譯科技 | 關(guān)于邊緣計(jì)算，你需要了解四件事

來(lái)源：venturebeat 時(shí)間：2020-04-07 15:03:25 作者：James Falkoff

4 things you need to understand about edge computing

數(shù)據(jù)觀丨王婕（譯）

　　Edge computing has claimed a spot in the technology zeitgeist as one of the topics that signals novelty and cutting-edge thinking. For a few years now，it has been assumed that this way of doing computing is，one way or another，the future. But until recently the discussion has been mostly hypothetical，because the infrastructure required to support edge computing has not been available.

　　邊緣計(jì)算作為頗富新穎的前沿思想話題之一，已經(jīng)在當(dāng)今技術(shù)時(shí)代思潮中占據(jù)了一席之地。幾年來(lái)，人們一直認(rèn)為這種計(jì)算方式是未來(lái)的發(fā)展方向。直到現(xiàn)在，這種論調(diào)仍停留在理論階段，因?yàn)槟軌蛑芜吘売?jì)算的基礎(chǔ)設(shè)施尚未出現(xiàn)。

　　That is now changing as a variety of edge computing resources，from micro data centers to specialized processors to necessary software abstractions，are making their way into the hands of application developers，entrepreneurs，and large enterprises. We can now look beyond the theoretical when answering questions about edge computing’s usefulness and implications. So，what does the real-world evidence tell us about this trend？In particular，is the hype around edge computing deserved，or is it misplaced？

　　隨著各種邊緣計(jì)算資源（從微數(shù)據(jù)中心到專業(yè)化處理器，再到必要的軟件抽象）逐漸涌入應(yīng)用程序開(kāi)發(fā)人員、企業(yè)家和大型企業(yè)的手中，這種情況正在發(fā)生變化。在回答有關(guān)邊緣計(jì)算的作用和影響的問(wèn)題時(shí)，我們現(xiàn)在可以試著超越理論層面。那么，關(guān)于這一趨勢(shì)，現(xiàn)實(shí)世界的案例能給我們什么啟示？特別是，圍繞邊緣計(jì)算的炒作究竟是實(shí)至名歸，還是不合時(shí)宜？

　　Distilled down，the evidence shows that edge computing is a real phenomenon born of a burgeoning need to decentralize applications for cost and performance reasons. Some aspects of edge computing have been over-hyped，while others have gone under the radar. The following four takeaways attempt to give decision makers a pragmatic view of the edge’s capabilities now and in the future.

　　總的來(lái)說(shuō)，事實(shí)表明邊緣計(jì)算趨勢(shì)真實(shí)存在，它是由于成本和性能原因而產(chǎn)生的一種新興的去中心化應(yīng)用程序的需求。邊緣計(jì)算的某些方面正在被過(guò)度炒作，而另一些方面則沒(méi)有引起應(yīng)有的注意。以下四個(gè)要點(diǎn)旨在幫助決策者對(duì)邊緣計(jì)算現(xiàn)在和未來(lái)的能力有一個(gè)務(wù)實(shí)態(tài)度。

　　1. Edge computing isn’t just about latency 邊緣計(jì)算不僅僅是關(guān)于延遲的技術(shù)

　　Edge computing is a paradigm that brings computation and data storage closer to where it is needed. It stands in contrast to the traditional cloud computing model，in which computation is centralized in a handful of hyperscale data centers.The edge can be anywhere that is closer to the end user or device than a traditional cloud data center. It could be 100 miles away，one mile away，on-premises，or on-device. Whatever the approach，the traditional edge computing narrative has emphasized that the power of the edge is to minimize latency，either to improve user experience or to enable new latency-sensitive applications. This does edge computing a disservice. While latency mitigation is an important use case，it is probably not the most valuable one. Another use case for edge computing is to minimize network traffic going to and from the cloud，or what some are calling cloud offload，and this will probably deliver at least as much economic value as latency mitigation.

　　邊緣計(jì)算是一種使計(jì)算和數(shù)據(jù)存儲(chǔ)得以有的放矢的范例，它與將計(jì)算集中在少數(shù)幾個(gè)超大規(guī)模的數(shù)據(jù)中心的傳統(tǒng)云計(jì)算模型形成鮮明對(duì)比?！斑吘墶笨梢允侵溉魏伪葌鹘y(tǒng)云數(shù)據(jù)中心更接近終端用戶或設(shè)備的地方，它可能在100英里外、1英里外，甚至是就在現(xiàn)場(chǎng)或設(shè)備上。無(wú)論采用哪種方法，一般對(duì)邊緣計(jì)算的描述都強(qiáng)調(diào)，邊緣計(jì)算的強(qiáng)大功能是延遲最小化，從而改善用戶體驗(yàn)或?yàn)閱⒂眯碌膶?duì)延遲很敏感的應(yīng)用程序賦能。但這樣的說(shuō)法的確對(duì)人們?nèi)嬲J(rèn)識(shí)邊緣計(jì)算很不利。雖然對(duì)邊緣計(jì)算來(lái)說(shuō)，緩解延遲是一個(gè)重要的應(yīng)用案例，但它卻可能不是最有價(jià)值的。邊緣計(jì)算的另一個(gè)應(yīng)用案例是最小化進(jìn)出云的網(wǎng)絡(luò)流量，也就是一些人所說(shuō)的“云卸載”，這可能會(huì)帶來(lái)至少與緩解延遲一樣多的經(jīng)濟(jì)價(jià)值。

　　The underlying driver of cloud offload is immense growth in the amount of data being generated，be it by users，devices， or sensors. “Fundamentally， the edge is a data problem，” Chetan Venkatesh，CEO of Macrometa，a startup tackling data challenges in edge computing，told me late last year. Cloud offload has arisen because it costs money to move all this data，and many would rather not move it to if they don’t have to. Edge computing provides a way to extract value from data where it is generated，never moving it beyond the edge. If necessary，the data can be pruned down to a subset that is more economical to send to the cloud for storage or further analysis.

　　云卸載的潛在驅(qū)動(dòng)力是生成數(shù)據(jù)量的突飛猛進(jìn)，無(wú)論是在用戶、設(shè)備還是傳感器層面。Macromet公司首席執(zhí)行官Chetan Venkatesh去年年底曾向作者表示，“從根本上講，邊緣計(jì)算是一個(gè)數(shù)據(jù)問(wèn)題”，云卸載之所以出現(xiàn)，是因?yàn)橐苿?dòng)數(shù)據(jù)需要花錢，而且如果沒(méi)有必要，許多人寧愿不移動(dòng)它們。邊緣計(jì)算提供了一種從本地設(shè)備直接提取值的方法，因?yàn)樗粫?huì)將數(shù)據(jù)移到“邊緣”之外。如果有必要，可以將數(shù)據(jù)精簡(jiǎn)為一個(gè)更為經(jīng)濟(jì)的子集，并發(fā)送到云端進(jìn)行存儲(chǔ)或進(jìn)一步分析。

　　A very typical use for cloud offload is to process video or audio data，two of the most bandwidth-hungry data types. A retailer in Asia with 10，000+ locations is processing both，using edge computing for video surveillance and in-store language translation services，according to a contact I spoke to recently who was involved in the deployment. But there are other sources of data that are similarly expensive to transmit to the cloud. According to another contact，a large IT software vendor is analyzing real-time data from its customers’on-premises IT infrastructure to preempt problems and optimize performance. It uses edge computing to avoid backhauling all this data to AWS. Industrial equipment also generates an immense amount of data and is a prime candidate for cloud offload.

　　云卸載的一個(gè)非常典型的用途是處理視頻或音頻數(shù)據(jù)——這是兩種最需要帶寬的數(shù)據(jù)類型。據(jù)我最近接觸到的一位參與部署的人士透露，一家在亞洲擁有1萬(wàn)多家分店的零售商正在運(yùn)用邊緣計(jì)算技術(shù)同時(shí)處理這兩項(xiàng)業(yè)務(wù)，以進(jìn)行視頻監(jiān)控和店內(nèi)語(yǔ)言翻譯服務(wù)。但除此之外，還有其他的數(shù)據(jù)源也需要花費(fèi)同樣多的錢才能傳輸?shù)皆浦?。另一位知情人士透露，為了防患于未然并?yōu)化性能，一家大型IT軟件供應(yīng)商正在分析來(lái)自其客戶的內(nèi)部IT基礎(chǔ)設(shè)施的實(shí)時(shí)數(shù)據(jù)，并使用邊緣計(jì)算來(lái)避免將所有這些數(shù)據(jù)返回到AWS。同時(shí)，工業(yè)設(shè)備也會(huì)產(chǎn)生大量的數(shù)據(jù)，是云卸載技術(shù)的主要應(yīng)用場(chǎng)景。

　　2. The edge is an extension of the cloud 邊緣計(jì)算是云計(jì)算的延伸

　　Despite early proclamations that the edge would displace the cloud，it is more accurate to say that the edge expands the reach of the cloud. It will not put a dent in the ongoing trend of workloads migrating to the cloud. But there is a flurry of activity underway to extend the cloud formula of on-demand resource availability and abstraction of physical infrastructure to locations increasingly distant from traditional cloud data centers. These edge locations will be managed using tools and approaches evolved from the cloud，and over time the line between cloud and edge will blur.

　　盡管在初期有關(guān)于邊緣計(jì)算將取代云計(jì)算的說(shuō)法，但毋寧說(shuō)是邊緣計(jì)算拓展了云計(jì)算的范圍。邊緣計(jì)算雖然不會(huì)對(duì)工作負(fù)載遷移到云的趨勢(shì)造成影響，但是，一系列活動(dòng)正在為了將按需資源可用性和物理基礎(chǔ)設(shè)施抽象的云計(jì)算公式擴(kuò)展到距離傳統(tǒng)云數(shù)據(jù)中心越來(lái)越遠(yuǎn)的位置而進(jìn)行。這些邊緣位置將使用來(lái)自云端的工具和方法進(jìn)行管理，隨著時(shí)間的推移，云和邊緣之間的界限將變得越來(lái)越模糊。

　　The fact that the edge and the cloud are part of the same continuum is evident in the edge computing initiatives of public cloud providers like AWS and Microsoft Azure. If you are an enterprise looking to do on-premises edge computing，Amazon will now send you an AWS Outpost–a fully assembled rack of compute and storage that mimics the hardware design of Amazon’s own data centers. It is installed in a customer’s own data center and monitored，maintained，and upgraded by Amazon. Importantly，Outposts run many of the same services AWS users have come to rely on，like the EC2 compute service，making the edge operationally similar to the cloud. Microsoft has a similar aim with its Azure Stack Edge product. These offerings send a clear signal that the cloud providers envision cloud and edge infrastructure unified under one umbrella.

　　邊緣計(jì)算和云計(jì)算是同一連續(xù)體的一部分，這一事實(shí)在AWS和Microsoft Azure等公共云提供商的邊緣計(jì)算解決方案中得到了證明。如果你是一家想要部署本地邊緣計(jì)算的企業(yè)，亞馬遜將會(huì)為你提供一項(xiàng)叫做AWS Outpost的服務(wù)——一個(gè)模仿了亞馬遜自己數(shù)據(jù)中心的硬件設(shè)計(jì)的完全組裝好的計(jì)算機(jī)和存儲(chǔ)機(jī)架。它將被安裝在客戶自己的數(shù)據(jù)中心，并由亞馬遜進(jìn)行監(jiān)控、維護(hù)和升級(jí)。重要的是，AWS Outpost運(yùn)行著AWS用戶所依賴的許多相同的服務(wù)，這使得邊緣計(jì)算在操作上類似于云計(jì)算，例如EC2計(jì)算服務(wù)。微軟的Azure Stack Edge產(chǎn)品也有類似的目標(biāo)。這些產(chǎn)品都發(fā)出了一個(gè)明確的信號(hào)——云提供商希望將云計(jì)算和邊緣基礎(chǔ)設(shè)施統(tǒng)一在同一個(gè)“保護(hù)傘”下。

　　3. Edge infrastructure is arriving in phases 邊緣計(jì)算基礎(chǔ)設(shè)施正分階段建設(shè)

　　While some applications are best run on-premises，in many cases application owners would like to reap the benefits of edge computing without having to support any on-premises footprint. This requires access to a new kind of infrastructure，something that looks a lot like the cloud but is much more geographically distributed than the few dozen hyperscale data centers that comprise the cloud today. This kind of infrastructure is just now becoming available，and it’s likely to evolve in three phases，with each phase extending the edge’s reach by means of a wider and wider geographic footprint.

　　雖然有些應(yīng)用程序最好在本地運(yùn)行，但在許多情況下，應(yīng)用程序所有者希望獲得邊緣計(jì)算的好處，而不必支持任何本地占用。這就需要訪問(wèn)一種新的基礎(chǔ)設(shè)施，這種基礎(chǔ)設(shè)施看起來(lái)很像云，但在地理分布上要比現(xiàn)在組成云的幾十個(gè)高級(jí)別數(shù)據(jù)中心分散得多。這種基礎(chǔ)設(shè)施現(xiàn)在才剛剛開(kāi)始使用，它可能會(huì)分三個(gè)階段發(fā)展，每個(gè)階段都會(huì)通過(guò)越來(lái)越廣泛的地理足跡擴(kuò)大邊緣計(jì)算的覆蓋范圍。

　　Phase 1： Multi-Region and Multi-Cloud 階段一：多區(qū)域、多云

　　The first step toward edge computing for a large swath of applications will be something that many might not consider edge computing，but which can be seen as one end of a spectrum that includes all the edge computing approaches. This step is to leverage multiple regions offered by the public cloud providers. For example，AWS has data centers in 22 geographic regions，with four more announced. An AWS customer serving users in both North America and Europe might run its application in both the Northern California region and the Frankfurt region，for instance. Going from one region to multiple regions can drive a big reduction in latency，and for a large set of applications，this will be all that’s needed to deliver a good user experience.

　　關(guān)于邊緣計(jì)算的第一步，很多人沒(méi)有考慮到的是將其應(yīng)用到大量應(yīng)用程序當(dāng)中，但這可以視為所有邊緣計(jì)算處理的頻譜終結(jié)。這一步就是利用公共云提供商所提供的多個(gè)區(qū)域。例如，AWS在22個(gè)地理區(qū)域擁有數(shù)據(jù)中心（另有4個(gè)已發(fā)布），其中，為北美和歐洲用戶提供服務(wù)的AWS客戶就可以在北加州地區(qū)和法蘭克福地區(qū)也運(yùn)行其應(yīng)用程序。對(duì)于一組大型應(yīng)用程序來(lái)說(shuō)，從一個(gè)區(qū)域到多個(gè)區(qū)域可以大大減少延遲，這將是其提供良好用戶體驗(yàn)所需的全部。

　　At the same time，there is a trend toward multi-cloud approaches，driven by an array of considerations including cost efficiencies，risk mitigation，avoidance of vendor lock-in，and desire to access best-of-breed services offered by different providers. “Doing multi-cloud and getting it right is a very important strategy and architecture today，”Mark Weiner，CMO at distributed cloud startup Volterra，told me. A multi-cloud approach，like a multi-region approach，marks an initial step toward distributed workloads on a spectrum that progresses toward more and more decentralized edge computing approaches.

　　與此同時(shí)，在一系列考慮因素（包括成本效率、風(fēng)險(xiǎn)降低、避免廠商鎖定以及希望訪問(wèn)不同提供商提供的最佳服務(wù)）的驅(qū)動(dòng)下，出現(xiàn)了向多云方法發(fā)展的趨勢(shì)。分布式云初創(chuàng)公司Volterra的首席營(yíng)銷官M(fèi)ark Weiner告訴我：“在今天，做多云并把它做好是一個(gè)非常重要的戰(zhàn)略和架構(gòu)?！迸c多區(qū)域方法一樣，多云方法標(biāo)志著云計(jì)算朝著分布式工作負(fù)載邁出了第一步，而分布式工作負(fù)載正朝著越來(lái)越分散的邊緣計(jì)算方法發(fā)展。

　　Phase 2： The Regional Edge 階段2：區(qū)域邊緣計(jì)算

　　The second phase in the edge’s evolution extends the edge a layer deeper，leveraging infrastructure in hundreds or thousands of locations instead of hyperscale data centers in just a few dozen cities. It turns out there is a set of players who already have an infrastructure footprint like this： Content Delivery Networks. CDNs have been engaged in a precursor to edge computing for two decades now，caching static content closer to end users in order to improve performance. While AWS has 22 regions，a typical CDN like Cloudflare has 194.

　　邊緣計(jì)算發(fā)展的第二階段將擴(kuò)展到更深一層：利用數(shù)百或數(shù)千個(gè)地點(diǎn)的基礎(chǔ)設(shè)施，而不是幾十個(gè)城市規(guī)模大小的超大數(shù)據(jù)中心。事實(shí)證明，已經(jīng)有一群玩家擁有了這樣的基礎(chǔ)設(shè)施部署，即內(nèi)容分發(fā)網(wǎng)絡(luò)。20年來(lái)，內(nèi)容分發(fā)網(wǎng)絡(luò)一直是參與邊緣計(jì)算發(fā)展的先驅(qū)，為了提高性能，其將靜態(tài)內(nèi)容緩存到更接近終端用戶的地方。目前AWS有22個(gè)區(qū)域部署了這樣的基礎(chǔ)設(shè)施，而像Cloudflare公司這樣的典型提供內(nèi)容分發(fā)網(wǎng)絡(luò)服務(wù)的則有194個(gè)區(qū)域。

　　What’s different now is these CDNs have begun to open up their infrastructure to general-purpose workloads，not just static content caching. CDNs like Cloudflare，F(xiàn)astly，Limelight， StackPath，and Zenlayer all offer some combination of container-as-a-service，VM-as-a-service， bare-metal-as-a-service，and serverless functions today. In other words，they are starting to look more like cloud providers. Forward-thinking cloud providers like Packet and Ridge are also offering up this kind of infrastructure，and in turn AWS has taken an initial step toward offering more regionalized infrastructure，introducing the first of what it calls Local Zones in Los Angeles，with additional ones promised.

　　現(xiàn)在不同的是，這些內(nèi)容分發(fā)網(wǎng)絡(luò)已經(jīng)開(kāi)始向通用工作負(fù)載開(kāi)放其基礎(chǔ)架構(gòu)，而不僅僅是靜態(tài)內(nèi)容緩存。如今，像Cloudflare、Fastly、Limelight、StackPath和Zenlayer這樣的內(nèi)容分發(fā)網(wǎng)絡(luò)提供商紛紛開(kāi)始提供一些容器即服務(wù)、虛擬化應(yīng)用即服務(wù)、裸機(jī)即服務(wù)和無(wú)服務(wù)器功能的組合。換句話說(shuō)，他們開(kāi)始變得更像云提供商。像Packet和Ridge這樣具有前瞻性的云提供商也在提供這種基礎(chǔ)設(shè)施，而AWS也朝著提供更區(qū)域化的基礎(chǔ)設(shè)施邁出了第一步，在洛杉磯引入了第一個(gè)它稱之為“區(qū)域型”的的新公有云服務(wù)，并承諾將在更多區(qū)域予以部署。

　　Phase 3： The Access Edge 階段3：接入邊緣計(jì)算

　　The third phase of the edge’s evolution drives the edge even further outward，to the point where it is just one or two network hops away from the end user or device. In traditional telecommunications terminology this is called the Access portion of the network，so this type of architecture has been labeled the Access Edge. The typical form factor for the Access Edge is a micro data center，which could range in size from a single rack to roughly that of a semi trailer，and could be deployed on the side of the road or at the base of a cellular network tower，for example. Behind the scenes，innovations in things like power and cooling are enabling higher and higher densities of infrastructure to be deployed in these small-footprint data centers.

　　在向前發(fā)展的第三個(gè)階段，邊緣計(jì)算將進(jìn)一步向外驅(qū)動(dòng)，直到距離終端用戶或設(shè)備只有一兩個(gè)網(wǎng)絡(luò)跳數(shù)。在傳統(tǒng)的電信術(shù)語(yǔ)中，這被稱為網(wǎng)絡(luò)的接入部分，因此這種類型的架構(gòu)被標(biāo)記為接入邊緣。接入邊緣的典型組成因素是微型數(shù)據(jù)中心，其大小可以從單個(gè)機(jī)架到大致相當(dāng)于半拖車的機(jī)架，并且可以部署在路邊或蜂窩網(wǎng)絡(luò)塔的底部。在這背后，電力和冷卻等方面的創(chuàng)新將使得越來(lái)越高密度的基礎(chǔ)設(shè)施能夠部署在這些占地面積小的數(shù)據(jù)中心。

　　New entrants such as Vapor IO，EdgeMicro，and EdgePresence have begun to build these micro data centers in a handful of US cities. 2019 was the first major buildout year，and 2020– 2021 will see continued heavy investment in these buildouts. By 2022，edge data center returns will be in focus for those who made the capital investments in them，and ultimately these returns will reflect the answer to the question：are there enough killer apps for bringing the edge this close to the end user or device？

　　像Vapor IO、EdgeMicro和EdgePresence公司這樣的新晉者已經(jīng)開(kāi)始在美國(guó)少數(shù)城市建立這些微型數(shù)據(jù)中心。2019年是這些微型數(shù)據(jù)中心的建設(shè)元年，2020-2021年對(duì)這些建設(shè)的投資將持續(xù)加大。到2022年，邊緣數(shù)據(jù)中心的回報(bào)率將成為那些對(duì)邊緣計(jì)算進(jìn)行資本投資的人所關(guān)注的焦點(diǎn)，最終這些回報(bào)率將反映出一個(gè)問(wèn)題的答案：是否有足夠的殺手級(jí)應(yīng)用程序可以讓邊緣計(jì)算如此接近終端用戶或設(shè)備？

　　We are very early in the process of getting an answer to this question. A number of practitioners I’ve spoken to recently have been skeptical that the micro data centers in the Access Edge are justified by enough marginal benefit over the regional data centers of the Regional Edge. The Regional Edge is already being leveraged in many ways by early adopters，including for a variety of cloud offload use cases as well as latency mitigation in user-experience-sensitive domains like online gaming，ad serving，and e-commerce. By contrast，the applications that need the super-low latencies and very short network routes of the Access Edge tend to sound further off：autonomous vehicles，drones，AR/VR，smart cities，remote-guided surgery. More crucially，these applications must weigh the benefits of the Access Edge against doing the computation locally with an on-premises or on-device approach. However，a killer application for the Access Edge could certainly emerge–perhaps one that is not in the spotlight today. We will know more in a few years.

　　我們很早就得到了這個(gè)問(wèn)題的答案。我最近采訪過(guò)的一些從業(yè)者對(duì)接入邊緣的微型數(shù)據(jù)中心是否比區(qū)域邊緣的區(qū)域數(shù)據(jù)中心更具有足夠的邊際效益表示懷疑。區(qū)域邊緣計(jì)算已經(jīng)在許多方面被早期采用者利用，包括各種云卸載案例，以及對(duì)在線游戲、廣告服務(wù)和電子商務(wù)等用戶體驗(yàn)敏感領(lǐng)域的延遲緩解。相比之下，那些需要超低延遲和非常短距離的接入邊緣網(wǎng)絡(luò)路徑的應(yīng)用程序往往聽(tīng)起來(lái)更加遙不可及：自動(dòng)駕駛、無(wú)人機(jī)、AR/VR、智能城市、遠(yuǎn)程手術(shù)。更重要的是，這些應(yīng)用程序必須權(quán)衡接入邊緣的好處，而不是使用本地或設(shè)備上的方法進(jìn)行本地計(jì)算。然而，訪問(wèn)邊緣的一個(gè)殺手級(jí)應(yīng)用程序肯定會(huì)出現(xiàn)——也許這不是今天的焦點(diǎn)。幾年后我們會(huì)知道更多。

　　4.New software is needed to manage the edge 需要新的軟件來(lái)管理邊緣計(jì)算

　　I’ve outlined above how edge computing describes a variety of architectures and that the “edge”can be located in many places. However，the ultimate direction of the industry is one of unification，toward a world in which the same tools and processes can be used to manage cloud and edge workloads regardless of where the edge resides. This will require the evolution of the software used to deploy，scale，and manage applications in the cloud，which has historically been architected with a single data center in mind.

　　在上文中我概述了邊緣計(jì)算是如何描述各種體系結(jié)構(gòu)，以及“邊緣”可以位于許多地方。然而，這一行業(yè)的最終方向是走向統(tǒng)一，走向一個(gè)可以使用相同的工具和流程來(lái)管理云和邊緣工作負(fù)載的世界，而不管邊緣位于何處。這將需要對(duì)用于在云上部署、擴(kuò)展和管理應(yīng)用程序的軟件進(jìn)行改進(jìn)，而云上的應(yīng)用程序在過(guò)去是以單個(gè)數(shù)據(jù)中心為架構(gòu)的。

　　Startups such as Ori，Rafay Systems，and Volterra，and big company initiatives like Google’s Anthos，Microsoft’s Azure Arc，and VMware’s Tanzu are evolving cloud infrastructure software in this way. Virtually all of these products have a common denominator：They are based on Kubernetes，which has emerged as the dominant approach to managing containerized applications. But these products move beyond the initial design of Kubernetes to support a new world of distributed fleets of Kubernetes clusters. These clusters may sit atop heterogeneous pools of infrastructure comprising the “edge，”on-premises environments，and public clouds，but thanks to these products they can all be managed uniformly.

　　像Ori、Rafay Systems和Volterra等初創(chuàng)公司，以及Google的antos、Microsoft的Azure Arc和VMware的Tanzu等大公司都在以這種方式發(fā)展云基礎(chǔ)設(shè)施軟件。幾乎所有這些產(chǎn)品都有一個(gè)共同點(diǎn)：它們基于Kubernetes進(jìn)行開(kāi)發(fā)，這一技術(shù)已經(jīng)成為管理集裝箱化應(yīng)用程序的主要方法。但這些產(chǎn)品已超越了Kubernetes最初支持一個(gè)由Kubernetes集群組成的分布式機(jī)群新世界的設(shè)計(jì)初衷。這些集群可能位于由“邊緣”、內(nèi)部部署環(huán)境和公共云組成的異構(gòu)基礎(chǔ)設(shè)施池之上，但由于這些產(chǎn)品的出現(xiàn)，它們都可以被統(tǒng)一管理。

　　kubernetes，簡(jiǎn)稱K8s，是用8代替8個(gè)字符“ubernete”而成的縮寫。是一個(gè)開(kāi)源的，用于管理云平臺(tái)中多個(gè)主機(jī)上的容器化的應(yīng)用，Kubernetes的目標(biāo)是讓部署容器化的應(yīng)用簡(jiǎn)單并且高效（powerful），Kubernetes提供了應(yīng)用部署，規(guī)劃，更新，維護(hù)的一種機(jī)制。

　　Initially，the biggest opportunity for these offerings will be in supporting Phase 1 of the edge’s evolution，i.e. moderately distributed deployments that leverage a handful of regions across one or more clouds. But this puts them in a good position to support the evolution to the more distributed edge computing architectures beginning to appear on the horizon. “Solve the multi-cluster management and operations problem today and you’re in a good position to address the broader edge computing use cases as they mature，”Haseeb Budhani，CEO of Rafay Systems，told me recently.

　　最初，這些產(chǎn)品的最大機(jī)會(huì)將是支持邊緣計(jì)算發(fā)展的第一階段，即通過(guò)一個(gè)或多個(gè)云利用少量區(qū)域的適度分布式部署。但這恰好使它們處于有利地位，可以支持即將來(lái)臨的更加分布式的邊緣計(jì)算架構(gòu)的演進(jìn)。Rafay Systems的首席執(zhí)行官Haseeb Budhani最近告訴我：“解決當(dāng)今多集群管理和操作問(wèn)題，你就可以在更廣泛的邊緣計(jì)算案例成熟時(shí)解決它們?！?/font>

　　On the edge of something great 偉大與邊緣之間

　　Now that the resources to support edge computing are emerging，edge-oriented thinking will become more prevalent among those who design and support applications. Following an era in which the defining trend was centralization in a small number of cloud data centers，there is now a countervailing force in favor of increased decentralization. Edge computing is still in the very early stages，but it has moved beyond the theoretical and into the practical. And one thing we know is this industry moves quickly. The cloud as we know it is only 14 years old. In the grand scheme of things，it will not be long before the edge has left a big mark on the computing landscape.

　　如今支持邊緣計(jì)算的資源正方興未艾，邊緣思維將在設(shè)計(jì)和支持應(yīng)用程序的人員中變得更加流行。在一個(gè)以計(jì)算資源集中在少數(shù)云數(shù)據(jù)中心為典型趨勢(shì)的時(shí)代之后，目前出現(xiàn)了一股支持進(jìn)一步分散的抵消力量。邊緣計(jì)算仍然處于非常早期的階段，但是它已經(jīng)超越了理論而進(jìn)入了實(shí)踐。在如今云計(jì)算只有14年的歷史背景下，我們能感受到這個(gè)行業(yè)的發(fā)展是如此之快。從長(zhǎng)遠(yuǎn)來(lái)看，用不了多久，邊緣計(jì)算將勢(shì)必在計(jì)算機(jī)領(lǐng)域留下濃墨重彩的一筆。

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　　注：《關(guān)于邊緣計(jì)算，你需要了解四件事》來(lái)源于venturebeat網(wǎng)站（點(diǎn)擊查看原文）。本文系數(shù)據(jù)觀原創(chuàng)編譯，譯者數(shù)據(jù)觀/王婕，轉(zhuǎn)載請(qǐng)務(wù)必注明譯者和來(lái)源。

責(zé)任編輯：張薇