The document outlines nine key enterprise technology trends for 2016 and beyond, emphasizing the central role of cloud computing and its evolution into cloud-native architectures focused on microservices and containers. It discusses advancements in big data processing with Spark, the rise of machine learning capabilities, and the emergence of hybrid cloud solutions. Other trends include the growing importance of software-defined networking, the enhanced performance of SSDs, and the potential of blockchain technology to ensure transaction integrity.

1. 9 enterprise techtrendsfor2016 andbeyond
Enterprise technologydevelopmentkeepsracingahead,andthisyear'sforecastexplainshow most
of itwill be wrappedinthe cloud
InfoWorld’sDavidLinthicumrecentlysuggesteditwastime toretire the phase “cloudcomputing”
and simplysay“computing.”That’showessential cloudhasbecome -- andwhyforthe past couple
of yearscloudhas framedmyannual attemptto identifythe nine keyenterprise techtrendsgoing
forward.
In 2015, it became a lotclearerwhat cloudinfrastructure inall itsscalable,self-service glorywillbe
bestfor: runningapplicationscomposedof microservicesoutfittedwithRESTful APIs.Mostlikely
those serviceswillrunincontainers,whichgive developersmore control thanever inbuilding,
testing,anddeployingapplications.Containersinturnsupportdevops,where opsleveragesnew
automation,instrumentation,andmonitoring -- anddevstake new responsibilityforapplicationsin
production.
Sure,that’sone sort of cloudoperation,andfew have all those piecesinplace today.Butit's
remarkable howquicklythissharedvisionof the future hascoalesced.
Still,several elementsof thispicture needtobe completedbeforeyouraverage enterprisecan
contemplate adoption.Which bringsustoour firsttrendof 2016:
1. 'Cloudnative'shapesthe future
Applicationsbuiltfrommicroservicesrunningincontainershave all sortsof advantagesover
monolithicapplications.Firstandforemost,insteadof dealingwithobscure internal dependencies
that make troubleshootingandupdatingpainful,youcanworkwithdecoupledservicesthatare
individuallymonitoredandmanaged.
But microservicesarchitecture addscomplications -- mainly,swarmsof containerstokeeptrackof.
Andwhomanagesliterallybillionsof containersinproductioneveryday?Google,the companythat
in2007 contributedthe Linux kernel’scgroupscontainerfeatureonwhichDockerwaslaterbuilt.
Last year Google introducedthe opensource Kubernetesproject,whichdistillsGoogle’scontainer
managementsystemintoopensource bitssomere mortalscanwrangle clustersof containersat
scale.Thissummerthe project’sfounder,CraigMcLuckie,announcedthe formationof the CNCF
(CloudNative ComputingFoundation),which will take Kubernetesasa startingpointto buildoutan
ecosystemforcontainerscheduling,management,andorchestration.Watchthisspace carefully.
2. Spark 'streaming'accelerates
A funnythinghappenedtobigdatain2015: Spark elbowedHadoopoutof the spotlight.Why?
Because ratherthan processingdatainbigbatchesacross many disks,asHadoopdoes,Sparkworks
itsmagic withsmall batchesinbigmemory -- close enoughtoreal time tobe indistinguishable from
streaming.(Storm,atrue streaming solution,hasalreadyfallenoutof favor.)
ClouderaandIBMhave gone all-inwithSpark,while Amazon,Google,andMicrosoftofferSparkasa
service intheirpublicclouds.ButSparkstill hasmajorannoyancesrelatingtomemorymanagement

2. and resiliency,amongotherdrawbacks.Withthiskindof momentum,though,youcanexpectmany
such problemstobe addressedinthe comingyear.
3. Developerstapintomachine learning
Notonlydo all the major cloudsnowofferanalyticsasa service,buttheyalsoprovide machine
learningAPIsinthe cloud;plus,opensource machine learningtoolsabound.Ubiquitousmachine
learningcapabilityenablesdeveloperstobuildapplicationsthatrecognize patternsingobsof data --
for frauddetection,face recognition,medical diagnoses,infrastructure optimization,Webad-
serving,youname it.
Of course,some commercial softwareandwebsiteshave hadmachine learningfeaturesforyears
(foranticipatinguseractions,recommendingrelatedproducts,andsoon).The difference todayis
that machine learningisbrokenoutasa separate capabilityanydevelopercanexploit,andwe now
have tonsof data and cloudcomputingcapacitytothrow at it,includingfancynew serversequipped
withGPU acceleratorsto run machine learningalgorithms.
4. Cisco’sACIreinvigoratesSDN
The veryideaof software-definednetworking(SDN) suggeststhat,eventually,hardware switches
will become commoditized,whichiswhySDN hasbeenseenasan existential threattoCisco.Sofar,
however,SDN adoptionhaslargelybeenconfinedtotelcoandcloudservice providersandhashad
little impactonthe enterprise.
NowCiscohas leapedaheadandintroducedanew SDN scheme dubbedApplicationCentric
Infrastructure (ACI) thatincludesanewoperationscontrol protocol,OpFlex,toreplace OpenFlow.
Designedforlarge-scaledeployments,ACIpushesSDN inanew direction,distributingsome of the
control overconfigurationtothe networkandgivingadminsthe abilitytoadjustsettingsata high
level basedon applicationrequirements.
Most surprisingof all maybe the degree of openness.ACIusesRESTful APIs,andCiscohaspostedan
opensource SDK alongwithvariousACItoolsonGitHub.Also,CiscohasproposedOpFlex asanboth
an IETF standardand as an OpenDaylightproject,andOpFlex alreadyhasthe supportof Microsoft,
IBM, F5, Citrix,RedHat, Canonical,andothers.ConsideringCisco’shuge enterprisemarketshare,
thiscouldbe the jumpstartSDN needs.
5. PaaS getsa secondchance
As AndrewOliver’sclassic2012 article “WhichfreakingPaaSshouldIuse?”made clear,the first
generationof PaaSwasbedeviledbyarbitrarylimitations.Asaresult,enterprisePaaSadoptionhas
beenrelativelyweak.Lotshashappenedrecently,though,includingarushto supportDockerby the
twoleadingon-premisesPaaSofferings,CloudFoundryandOpenShift.
I still believethat,onpremises,manyenterprisescanbenefitfromrunningPaaSasa modern,scale-
out,polyglotversionof the goodoldapplicationserver.AccordingtoMartinHeller’srecent
InfoWorldreview,OpenShiftEnterprise 3hasincorporatedDockercontainerswithoutskippinga
beat:“For both developersandoperators,OpenShiftfulfillsthe promiseof PaaS.”

3. 6. SSDs takesa biggerbite outof the data center
Alreadyflashbeatsspinningdiskinprice-performance forIOPS-intensive applicationssuchasVDIor
high-performance databases,becauseequallyperformantspinningdiskrequiressomanyspindlesto
keepup.All-flasharraysandSSD-packedserversare nolongerrare.Plus,everyone isexcitedabout
3D NAND,whichwill offermuchhigherSSDcapacitiesandperformance
A numberof Internetgiantshave filledtheirdatacenterswithSSDsforpowerconservationaswell
as performance reasons.Nonetheless,performance aside,the notionthatflashwill reachprice-per-
gigabyte paritywithspinningdiskwillremainapipe dreamforyears.Spinningdiskhasmade itsown
advances,includingheliumdrivesandshingledmagneticrecording,soSSDswon’tfullyreplace hard
drivesanytime soon.
7. The hybridcloudgetsreal
I’ve hadtrouble withthe phrase “hybridcloud.”Wasit supposedtomeanintegrationbetweenon-
premisesinfrastructure andthe publiccloud?The integrationof anytwoclouds?If it requireda
private cloudsetuplike a publiccloud,well,sofew of the formerexist,the hybridcloudmightas
well be mythical.
But Microsoftis changingthatwithitsAzure Stack for WindowsServer,whichenablescustomersto
at leastpartiallyduplicateAzure publiccloudinfrastructurelocally.WhenWindowsServerand
SystemCenter2016 shipnextyear,integratingthemwithAzurepromisestoyieldatrue hybridIaaS
environment.Throughitsprofessionalservices,IBMappearstobe workinginthe same direction
withhybridpublicandprivate cloudOpenStackdeployments.
Amazonlacksa hybridplay(unlessyouconsidersome customers’effortstoduplicate theirlocal
environmentsonAWS“hybrid”).Google doesn’thave ahybridplayeither,butthankstoKubernetes
and the CNCF(see No.1) it'sonlya matter of time.Withthe recenthire of VMware co-founder
Diane Greene toheadup Google Cloud,I’mfinallyconvincedthatGoogle isseriousaboutserving
enterprise cloudcustomers,andahybridKubernetes(andmore) scheme will be partof the deal.
8. Machine learningampsupsecurity
You’ve probablyheardaboutfinancial servicescompaniesusingmachine learningtodetectfraud.
But othersecuritypossibilitiesformachine learningabound,suchasflaggingnetworkanomalies,
trackinguserbehavior,ordetectingzero-daymalware.
Cylance,whichrecentlypartneredwithDell,providesahigh-profileexample:The companyuses
deeplearningalgorithmstodetectaclaimed99 percentof malware.Yetbuyerbeware,because
machine learningalgorithmshave beenusedinsecurityapplicationsforyearswithvaryingsuccess
and manyfalse positives.Advanceswill keepunfoldingthankstobigdata analyticsinthe cloud,but
expectincremental gains,notmiracles.
9. Blockchainbreaksout
Bitcoinhasbeentarnishedmanytimesover.Butblockchain,the mathematical magicbehindbitcoin,
ison the verge of becomingaviable waytoensure the integrityof all kindsof transactions.Ina
recentfeature article,InfoWorld’sPeterWaynercountedmore than100 companiesexploringways

4. to extendblockchainfortradingplatforms,IDcards,contracts,secure storage,and more.Yes,even
banksare testingitout -- an indicationwe’ll seeblockchaingomainstreamin2016.
Source : infoworld.com
Recommendedby:
JonCohn ,CTO, VP IT Architecture
https://www.linkedin.com/in/jonacohn
joncohn@comcast.net
"JonCohn ExtonPA""JonCohn Exton""JonCohnEvolution"