Virtualization allows the abstraction and pooling of hardware resources to support virtual machines in a Software-Defined Networking (SDN) environment, such as a Software-Defined Data Center (SDDC). For example, through server virtualization, virtual machines (VMs) running different operating systems may be supported by the same physical machine (e.g., referred to as a “host”). Each VM is generally provisioned with virtual resources to run an operating system and applications. Further, through virtualization for networking service, logical overlay networks may be provisioned, changed, stored, deleted and restored programmatically without having to reconfigure the underlying physical hardware architecture. In practice, when a VM has a large amount of data to send to a destination over a logical network, the data may be transmitted as a series of smaller packets, each including a fragment of the data. However, existing approaches for handling encapsulated fragmented packets may lack efficiency, which may affect the performance of hosts and VMs.
In the following detailed description, reference is made to the accompanying drawings, which form a part hereof. In the drawings, similar symbols typically identify similar components, unless context dictates otherwise. The illustrative embodiments described in the detailed description, drawings, and claims are not meant to be limiting. Other embodiments may be utilized, and other changes may be made, without departing from the spirit or scope of the subject matter presented here. It will be readily understood that the aspects of the present disclosure, as generally described herein, and illustrated in the drawings, can be arranged, substituted, combined, and designed in a wide variety of different configurations, all of which are explicitly contemplated herein.
SDN environment 100 includes multiple hosts 110A-B that are inter-connected via physical network 105. Each host 110A/110B may include suitable hardware 112A/112B and virtualization software (e.g., hypervisor-A 114A, hypervisor-B 114B) to support virtual machines (VMs). For example, hosts 110A-B may support respective VMs 131-134. Hardware 112A/112B includes suitable physical components, such as central processing unit(s) (CPU(s)) or processor(s) 120A/120B; memory 122A/122B; physical network interface controllers (PNICs) 124A/124B; and storage disk(s) 126A/126B, etc. In practice, SDN environment 100 may include any number of hosts (also known as a “host computers”, “host devices”, “physical servers”, “server systems”, “transport nodes,” etc.), where each host may be supporting tens or hundreds of VMs.
Hypervisor 114A/114B maintains a mapping between underlying hardware 112A/112B and virtual resources allocated to respective VMs. Virtual resources are allocated to respective VMs 131-134 to support a guest operating system (OS; not shown for simplicity) and application(s); see 141-144, 151-154. For example, the virtual resources may include virtual CPU, guest physical memory, virtual disk, virtual network interface controller (VNIC), etc. Hardware resources may be emulated using virtual machine monitors (VMMs). For example in
Although examples of the present disclosure refer to VMs, it should be understood that a “virtual machine” running on a host is merely one example of a “virtualized computing instance” or “workload.” A virtualized computing instance may represent an addressable data compute node (DCN) or isolated user space instance. In practice, any suitable technology may be used to provide isolated user space instances, not just hardware virtualization. Other virtualized computing instances may include containers (e.g., running within a VM or on top of a host operating system without the need for a hypervisor or separate operating system or implemented as an operating system level virtualization), virtual private servers, client computers, etc. Such container technology is available from, among others, Docker, Inc. The VMs may also be complete computational environments, containing virtual equivalents of the hardware and software components of a physical computing system.
The term “hypervisor” may refer generally to a software layer or component that supports the execution of multiple virtualized computing instances, including system-level software in guest VMs that supports namespace containers such as Docker, etc. Hypervisors 114A-B may each implement any suitable virtualization technology, such as VMware ESX® or ESXi™ (available from VMware, Inc.), Kernel-based Virtual Machine (KVM), etc. The term “packet” may refer generally to a group of bits that can be transported together, and may be in another form, such as “frame,” “message,” “segment,” etc. The term “traffic” or “flow” may refer generally to multiple packets. The term “layer-2” may refer generally to a link layer or media access control (MAC) layer; “layer-3” to a network or Internet Protocol (IP) layer; and “layer-4” to a transport layer (e.g., using Transmission Control Protocol (TCP), User Datagram Protocol (UDP), etc.), in the Open System Interconnection (OSI) model, although the concepts described herein may be used with other networking models.
Hypervisor 114A/114B implements virtual switch 115A/115B and logical distributed router (DR) instance 117A/117B to handle egress packets from, and ingress packets to, corresponding VMs. In SDN environment 100, logical switches and logical DRs may be implemented in a distributed manner and can span multiple hosts. For example, logical switches that provide logical layer-2 connectivity (i.e., an overlay network) may be implemented collectively by virtual switches 115A-B and represented internally using forwarding tables 116A-B at respective virtual switches 115A-B. Forwarding tables 116A-B may each include entries that collectively implement the respective logical switches. Further, logical DRs that provide logical layer-3 connectivity may be implemented collectively by DR instances 117A-B and represented internally using routing tables (not shown) at respective DR instances 117A-B. The routing tables may each include entries that collectively implement the respective logical DRs.
Packets may be received from, or sent to, each VM via an associated logical port. For example, logical switch ports 165-168 (labelled “LSP1” to “LSP4”) are associated with respective VMs 131-134. Here, the term “logical port” or “logical switch port” may refer generally to a port on a logical switch to which a virtualized computing instance is connected. A “logical switch” may refer generally to a software-defined networking (SDN) construct that is collectively implemented by virtual switches 115A-B in
Through virtualization of networking services in SDN environment 100, logical networks (also referred to as overlay networks or logical overlay networks) may be provisioned, changed, stored, deleted and restored programmatically without having to reconfigure the underlying physical hardware architecture. SDN controller 180 and SDN manager 184 are example network management entities in SDN environment 100. One example of an SDN controller is the NSX controller component of VMware NSX® (available from VMware, Inc.) that operates on a central control plane. SDN controller 180 may be a member of a controller cluster (not shown for simplicity) that is configurable using SDN manager 184 operating on a management plane. Network management entity 180/184 may be implemented using physical machine(s), VM(s), or both. To send or receive control information, a local control plane (LCP) agent (not shown) on host 110A/110B may interact with central control plane (CCP) module 182 at SDN controller 180 via control-plane channel 107/108.
A logical overlay network may be formed using any suitable tunneling protocol, such as Virtual eXtensible Local Area Network (VXLAN), Stateless Transport Tunneling (STT), Generic Network Virtualization Encapsulation (GENEVE), etc. For example, VXLAN is a layer-2 overlay scheme on a layer-3 network that uses tunnel encapsulation to extend layer-2 segments across multiple hosts which may reside on different layer 2 physical networks. In the example in
Some example logical overlay networks are shown in
A logical DR (see “DR” 205) connects logical switches 201-202 to facilitate communication among VMs 131-134 on different segments. See also logical switch ports “LSP7” 203 and “LSP8” 204, and logical router ports “LRP1” 207 and “LRP2” 208 connecting DR 205 with logical switches 201-202. Logical switch 201/202 may be implemented collectively by multiple hosts 110A-B, such as using virtual switches 115A-B and represented internally using forwarding tables 116A-B. DR 205 may be implemented collectively by multiple transport nodes, such as using EDGE1710 and hosts 110A-B. For example, DR 205 may be implemented using DR instances 117A-B and represented internally using routing tables (not shown) at respective hosts 110A-B.
EDGE1710 may implement one or more logical DRs and logical service routers (SRs), such as DR 205 and SR 209 in
To facilitate communication among VMs 131-134 deployed on various logical overlay networks, hypervisor 114A/114B may implement a virtual tunnel endpoint (VTEP) to encapsulate and decapsulate packets with an outer header (also known as a tunnel header) identifying a logical overlay network. For example, hypervisor-A 114A implements a first VTEP-A associated with (IP address=IP-A, VTEP label=VTEP-A) and hypervisor-B 114B implements a second VTEP-B with (IP-B, VTEP-B). For simplicity, VTEPs are not shown in
In practice, when a source endpoint (e.g., VM1131 on host-A 110A) has a large amount of data to send to a destination endpoint (e.g., VM3133 on host-B 110B), the data may be transmitted as a series of fragmented packets that are each encapsulated with an outer header. Through fragmentation, the data may be divided into smaller fragments to satisfy a predetermined maximum transmission unit (MTU) size. However, fragmentation necessitates reassembly at the destination, which increases receive-side processing overhead because all fragments have to be received before reassembly is performed. Further, existing implementation of packet encapsulation (e.g., GENEVE encapsulation) may result in out-of-order delivery of fragmented packets, which affects throughput and performance.
Encapsulated fragmented packet handling
According to examples of the present disclosure, handling of encapsulated fragmented packets may be improved to reduce the overhead relating to receive-side processing. In particular, at a transmit (TX) side, encapsulated fragmented packets generated from the same (unfragmented) large packet may be configured to include the same outer connectionless transport layer value. This way, receive-side processing may be performed based on the outer connectionless transport layer value, such as to facilitate assignment of the encapsulated fragmented packets to the same receive (RX) queue at the destination. This may in turn reduce the likelihood of out-of-order delivery at destination (e.g., due to receive-side processing) to reduce the overhead associated with re-ordering and packet reassembly.
Examples of the present disclosure may be implemented for large packets that are generated according to a connectionless transport layer protocol, such as user datagram protocol (UDP), etc. In general, transport layer delivery of data may be either connection-oriented or connectionless. As used herein, the term “connectionless transport layer” may refer generally to a transport layer that does not require a connection to be established between two endpoints prior to sending packets (also known as “UDP datagrams” for UDP). A “connectionless transport layer” (e.g., UDP) should be contrasted against a connection-oriented transport layer protocol (e.g., TCP). For example, TCP requires a connection establishment (e.g., three-way handshake) between two endpoints prior to packet transmission. TCP is designed to provide a reliable error-free packets in the correct order, whereas UDP does not provide any order of delivery.
In more detail,
At 310 in
At 320 in
At 330 in
At 340 in
At 350 in
Examples of the present disclosure should be contrasted against conventional approaches that do not configure the outer header of encapsulated fragmented packets based on the inner UDP header. In this case, the conventional approaches may configure different outer source PNs in encapsulated fragmented packets generated from the same (unfragmented) large UDP packet. The different outer source PNs may in turn result in assignment to different RX queues and out-of-order delivery. Using examples of the present disclosure, the receive-side processing overhead at host-B 110B may be reduced compared to the conventional approaches. By influencing host-B 110B to assign ENCAP1103 and ENCAP2104 into the same RX queue, overhead relating to reassembly may be reduced.
Various examples relating to east-west and north-south traffic will be discussed below using
East-West Packet Handling
(a) Transmit-Side Processing
At 410 in
The example in
Referring to 511 in
At 415-420 in
At 425 in
At 430 in
At 435-440 in
To improve receive-side processing relating to UDP fragmentation, outer header 541/551 may include the outer source PN determined at block 430. In particular, outer header 541/551 may be configured to specify OUTER_SPN=X in an outer UDP header, where X=h1(IP-VM1, IP-VM3, S1, D1). Similarly, may be configured to specify OUTER_SPN=X. This way, ENCAP1540 and ENCAP2550 generated from the same DATAGRAM1510 may specify the same OUTER_SPN=X.
According to GENEVE encapsulation, outer header 541/551 may specify any suitable logical network information (e.g., VNI=5000) and outer destination PN, such as OUTER_DPN=6081. Example implementation details relating to GENEVE encapsulation may be found in a draft document entitled “Genève: Generic Network Virtualization Encapsulation” (draft-ietf-nvo3-geneve-16) published by Internet Engineering Task Force (IETF). The document is incorporated herein by reference.
(b) Receive-Side Processing
At 445-450 in
For example, a tuple-based approach may be implemented for queue assignment to select a particular RX queue based on outer tuple information in outer header 541/551, such as outer source IP address (“OUTER_DIP”), outer destination IP address (“OUTER_DIP”), outer source PN (“OUTER_SPN”), outer destination PN (“OUTER_DPN”). Using the tuple-based approach, encapsulated fragmented packets having the same outer tuple information may be assigned to the same RX queue.
For ENCAP1540, host-B 110B may apply a hash function h2( ) on 4-tuple information in first outer header (01) 541 to determine a first hash value (k1) as follows: k1=h2(OUTER_SIP=IP-A, OUTER_DIP=IP-B, OUTER_SPN=X, OUTER_DPN=6081). Based on the first hash value (k1), ENCAP1540 may be assigned or hashed to a first RX queue (see “RXQ-1” 571). See corresponding 560 in
For ENCAP2550, host-B 110B may apply the same hash function on 4-tuple information in second outer header (O2) 551 to determine a second hash value (k2) as follows: k2=h2(OUTER_SIP=IP-A, OUTER_DIP=IP-B, OUTER_SPN=X, OUTER_DPN=6081). Based on the second hash value (k2), ENCAP2550 may also be assigned or hashed to the same queue (see “RXQ-1” 571) as ENCAP1540. See corresponding 561 in
By configuring OUTER_SPN=h1(S1) in outer header 541/551 based on the same INNER_SPN=S1 in DATAGRAM1510, source host-A 110A may influence destination host-B 110B to assign ENCAP1540 and ENCAP2550 to the same RX queue 571 and/or CPU core for processing. This way, related encapsulated fragmented packets may be retrieved from the same RX queue 571 for decapsulation and reassembly (see 453) before the reassembled packet is forwarded towards destination VM3133 (see 460). This also decreases the likelihood of out-of-order delivery for ENCAP1540 and ENCAP2550 and improves efficiency during reassembly.
In practice, it should be understood that large UDP datagram 510 may be divided into two or more encapsulated fragmented packets (i.e., not just ENCAP1540 and ENCAP2550). Similar to ENCAP2550, any additional encapsulated fragmented packet also does not carry the inner UDP header. By configuring multiple encapsulated fragmented packets that are generated from the same UDP datagram to have the same outer tuple information, host-A 110A may influence host-B 110B to assign them to the same RX queue in a similar manner. Again, this should be contrasted against conventional approaches that do not configure outer UDP information in outer header 541/551 based on the inner UDP header.
Throughput Improvement
Examples of the present disclosure may be implemented to improve parallelism and throughput at host-B 110B. The example in
At 620 in
At 630-632, fragmentation may be performed to generate multiple fragmented packets denoted as “FRAGMENT3” 630, “FRAGMENT4” 631 and “FRAGMENTS” 632. Similar to the example in
At 640-660 in
At 670-672 in
Using examples of the present disclosure, a first set of encapsulated fragmented packets 540-550 in
North-South Packet Handling
Examples of the present disclosure may be implemented for north-south packet handling where a source and a destination located at different geographical sites. An example will be described using
To facilitate cross-site traffic over physical network 703, EDGE1710 (also shown in
(a) Source Host-A 110A
In the example in
(b) Edge Node Processing
At EDGE1710, ENCAP1740 and ENCAP2741 may be assigned to the same RX queue (see 712) for receive-side processing based on OUTER_SPN=X. Depending on the desired implementation, EDGE1710 may perform (a) decapsulation to remove the outer header and (b) reassembly to obtain unfragmented UDP datagram 730. This way, EDGE1710 may process the original DATAGRAM3730 to perform any suitable networking service(s).
Next, fragmentation and encapsulation are performed to generate and send ENCAP3750 and ENCAP4751 towards EDGE2720. Since ENCAP3750 and ENCAP4751 each include a fragment of UDP datagram 730, they are configured to have the same outer tuple information that includes (OUTER_SIP=IP-EDGE1, OUTER_DIP=IP-EDGE2, OUTER_SPN=Y, OUTER_DPN). Here, IP-EDGE1=source RTEP IP address associated with EDGE1710 and IP-EDGE2=destination RTEP IP address associated with EDGE2720. OUTER_SPN=Y may be configured based on the inner tuple information, such as Y=h2(IP-VM1, IP-VMS, S3, D3).
Depending on the desired implementation, OUTER_SPN=Z may be the same as, or configured based on, hash value=X in ENCAP1740 and ENCAP2741 received from host-A 110A. Alternatively, a different hash function h3( ) may be applied to generate a different hash value may be used, such as Z=h3(IP-VM1, IP-VMS, S3, D3). In practice, it is not necessary for X=Y, provided that ENCAP3750 and ENCAP4751 both include the same OUTER_SPN.
At EDGE2720, ENCAP3750 and ENCAP4751 may be assigned to the same RX queue (see 722) for receive-side processing based on OUTER_SPN=Y. Similarly, EDGE2720 may perform any suitable receive-side processing before generating and sending ENCAPS 760 and ENCAP6761 towards host-C 110C. Since ENCAPS 760 and ENCAP6761 each include a fragment of DATAGRAM3730, they are configured to have the same outer tuple information that includes OUTER_SPN=Z. Again, it is not necessary for Z=X or Z=Y, provided the same OUTER_SPN is used for fragments of the same UDP datagram.
(c) Destination Host Processing
At host-C 110C, ENCAP5760 and ENCAP6761 may be assigned to the same RX queue (see 770) for receive-side processing based on OUTER_SPN=Z. Similarly, EDGE2720 may perform any suitable receive-side processing, including decapsulation and reassembly. The resulting unfragmented UDP datagram 780/730 may then be delivered towards destination VM5135.
Depending on the desired implementation, the MTU limit at host-A 110A may be different from that at EDGE1710 and/or EDGE2720. As such, the size of encapsulated fragmented packets 740-741, 750-751 and 760-761 may vary from one transport node to another. As mentioned above, OUTER_SPN=X may be the same or (more likely) different from Y and Z, depending on the hash algorithm used at each transport node (i.e., host-A 110A, EDGE1710 and EDGE2720). Using the same OUTER_SPN, the likelihood of assigning or hashing multiple encapsulated fragmented UDP packets generated from the same (unfragmented) large UDP packet to different RX queues may be reduced.
Container Implementation
Although explained using VMs, it should be understood that public cloud environment 100 may include other virtual workloads, such as containers, etc. As used herein, the term “container” (also known as “container instance”) is used generally to describe an application that is encapsulated with all its dependencies (e.g., binaries, libraries, etc.). In the examples in
Computer System
The above examples can be implemented by hardware (including hardware logic circuitry), software or firmware or a combination thereof. The above examples may be implemented by any suitable computing device, computer system, etc. The computer system may include processor(s), memory unit(s) and physical NIC(s) that may communicate with each other via a communication bus, etc. The computer system may include a non-transitory computer-readable medium having stored thereon instructions or program code that, when executed by the processor, cause the processor to perform process(es) described herein with reference to
The techniques introduced above can be implemented in special-purpose hardwired circuitry, in software and/or firmware in conjunction with programmable circuitry, or in a combination thereof. Special-purpose hardwired circuitry may be in the form of, for example, one or more application-specific integrated circuits (ASICs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), and others. The term ‘processor’ is to be interpreted broadly to include a processing unit, ASIC, logic unit, or programmable gate array etc.
The foregoing detailed description has set forth various embodiments of the devices and/or processes via the use of block diagrams, flowcharts, and/or examples. Insofar as such block diagrams, flowcharts, and/or examples contain one or more functions and/or operations, it will be understood by those within the art that each function and/or operation within such block diagrams, flowcharts, or examples can be implemented, individually and/or collectively, by a wide range of hardware, software, firmware, or any combination thereof.
Those skilled in the art will recognize that some aspects of the embodiments disclosed herein, in whole or in part, can be equivalently implemented in integrated circuits, as one or more computer programs running on one or more computers (e.g., as one or more programs running on one or more computing systems), as one or more programs running on one or more processors (e.g., as one or more programs running on one or more microprocessors), as firmware, or as virtually any combination thereof, and that designing the circuitry and/or writing the code for the software and or firmware would be well within the skill of one of skill in the art in light of this disclosure.
Software and/or to implement the techniques introduced here may be stored on a non-transitory computer-readable storage medium and may be executed by one or more general-purpose or special-purpose programmable microprocessors. A “computer-readable storage medium”, as the term is used herein, includes any mechanism that provides (i.e., stores and/or transmits) information in a form accessible by a machine (e.g., a computer, network device, personal digital assistant (PDA), mobile device, manufacturing tool, any device with a set of one or more processors, etc.). A computer-readable storage medium may include recordable/non recordable media (e.g., read-only memory (ROM), random access memory (RAM), magnetic disk or optical storage media, flash memory devices, etc.).
The drawings are only illustrations of an example, wherein the units or procedure shown in the drawings are not necessarily essential for implementing the present disclosure. Those skilled in the art will understand that the units in the device in the examples can be arranged in the device in the examples as described or can be alternatively located in one or more devices different from that in the examples. The units in the examples described can be combined into one module or further divided into a plurality of sub-units.