modules,
components, etc. therein, such as, node computing devices
206(1)-206(n), for example), although any number of other elements
or components can also be included in the clustered network
environment 200 in other examples. This technology provides a
number of advantages including methods, non-transitory computer
readable media, and computing devices that implement the techniques
described herein.
[0044] In this example, node computing devices 206(1)-206(n) can be
primary or local storage controllers or secondary or remote storage
controllers that provide client devices 208(1)-208(n) with access
to data stored within data storage devices 210(1)-210(n) and cloud
storage device(s) 236. The node computing devices 206(1)-206(n) may
be implemented as hardware, software (e.g., a virtual machine), or
combination thereof.
[0045] The data storage apparatuses 202(1)-202(n) and/or node
computing devices 206(1)-206(n) of the examples described and
illustrated herein are not limited to any particular geographic
areas and can be clustered locally and/or remotely via a cloud
network, or not clustered in other examples. Thus, in one example
the data storage apparatuses 202(1)-202(n) and/or node computing
device 206(1)-206(n) can be distributed over a plurality of storage
systems located in a plurality of geographic locations (e.g.,
located on-premise, located within a cloud computing environment,
etc.); while in another example a clustered network can include
data storage apparatuses 202(1)-202(n) and/or node computing device
206(1)-206(n) residing in a same geographic location (e.g., in a
single on-site rack).
[0046] In the illustrated example, one or more of the client
devices 208(1)-208(n), which may be, for example, personal
computers (PCs), computing devices used for storage (e.g., storage
servers), or other computers or peripheral devices, are coupled to
the respective data storage apparatuses 202(1)-202(n) by network
connections 212(1)-212(n). Network connections 212(1)-212(n) may
include a local area network (LAN) or wide area network (WAN)
(i.e., a cloud network), for example, that utilize TCP/IP and/or
one or more Network Attached Storage (NAS) protocols, such as a
Common Internet Filesystem (CIFS) protocol or a Network Filesystem
(NFS) protocol to exchange data packets, a Storage Area Network
(SAN) protocol, such as Small Computer System Interface (SCSI) or
Fiber Channel Protocol (FCP), an object protocol, such as simple
storage service (S3), and/or non-volatile memory express (NVMe),
for example.
[0047] Illustratively, the client devices 208(1)-208(n) may be
general-purpose computers running applications and may interact
with the data storage apparatuses 202(1)-202(n) using a
client/server model for exchange of information. That is, the
client devices 208(1)-208(n) may request data from the data storage
apparatuses 202(1)-202(n) (e.g., data on one of the data storage
devices 210(1)-210(n) managed by a network storage controller
configured to process I/O commands issued by the client devices
208(1)-208(n)), and the data storage apparatuses 202(1)-202(n) may
return results of the request to the client devices 208(1)-208(n)
via the network connections 212(1)-212(n).
[0048] The node computing devices 206(1)-206(n) of the data storage
apparatuses 202(1)-202(n) can include network or host nodes that
are interconnected as a cluster to provide data storage and
management services, such as to an enterprise having remote
locations, cloud storage (e.g., a storage endpoint may be stored
within cloud storage device(s) 236), etc., for example. Such node
computing devices 206(1)-206(n) can be attached to the cluster
fabric 204 at a connection point, redistribution point, or
communication endpoint, for example. One or more of the node
computing devices 206(1)-206(n) may be capable of sending,
receiving, and/or forwarding information over a network
communications channel, and could comprise any type of device that
meets any or all of these criteria.
[0049] In an example, the node computing devices 206(1) and 206(n)
may be configured according to a disaster recovery configuration
whereby a surviving node provides switchover access to the storage
devices 210(1)-210(n) in the event a disaster occurs at a disaster
storage site (e.g., the node computing device 206(1) provides
client device 212(n) with switchover data access to data storage
devices 210(n) in the event a disaster occurs at the second storage
site). In other examples, the node computing device 206(n) can be
configured according to an archival configuration and/or the node
computing devices 206(1)-206(n) can be configured based on another
type of replication arrangement (e.g., to facilitate load sharing).
Additionally, while two node computing devices are illustrated in
FIG. 2, any number of node computing devices or data storage
apparatuses can be included in other examples in other types of
configurations or arrangements.
[0050] As illustrated in the clustered network environment 200,
node computing devices 206(1)-206(n) can include various functional
components that coordinate to provide a distributed storage
architecture. For example, the node computing devices 206(1)-206(n)
can include network modules 214(1)-214(n) and disk modules
216(1)-216(n). Network modules 214(1)-214(n) can be configured to
allow the node computing devices 206(1)-206(n) (e.g., network
storage controllers) to connect with client devices 208(1)-208(n)
over the storage network connections 212(1)-212(n), for example,
allowing the client devices 208(1)-208(n) to access data stored in
the clustered network environment 200.
[0051] Further, the network modules 214(1)-214(n) can provide
connections with one or more other components through the cluster
fabric 204. For example, the network module 214(1) of node
computing device 206(1) can access the data storage device 210(n)
by sending a request via the cluster fabric 204 through the disk
module 216(n) of node computing device 206(n). The cluster fabric
204 can include one or more local and/or wide area computing
networks (i.e., cloud networks) embodied as Infiniband, Fibre
Channel (FC), or Ethernet networks, for example, although other
types of networks supporting other protocols can also be used.
[0052] Disk modules 216(1)-216(n) can be configured to connect data
storage devices 210(1)-210(2), such as disks or arrays of disks,
SSDs, flash memory, or some other form of data storage, to the node
computing devices 206(1)-206(n). Often, disk modules 216(1)-216(n)
communicate with the data storage devices 210(1)-210(n) according
to the SAN protocol, such as SCSI or FCP, for example, although
other protocols can also be used. Thus, as seen from an operating
system on node computing devices 206(1)-206(n), the data storage
devices 210(1)-210(n) can appear as locally attached. In this
manner, different node computing devices 206(1)-206(n), etc. may
access data blocks, files, or objects through the operating system,
rather than expressly requesting abstract files.
[0053] While the clustered network environment 200 illustrates an
equal number of network modules 214(1)-214(2) and disk modules
216(1)-216(n), other examples may include a differing number of
these modules. For example, there may be a plurality of network and
disk modules interconnected in a cluster that do not have a
one-to-one correspondence between the network and disk modules.
That is, different node computing devices can have a different
number of network and disk modules, and the same node computing
device can have a different number of network modules than disk
modules.
[0054] Further, one or more of the client devices 208(1)-208(n) can
be networked with the node computing devices 206(1)-206(n) in the
cluster, over the storage connections 212(1)-212(n). As an example,
respective client devices 208(1)-208(n) that are networked to a
cluster may request services (e.g., exchanging of information in
the form of data packets) of node computing devices 206(1)-206(n)
in the cluster, and the node computing devices 206(1)-206(n) can
return results of the requested services to the client devices
208(1)-208(n). In one example, the client devices 208(1)-208(n) can
exchange information with the network modules 214(1)-214(n)
residing in the node computing devices 206(1)-206(n) (e.g., network
hosts) in the data storage apparatuses 202(1)-202(n).
[0055] In one example, the storage apparatuses 202(1)-202(n) host
aggregates corresponding to physical local and remote data storage
devices, such as local flash or disk storage in the data storage
devices 210(1)-210(n), for example. One or more of the data storage
devices 210(1)-210(n) can include mass storage devices, such as
disks of a disk array. The disks may comprise any type of mass
storage devices, including but not limited to magnetic disk drives,
flash memory, and any other similar media adapted to store
information, including, for example, data and/or parity
information.
[0056] The aggregates include volumes 218(1)-218(n) in this
example, although any number of volumes can be included in the
aggregates. The volumes 218(1)-218(n) are virtual data stores or
storage objects that define an arrangement of storage and one or
more filesystems within the clustered network environment 200.
Volumes 218(1)-218(n) can span a portion of a disk or other storage
device, a collection of disks, or portions of disks, for example,
and typically define an overall logical arrangement of data
storage. In one example volumes 218(1)-218(n) can include stored
user data as one or more files, blocks, or objects that reside in a
hierarchical directory structure within the volumes
218(1)-218(n).
[0057] Volumes 218(1)-218(n) are typically configured in formats
that may be associated with particular storage systems, and
respective volume formats typically comprise features that provide
functionality to the volumes 218(1)-218(n), such as providing the
ability for volumes 218(1)-218(n) to form clusters, among other
functionality. Optionally, one or more of the volumes 218(1)-218(n)
can be in composite aggregates and can extend between one or more
of the data storage devices 210(1)-210(n) and one or more of the
cloud storage device(s) 236 to provide tiered storage, for example,
and other arrangements can also be used in other examples.
[0058] In one example, to facilitate access to data stored on the
disks or other structures of the data storage devices
210(1)-210(n), a filesystem may be implemented that logically
organizes the information as a hierarchical structure of
directories and files. In this example, respective files may be
implemented as a set of disk blocks of a particular size that are
configured to store information, whereas directories may be
implemented as specially formatted files in which information about
other files and directories are stored.
[0059] Data can be stored as files or objects within a physical
volume and/or a virtual volume, which can be associated with
respective volume identifiers. The physical volumes correspond to
at least a portion of physical storage devices, such as the data
storage devices 210(1)-210(n) (e.g., a Redundant Array of
Independent (or Inexpensive) Disks (RAID system)) whose address,
addressable space, location, etc. does not change. Typically the
location of the physical volumes does not change in that the range
of addresses used to access it generally remains constant.
[0060] Virtual volumes, in contrast, can be stored over an
aggregate of disparate portions of different physical storage
devices. Virtual volumes may be a collection of different available
portions of different physical storage device locations, such as
some available space from disks, for example. It will be
appreciated that since the virtual volumes are not "tied" to any
one particular storage device, virtual volumes can be said to
include a layer of abstraction or virtualization, which allows it
to be resized and/or flexible in some regards.
[0061] Further, virtual volumes can include one or more logical
unit numbers (LUNs), directories, Qtrees, files, and/or other
storage objects, for example. Among other things, these features,
but more particularly the LUNs, allow the disparate memory
locations within which data is stored to be identified, for
example, and grouped as data storage unit. As such, the LUNs may be
characterized as constituting a virtual disk or drive upon which
data within the virtual volumes is stored within an aggregate. For
example, LUNs are often referred to as virtual drives, such that
they emulate a hard drive, while they actually comprise data blocks
stored in various parts of a volume.
[0062] In one example, the data storage devices 210(1)-210(n) can
have one or more physical ports, wherein each physical port can be
assigned a target address (e.g., SCSI target address). To represent
respective volumes, a target address on the data storage devices
210(1)-210(n) can be used to identify one or more of the LUNs.
Thus, for example, when one of the node computing devices
206(1)-206(n) connects to a volume, a connection between the one of
the node computing devices 206(1)-206(n) and one or more of the
LUNs underlying the volume is created.
[0063] Respective target addresses can identify multiple of the
LUNs, such that a target address can represent multiple volumes.
The I/O interface, which can be implemented as circuitry and/or
software in a storage adapter or as executable code residing in
memory and executed by a processor, for example, can connect to
volumes by using one or more addresses that identify the one or
more of the LUNs.
[0064] Referring to FIG. 3, node computing device 206(1) in this
particular example includes processor(s) 300, a memory 302, a
network adapter 304, a cluster access adapter 306, and a storage
adapter 308 interconnected by a system bus 310. In other examples,
the node computing device 206(1) comprises a virtual machine, such
as a virtual storage machine. The node computing device 206(1) also
includes a storage operating system 312 installed in the memory 302
that can, for example, implement a RAID data loss protection and
recovery scheme to optimize reconstruction of data of a failed disk
or drive in an array, along with other functionality such as
deduplication, compression, snapshot creation, data mirroring,
synchronous replication, asynchronous replication, encryption, etc.
In some examples, the node computing device 206(n) is substantially
the same in structure and/or operation as node computing device
206(1), although the node computing device 206(n) can also include
a different structure and/or operation in one or more aspects than
the node computing device 206(1).
[0065] The network adapter 304 in this example includes the
mechanical, electrical and signaling circuitry needed to connect
the node computing device 206(1) to one or more of the client
devices 208(1)-208(n) over network connections 212(1)-212(n), which
may comprise, among other things, a point-to-point connection or a
shared medium, such as a local area network. In some examples, the
network adapter 304 further communicates (e.g., using TCP/IP) via
the cluster fabric 204 and/or another network (e.g. a WAN) (not
shown) with cloud storage device(s) 236 to process storage
operations associated with data stored thereon.
[0066] The storage adapter 308 cooperates with the storage
operating system 312 executing on the node computing device 206(1)
to access information requested by one of the client devices
208(1)-208(n) (e.g., to access data on a data storage device
210(1)-210(n) managed by a network storage controller). The
information may be stored on any type of attached array of
writeable media such as magnetic disk drives, flash memory, and/or
any other similar media adapted to store information.
[0067] In the exemplary data storage devices 210(1)-210(n),
information can be stored in data blocks on disks. The storage
adapter 308 can include I/O interface circuitry that couples to the
disks over an I/O interconnect arrangement, such as a storage area
network (SAN) protocol (e.g., Small Computer System Interface
(SCSI), Internet SCSI (iSCSI), hyperSCSI, Fiber Channel Protocol
(FCP)). The information is retrieved by the storage adapter 308
and, if necessary, processed by the processor(s) 300 (or the
storage adapter 308 itself) prior to being forwarded over the
system bus 310 to the network adapter 304 (and/or the cluster
access adapter 306 if sending to another node computing device in
the cluster) where the information is formatted into a data packet
and returned to a requesting one of the client devices
208(1)-208(2) and/or sent to another node computing device attached
via the cluster fabric 204. In some examples, a storage driver 314
in the memory 302 interfaces with the storage adapter to facilitate
interactions with the data storage devices 210(1)-210(n).
[0068] The storage operating system 312 can also manage
communications for the node computing device 206(1) among other
devices that may be in a clustered network, such as attached to a
cluster fabric 204. Thus, the node computing device 206(1) can
respond to client device requests to manage data on one of the data
storage devices 210(1)-210(n) or cloud storage device(s) 236 (e.g.,
or additional clustered devices) in accordance with the client
device requests.
[0069] The file system module 318 of the storage operating system
312 can establish and manage one or more filesystems including
software code and data structures that implement a persistent
hierarchical namespace of files and directories, for example. As an
example, when a new data storage device (not shown) is added to a
clustered network system, the file system module 318 is informed
where, in an existing directory tree, new files associated with the
new data storage device are to be stored. This is often referred to
as "mounting" a filesystem.
[0070] In the example node computing device 206(1), memory 302 can
include storage locations that are addressable by the processor(s)
300 and adapters 304, 306, and 308 for storing related software
application code and data structures. The processor(s) 300 and
adapters 304, 306, and 308 may, for example, include processing
elements and/or logic circuitry configured to execute the software
code and manipulate the data structures.
[0071] The storage operating system 312, portions of which are
typically resident in the memory 302 and executed by the
processor(s) 300, invokes storage operations in support of a file
service implemented by the node computing device 206(1). Other
processing and memory mechanisms, including various computer
readable media, may be used for storing and/or executing
application instructions pertaining to the techniques described and
illustrated herein. For example, the storage operating system 312
can also utilize one or more control files (not shown) to aid in
the provisioning of virtual machines.
[0072] In this particular example, the memory 302 also includes a
module configured to implement the techniques described herein.
[0073] The examples of the technology described and illustrated
herein may be embodied as one or more non-transitory computer or
machine readable media, such as the memory 302, having machine or
processor-executable instructions stored thereon for one or more
aspects of the present technology, which when executed by
processor(s), such as processor(s) 300, cause the processor(s) to
carry out the steps necessary to implement the methods of this
technology, as described and illustrated with the examples herein.
In some examples, the executable instructions are configured to
perform one or more steps of a method described and illustrated
later.
[0074] One embodiment of load balancing for IP failover is
illustrated by an exemplary method 400 of FIG. 4 and further
described in conjunction with system 500 of FIGS. 5A and 5B. FIG.
5A illustrates a computing environment, such as a cloud computing
environment 506 hosted by a 3.sup.rd party cloud service provider,
where a first node 532 and a second node 538 are operating under
normal operation conditions, such as where the first node 532 is
operational and has not failed. The first node 532 and the second
node 538 may comprise nodes maintained on behalf of a service
provider different than the 3.sup.rd party cloud service provider,
such as nodes maintained on behalf of a storage service provider.
The first node 532 and/or the second node 538 may be implemented as
virtual machines, hardware, software, or combination thereof.
[0075] The first node 532 and the second node 538 may be configured
as high availability partners. In particular, the first node 532
may be configured to actively process requests from client devices,
such as read/write operations targeting a first volume 530 (a
destination data structure) maintained by the first node 532 for
storing data on behalf of a client device 502. The second node 538
may be configured to passively wait to take over for (failover
from) the first node 532 in the event the first node 532 is unable
to process requests such as due to a failure. The second node 538
may or may not process other requests from client devices while
passively waiting to take over for the first node 532. It may be
appreciated that any number of high availability partners may be
maintained within the cloud computing environment 506 and/or that
any number of nodes may be grouped into a high availability pairing
or other grouping of nodes (e.g., one active node with multiple
passive nodes).
[0076] The cloud service may host a load balancer 510 within the
cloud computing environment 506. The load balancer 510 may maintain
a backend address pool 518 comprising backend addresses of nodes to
which load is to be distributed, such as a first backend address
for the first node 532 (e.g., a first IP address of a virtual
machine network interface card of the first node 532), a second
backend address for the second node 538 (e.g., a second IP address
of a virtual machine network interface card of the second node
538), etc. In an embodiment, a single backend pool of backend
addresses are maintained for the nodes. In another embodiment, a
plurality of backend pools of backend addresses are maintained for
the nodes (e.g., a backend pool for each high availability pair of
nodes).
[0077] The load balancer 510 may be configured with a frontend
address configuration 516. The frontend address configuration 516
may include one or more frontend addresses (e.g., virtual IPs) that
serve as ingress for incoming requests from client devices. For
example, the client device 502 may transmit a first request 504 to
a storage service hosted by the first node 532 within the cloud
computing environment 506. The first request 504 may specify a
frontend address as a destination address of the first request 504.
The first request 504 may be received/intercepted by the load
balancer 510 through a first frontend address configuration 508
corresponding to the frontend address specified by the first
request 504.
[0078] The load balancer 510 is configured with load balancer rules
512 that map frontend addresses to backend addresses of nodes to
which requests are to be routed. For example, the load balancer
rules 512 may map the frontend address, specified by the first
request 504, to the first backend address of the first node 532 for
routing of requests to the first node 532 when the first node 532
is operational. The load balancer rules 512 may map the frontend
address to the second backend address of the second node 538 for
routing of requests to the second node 538 when the first node 532
has failed. In this way, the first backend address of the first
node 532 is identified as a routing destination to which the first
request 504 is to be routed by the load balancer 510, at 402. The
first node 532 may comprise a primary network interface 526
corresponding to the first backend address. The primary network
interface 526 has the same address as the first backend address
specified within the backend address pool 518 for the first node
532.
[0079] At 404, the load balancer 510 routes the first request 504
through the cloud computing environment 506 to the primary network
interface 526 of the first node 532 using the first backend
address. In an example, the first request 504 is routed to a cloud
computing environment NIC 522 attached to the first node 532 and
corresponding to a port 524 of the first node 532. The first node
532 has a loopback interface 540 with an address matching the
frontend address specified by the first request 504. Because the
frontend address is maintained within the first request 504 as the
destination address corresponding to a first volume 530, the first
request 504 is routed by the loopback interface 540 to the first
volume 530. This may be accomplished by enabling a floating address
option for routing requests to backend addresses of nodes by the
load balancer 510 while retaining the frontend address of the
requests as the request destination corresponding to a destination
data structure, such as the first volume 530, maintained by the
nodes to which the requests are routed by the load balancer 510
using the backend addresses.
[0080] The load balancer 510 may be configured with health probes
514 used to determine whether nodes are operational or experiencing
issues, such as failures. The load balancer 510 may transmit a
health probe to a first port of the first node 532 using the first
backend address of the first node 532. For example, the health
probe may be transmitted to the primary network interface 526 by
routing the health probe to the cloud computing environment NIC
522, corresponding to the port 524, using the first backend address
of the first node 532. Based upon the first backend address, the
health probe is routed through the primary network interface 526 to
a health probe process 528 executing on the first node 532. In an
example, the health probe is transmitted to the first node 532 for
routing to the health probe process 528 based upon a health probe
definition. The health probe definition may specify defined
intervals (e.g., every 4 seconds) at which health probes are to be
transmitted by the load balancer to nodes. The health probe
definition may specify a threshold number of failures to receive
acknowledgments to health probes before determining that a node has
encountered the issue (e.g., a determination that the first node
532 has failed and a failover should occur after 4 failed health
probes where no acknowledgements are received from the first node
532 for 4 consecutive health probes sent to the first node
532).
[0081] The load balancer 510 may transmit a health probe to the
second backend address of the second node 538 for determining
whether the second node 538 is operational. For example, the load
balancer 510 transmits the health probe to a primary network
interface 534 of the second node 538 by routing the health probe to
the cloud computing environment NIC 522, corresponding to the port
524, using the second backend address of the second node 538. Based
upon the second backend address, the health probe is routed through
the primary network interface 534 to a health probe process 536
executing on the second node 538. In an example, the health probe
is transmitted to the second node 538 for routing to the health
probe process 536 based upon the health probe definition. In this
way, the health probe definition is used to determine a frequency
of transmitting health probes and to define when a failure of a
node has occurred.
[0082] FIG. 5B illustrates the first node 532 experiencing a
failure 560, such that the first node 532 is unable to adequately
process requests from client devices 502. For example, the second
node 538 may determine that the first node 532 has failed 560, such
as due to a communication loss over an interconnect network.
Accordingly, the second node 538 initiates a failover. As part of
the failover, the second node 538 starts to listen to health probes
being sent to a port of the first node 532 (e.g., a health probe
sent to the port 524 using the first backend address of the first
node 532). In this way, the second node 538 will send an
acknowledgement to a health probe in place of the first node 532,
which may provide an indication to the load balancer 510 that the
first node 532 has failed (e.g., the acknowledgement may trigger
the load balancer 510 to redirect requests to the second backend
address of the second node 538). Also, the loopback interface 540
associated with the frontend address is migrated from the first
node 532 to the second node 538, along with the first volume 530 so
that the second node 538 can process requests targeting the first
volume 530 in place of the first node 532 that is unable to process
such requests. Furthermore, the load balancer 510 may determine
that the first node 532 has failed 560 based upon the threshold
number of failed health probes occurring (e.g., a failure to
receive an acknowledgement for at least 4 consecutive health
probes).
[0083] Upon determining that the first node 532 has failed 560, the
load balancer 510 utilizes the load balancer rules 512 to determine
that requests, such as a second request 550 from the client device
502 and having the frontend address, are to be routed to the second
backend address of the second node 538 while the first node 532 has
failed 560. Accordingly, the second request 550 is routed through
the cloud computing environment 506 by the load balancer 510 to the
primary network interface 534 of the second node 538 using the
second backend address. Because the second request 550 maintains
the frontend address as a destination address, the migrated
loopback interface 540, having the address matching the frontend
address, routes the second request 550 to the migrated first volume
530 based upon the migrated loopback interface 540 having the same
address as the frontend address specified by the second request
550. In this way, failover from the first node 532 to the second
node 538 can be quickly performed, such as within seconds.
[0084] Still another embodiment involves a computer-readable medium
600 comprising processor-executable instructions configured to
implement one or more of the techniques presented herein. An
example embodiment of a computer-readable medium or a
computer-readable device that is devised in these ways is
illustrated in FIG. 6, wherein the implementation comprises a
computer-readable medium 608, such as a compact disc-recordable
(CD-R), a digital versatile disc-recordable (DVD-R), flash drive, a
platter of a hard disk drive, etc., on which is encoded
computer-readable data 606. This computer-readable data 606, such
as binary data comprising at least one of a zero or a one, in turn
comprises a processor-executable computer instructions 604
configured to operate according to one or more of the principles
set forth herein. In some embodiments, the processor-executable
computer instructions 604 are configured to perform a method 602,
such as at least some of the exemplary method 400 of FIG. 4, for
example. In some embodiments, the processor-executable computer
instructions 604 are configured to implement a system, such as at
least some of the exemplary system 500 of FIGS. 5A and 5B, for
example. Many such computer-readable media are contemplated to
operate in accordance with the techniques presented herein.
[0085] In an embodiment, the described methods and/or their
equivalents may be implemented with computer executable
instructions. Thus, in an embodiment, a non-transitory computer
readable/storage medium is configured with stored computer
executable instructions of an algorithm/executable application that
when executed by a machine(s) cause the machine(s) (and/or
associated components) to perform the method. Example machines
include but are not limited to a processor, a computer, a server
operating in a cloud computing system, a server configured in a
Software as a Service (SaaS) architecture, a smart phone, and so
on). In an embodiment, a computing device is implemented with one
or more executable algorithms that are configured to perform any of
the disclosed methods.
[0086] It will be appreciated that processes, architectures and/or
procedures described herein can be implemented in hardware,
firmware and/or software. It will also be appreciated that the
provisions set forth herein may apply to any type of
special-purpose computer (e.g., file host, storage server and/or
storage serving appliance) and/or general-purpose computer,
including a standalone computer or portion thereof, embodied as or
including a storage system. Moreover, the teachings herein can be
configured to a variety of storage system architectures including,
but not limited to, a network-attached storage environment and/or a
storage area network and disk assembly directly attached to a
client or host computer. Storage system should therefore be taken
broadly to include such arrangements in addition to any subsystems
configured to perform a storage function and associated with other
equipment or systems.
[0087] In some embodiments, methods described and/or illustrated in
this disclosure may be realized in whole or in part on
computer-readable media. Computer readable media can include
processor-executable instructions configured to implement one or
more of the methods presented herein, and may include any mechanism
for storing this data that can be thereafter read by a computer
system. Examples of computer readable media include (hard) drives
(e.g., accessible via network attached storage (NAS)), Storage Area
Networks (SAN), volatile and non-volatile memory, such as read-only
memory (ROM), random-access memory (RAM), electrically erasable
programmable read-only memory (EEPROM) and/or flash memory, compact
disk read only memory (CD-ROM)s, CD-Rs, compact disk re-writeable
(CD-RW)s, DVDs, cassettes, magnetic tape, magnetic disk storage,
optical or non-optical data storage devices and/or any other medium
which can be used to store data.
[0088] Although the subject matter has been described in language
specific to structural features or methodological acts, it is to be
understood that the subject matter defined in the appended claims
is not necessarily limited to the specific features or acts
described above. Rather, the specific features and acts described
above are disclosed as example forms of implementing at least some
of the claims.
[0089] Various operations of embodiments are provided herein. The
order in which some or all of the operations are described should
not be construed to imply that these operations are necessarily
order dependent. Alternative ordering will be appreciated given the
benefit of this description. Further, it will be understood that
not all operations are necessarily present in each embodiment
provided herein. Also, it will be understood that not all
operations are necessary in some embodiments.
[0090] Furthermore, the claimed subject matter is implemented as a
method, apparatus, or article of manufacture using standard
application or engineering techniques to produce software,
firmware, hardware, or any combination thereof to control a
computer to implement the disclosed subject matter. The term
"article of manufacture" as used herein is intended to encompass a
computer application accessible from any computer-readable device,
carrier, or media. Of course, many modifications may be made to
this configuration without departing from the scope or spirit of
the claimed subject matter.
[0091] As used in this application, the terms "component",
"module," "system", "interface", and the like are generally
intended to refer to a computer-related entity, either hardware, a
combination of hardware and software, software, or software in
execution. For example, a component includes a process running on a
processor, a processor, an object, an executable, a thread of
execution, an application, or a computer. By way of illustration,
both an application running on a controller and the controller can
be a component. One or more components residing within a process or
thread of execution and a component may be localized on one
computer or distributed between two or more computers.
[0092] Moreover, "exemplary" is used herein to mean serving as an
example, instance, illustration, etc., and not necessarily as
advantageous. As used in this application, "or" is intended to mean
an inclusive "or" rather than an exclusive "or". In addition, "a"
and "an" as used in this application are generally be construed to
mean "one or more" unless specified otherwise or clear from context
to be directed to a singular form. Also, at least one of A and B
and/or the like generally means A or B and/or both A and B.
Furthermore, to the extent that "includes", "having", "has",
"with", or variants thereof are used, such terms are intended to be
inclusive in a manner similar to the term "comprising".
[0093] Many modifications may be made to the instant disclosure
without departing from the scope or spirit of the claimed subject
matter. Unless specified otherwise, "first," "second," or the like
are not intended to imply a temporal aspect, a spatial aspect, an
ordering, etc. Rather, such terms are merely used as identifiers,
names, etc. for features, elements, items, etc. For example, a
first set of information and a second set of information generally
correspond to set of information A and set of information B or two
different or two identical sets of information or the same set of
information.
[0094] Also, although the disclosure has been shown and described
with respect to one or more implementations, equivalent alterations
and modifications will occur to others skilled in the art based
upon a reading and understanding of this specification and the
annexed drawings. The disclosure includes all such modifications
and alterations and is limited only by the scope of the following
claims. In particular regard to the various functions performed by
the above described components (e.g., elements, resources, etc.),
the terms used to describe such components are intended to
correspond, unless otherwise indicated, to any component which
performs the specified function of the described component (e.g.,
that is functionally equivalent), even though not structurally
equivalent to the disclosed structure. In addition, while a
particular feature of the disclosure may have been disclosed with
respect to only one of several implementations, such feature may be
combined with one or more other features of the other
implementations as may be desired and advantageous for any given or
particular application.
* * * * *