CLOUD-EXTENSIBLE TRANSCODING AVOID THE TRAP OF SINGLE CLOUD OVER-DEPENDENCY

Transcription

1 CLOUD-EXTENSIBLE TRANSCODING AVOID THE TRAP OF SINGLE CLOUD OVER-DEPENDENCY compny

2 Cloud-Extensible Trnscoding TABLE OF CONTENTS Trnscode Worklod Chllenges... 3 Cloud Dependency... 4 Cloud-Extensibility... 5 Elstic Trnscoding... 6 Scle-Out Trnscoding... 7 Compute Agnosticism & Awreness... 8 Criticl Or Nice To Hve?... 9 The Concurrent Solution c o m p n y 2

3 Cloud-Extensible Trnscoding TRANSCODE WORKLOAD CHALLENGES Hndling video trnscoding worklods with unpredictble, rpidly evolving scle is n opertionl chllenge in tody s world of lrger files nd growing SVOD demnd. Brodcsters need elstic resources to efficiently nd quickly mke originl brodcst content vilble for on-demnd consumption. Studios working with mster files need lrge mounts of compute resource for distributing progrms on-time to their content distributors. As result, the flexibility, speed nd sclbility of the content trnscoding function hs become criticl success fctor in medi workflows. But wht does this men for Medi businesses tht use trnscoding solutions nd services? Wht type of trnscode solution is best-positioned to help Medi businesses meet their objectives? This pper explores how the ltest cloud-extensible trnscoding solutions cn contribute to fster nd more cost-effective content workflows, while lso voiding the emerging cloudtrp. c o m p n y 3

4 Cloud-Extensible Trnscoding CLOUD DEPENDENCY Cloud-bsed compute seemed like gret solution to solve your trnscoding problem just few short yers go. You hd n ging, hrdwre bsed trnscoder well integrted in your workflow, nd were experimenting with few softwre pplictions. The hrdwre vendor ws incresing their support costs yers over yer, nd your procurement tem ws questioning the vlue in mintining pltform lmost decde old. Menwhile the softwre ws difficult to deploy, often required dedicted computing hrdwre nywy, nd wsn t well integrted. Cloud-bsed trnscoding cme onto the scene nd solved your problems with reltively light outly of opertionl expense. As your relince on this solution to your problem incresed, new problems emerged. You relized you hve dependency nd cost problem. As businesses use cloud-hosted trnscoding they re lerning the limittions nd the issues. Wht is emerging is tht businesses need something slightly, but fundmentlly, different. The customer requirement is chnging from I need flexible trnscoding cpcity to hndle my pek trnscode worklods to I need flexible trnscoding cpcity to hndle my pek trnscode worklods tht does not tie me to single service provider s environment nd helps me better mnge cost. c o m p n y This requirement hs emerged due to the disconcerting over-relince on single service provider. Cloud-hosted services re ppeling, but when ll your VOD sset workflows re tied up with single, very lrge, cloud service provider, set of new business risks emerge. The primry risk tends to be commercil, nd is generlly described s cost creep. The relity is tht cloudbsed services often strt s cost effective solution, but chnge over time due to incresing scle or pricing structure modifictions. For exmple, tody the policy might be tht uplods re free nd downlods / deliveries re chrgeble. When the uploded file is lrge XDCAM 50mbps file, nd the output is smller MPEG-4 10mbps files, this is ttrctive. Wht hppens if the pricing policy chnges to chrge for uplods rther thn downlods? Or, wht hppens when the scle of your opertions increse? Wht impct does 4K content hve? In the subsequent risk mitigtion plnning, you cn try to negotite lower prices with your cloud service provider, or ccept nd bsorb the higher costs, or move your trnscoding worklods to nother loction. The best option would be to hve no dependency on remining with the cloud service provider so you cn control your own destiny nd mnge your costs nd mrgins. One technicl problem bout moving your trnscoding pltform is tht medi sset cretion workflows cn be certified by the receiving video pltform. So your trnscoding solution hs to remin complint. Wht if you ve used trnscoding solution tht is n intrinsic prt of your cloud service - cn you find this sme solution elsewhere? 4

5 Cloud-Extensible Trnscoding CLOUDEXTENSIBILITY So wht do you do? First you need to be ble to move to new environment tht llows you to mnge your costs, while lso being complint with your customer s requirements. Over dependency on the cloud nd high costs re voidble with the right trnscoding solution. Forwrdlooking medi businesses evluting their long-term infrstructure strtegy re proctively figuring out how to chieve the best of both worlds - mximum control t optimized cost. The concept of cloud-extensibility is fst emerging. We cn define cloud-extensible s orchestrtion of compute gnostic resources between single or multiple public nd/or privte clouds. It s lredy common prctice to diversify video trnsport worklods cross different service providers such s stellite providers nd CDNs. So why not video processing worklods? With softwre-defined trnscoding solutions it s possible to blend privte nd public cloud environments for your trnscoding worklods. Cloud-extensibility voids the business risk of being trpped with single service provider. Softwre-defined enbles you to deploy common trnscoding softwre cross ny hrdwre infrstructure environment. A cloud-extensible solution mens you cn utilize ny environment you wish in order to protect your business from uncontrollble chnges by single cloud service c o m p n y provider. It lso mens tht you cn blnce worklods, nd costs, between privte cloud / on-premise infrstructure nd public cloud infrstructure. To complete the solution you ll use the workflow mnger of your choice to control, vi API, trnscode mnger tht will llocte work to different trnscode environments. This ll sounds firly simple, but the business requirement is only now emerging s orgniztions come to terms with cloud-bsed trnscoding costs nd relize there cn be better wy. The good news is tht cloud-extensible solutions re vilble tody. Solution chrcteristics Wht re the key chrcteristics cloud-extensible solution must hve in order to mke rel difference to the business s bottom line? ELASTICITY - cpcity cn be scled up or down s required nd, if desired, cn lso be pid for on per-use bsis. SCALE-OUT - extr cpcity cn be bolted on to support s mny instnces of the softwre-defined trnscoder s required no forklift upgrdes, no proprietry hrdwre. COMPUTE AGNOSTICISM AND AWARENESS the trnscoder must be ble to be run in generl compute environment nd longside other pplictions in continerized or virtulized ecosystem. Worklod cn be distributed to consistent trnscoding functions in ny compute loction. 5

6 Cloud-Extensible Trnscoding ELASTIC TRANSCODING Elsticity hs become synonymous with expnding cpcity. But it is more thn tht. Elsticity relly mens using for nd pying for cpcity only when required. There re both technicl nd commercil considertions. The idel trnscoding solution is py-per-use model. Like mny other on-demnd video processing functions, medi businesses re looking for trnscoding cpcity when they need it rther thn building out systems for pek lod nd then leving cpcity idle most of the time. c o m p n y The best solutions therefore include softwre nd hrdwre on py-per-use bsis. Hrdwre is just compute power nd is generlly the lowest cost prt of the solution, mking it reltively simple to run hrdwre pltform. Softwre is where the differences re found in processing qulity nd speed when hrdwre pltforms re equl. But softwre is reltively esy to instntite on-demnd. Whether trnscoding is performed in public cloud environment or on-premise, the softwre needs to be deployble nd chrged for s used. Billing engines within the trnscode softwre communicte with the workflow mnger to trck usge nd crete invoices. This gives the most ccurte method of billing, to the minute or the pixel. This lso provides level of predictbility for mnging wht cn be very lumpy opertionl costs. Elsticity is necessity in tody s world of fst-chnging demnds nd technologies. Trnscoding is n idel use cse for elstic cpcity. 6

7 Cloud-Extensible Trnscoding SCALE-OUT TRANSCODING Scle-out refers to the bility of the video infrstructure to expnd without limits. Softwre-defined pplictions, like trnscoder or storge system, hve scle-out cpbility tht recognizes extr hrdwre cpcity simply s somewhere to do their work. Compre this to the big iron, proprietry hrdwre solutions of the pst. Vendors tht re ble to work in depth in both storge nd trnscode environments hve nturl dvntge to deliver this hyper-converged solution. In scle-out storge environments, where ech dditionl dt node dds storge, network nd compute cpcity, the compute resources re typiclly higher thn the storge ppliction requires, nd so it is nturl trget for optimizing on premise compute efficiencies. This hyper-converged scle-out process is mostly intended for trnscoding files rther thn live strems. However, the best trnscoding solutions use blde rchitecture tht cn be expnded for file or live content simply by dding dditionl bldes to the system. In scle-out trnscoding, Scheduler function nlyses incoming jobs nd lloctes them to Worker nodes tht perform the ctul source content fetching, processing nd writing out the output to its trget destintion. Adding extr cpcity to the system involves creting dditionl worker instnces on hrdwre with similr processing cpbilities - in public cloud environment this mens llocting dditionl hrdwre. In privte cloud environment, the hrdwre cpcity cn be llocted in the sme wy if enough hrdwre is vilble. Once creted, the new instnces utomticlly join the pool of cpcity vilble for the Scheduler to use. One re of scle-out innovtion from leding vendors is to use under-utilized compute resources in softwredefined, distributed scle-out storge pltforms to run trnscoding jobs. In other words, it is possible to run storge nd trnscoding in hyper-converged pltform for mximum efficiency. c o m p n y 7

8 Cloud-Extensible Trnscoding COMPUTE AGNOSTICISM & AWARENESS As compute resources become more esily ccessible in cloud environments, it is possible for trnscoding worklods to be flexibly moved between the best loctions. The compute loction-wreness nd intelligence to utomticlly select the best loction bsed on trde-off between processing costs nd job output dedlines cn be embedded in business rules within n existing workflow mnger. With common softwre-defined solution vilble in multiple loctions including on-premise - the tsk of the workflow mnger is to choose the best loction to complete ech job. c o m p n y While public cloud services re well-suited to hndling worklod peks becuse of the ese of scling the compute resources (i.e. llocting more hrdwre nd virtul mchines), there re severl downsides in terms of speed nd efficiency: 1. Content uplods cn tke hours nd dys. 2. Mssively virtulized environments cn reduce compute efficiency. From workflow speed nd efficiency perspective, on-premise trnscoding in generl compute-bsed privte cloud cn yield best results. For the most prt, commercilly off the shelf (COTS) hrdwre is used in these environments. As internl IT deprtments become more dept t mnging privte cloud environments, it is possible to hve it ll: speed, horsepower, nd opertionl efficiency. An idel solution therefore combines n intelligent workflow mnger/scheduler, scle-out cpbilities on-premise, nd ccess to trnscoding cpcity with either public cloud services or privte cloud services running the sme softwre to hndle ny pek worklod. Trnscoding processes cn be cloud-extensible. 8

9 Cloud-Extensible Trnscoding CRITICAL OR NICE TO HAVE? Trnscoding is criticl prt of ny content distribution workflow, to prepre content for ech delivery pltform nd optimize distribution efficiency. Mking the trnscoding function s gile, efficient nd cost-effective s possible is business requirement. Compnies tht hve lredy used cloud-hosted trnscoding services or cloud-hosted compute to run softwre-trnscoders hve lerned some lessons bout mnging their dependency on, nd costs with, cloud service providers. Mny of these compnies hve evolved their strtegy to invest in solutions tht re cloud-extensible. Core to tht strtegic pproch is the employment of py-peruse elstic cpcity model to complement their onpremise scle-out cpcity. Coupled with n pproprite workflow mngement tool, this strtegy optimizes the utomted lloction of trnscode jobs to the best compute loctions which is criticl for n efficient nd predictble opertionl model. Trnscoding worklods re set to grow. Lrger file sizes nd more VOD outlets re the trend every medi business should expect. Choosing the best trnscoding solution to mnge your costs, meet your dedlines nd improve your profitbility is business-criticl decision. c o m p n y 9

10 Cloud-Extensible Trnscoding THE CONCURRENT SOLUTION Concurrent s softwre-defined trnscoding solution, Zephyr, is designed from the ground up to be cloudextensible. With support for live nd file workflows, deployment s Linux continers in hyper-converged environments, nd esily integrted vi API into ny workflow mnger, Zephyr cn help your business mnge ny type or scle of trnscoding worklod in the most flexible nd cost-effective wy. Zephyr Trnscode Webpge & Product Brief Solutions for Content Providers MAM Storge & Trnscode Solutions for Service Providers TO LEARN MORE ABOUT HOW CONCURRENT CAN HELP YOU MANAGE YOUR TRANSCODING WORKLOADS MOST COST-EFFECTIVELY, PLEASE VISIT FOR MORE INFORMATION OR CALL c o m p n y 10