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Distributed Edge CloudsAre Complex, But MustThey Be Difficult?

IntroductionCentralized cloud computing platforms built on huge, monolithic data centershave served IT and communications networks well for more than a decade. Theseemingly boundless capacity of traditional data centers has supportedmassive growth of cloud-based services. But new applications and serviceshave emerged that reveal the limitations of the stalwart centralizedarchitecture. In order to meet the needs of existing customers while alsoattracting new types of customers, service providers will need to supportapplications requiring extremely low latency and extremely high bandwidth tocloud services. To deliver these new services and optimize existing ones,operators need an edge cloud architecture that distributes cloud resourcescloser to end users at the edge of the network.

The communications industry’s drive for edge computing solutions can be seenin the expanding activities at industry standards bodies and open sourcegroups. The European Telecommunications Standards Institute (ETSI), LinuxFoundation, and OpenStack Foundation as well as the Telecom Infra Projecthave all launched working groups dedicated to accelerating edge computingfor network operators. Projects include ETSI’s Multi-access Edge Computing(MEC), the Linux Foundation-hosted Akraino Edge Stack and OpenStack’sStarlingX edge computing infrastructure.

The biggest initial challenge for distributed edge cloud architecture isoperational complexity. While distributed edge clouds resolve latency andbandwidth networking issues, deployments will not be feasible for criticalinfrastructure operators if the management of edge clouds is so complex that itresults in soaring operational costs.

With distributed edge cloud deployments comprising potentially thousands ofgeographically dispersed remote nodes, service providers need comprehensivemanagement tools for system-wide orchestration to successfully implement thedistributed cloud architecture and deliver new revenue-generating services.This paper presents the key requirements for distributed edge cloud solutions,evaluates progress to date in improving manageability and proposes next stepsfor accelerating the implementation of edge cloud architectures.

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What Are Distributed Edge Clouds?There are many terms for describing edgecomputing in critical infrastructure networks, andeach one can mean different things to differentpeople. We define distributed edge clouds simplyas providing cloud services — compute, storageand networking — close to the end user devicewith integral system-wide managementcapabilities. The last point is especially importantbecause without management you have thepotential to increase cost with the introduction ofcomplexity. The objective of distributing cloudservices to the network edge is to reduce latencyand reduce bandwidth requirements in access andbackhaul networks, which will not only improveapplication performance and network efficiency,but also support an emerging set of new services.

By locating cloud resources closer to whereapplications are consumed and where applicationdata is generated, service providers eliminate theneed to backhaul data to the core network forprocessing. This greatly reduces latency in

applications, such as mobile HD video streaming,and enables new real-time applications that werepreviously not possible to deliver, such as vehicle-to-infrastructure or autonomous vehicle services.

To achieve similar network improvements with acentralized cloud architecture, criticalinfrastructure operators would have tosignificantly increase bandwidth in access andbackhaul networks, but this is a costly solutionthat may not even meet low latency requirements.Alternatively, operators could provide morecompute and storage resources on edge devices,but this is a far less dynamic solution and resultsin more costly, complex and power-hungrydevices; and in many cases may be impracticaldue to the size of the devices. The alternatives todistributed edge clouds cannot efficiently mitigatelatency and bandwidth restrictions mainlybecause they are too costly, inflexible and difficultto manage.

Edge Cloud Development Enables Delivery of New Services

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Low-latency, high-bandwidth environments arefertile ground for network operators to developunique real-time services. By distributing cloudresources to the network edge, operators havetremendous opportunities to grow revenue byoffering innovative services. In addition, edgeclouds minimize the traffic load on backhaulnetworks by processing data locally, whichreduces transport costs..

High-bandwidth content deliveryDistributed edge clouds will transform contentdelivery services over mobile and fixed networks,such as mobile HD video streaming or securitysurveillance applications, enabling serviceproviders to offer a higher quality of experiencefor consumers and businesses. Distributed cloudenvironments allow network operators to cacheand process content locally so that it does nothave to be retrieved from the core network,thereby reducing network latency and improvingvideo service quality. Edge clouds can also hostreal-time analytics that provide insight intocurrent network conditions, enabling operatorsto route traffic over paths that will deliver thebest content experience.

Immersive AR/VR servicesAugmented reality and virtual reality promise tocreate immersive communications experiences.The benefits will not only improve consumerapplications like gaming, but they will also impactindustries including retail, healthcare andeducation. But to be viable, these resource-intensive services require data processing andintelligence close to the end user devices.

Enterprise private networksNetwork operators can deploy edge computeresources directly on customer premises or inpublic venues like a sports stadium to create anew breed of specialized services. In a sportsarena, for example, network operators cancreate new experiences for fans by deliveringpersonalized content to their smartphones,representing a welcome new source of revenuethat offsets the cost of the new infrastructure.

5G and Industrial IoTThe requirements for 5G networks aim to reducelatency down to a single millisecond to supporttactile Internet applications, which arecharacterized by real-time interaction betweenhumans and machines. Such services are currentlynot possible via today’s centralized cloudarchitectures. But the combination of ultra-lowlatency and 5G speeds (up to 10 Gbps) will enableremote surgeries, new levels of industrialautomation, connected vehicle applications andeven autonomous vehicles whether they aredrones, cars or trucks. Vehicle-to-everything (V2X)communication applications are underdevelopment that will facilitate smart cityimplementations, reduce traffic congestion andimprove road safety. In industrial settings, edgecloud deployments will improve the operation ofcontrol systems in manufacturing and energyapplications as well as enable better patientmonitoring in the healthcare sector.

“ By distributing cloud resources to the network edge,operators have tremendous opportunities to growrevenue by offering innovative services.”

Distributed Edge Clouds Are Complex, But Must They Be Difficult? | 5

Distributed Edge Cloud TopologyThe basic topology of distributed edge cloud networks comprises two levels: a central site and manygeographically dispersed edge sites (i.e., edge clouds), which are connected to the central site overLayer 3 networks. The number of edge clouds in a distributed deployment can be anywhere from oneto tens, or even hundreds, of thousands.

The central site acts as the system controller andhosts the system-wide management functions.These centralized functions enableadministrators to remotely synchronize thedeployment, configuration and management ofall the edge clouds.

The edge clouds can run on a variety ofhardware form factors, from a single server tomulti-server scenarios. Smaller footprintimplementations may be limited in terms ofpower, compute and storage resources and mayrun a reduced control plane since they will sharemanagement functions from the central site.Communications between the remote edgeclouds and the central site is supported by RESTAPIs over Layer 3 networks.

Latency Requirement

~20ms ~50ms ~100ms

Far Edge Servers

Edge Servers

Regional Data Center

Servers

Edge Use Cases

VMs & Containers

Multi-access Edge

vRAN

Industrial 4.0

Transportation

Distributed Edge Cloud Fast Reliable

Scalable Secured

“To ensure deploymentflexibility, a distributed edgecloud solution must be highlyscalable to support any size ofdeployment. The solution needsto be able to scale seamlessly totens or hundreds of thousandsof distributed edge clouds ingeographically dispersedlocations.”

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Critical Requirements for Distributed Edge CloudsWith edge clouds scalable from small singleserver solutions to large multi-server solutions,replicated hundreds or thousands of times andspread out over a wide area, the biggest challengeis manageability. How can service providers cost-efficiently manage thousands of distributed edgeclouds over diverse network conditions?

To overcome manageability issues, distributededge cloud solutions require centralizedmanagement capabilities, massive scalability,edge cloud autonomy and zero touchprovisioning. These features are the key essentialsfor cost-efficient management. Together, thesecapabilities will shorten edge cloud deploymenttimes, streamline operations, ensure availability,minimize human errors, and, ultimately, loweroverall operating costs to support the businesscase for distributed edge cloud deployments.

Centralized management of edge cloudinfrastructure and workloads. Large-scaledeployments of geographically dispersed edgeclouds simply cannot be managed manually.Unlike centralized data centers with teams oftechnicians, administrators, and engineers, mostremote edge clouds will not have anyone on siteto configure, provision and manage operations. Ofcourse, the servers themselves do need to bephysically installed, cabled and powered up onsite. But once the servers are up and running,service providers need the ability to remotely

manage the cloud infrastructure as well as theapplication workloads across the entiredistributed system from a central site.

It is essential to centrally manage theconfiguration and status of the edge cloudinfrastructure to save time and minimizeoperational costs. All the components of edgecloud infrastructure need to be configured forhow the cloud will be used and what resourceswill be made available to users. This includessetting user login parameters, establishing thephysical nodes that the cloud software will run on,determining what software will be running andwhat software images will be available to installfor the applications, and configuring the storageclusters.

The virtualized applications, whether implementedas containers or virtual machines, also need to belaunched and defined according to the resourcesthey will be allowed to use – that is, setting thenumber of CPU cores needed and amount ofRAM memory and disk space required. Otheradministrative configuration tasks includesecuring the network traffic by creating securitygroups and security group rules for ingress andegress packet filtering. In an OpenStack-basedsystem, for example, VM or container imagedefinitions, packet filtering and quotas would behandled by elements of Nova, Neutron and Cinderresources, respectively.

“Large-scale deployments of geographically dispersed edge cloudssimply cannot be managed manually. Unlike centralized data centerswith teams of technicians, administrators, and engineers, mostremote edge clouds will not have anyone on site to configure,provision and manage operations.”

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With centralized management tools and APIs,administrators can configure the infrastructureonce and synchronize the configuration across thedistributed edge clouds. Configuration updatesmade on the system controller can also beautomatically applied to all edge clouds.OpenStack resources can be synchronized andautomatically applied during installation.Synchronizing the configuration data preventsadministrators from having to configure each edgecloud separately, which can be error prone, withthe same tasks (errors) potentially repeatedthousands of times depending on the size ofdeployment.

It is worth noting that there may be somecircumstances where service providers may notwant to configure all distributed edge clouds in thesame way. Centralized management tools need toallow for exceptions in the synchronization ofconfiguration data.

In addition to configuring the infrastructure, thestatus of the edge cloud infrastructure also needsto be managed centrally so that administrators caneasily monitor the health of the entire system aswell as individual edge clouds. The systemcontroller at the central site needs to aggregatefault and telemetry data from all the edge clouds,including fault alarms, logs and telemetry statistics.

The user workloads running on the distributededge clouds also need to be centrally managed.This allows users to launch applications on VMs orcontainers from different edge cloud sites whenneeded. It also allows VMs to be migrated from oneedge cloud site to another. Being able to centrallymanage the edge cloud workloads also assists infault scenarios across edge sites and disasterrecovery efforts.

Software updates can be challenging in distributedcloud environments. To make software updateseasier and faster, it is necessary to orchestratesoftware patching across the entire system toensure bug fixes and new features are appliedcorrectly on each edge cloud. Once the softwareupdate has been applied to the system controllerat the central site, the update should beautomatically applied across each node of everyedge cloud. During the update process, it is alsoimportant that VMs are automatically migrated toensure network uptime.

Single pane of glass provides system-wide view.Centralized management capabilities must besupported by a single pane of glass view. Systemadministrators need a simple way to seeeverything that’s going on across their entiredistributed edge cloud deployment, frominfrastructure data synchronization toconnectivity and overall health status to softwareupdates, without having to access multipledifferent interfaces and correlate the information.

Massive scalability is a must. A distributed edgecloud architecture provides unprecedentedflexibility for network operators to deploy cloudresources where they are needed most, whetherthe edge clouds are deployed to optimize existingservices or support new applications. To ensuredeployment flexibility, a distributed edge cloudsolution must be highly scalable to support anysize of deployment. The solution needs to be ableto scale seamlessly to tens or hundreds ofthousands of distributed edge clouds ingeographically dispersed locations. The edgeclouds themselves need to be scalable from asingle node to thousands of nodes.

Edge cloud autonomy. In many cases it’s criticalthat edge clouds are completely autonomous. Ifconnectivity is lost between the central site andan edge cloud site, the edge cloud still needs toperform its mission critical operations and usersstill need to be able to access the edge cloud. Thisis a possible scenario if, for example, an edgecloud is located where mobile or satellite networkcoverage is patchy. But if the infrastructure andworkload data is synchronized across all the edgesites, then users will still be able to access theirservices and the edge cloud will functionindependently until connectivity is restored.

Zero touch provisioning. Installation andcommissioning at the edge sites need to be assimple as possible. Beyond the physical serverinstallation and power-on at the edge site, theremaining installation and commissioning tasksmust be as automated as possible, reducing theneed for human interaction. From that point, theadministrator back at the central site should beable to bring up the cloud environment on thenodes at the edge sites with just one button click.

State of Play for Distributed Edge Clouds

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How close is the industry to meeting theserequirements for distributed edge clouds? Asnoted above, many initiatives at open source andindustry standards groups are tackling variousaspects of edge computing for networkoperators. Among these efforts, the OpenStackFoundation’s StarlingX project is notable for itswork on distributed edge cloud manageabilityand contribution to other open source projectsto broaden community engagement and widenindustry support.

As part of OpenStack’s Edge Computing group,StarlingX provides a deployment-ready, scalable,highly reliable edge infrastructure softwareplatform. It was originally based on proven codethat has been widely deployed to deliver reliableuptime, performance, security, and operationalsimplicity that will be necessary for distributededge cloud solutions. StarlingX provides a fully-featured open source cloud for the distributededge. StarlingX code has also been included in

blueprints contributed to and accepted by theLinux Foundation’s Akraino Edge Stack project.

To date, StarlingX has demonstrated manycritical capabilities, such as synchronizingOpenStack and infrastructure configuration aswell as dynamically managing quotas across alledge clouds from the central system controller.The project has also developed a simpleinstallation sequence for edge clouds, which isapproaching the goal of zero touch provisioning.The platform can automatically orchestratesoftware upgrades across edge clouds andaggregate fault alarms and telemetry data. Andthe project is working on improving thescalability and autonomy of authentication andauthorization processes.

StarlingX is available free from the community atwww.StarlingX.io. Going forward Wind RiverTitanium Cloud will be a fully supported versionof StarlingX for commercial deployments.

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Next Steps for Edge Cloud ManageabilityInitiatives like the StarlingX and Akraino Edge Stack projects have made great strides in reducingoperational complexity of distributed edge cloud deployments, but there is more work to be done.Priorities should include georedundancy for system controller central sites to ensure highly availabledeployments; enhanced security for communication between edge clouds; increased installationautomation to achieve truly zero-touch provisioning; and support for the lifecycle management of bothvirtual network functions (VNFs) and container network functions (CNFs) among edge clouds. Otherimprovements that will make management easier include the distribution and synchronization of imagesacross edge clouds as well as the ability to synchronize configuration to a subset of edge clouds.

With edge environments being unique in almost every case, distributed clouds will need to support avariety of heterogenous deployments for the foreseeable future. While containers may be the path tothe future there will continue to be a requirement to support VMs alongside or separate from containersas well as pure container based environments. Also, where does the edge stop? We may see moremovement toward extending a distributed cloud solution to encompass not only cloud and edge servers,but into the devices as well. As the edge extends beyond edge cloud servers, there may also be a needto support bare metal nodes. Reducing the complexity of supporting this wide variety of deploymentswill be key to success.

ConclusionOperational complexity is the biggest initial challenge for distributed edge clouddeployments. Network operators need confidence that they can easily manageedge clouds to meet service quality commitments without incurring excessiveoperating costs. Distributed edge cloud solutions must be designed to supportcentralized management, scalability, edge cloud autonomy and zero touchprovisioning. These basic requirements will provide the operational simplicity,high performance and reliable uptime for distributed edge cloud deploymentsso that network operators can seize the opportunities to deliver new real-timeservices that deliver new sources of revenue.

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© 2018

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