Ang ulap ay kailangan - ano, bakit, kailan at paano - techwise episode 3 transcript

Eric Kavanagh: Mga kababaihan at ginoo, kumusta at maligayang pagdating muli sa TechWise. Ang pangalan ko ay Eric Kavanagh. Ako ang magiging moderator mo para sa Episode 3. Ito ay isang bagong palabas na dinisenyo namin sa aming mga kaibigan mula sa Techopedia, isang napaka-cool na website na malinaw na nakatuon sa teknolohiya, at siyempre, dito sa The Bloor Group, medyo nakatuon kami sa negosyo teknolohiya. Kaya, ang software ng enterprise ng lahat ng mga uri, at ang buong format ng TechWise ay idinisenyo upang mabigyan ang aming mga dadalo ng isang tunay na mahusay na mahirap na pagtingin sa isang tiyak na espasyo. Kaya, nagawa namin ang Hadoop halimbawa, ginawa namin ang analytics sa huling palabas at sa partikular na palabas na ito, pinag-uusapan namin ang lahat tungkol sa ulap.

Kaya, tinawag itong "The Cloud Imperative - Ano, Saan, Kailan at Paano." Kami ay makipag-usap sa isang pares ng mga analyst ngayon at pagkatapos ng tatlong mga nagtitinda. Kaya, ang Qubole, Cloudant at Attunity ang mga sponsor ng palabas ngayon. Isang malaking pasasalamat sa mga taong ito sa kanilang oras at atensyon ngayon at isang malaking pasasalamat, siyempre, sa inyong lahat doon. At tandaan na bilang mga dadalo sa mga palabas na ito, may mahalagang papel ka. Nais naming hilingin sa iyo na magtanong, makisali, makipag-ugnay, ipaalam sa amin kung ano ang iniisip mo dahil malinaw naman, ang buong layunin ng palabas dito upang matulungan ka na maunawaan kung ano ang nangyayari doon sa mundo ng cloud computing.

Ang Cloud Imperative Deck

Kaya, lumipat tayo mismo. Unang host, ang host mo doon, si Eric Kavanagh na ako at pagkatapos ay mayroon kaming Dr. Robin Bloor na tumawag mula sa isang paliparan, bilang isang bagay at ang aming mabuting kaibigan na si Gilbert, Gilbert Van Cutsem, isang independiyenteng analyst, ay nais ding magbahagi ilang mga saloobin sa iyo. Pagkatapos ay maririnig natin mula sa Ashish Thusoo, CEO at co-founder ng Qubole. Naririnig namin mula kay Mike Miller, punong siyentipiko sa Cloudant at sa wakas mula sa Lawrence Schwartz, VP ng Marketing sa Attunity. Kaya, nakakuha kami ng isang buong maraming nilalaman na nakalinya para sa iyo ngayon.

Kaya, ang ulap - utos mula sa itaas - ito ay isang konsepto na dumating sa akin sa ibang araw nang iniisip ko ito. Talagang, ang cloud computing ay napakalaking mga araw na ito. Ibig kong sabihin, talagang kamangha-manghang panoorin ang ebolusyon ng mga bagay na ito at isa sa mga halimbawa na madalas kong ibinibigay ay sa mismong webcasting technology mismo. Siyempre, ang mga sa iyo na nag-dial nang maaga ay nakarinig ng ilang mga kagiliw-giliw na mga hamon sa teknikal. Iyon ay isang problema sa ulap ay ito ay nagbabago, nagbabago ang mga format, nagbabago ang mga pamantayan, nagbabago ang mga interface at kung minsan kapag sinusubukan mong i-hook up ang dalawang magkakaibang lugar, magkakaroon ka ng kahirapan, nagkakaroon ka ng ilang problema. Kaya, ito ay talagang isa sa mga bagay na mag-alala tungkol sa cloud computing. Mag-ingat sa arkitektura! Maaari mong makita na sa huling punto ng bullet.

Isa sa mga bagay na ginagawa namin, tulad ng isang tala sa tabi dito, para sa aming webcast, mayroon kaming isang hiwalay na vendor ng telepono sa kumperensya. Pagkatapos ay gumagamit kami ng WebEx. Hindi namin ginagamit ang WebEx audio dahil lantaran, isang beses na ginamit namin ang audio ng WebEx taon na ang nakalilipas at ito ay nag-crash at sinunog sa isang hindi kanais-nais na paraan. Kaya, hindi kami handa na patakbuhin muli ang panganib na iyon. Kaya, ginagamit namin ang aming sariling kumpanya ng pag-record ng audio na tinatawag na Arkadin bilang isang bagay at pinagsama namin ang magkasama, sa real time, lahat ng iba't ibang mga solusyon. At ang ideya ay maaari naming mag-email sa iyo ng isang hiwalay na application ng email kasama ang mga slide kung sakaling halimbawa, ang WebEx ay na-crash, sasabihin namin sa iyo na lahat ay mag-dial sa, nais naming mag-email sa iyo ang mga slide at pupunta lamang sa higit pa o mas mababa nang walang uri ng WebEx na mga kapaligiran. Kaya, ang paraan na maaari mong makuha sa paligid ng mga ganitong uri ng mga problema, ngunit ang mga ganitong uri ng isyu ay nasa buong lugar.

Ngunit, maraming mga benepisyo sa ulap. Malinaw, ito ay isang mababang hadlang sa pagpasok, maaari mong tingnan ang poster na anak ng cloud computing ay salesforce.com siyempre, na nagbago lamang ng negosyo, partikular na ang lakas ng pagbebenta ng automation, malinaw naman. Ngunit, pagkatapos ay nakakuha ka ng mga bagay tulad ng Marketo at iContact at Constant Makipag-ugnay at Sailthru at, ang kabutihang-palad, sa mga tuntunin ng marketing at sales automation, mayroong maraming mga tool, ngunit hindi iyon lahat. Nakukuha ito ng HR sa buong laro ng ulap, ang analytics ay nasa laro ng ulap. Tumingin sa maliit na kilalang kumpanya sa labas ng Amazon Web Services, kung ano ang ginagawa nila sa cloud computing - napakalaking ito. At narinig ko ang isang mahusay na quote sa ibang araw mula sa isang tao na marami kaming ginagawa sa David na ngayon ay natapos sa Cisco, bilang isang bagay, ang kumpanya na bumili ng WebEx. Hindi sigurado na namuhunan sila hangga't nais kong magkaroon sila sa WebEx, ngunit hindi iyon ang aking desisyon, ito ba? Ngunit, naroroon siya sa Cisco sa mga araw na ito at nagkaroon siya ng isang napaka nakakatawa, pithy quote lamang, at iyon ay, "walang isang ulap, maraming mga ulap, " at iyan mismo ang tama. Maraming mga ulap sa labas. Sa katunayan, ang bawat cloud provider ay ang kanyang sariling ulap. Kaya, ang isa sa mga hamon sa mga araw na ito ay upang ikonekta ang ulap, di ba? Kung ikaw ay lakas ng benta, hindi ba maganda na kumonekta nang direkta sa iContact at ang patuloy na Makipag-ugnay at sa LinkedIn, halimbawa, at marahil sa Twitter at iba pang mga kapaligiran, ang iba pang mga ulap sa labas doon ay naayos na magkasama ang mga solusyon sa negosyo na may katuturan para sa iyo at iyong kumpanya.

Kaya, ito ang ilang mga isyu na dapat tandaan, ngunit ang ulap ay narito upang manatili. Basta alam na ang tungkol doon, ang premyo na software ay narito upang manatili. Kaya, kung ano ang kailangan nating malaman sa negosyo o kahit na maliit - hanggang sa kalagitnaan ng laki ng mga negosyo, paano mo tinukoy ang iyong arkitektura at mapanatili ito upang maaari mong pag-agahan ang ulap nang hindi lumilikha ng isang higanteng up sa ibang lugar sa labas ng iyong kontrol? Kaya, malinaw naman ang buong industriya ng warehousing ng data ay umusbong sa paligid ng isang pangangailangan upang pagsama-samahin ang mga kritikal na impormasyon upang masuri ang impormasyong iyon at gumawa ng mas mahusay na mga pagpapasya.

Well, ngayon ang Amazon Web Services ay mayroong Redshift. Iyon ang isa sa pinakamalaking mga webcater na nagawa namin ay kasama si Redshift. Iyon ay isang magandang deal. Binago nila ang dinamika, binabago nila ang mga istruktura ng pagpepresyo. Maaari kang manood habang bumababa ang iyong presyo sa tradisyunal na paglilisensya ng software ng kumpanya sa bahagi dahil sa cloud computing at bahagi dahil ang mga taong ito ay nasa labas ng pagbaba ng punto ng presyo, paglalagay ng presyon sa presyo. Kaya, magandang balita iyon para sa mga end user. Ito ay isang bagay na dapat tandaan tiyak para sa sinumang nasa labas doon na nagsisikap na gamitin ang ilan sa mga teknolohiyang ito. Kaya, ito ay isang bagay na dapat tandaan at pag-uusapan natin ngayon sa palabas.

Kaya, ang analyst na si Dr. Robin Bloor ay magiging aming unang analyst para sa araw. Kaya, itutuloy ko at itulak ang kanyang unang slide at ibigay ang mga susi sa kanya. Robin, sa palagay ko nandito ka sa isang lugar, nandiyan ka. At kasama ko itong ihahatid, at ang sahig ay iyo!

Robin Bloor: Okay, Eric. Salamat sa pagpapakilala na iyon. Natagpuan ko … ilang araw na ang nakalilipas, nakita ko ang isang survey ng mga mamimili, sa katunayan, na nagtanong tanong - sa palagay mo ba na ang bagyo ay nakakasagabal sa cloud computing? At higit sa 50 porsiyento ng mga ito ang nagsabi ng oo. Akala ko lang ipapaalam ko sa iyo na hindi, kung isa ka sa mga naniniwala sa iyon. At pagkatapos, iyan ay tulad ng paniniwala na, alam mo, kapag mayroon kang snow sa telebisyon ay dahil sa snowing sa labas.

Ang ulap, alam mo, ang isa sa mga bagay ay uri ng, alam mo, isang mahalagang, kung gusto mo, simpleng detalye ng ulap ay na ang ulap ay talagang isang data center sa isang paraan o sa iba pa, o anumang partikular na serbisyo sa ulap ay isang sentro ng data. Ang tanging bagay ay, ito ay isang iba't ibang data center kaysa sa tradisyonal na ulap. Kaya, ako ay makipag-usap sa pangkalahatang-ideya tungkol sa ulap upang ang iyong backup na pumunta sa mas detalyado tungkol sa paggamit ng ulap dahil walang punto sa takip ng parehong lupa.

Kaya, ang unang uri ng punto na nais kong gawin ay ang serbisyo ng ulap na iyon, alam mo? At ang isa sa mga bagay na talagang nangyayari dahil sa cloud computing ay mayroong … well, tinawag ko ang pagkamatay ng mga tatak, isang buong serye ng mga tatak ng software ay may kakila-kilabot na lakas at patuloy na mayroong mga kapangyarihan sa corporate computing. Kapag nakarating ka sa ulap, wala na silang maraming kapangyarihan, alam mo? Kapag bumili ka ng isang serbisyo sa ulap, nagmamalasakit ka sa application, siyempre, nagmamalasakit ka sa antas ng serbisyo na ibibigay sa iyo ng ulap, hindi mo nais na mabigo ang serbisyo sa ulap, nagmamalasakit ka tungkol sa gastos sa paggamit at nagmamalasakit ka tungkol sa mga ito mga bagay dahil ito ay isang serbisyo, ngunit kung ano ang hindi mo pakialam tungkol sa ngayon ay hindi mo na pinangangalagaan kung ano ang hardware na pinapatakbo nito lalo na, wala kang pakialam kung ano ang teknolohiya sa networking, hindi mo pinangangalagaan kung ano ang operating system tumatakbo ito ay, hindi mo pinapahalagahan kung ano ang mga file system, hindi mo na pinapahalagahan kung ano ang database at aktwal na ginamit ng anumang mga serbisyo sa database ng ulap, alam mo? At ang epekto ng iyon sa isang paraan ay ang ulap ay isang kakila-kilabot na mga tatak ng software na walang tunay na halaga sa ulap dahil, alam mo, pumapasok ka sa ulap sa isang paraan o sa iba pa para sa isang bagay na isang serbisyo at hindi na isang produkto. Kaya, naisip kong makakagawa ako ng isang pares ng mga slide ng mga kadahilanan na hindi gamitin ang ulap, alam mo, at ito ang lahat, kung gusto mo, alam mo, madugong simple, malinaw na mga dahilan, ngunit ang isang tao ay kailangang ipahayag sa kanila, kaya, ako naisip ko.

Kaya, ang mga kadahilanan na hindi sa akin … hindi gagamitin ang ulap - kung hindi nila maibibigay ang uri ng data at proseso ng pamamahala na gusto mo sa kanila, alam mo, kung gayon hindi lamang nito matugunan ang iyong pamantayan. Kung hindi nila maibibigay sa iyo ang pagganap na gusto mo, hindi nito matugunan ang pamantayan. Kung ang ulap ay nagbibigay sa iyo ng kakayahang umangkop sa mga tuntunin ng kung paano mo maililipat ang mga bagay-bagay sa gayon ay hindi ito makakamit ng isang pamantayan. Iyon ay malinaw na mga kadahilanan kung bakit ang mga partikular na serbisyo sa ulap ay hindi magkasya sa isang kakila-kilabot na maraming tao sa labas maliban sa paggawa ng computing sa corporate.

Hindi mo maaaring gawin ito dahil magagawa mo ito ng mas mura. Ang ulap ay hindi palaging ang pinakamurang pagpipilian. Ang ilang mga tao ay tila iniisip dahil madalas na isang murang pagpipilian ito ay palaging gaanong mas mura, hindi ito palaging mas mura. At ang iba pang bagay ay kung ikaw ay kumuha ng isang aplikasyon mula sa isang ulap, hindi ito isinama nang maayos sa iyong ginagawa, kung gayon marahil ay hindi ka ituloy ito at ang mga, alam mo, mga dahilan upang tumalikod .

Narito ang mga dahilan upang magpatibay. Alam mo, ang isa sa mga bagay na maaari mong gawin sa ulap, medyo hindi kalaban ng bala, ay prototyping na aktibidad. Kung maaari mong alinman sa maaari kang prototype sa ulap at ipatupad sa data center, ito ay ganap na mabubuhay at maraming mga tao ang gumagawa nito. Maaari kang mag-upload ng trabaho mula sa sentro ng data na may mga hindi kritikal na aplikasyon dahil marahil, makakahanap ka ng ilang uri ng mga serbisyo ng ulap na matugunan ang antas ng iyong serbisyo sa mga uncritical na bagay. At maaari kang mag-upload ng mga tukoy na application tulad ng salesforce.com at mga katulad na alok sa iyon, alam mo, ang karaniwang mga aplikasyon. Lahat ng tao ay may kakayahan sa lugar na iyon at ang larangan ay hindi dalubhasa at, alam mo, ang tradisyonal … anuman ang magagamit sa ulap ay marahil ay magiging kung ano ang sasama ka.

Kaya, ang pangwakas na bagay na nais kong sabihin, ito ay isang kaakit-akit na bagay, talaga, ay kapag talagang naghahanap ka ng ulap, isang paraan ng pag-unawa ay tulad lamang ng isang serye ng mga ekonomiya ng scale. Ang buong punto ay, alam mo, na nagpapatakbo ng isang data center sa labas at pupunta ka sa dial data na iyon mula sa isang lugar o iba pa at gamitin ito at samakatuwid, ito ay magiging mas mahusay, mas mahusay na maging sa pangunahing murang kaysa sa kung ginagawa mo ito sa iyong sarili. Kaya, alam mo, ito ay talagang tungkol sa mga ekonomiya ng scale.

Ang mga provider ng ulap, pinili nila ang lokasyon ng data center at ang pinakamahusay na lugar upang mahanap ang data center ay nasa tabi mismo ng isang power station, at lalo na sa tabi ng isang murang istasyon ng kuryente. Kaya, ang isang power station pataas sa hilaga na nangyayari na hydroelectric o isang katulad nito. Ito ay karaniwang ang pinakamurang, alam mo? Maaari mong aktwal na mahanap ang data center doon at makikita mo itong mas madali. Mas mura ang pag-upa ng mga tao sa mga nasabing lokasyon kaysa sa gitna ng New York o San Francisco. Maaari mong pamantayan ang buong pasilidad sa mga tuntunin ng air conditioning at kapangyarihan. Iyon ay makakapagtipid sa iyo dahil nangangahulugan ito, alam mo, maaari kang magbigay ng isang buong gusali dito at iyon ang eksaktong ginagawa ng lahat ng mga operator ng ulap. Nag-standardize sila sa networking hardware, na-standardize nila ang computer hardware na ginagamit nila, normal na commodity x86 boards, madalas na i-tipunin nila ang kanilang mga sarili. Kaya, ang ilan ay talagang nagtatayo ng buong bagay. Gagamitin nila ang software ng Amazon na kaya nila dahil talagang nangangahulugan ito na walang gastos sa pag-ampon nito. Sila ay pamantayan sa lahat ng software. Kaya, hindi na nila mai-upgrade ang anumang bagay maliban sa pag-upgrade nang sabay-sabay. Inayos nila ang suporta. Kaya, magbabayad sila ng suporta sa maraming iba't ibang mga tagapagkaloob na mayroon lamang kanilang sariling pasilidad sa suporta. Gagawin nila, magkaroon ng kakayahang scale-up at scale-out sa kamalayan na tatakbo sila nang higit kaysa sa nais mong patakbuhin ang ganitong uri ng serbisyo at susubaybayan nila ang kanilang paggamit sa isang paraan na ang karamihan sa mga sentro ng data ay hindi maaaring dahil sila ay uri ng pagpapatakbo lamang ng isang ulirang serbisyo, ngunit ang karamihan sa mga sentro ng data ay tumatakbo ng isang buong serye ng mga bagay. At iyon ang tinutukoy ng ulap, talaga, at sa isang tiyak na paraan, maaaring tukuyin kung interesado ka sa iyo o hindi ito para sa anumang partikular na aplikasyon. Kaya, alam mo, ang aking uri ng magaspang na panuntunan ng hinlalaki ay kung saan posible ang mga ekonomiya ng sukat, ang ulap ay kukuha ng mas maaga o mas bago. Ngunit, ang paraan ng pagbabago at kakayahang umangkop at isang napaka-tiyak na mga bagay na pupunta ka sa iyong sarili ay talagang hindi makakaya. Ang ulap ay palaging magiging pangalawang pinakamahusay.

Sige. Ipaalam ko ito pabalik kay Eric, o papunta kay Gilbert.

Eric Kavanagh: Okay, Gilbert, bibigyan kita ng mga susi dito sa WebEx. Standby. I-click lamang kahit saan sa slide na iyon at gamitin ang down arrow sa iyong keyboard.

Gilbert Van Cutsem: Sa palagay ko nasa kontrol ako.

Eric Kavanagh: Ikaw ay nasa control.

Gilbert Van Cutsem: Sige. Dito tayo pupunta. Ang ulap na kailangan - ang langit ay ang limitasyon, ito ba ay isang alamat sa lunsod, o ano ang iisipin mo tungkol dito? Ilan lamang ang mga pag-uusap at mga bagay na dapat isaalang-alang.

Una, mula sa "ano" sa harap, alam mo, tulad ng alam nating lahat, hindi sa palagay ko ay may nag-aalinlangan dito. Ang SaaS-ification ay narito upang manatili dahil ang software ay talagang hindi namatay, gumagalaw lamang ito sa ulap, di ba? Sa palagay ko sinabi ko ito bago sa nakaraang edisyon nito. O hindi, o sinabi ni Eric na para sa akin sa isang nakaraang edisyon. At sa palagay ko ang malinaw na dahilan, at bumalik ito sa Robin sa paraang rin, ay sa corporate side ng mga bagay, ang corporate timeline ay medyo madali. Ang CMO ay palaging nangangailangan ng lahat at kailangan niya ito ngayon. Kaya, malapit na siya sa oras sa pamilihan. Kaya nakalulungkot, magandang dahilan ito para sa kanya sa paraang para sa kanya. Ang CIO, gayunpaman, ay medyo nerbiyos tungkol sa SaaS at mga ulap dahil, alam mo, ang buong problema sa pagkalastiko ay nangangahulugang ang bumabangon ay dapat ding bumaba. Dapat kang maging handa upang masukat out, ngunit din upang masukat muli. Kaya, medyo kinakabahan siya tungkol doon. Ang CFO ay hindi kinakabahan, hindi higit sa karaniwan, ngunit siya ay tulad ng, "Hoy, ito … kung magkano ito ibabalik sa amin?" Ito ang, alam mo, ang nakahihiyang paggasta ng kapital laban sa diskusyon sa OPEX. Medyo matanda ito, ngunit napaka, alam mo, napakahalaga sa mundong ito. At pagkatapos, huling ngunit hindi bababa sa, ay CEO, siyempre. Siya ay tulad ng, "Oh! Peligro ng peligro! Guys, kayong lahat ay nasasabik, ngunit handa ba tayo para dito?" Dahil ang panganib ay ang iniisip niya.

Kaya, ano ang panganib? Kaunti lang ang naiisip, di ba? Kami ay nakikipag-ugnayan dito sa pamunuan ng pag-iisip, ngunit sa isang hindi natapos na landas dahil lahat ito ay medyo bagong bagay, lahat ng mga pinakahuling bagay. Wala kaming maraming mga puntos ng data, talaga, kung iniisip mo ito. At kung gayon, kami din, sa peligro, kailangan nating harapin ang mga sakay na board, alam mo, ang mga taong pumirma ng mga kasunduan ay tulad ng, "Oo, iyon ang nais natin, ang paraan upang pumunta, " sila ay nag-sign up, ngunit pagkatapos hindi sapat iyon. Alam mo, mayroon kang mga on-board na mga tao at iyon, tandaan ang mga pelikula? Bumalik sa pagsasalin, na kaunti, alam mo, kung ano ang nasa boarding. At pagkatapos din, tulad ng sinabi lamang ni Robin, alam mo na, ang premyo ay hindi kinakailangang umalis kaagad. Kaya, kailangan mong pagsamahin ang parehong mga mundo. Ito ay isang mestiso na mundo. At kung gayon, paano mo gagawin iyon? Ito ay 80-20, ang 80-20 na namamahala sa Pareto, okay lang ba iyon? Iyon ba ay sapat na? At pagkatapos ay ang basura in / basura out kapag ikinonekta mo ang mga system. Okay lang ba yun? Matibay ba iyon? Dahil, alam mo, pupunta ka ba upang lumipat, pupunta ka ba sa mapa ng iyong negosyo sa root system, paano mo ito gagawin? At pagkatapos ay ang pinakahuli, na sa palagay ko ay napakahalaga, ay maraming arkitektura, nangangahulugang ang privacy ng data sa iyong sariling data, kung minsan ay tinawag itong "sariling iyong sariling data, " ay napakahalaga, alam mo? Isang daang tao na gumagamit ng parehong sistema, isang database ay nakaupo sa ilalim ng system, sino ang makakakita ng aking data? Ako lang, di ba? Sigurado ka bang sigurado tungkol sa na? Ang pagkapribado ng data, ang seguridad ng data ay nakakatulong sa mga eksperto. Kung ikaw ang CIO, ibabalik nito ang "I" sa CIO dahil sa ngayon ikaw ay namamahala sa impormasyon. Iyon ay medyo kawili-wili kung ikaw ay isang CIO.

Kaya, pag-usapan natin nang kaunti ang tungkol sa "bakit." Kaya, ang madiskarteng hangarin ng lahat ng ito ay napaka, napaka-simple, sa palagay ko. Kung ikaw ay isang tagasuskribi, mayroong presyon ng merkado. Kung ikaw ay isang tagapagbigay ng serbisyo, mayroong mapagkumpitensya na presyon. Kung mayroon kang mga kapantay, mayroong peer pressure. Kung ikaw ay isang tagasuskribi, ito ay ang sikolohiya ng merkado. Gusto ng lahat na pumunta sa ulap, SaaS o kung ano man ang tawag mo dito, ulap sa SaaS, kailangan nating lahat at nais na pumunta doon. At ang dahilan ay karaniwang pinansyal. Iyon ang halata na dahilan, ngunit kung iniisip mo ang tungkol sa pinansiyal na aspeto, nakakuha ka ng tinatawag kong paradoks sa kuwenta laban sa badyet. Pupunta ka ba para sa isang subscription, all-you-can-eat system, $ 50, $ 500 sa isang buwan o isang bagay na tulad nito, o nangangarap ka ba tungkol sa paggamit batay upang magbayad ka lamang para sa kung ano talaga ang iyong ginagamit? At kung paano, paano gumagana ang pagpunta sa trabaho, batay sa paggamit, batay sa pagkonsumo? Pupunta ka bang metro ang lahat ng bagay na iyon? Marahil ay hindi ito mangyayari kaagad. Kaya, tatapusin mo ang isang mekanismo ng mestiso, na kung saan, nagbabayad ako ng 200 sa isang buwan at maaaring paminsan-minsan 500 dahil kailangan kong magbayad para sa labis na pagkonsumo. Ang retainer Plus, marahil ay pupunta, sa palagay ko, ang paraan upang pumunta.

Ngunit, mayroon ding isang bagay na tinawag ko ang nakatagong intensyon sa malawak na harapan, at naniniwala ako na, alam mo, ito ay talagang totoo. Ito ang pagbabago ng kontrol, ito ay ang CIO kumpara sa CMO, ang power shift o ang lakas ng pakikibaka sa pagitan ng CMO, "Gusto ko ito at nais ko ito ngayon, " at ang CIO, na nagsasabing tulad ng, "Uy, ito ay lahat tungkol sa data, alam mo? Dati akong tumakbo, 20 taon na ang nakararaan, ito ay tungkol sa mga sistema ng hardware.Sa sampung taon na ang nakalilipas ay tungkol sa mga aplikasyon.Sa ngayon, ito ay tungkol sa data.At dahil ako ang CIO - impormasyon - lahat ito ay tungkol sa ako. nasa kontrol ako. " Kaya, iyon ay uri ng paglipat ng kuryente o pakikibaka ng kapangyarihan Naniniwala ako na nangyayari ngayon sa pagitan ng dalawang ito, ang CMO at ang CIO.

Kaya, sa huli, ito ay ang lahat ng bata na walang sinuman ang talagang nakakaalam kung tayo ay nasa uri ng innovator ng kapaligiran o sa unang bahagi ng uri ng kapaligiran. Naniniwala ako na nasa maagang uri kami ng adopter, hindi ang unang bahagi, ang maagang umampon, ngunit, alam mo, uri ng kalahati. At sa gayon, alam mo, para sa customer, ang end user, ang tagasuskribi, ito ay tungkol sa pagsisimula ng ulo dahil nais ng CMO na magsimula ang ulo, di ba? At sa gayon, mahalaga na hindi matapos ang tinatawag nating pagbabawas. Ang paglilimita sa pagsisimula ng ulo ay maaaring humantong sa pagbawas ng pagbabalik. Iyon ang dahilan kung bakit napakahalaga sa, alam mo, hahanapin, tiwala sa mga partido na maaaring matiyak na ang isang punto ng pagkabigo ay hindi isang isyu at ang seguridad ng data ay iginagalang. Kaya, kakailanganin nito ng kaunting pamamahala ng pagbabago. At kaya, sa huli - halos tapos na, ito na ang huling slide - paano natin ito gagawin? Paano ang paglipat sa ulap, ang paglipat sa SaaS na magiging, alam mo, walang tahi at madali? Kaya, sa pamamagitan ng paggawa ng dalawang bagay: pagbibigay pansin - pagbibigay - talagang mahalaga, at sa boarding, mas mahalaga.

Eric Kavanagh: Sige …

Gilbert Van Cutsem: At sa pagkakataong iyon, ang langit ay ang hangganan. Salamat.

Eric Kavanagh: Oo. Iyon ay mahusay. Gustung-gusto ko ang napaka-mapusok na ideya, gusto ko ang paraan na nasira mo ang lahat. Sa palagay ko ay gumagawa ng maraming kahulugan. At sige at itulak muna ang slide ni Ashish at ibibigay ko sa iyo ang mga susi sa WebEx, Ashish. Okay, sige na. I-click lamang kahit saan sa slide na iyon at gamitin ang down arrow sa iyong keyboard. Doon ka pupunta.

Ashish Howoo: Sige. Salamat, Eric. Kumusta mga tao, ito ay si Ashish at sasabihin ko sa iyo ang tungkol sa Qubole. Kaya, upang simulan ang off, Qubole, mahalagang nagbibigay ito ng malaking data bilang isang platform ng serbisyo. Ito ay isang platform na nakabase sa cloud na naka-host sa Amazon cloud at ang Google cloud at nagbibigay kami ng teknolohiya tulad ng Hadoop, Hive, Presto at isang grupo ng iba na dapat kong pag-usapan, lahat sa isang paraan ng turnkey upang ang aming mga kliyente ay maaaring lumabas ng ang lahat ng pagkalito sa malaking mundo ng imprastraktura ng data o lumabas na aktwal na nagpapatakbo ng isang imprastrukturang ito at talagang nakatuon sa kanilang data at mga pagbabagong nais nilang gawin sa kanilang data. Kaya, iyon ang tungkol sa Qubole.

Sa mga tuntunin ng mga nasasalat na benepisyo, isang paraan ng pag-iisip tungkol sa Qubole, alam mo, siyempre ito ay isang turnkey, platform ng serbisyo sa sarili para sa malaking pagsusuri ng data at pagsasama ng malaking data na itinayo sa paligid ng Hadoop, ngunit higit sa panimula, kung ano ang ginagawa nito, ikaw alamin, para sa lahat ng mga malalaking makina ng data tulad ng Hadoop, Hive, Presto, Spark, Chartly at iba pa, dinadala nito ang lahat ng mga pakinabang ng ulap sa mga malalaking makina ng data at ilan sa mga mahahalagang manifests na nagdala mula sa Ang pananaw ng ulap ay, alam mo, ang paggawa ng mga imprastraktura na umaangkop at sa pamamagitan ng pag-adapt, ang ibig kong sabihin ay parehong maliksi pati na rin nababaluktot sa mga workload na pinapatakbo sa alinman sa mga engine na ito at gumagawa din ng mga makina na mas maraming serbisyo sa sarili at pakikipagtulungan sa kamalayan na, alam mo, ang Qubole ay nagbibigay ng mga interface kung saan maaari mong gamitin ang mga partikular na teknolohiyang ito hindi lamang para sa iyong pag-unlad o, alam mo, mga gawain na nakatuon sa developer, ngunit kahit na ang iyong iba pang mga analyst ng data ay maaari ring simulan ang pagkuha ng mga pakinabang ng mga teknolohiyang ito sa isang serbisyo sa sarili interface.

Kumuha kami ng maraming, alam mo, nauugnay sa partikular na ito, alam mo, webinar, alam mo, ito ay isa sa aming mga pananaw tungkol sa kung ano ang mga pakinabang ng ulap na dinadala ng Qubole sa malaking data. Kaya, kung gumawa ka lamang ng isang paghahambing sa pagitan ng kung paano mo patakbuhin, sabihin, Hadoop at hayaan itong magtrabaho sa isang pre-premyong setting, sa isang premyo, lagi kang nag-iisip sa mga tuntunin ng mga static na kumpol, alam mo, ayusin mo ang iyong mga kumpol, maaari mong sukat ang mga ito sa iyong paggamit ng rurok at panatilihin mo sila doon at pagkatapos kung kailangan mong baguhin ang mga ito pagkatapos ay kailangan mong dumaan sa isang buong proseso ng pagkuha, ng paglawak, pagsubok at iba pa. Ang mga pagbabago sa Qubole na sa pamamagitan ng paglikha ng mga kumpol nang lubusan sa hinihingi, ang aming mga kumpol ay ganap na nababanat, ginagamit namin ang mga bagay na nakaimbak mula sa ulap upang aktwal na mag-imbak ng data at ang mga kumpol ay bumubuo at, alam mo, ang mga ito ay nagmula sa batayan ng kahilingan na nabuo ng ang mga gumagamit at umalis sila kapag walang hinihingi. Kaya, ginagawa nito ang imprastraktura na higit na maliksi at nababaluktot at umaangkop sa iyong mga workload.

Ang isa pang halimbawa ng kakayahang umangkop ay, alam mo, ngayon ay maaaring nilikha mo ang iyong mga static na kumpol dito, alam mo, na may isang tiyak na pag-aalala sa trabaho at kung nagbago ang iyong mga kargamento at ang iyong imprastraktura ngayon ay kailangang ma-upgrade, marahil kailangan mo ng higit pang memorya sa iyong mga makina at mga bagay na ganyan. Muli, alam mo, ginagawa ito sa ulap sa pamamagitan ng Qubole halimbawa, ginagawang simple. Maaari kang laging magrenta ng bago, iba't ibang uri ng mga makina at, alam mo, kumuha ng mga kumpol, 100-node na kumpol at tumatakbo sa loob ng ilang minuto kumpara sa mga linggo na kailangan mong maghintay para sa on-premyo na Hadoop.

Ang iba pang mga pangunahing bagay na kung saan ang Qubole ay naiiba ang sarili mula sa nauna na ang Qubole ay mahalagang, bilang isang alay ng serbisyo, kaya lahat ng mga tool at imprastraktura na kailangan mo upang maisama ang serbisyo, hindi mo kailangang … kung saan man sa premyo, alam mo, pangunahin mo ang software, kailangan mong patakbuhin ang iyong sarili, kailangan mong isama ito sa iyong sarili at gawin ang lahat ng mga benepisyo na iyon, ang lahat ng mga pakinabang ng modelo ng SaaS ay isang clue sa, alam mo, kung paano Nag-aalok ang Qubole ng malaking data kumpara sa pagpapatakbo ng Hadoop on-prem sa iyong sarili.

Ang slide na ito ay karaniwang sumasaklaw sa aming arkitektura. Siyempre, batay sa ulap, inimbak namin ang aming data sa mga bagay sa ulap sa ulap, Google cloud at Google Compute Engine o Amazon Web Services. Kinukuha namin ang lahat ng mga proyekto ng ekosistema ng Hadoop at sa paligid na iyon, kami ay nakabuo ng susi ng IP sa paligid ng pag-scale ng auto at pamamahala sa sarili, nakagawa kami ng maraming pag-optimize sa ulap upang gawing maayos ang mga teknolohiyang sangkap na ito sa ulap na, alam mo, ang imprastrakturang ulap ay ibang-iba mula lamang sa pagpapatakbo ng mga bagay sa hubad na metal at isang buong grupo ng mga konektor ng data upang paganahin ang data na ilipat at papasok sa platform na ito. Kaya, na kinukumpara ang platform ng ulap at nagbibigay-daan sa, alam mo, iyon ay isang susi … ang pangunahing tampok doon ay kung paano gawin ang lahat ng serbisyo sa sarili upang hindi mo na kailangang magkaroon ng isang malakas … hindi mo Mayroon kaming isang napakalaking footprint ng pagpapatakbo habang nagpapatakbo nito, ngunit itinatali namin na kasama ng aming data ng workbench kung ito ay mga tool para sa mga analyst, kung ito ay mga tool sa pamamahala ng data, kung ito ay mga templating tool, at iba pa at iba pa upang ikaw ay ay maaaring magdala ng mga benepisyo ng teknolohiyang ito, hindi lamang sa mga nag-develop, ngunit ang iba pang mga gumagamit ng negosyo at pati na rin ang negosyo. At siyempre, itinatali din namin ang platform ng ulap na ito sa mga tool na maaari mong magamit ng mga tao kung ito ay, alam mo, mga tool sa paggamit o lamang ang Tableau o kung gumagamit sila, alam mo, mas maraming uri ng data ng pangangalakal ng data ng mga produkto tulad ng Redshift at iba pa at iba pa.

Ngayon, ang serbisyo ay tumatakbo sa medyo malaking sukat, pinoproseso namin ang tunay na malapit sa 40 petabytes ng data bawat buwan ngayon sa kabuuan ng aming client base. Ang aming mga kumpol ay nag-iiba sa laki mula sa mga kumpol na 10-node hanggang sa mga kumpol na 1500-node at, alam mo, sa mga tuntunin ng saklaw na sukat na maaari naming iproseso at sa pamamagitan ng malaki, hanggang sa abot ng aking kaalaman, tumatakbo kami marahil ang ilan sa pinakamalaking mga kumpol sa ulap hanggang sa Hadoop ay nababahala at pinoproseso namin ang halos 250, 000 virtual machine sa isang solong buwan sa aming mga kumpol. Alalahanin, ang aming modelo ay kumpol na hinihingi, na may napakalaking benepisyo sa mga tuntunin ng pagbabawas ng iyong mga pag-andar sa pagpapatakbo pati na rin ang pagpapabuti ng iyong at iba pa.

Sa wakas, alam mo, isa sa aming, alam mo, ito ay isang sampling lamang kung paano nagbago ang Qubole sa iba't ibang mga kumpanya. ay isang halimbawa ng aming kliyente. Nasa ulap na sila, nagpapatakbo sila ng Elastic MapReduce sa ulap, halimbawa, at ang paggamit ng data doon ay medyo napilitan. Magkakaroon sila ng tungkol sa 30-kakaibang mga gumagamit na maaaring magamit ang teknolohiyang iyon. Sa Qubole, nagawa nilang mapalawak iyon sa higit sa 200-kakaibang mga gumagamit sa kumpanya na nakakita ng pagpapalawak ng mga malalaking kaso ng paggamit ng data at nadala talaga, alam mo, kung ano ang tinatawag namin na kahulugan ng isang maliksi malaking platform ng data at na ito ay naging tunay na sentral sa maraming ng kanilang mga pag-load sa analytics.

Kaya, lamang upang isara, alam mo, iyon ay isang maikling panimulang aklat sa Qubole. Mahalaga, ang aming pangitain ay kung paano namin gumawa ng mga negosyo na mas maliksi sa paligid ng malaking data at mahalagang, naikot namin ang mga benepisyo ng ulap at dalhin sila upang madala sa malaking teknolohiya ng data sa paligid ng Hadoop upang ang aming mga kliyente ay maaaring magamit ang mga pakinabang ng liksi at mga benepisyo ng kakayahang umangkop at ang mga benepisyo ng kalikasan sa paglilingkod sa sarili sa ulap upang maging mas epektibo sa kanilang mga pangangailangan ng data. Kaya, titigil ako doon at ibabalik ito kay Eric.

Eric Kavanagh: Alright. Iyon ay mahusay na tunog at ngayon, ibibigay ko ito kay Mike Miller ng Cloudant. Mike, ipinapasa ko sa iyo ang mga susi ngayon. Mag-click lamang sa slide, dito ka pupunta. Kunin mo na.

Mike Miller: Mukhang mayroon akong mga susi. Kaya, hihingi ako ng paumanhin. Nawala ako … Sa palagay ko nakalimutan kong ipadala ang ilang mga font sa aking pagtatanghal. Kaya, sana ay tumingin ka sa nakaraan at isipin na maganda ito. Ngunit, oo, masaya ito. Mayroon akong mahabang listahan dito, mga nakakatawang bagay na narinig ko na isinulat ko na sabik akong bumalik sa iyo sa panel. Kaya, susubukan kong makadaan nang mabilis.

Kaya, nagsisimula ako sa Cloudant. Ang Cloudant ay isang database bilang isang serbisyo, aming cloud provider at sa totoo lang, wala akong bagong logo. Kami ay nakuha ng IBM hindi masyadong matagal. At gayon, kami ay … Pinag-uusapan ko ang aming serbisyo at partikular na nakatuon sa pagsisikap na gawing madali ang aming mga gumagamit at customer sa isang medyo kakaibang paraan kaysa sa nakaraang nagsasalita.

Nagbibigay ang Cloudant ng database bilang isang serbisyo at iba pang mga serbisyo na nauugnay sa data para sa mga taong nagtatayo ng mga aplikasyon. Kaya, nakikipag-ugnay kami nang direkta sa mga developer at nakatuon kami sa data ng pagpapatakbo o OLTP kumpara sa mga analytics na narinig namin mula sa Ashish. At ang punto doon, ang buong halaga ng Cloudant, na maaaring masira sa pagtulong sa aming mga gumagamit na gumawa ng higit pa at sa gayon ay magtatayo ito ng mas maraming mga app, lumalaki nang higit pa at makatulog nang higit pa. Pag-uusapan ko ang mga ito sa isang maliit na detalye, ngunit ang pangkalahatang ideya dito ay kung ikaw ay isang gumagamit, alam mo, ikaw ay nasa isang negosyo ng negosyo, nagtatayo ka ng isang bagong aplikasyon, pagdaragdag ng isang tampok sa umiiral na application o web mobile startup, dapat kang tumuon sa iyong pangunahing kakayahan. At dati, marahil hanggang sa isang dekada na ang nakalilipas, ang IT ay maging isang kilalang-kilala, alam mo, kumpetisyon, pasensya, mapagkumpitensyang pinsala kahit na ang pagpapatakbo ng isang database ng mabuti upang maging isang kalamangan sa kompetisyon. Nakahinga na matapos ang mga araw na iyon! At sa gayon, ang paraan na talagang sinubukan nating magtrabaho sa aming mga gumagamit ay hikayatin silang gamitin ang mga composite services, modular, reusable, composible sa ideya na binabawasan ang oras sa marketing, pinatataas ang scalability. At ang pangkalahatang ideya dito ay ang ulap ay hindi lamang, alam mo, isang bagong bagay na itinulak sa mga gumagamit, ito ay talagang isang merkado … ito ay isang ebolusyon sa merkado dahil ang paraan ng pagbuo ng mga aplikasyon, kumonsumo ng mga aplikasyon, ang mga aparato kung saan sila tumatakbo at ang laki ng data ay nagbabago ng radikal sa huling 5-10 taon. Iyon ay talagang nabigyang diin ang umiiral na arkitektura ng aplikasyon para sa pagbuo ng mga app pati na rin ang pakikitungo sa data na iyon at mga analyst na workloads sa offline. At sa gayon, binubuksan nito ang isang buong stream ng pagkakataon.

Kaya, ang Cloudant ay isang ipinamamahaging database bilang isang serbisyo at natatangi ako, naniniwala ako, sa umpisa nito na talagang ipinadala ito ng isang mobile na diskarte mula sa simula, at pag-uusapan ko ito nang detalyado, ngunit ang ideya ay ang pagsulat ng mga aplikasyon ngayon, hindi ka ba sumusulat para sa isang solong platform, di ba? Sumusulat ka para sa isang bagay na maaari kong magpatakbo ng isang petabyte scale sa ulap, mayroon din itong magagawang tumakbo nang maayos sa isang desktop o sa isang browser at higit pa at higit pa nakakakita kami ng mga bagay, nagkakaroon kami upang tumakbo sa isang mobile device o isang aparato na konektado sa semi o nakasuot ng aparato o isang bagay na tinutukoy namin bilang IOT. At sa gayon, sa palagay ko, alam mo na, ang mga aplikasyon na maaaring makitungo nang maayos at magamit ang iba't ibang mga kliyente ay hindi kapani-paniwala na mapagkumpitensya sa merkado at kung ano ang susubukan nating gawin ay gawing simple para sa mga tao sa iisang API sa iisang programming model na isulat, sa pangasiwaan ang data sa lahat ng iba't ibang mga aparato na may iba't ibang sukat. The interesting thing is, you know, initial uptake in web and mobile, this is where we saw our big subtraction, but even now before the acquisition, we are seeing larger and larger number of enterprise users even in things as what I say as conservative as fidelity investments, right, working with a virtual building, a virtual safe deposit box. So, I think that this market is actually taken off much faster than even we had expected.

Let's talk about cloud and a little bit more and then turn it over. The idea here is that we really make it easier for you to build more and use a service like Cloudant to store the database state of your application and then move that to your different devices and keep things in sync and start contrast on how you build application, traditional stack or you have to buy servers like we heard about before, where you have to provision those and install license things. With Cloudant, we try to make easy. All the data that you will need, all the search services, database, etc. for your application can be acquired by signing up and getting a single endpoint URL and then starting to use that URL. The idea being that, that is a service that uses multiple indexes, some multiple technologies underneath, some proprietary and many open source, but we use them together in a way that the end developer or product team needs to build something. And so, database analytics, very different than they did it in inception where you would have, you know, rows and columns to store business ledgers, now we need to start JSON documents that generally happens over HTTP or using existing open-source APIs and then finally, we give you the things that database should do like a primary index and secondary indexes for, you know, retrieval and LTT and then driving application logic. But in addition, there is a wide range of things like search, geo-special and replication between devices that are very important. So, that's all provided underneath our API.

But, the really distinguishing thing that allows our users to grow and, for instance, why Samsung was one of our earliest and biggest customers is that, you know, Cloudant now is underneath cluster. Each cluster shares enough architecture of three to hundreds of nodes, but we run those in over 35 data centers now globally so that there is always a place for you to store your data within a millisecond of any other cloud provider or most existing data centers. So, one of the big early things that we are challenging in the cloud as well, is how do I split a hybrid architecture for my application service maybe here and my database servers maybe someplace else that will never work. They have to be on the same machine or in the same place. Well, the reality now is that by cobbling together different cloud providers, and this is something that we still do as an IBM company, you can make sure that your database is always within a millisecond of any other place and we take care of the peering agreements and just take down with the cost off the table, something that we worry about. So, Cloudant is really a database as a service, but you can think of it more like a CDN like for your database for data that changes, you know, on millisecond time scale.

And really, finally, I think the major selling point is if you build an application that's successful, you have to decide as an organization whether or not if you want to then grow the 24x7, 365 globally distributed, you know, operation team that it takes to run that at the large scale to whether that's something that now is commoditized as well. And so we focus very heavily on helping on-board new users and new customers and help them make the jump to the cloud and build architectures that use cloud analysts and works everything in a very coherent and scalable way so that is the end, you know, our users focus on building applications and not on surviving their own success.

And with that, I will just say thanks, skipped over some slides that were skipped and I will turn it back over to Lawrence.

Eric Kavanagh: That is fantastic. So, Lawrence, let me hand you the keys to the WebEx here. Just give me one second. There you are. Keys being transferred. Just click on that slide anywhere and use the down arrow.

Lawrence Schwartz: Great! Well, thank you for the handover and, you know, thanks to all the presenters today. Nice way to set everything up and there will be a lot of things to talk about it as I get through with the presentation here. So, again, I am Lawrence Schwartz. I run marketing over at Attunity and, you know, want to talk about some of the issues that we see and then some of the challenges in the space that we are in.

So, a quick overview and introduction to Attunity as a company and who we are. We focus on moving data. So, we talk about moving any type of data anytime, anywhere and enabling that for users. We are a public company based out of the Boston area, or near Boston, and when we talk about the cloud, we have some great relationships, we are part of the AWS network, a big data integration partner, and we have been close to them since the launch of their Redshift, even working with them before that. We have gotten some nice recognition for the work that we have done and as a company, we are in over 2000 places use Attunity, and we are in half of the Fortune 100 companies. So, we got some good experiences.

As you can see on kinda of the bottom of the slide here, a big issue is you've got data that's generated from all different types of sources these days from traditional, you know, CRM systems, all different places on the Internet, all the different places where data could start and then it has to go to places to be analyzed, to work with and to be looked at and we spoke if, you know, getting the data, you know, where it needs to be. So, I am gonna talk about our solutions that we do specifically on the cloud and when you think about that, often times the data, we have somewhere on-premise. So, besides having relationships with places like Amazon, we have very close working relationships with places like Teradata, Oracle, and Microsoft, all the places where data traditionally existed on-premise.

So, when you think about this, you know, and I think it was Eric who, you know, talked about on-boarding is the key to the whole process, right? I have been thinking about the issues to getting data on a system. Now, we are just some of the bottlenecks that exist today and when you look at the people moving data into a data warehouse or a database and to the cloud, we can see a lot of time is spent on what's called the ETL process, the extraction, transformation and loading of the data from where it resides to where it needs to go. If you think about getting the value on the data, that's not where you want to be spending your time and efforts, that's not the most productive area for a data scientist. And the flipside to that is this - very few people who are very satisfied with that process. It's no less than 20 percent. We really find that to be a big process. So, there is the real kind of painpoint bottleneck, if you will, in getting to the cloud and doing that type of on-boarding that people need to do and there's even, you know, real performance issues, you know, you could look at how do you get stuff into the cloud and if you want to get, you know, a couple of terabytes into the cloud, you could certainly ship it to the cloud and there are still places that do that with larger data sets, or a lot of the traditional methods, just don't have the performance to get their to do that. So, it's a real, you know, painpoint in the marketplace as people think about how do they get and how do they move onto the cloud.

So, if we step back in and look at what that means or why that's there and, you know, how this has come about, you know, both Eric and Gilbert talked about the fact that, you know, the data that's on there today, that exists today, you know, on-prem is here to stay, you know, cloud is here to stay. So, that integration becomes all the more important and often times, people fall back on the tools that they have to move over data. Again, there is a lot of ETL or traditional tools out there to kinda move data over in batches, but there's a lot of issues with that. People find that traditional ways of moving data are very time and resource intensive to set up. They often require a lot of scripting, even if they are autonomous in some way, a lot of people, a lot of manpower. There's so many sources and targets, particularly on-premise today to move it into the cloud, you know, all the systems I mentioned earlier, Oracle, Microsoft, Teradata, some managing that whole part of it. And then, you know, looking at the performance as it moves over, being able to have the tools to make sure everything is building quickly, there is a lot of thought systems that exist today aren't well built for that.

And then lastly, a lot of the way people think about moving data is kind of done in the batch process and if you are thinking about trying to do more in real time, that's not the most effective way, kind of using stale data that's not interesting to the organization. So, when you look at what Attunity does in this stage and how we think about it is, it's a different architecture that we are focused on, we really built this from the ground up and thought about when you have to go from Pentaho open-source database out to the cloud, how do you make sure that it's very easy and straightforward to do? So, that requires rethinking, how you do the monitoring and kind of set up for. It's making the whole thing just kind of a couple of clicks to get started. It's really thinking about the movement and optimizing the performance over the channel and working with just a wide variety of platforms because a lot of big organizations kinda have the best degree approach and a lot of different types of databases or data warehouses are ready in their environment. So, you have to think about it differently. You can't just do an extract, you know, dump the data out to some sort of information loaded somewhere. You have to kinda think about the architecture change, how you do the processing, do it more in memory and focus on a more performance version.

So, what does that mean and what does that look like? So, one key tenent to get to the problem with the cloud is, that things have to be easier to set up. You know, that screen there, it's just some screenshots from how we do it, but it's, you know, 1, 2, 3, kinda pick your source and target, pick what you want to do, you want to do one time CDC and then just go. It needs to be no harder than that, you know? I know we just, you know, saw the presentation from Mike and he talked about how easy it was for people to get started with Cloudant. It's the same type of thing, you have to deal with, kinda get going in a few steps otherwise you will start losing the value of it. When you think about the monitoring and control of it, there are some great companies out there, I know you're familiar with, like Tableau and others, who have done a great job in visualizing the end product of data and how to do it. But, you know, being able to visualize the movement process, the management or where's the data set on-premise, in the clouds and moving over, is there a lag, there is a vacancy. Having that viewpoint is critical and that's an important part of moving forward.

Another aspect that becomes important is the performance. You can't just rely on the standard FTP kinda two-way protocol that people have been using for years. As you move more and more data over, you have to have optimized, a file-channel protocol that is geared more towards, you know, one-directional movement most of the time after we think about how you break up tables and ship them out and move them over and you have to give people the flexibility to do that, otherwise you can't get it there in time and if you do that differently, think about it differently, you can get a 10x performance, but you have to rethink the technology.

And then lastly, as I mentioned earlier, you know, you have got a lot different places that databases exist today. So, you got to be able to work with all those and offer the widest kind of amount of support so that people can get onto the cloud. So, what does that mean for users and, you know, and those who are out there who wanted, two kind of quick cases of how people had challenges getting to the cloud, see the value, but then are able to do that if they have the right toolset.

So, one company that we work with, Etix, they do online ticketing, major provider in this space and I know Robin talked about data center offload is kind of a key in this case for the cloud. This is exactly what they are trying to do. They were trying to load and sync their data from Oracle on-premise to Redshift and do that in a timely fashion. And the interesting thing is, you know, go back to what Gilbert said, you know, it's really tough about on-boarding being an issue. They could see the intrinsic value of Redshift, they could see the cost savings, they could see all the advanced analytics that they quickly start doing that they continue for, they knew that value, but there was a roadblock to getting there. In this case, they looked at it and said, "Well, I see the value of Redshift, but it's gonna take them, you know, three months, development effort and time and, you know, maybe hiring the DBA and doing all this extra work to get there." So, there is a real block in the path to do it. Once you have the right toolset to do that, the right data integration capability to do that, they were able to go down from, you know, months of planning to literally just get going in minutes, and that's again lowering that barrier of getting people onto the cloud, we need to have the right capabilities to deliver on the promise.

The last, you know, slide I have here, and kind of another use case is, you know, we've worked with other companies, Philips, you know, well known in many spaces, we work with their health-care division and again, they were trying to go from an on-premise source over to Redshift, in this case SQL Server, and they knew the value, they knew all the analytics, they could do on it and they had done some testing on it, but they saw that without having the right tools, this is something that was gonna take them, you know, weeks and they had been spending actually weeks spinning their wheels and trying to get things moved over once they had the right tools that simplify, get it moved over quickly, they were able to go down and start loading in less than an hour, you know, over 30 million records. So, the real time went from couple of months to about two hours for them. And then they were able to do the things that they wanted to do. They didn't have to focus on the data loading, they could focus on the operational support. They got a much better matrix for all these care, cost and operations. So, you think about the whole challenge, you know, we design that spaces, enabling the data movement and now more than ever with the cloud when you think of it being kind of a remote place to pick your data, you know, this becomes an area that, you know, more and more people need to solve, to take advantage of what's out there. So, that's an overview of what we do and with that I will pass it back to you, Eric.

Eric Kavanagh: Okay. That sounds great. We've got a good amount of time here. We'll go a bit long to get to some of your good questions, folks. So, feel free to send your questions and I've got a few questions myself.

Lawrence, I guess I will start off with you. You guys have been in this space of kinda supercharging the movement of data for a while and you have been watching the cloud very carefully and I've really been kinda surprised at how long it's taken major enterprises, Fortune 1000 companies to fully embrace cloud. I mean, there are, of course, pockets of severe interests, let's call it, in large organizations, but as a general rule, there's been a bit of a reluctance that is only starting to wane in the last year or so, at least from my perspective, but what do you see out there in terms of cloud adoption and readiness of the enterprise to use cloud computing?

Lawrence Schwartz: Sure, I think you are right. It has been a significant change and it's certainly taken time, you know, they have that joke about, you know, that successful - overnight sensation - or really overnight success, that really takes years in the making, and that's been true for the cloud, right? It's… you have seen that kick in the last year, but it's due to all the hard work of a lot of players like Amazon who have been doing this for years, you know, to get the service adopted, the kind of, you know, prove the metal and there's, you know, failures and problems to give the diversity and flexibility that they have, that's something that Redshift offers. So, I think the maturity has gotten there, the confidence has gotten there, you know, the… I think it's infiltrated into a lot of companies through small areas, you know, small use cases, small trials, kind of outside that kinda IT control and with that, you know, those successful kind of periphery projects have proven now, there's now more of a willingness to have the conversations about how that spread. And frankly, you know, there's been additional tool that has, you know, have also come out to make these easier, like what we do and, you know, there is that, not just move the data, but show the value of BI in the cloud, and showing that.

So, it's, in one way, it's an overnight or a big uptick in the last year, but a big part of that's been all the hard work of building up to that. So, now we as a company see a lot more adoption. It's as a business for what we do, it's grown quite a bit and the cloud, you know, we do a lot of on-premise to on-premise movement. Now, cloud shows up in a lot of the conversations as, you know, real business cases, real offloading cases out where a year ago was certainly, you know, just more exploratory. Now, they have got real projects to move. So, it's been nice to see that movement.

Eric Kavanagh: Okay. Great. And Mike Miller, you had mentioned that you heard a couple of provocative statements that you wanted to comment on, so, by all means, what do you find interesting or what do you wanna talk about?

Mike Miller: Oh, I think Robin, he made a point, his second-to-last slide contrasting where innovation counts. The cloud will always be second best and I'd love to hear a little bit more about that because in my mind, if I was thinking about building, you know, an application or some new service, it's hard for me to think that my organization, no matter what they are, really wants to go engineer-to-engineer with Google, Amazon, IBM, Microsoft. So, I think maybe I misunderstood his point with that.

Eric Kavanagh: Interesting. Robin, Mike has thrown down the gauntlet. Ano sa tingin mo?

Dr. Robin Bloor: Well, I mean the point here is that there are a number of situations that I've come across which… where people have gone into the cloud and walked back out and the reason they walked back out was, you know, when it came to actually having emotionally, this was performance driven, but the performance was actually the crux of the application is being built as they couldn't get the low latency they wanted and the cloud was of no use to them. And, you know, the situation was that, you know, actually going into the cloud, even if they were given the ability to measure behavior of the networks for them in the cloud and that workloads in the cloud with something they had absolutely no control over, and because of that, they couldn't create the tailor-made services that they were looking for, and that's a performance edge. I don't think there's anything in terms of, you know, coding that's going to be constricted, what you can do in the cloud. It's service level, it's a constriction… if that's part of where your critical capability is going to be, then the cloud is not going to be able to deliver it.

Mike Miller: Right. The… So, I appreciate that clarification. I do agree, actually, that transparency is one of the big things that here as desire right now from users across many different providers. So, I think you raised a very fair point. When it comes to performance, I think that traditionally it has been very hard to, you know, to go to a cloud provider or any given cloud provider and find exactly the hardware you are looking for, but it will noting kind of the upping the ante in the race to basically free storage between Google and Amazon and other competitors that it is and I think you see the pressure that puts on driving on the cost of SSD, flash, etc. So, I think that's a fun one to watch going forward.

Dr. Robin Bloor: Oh, absolutely correct, you know? I mean, I think there's one of the things that is actually happening is that the second wave is coming on. The first wave was this, you know, this wonderfully tailored services as long as, you know, it's a little bit Henry Ford; you can have it recolor as long as it is black, but, you know, even so, extreme reduction in certain kinds of costs of having the data center. Or, the second thing that happens is, having actually built these huge data centers out, they start these cloud operators, suddenly start discovering things that you can actually do. You couldn't do before because you didn't have the scale. So, there is, I think, a second wave which, to a certain extent, is going to make the cloud even more appealing.

Eric Kavanagh: Okay. Mabuti. Let me go ahead and bring Ashish as I am gonna go ahead and throw up your architecture slide here. We always love these kind of architecture slides that help people wrap their heads around what's going on. I guess, one thing that just jumps out at me is, of course, YARN. We talked about that on yesterday's briefing. YARN is not a small deal. For those of you who aren't familiar with this concept, it is "yet another resource negotiator." It's, really it's a very interesting development because what happened is in the Hadoop movement, YARN is kind of replacing the engine really, if you will. Our speaker from yesterday will refer to it as the operating system. It's like the new operating system of Hadoop, which of course, consists of the hybrid distributed file system underneath, which is basically storage when you get right down to it, and then MapReduce is what you used to have to use to use HDFS. MapReduce is an absurdly constraining environment in terms of how you get things done. So, the purpose of YARN was to make HDFS much more accessible and make the entire Hadoop ecosystem much more flexible and agile. So, Ashish, I am just gonna ask you in general, since you are mentioning YARN here, I am guessing that you guys are YARN compliant or certified. Can you kinda talk about what… how you see that change in the game for Hadoop and big data?

Ashish Thusoo: Yeah, sure. Ganap. So, I think, you know, there are two parts to… So, let me first talk about, you know, why YARN was done and then talk about how that potentially changes the game and what's fundamentally still is the same, you know, where it doesn't change the game. I think that's an important thing to realize also because many times you, you know, you get caught up on this hype of say, this is the new, shiny thing and, you know, everything is going to, you know, all the problems are going to go away and so on and so forth. So, but the primary thing is that, you know, the strength and the weakness of the MapReduce API was that it was a very simple API and essentially, any problem that you could structure around being a sorting problem could be represented in, you know, that API. And some problems are naturally, you know… can naturally be transformed into that and some problems, you know, you sort of, you know, once you have just MapReduce at your disposal then you try to fit into a sorting problem.

So, I think the latter is where YARN plays a role by expanding out those APIs by, you know, being able to compose, you know, maps and reductions and, you know, whole bunch of different types of APIs in terms of how the data can be distributed between these two stages, and so on and so forth. You just made that API that much more richer. So, now you have at your disposal, different ways of solving that same problem, right? So, you just don't have to, you know, be constrained by the API and the problem gets solved one way or the other like, you know, if you are, you know, trying to do an analytics, you know, workload, you can express that in MapReduce, you can express that in YARN. The big difference that happens, that starts to happen is, you know, in terms of, you know, the performance matrix that you start seeing, you know, once you start, say programming to YARN and in some cases, a newer set of things, for example, streaming analysis and so on and so forth starts becoming a reality when you start, you know, doing that, you know, those things in YARN.

So, those are the differences that, you know, that thing has brought into the ecosystem. I think it's much, the richness there is much more on the API side as opposed to it being another resource manager, especially in the cloud context. If you think about it in cloud context, the resource manager is actually your… the VMs that you bring up, you know, you have virt… you know, it's not necessarily… Again, this is a big difference between say, on-prem how you are running Hadoop clusters and how you are running in the cloud then, you know, you have like the constrained static set of machines, you want to distribute those machines amongst different resources and they were used for YARN there. But, in the cloud, you know, you can bring up machines left and right. And so, just from the perspective of being a resource manager, it probably doesn't have that, you know, that bigger need and specifically in the cloud, but from the perspective of providing these, you know, richness of APIs which allow you to, for example, the Hive is initiative they can now program Hive to not just to use MapReduce, but have much more richer plans of doing jobs and things like that. It brings those benefits to the ecosystem. I think that is where the true value of YARN belongs. And in the cloud context, definitely, it's not that interesting from the resource management point of view, but it's much more interesting in terms of what it enables other projects to do, in terms of, you know, workloads that now, it now can be used to be programmed on to your data or the previous workloads that can be done in a much more efficient way.

Eric Kavanagh: Right.

Ashish Thusoo: I had, you know, one more just, you know, adding to Mike, you know, there was another provocative thing which was said which is around and, you know, which was around, hey, treating the cloud as yet another data center. I think you… you know, that is one point of view which most companies, you know, look at and say, okay, you know, that's the easiest point of view actually to look at saying that, okay, you know, this is, you have bunch of machines on your, you know, you have compute, you have storage and you have networking on your on-prem data center and cloud provides the same thing out there. So, I am just going to do exactly the same thing that I am doing on my own on-prem data center and do the same thing in the cloud and viola - that's how it should work. What we have found out, you know, having been running the clouds for, the two clouds where, you know, you have the ability to provision VMs within a minute, the ability to use a highly scalable objects to store data and things like that. We have found that cloud actually, the cloud architecture and these inherent abilities actually enable different ways of doing things, you know, and this is what I have talked about in my slide as well, you know, the whole notion of… in just, you know, in… the perspective of just Hadoop, the whole notion of just running the static cluster versus on-demand dynamic clusters, that is something that you don't see happening in an on-prem data center, you know, versus, you know, true cloud where the, you know, there's a enough capacity to be able to support these types of workloads.

And so, I think there is definitely some shift needed. You know, the big fear for me is that if you just treat cloud as yet another data center, you actually… while you, you know, there are lot of other benefits, but there are lot of intrinsic benefits that you might ignore if you, you know, start doing that, security is another one, the way you deal with security and the cloud, there's a lot of differences in terms of how you would deal with, you know, in… from on-prem perspective and so on and so forth. Just wanted to add that in, from my perspective.

Eric Kavanagh: Sure. Oo. Walang problema. We have one attendee asking about various types of use cases like logistics and specifically HR, so I threw up this website of Workday, wanted to make a couple of comments on that, and then Gilbert, maybe I will bring you in to comment on the whole concept of architecture. So, in terms of HR, I actually heard a rather well, I will call it, let's say comment from an analyst a couple of months ago, a few months ago I suppose, about going to the cloud for Human Resources. I have been doing some research on this to know lot of HR-type functions are being outsourced to the cloud, certainly stuff like payroll is fairly easy to outsource these days, benefits programs and insurance, that kind of thing, but there is a real serious caveat to keep in mind and Gilbert, this is what I want you to comment on from an architectural perspective, which is you have to be very careful about when you are moving to the cloud for some kind of critical business service because you either want to be very strategic and very thoughtful, meaning you go through the process of making sure that you understand what's going on in the cloud and what's staying on-premise, and there is the folk from Attunity will tell you that truly one of the things they specialize in is making those connections such that they provide the kind of connectivity you need because what's happening with some organizations is they go and they will use Workday for example, to put some of their HR stuff to the cloud, but they don't do it all or they don't do enough or they don't think through it enough, and what happens then? Then they want to happen to manage the cloud environment and their original on-premises environment as well, which means, guess what? He just increased your cost, you doubled your workload and you created lots and lots of headaches for people, and that's usually when someone gets fired and then the guy who comes in has a real mess to clean up. So, you really do have to think through the architecture of the data and the systems and the processes and make sure you dot all your i's and cross all your t's and with that, I will throw it over to Gilbert for comments. I am guessing it will be with that, but maybe not.

Gilbert Van Cutsem: Alright. Oo. So, just another example of something similar, just yesterday happened to me. So, I lost one of my doctors because he went out of business. Hindi ko alam. It sounds amazing. He was a chiropractor and he went out of business. I don't know why, but, the thing was this - I have no chiropractor and I like to go to a chiropractor, you know, occasionally. So, I find a new one and it's close to, you know, close by and all that. It's all good. And so, they go, as usual, you have to do all the paperwork and let us know if blah, blah, blah. But, the good news is we have a new system because, you know, we're on the Web now, in the cloud. It's all cool. I go like, okay, you know, and they send me a link and I have to do all the paperwork online, which is fine and I put all kinds of things in there about, kind of secret like, you know, social security numbers and that type of stuff and who I am, how old I am… all my details. I put it all there and I submit because of course, I do believe in technology.

And then I walk up to the office, the next day for my first appointment and they go like, "Did you do the form?" I go like, "Yes, Ma'am, I did." "Okay. Then we will go and find it." I go like, "Well, I did do it." And she goes, "Yes, we know because you are the fifth person today to walk in, to walk up to me and complain about that's not finding the form." And I go like, "But, you can't be serious about that. This is pretty confidential information. Where is it?" This happened to me yesterday, yeah, which brings back the whole issue and the whole idea of who owns the data really, right?

I know you move to the cloud and people get onboard it into a new system like in this case, my chiropractor and they subscribe to a new system. It's in the cloud, it's all safe, it's fully multi-tenant, they used to have it on-premise system, all the data was moved into the new system, but now apparently, they can't get it out.

Eric Kavanagh: Yeah. That's not good.

Gilbert Van Cutsem: So, I don't know where my data is and assume she gets really mad, right? She goes like, "Oh, this is impossible. I pay you money and my customers are, my patients, sorry, are unhappy and with the data is gone, I wanna get away from you. I wanna go to a different system maybe also in the cloud, right?" How do you then move the data of your patients in this case, the data your business owns, to another system? How do I get it out first of all and then load it again? I am sure ETL in the cloud is an answer somehow and we have experts on that, but it's not that easy.

Eric Kavanagh: Yeah, but that's exactly right and folks, I threw up this other slide here, this other, another screen to show you where you can find the archives. So, anytime you want to check out - oh, there's the inside of our website, I don't want to show you that. So, here is the main website and on the right column here you can see a different show. So, TechWise is right here. You click on that and on these different pages where we will actually post the archives. So, we do archive all these webcasts.

Actually, I wanna throw back over to Mike, I suppose, and then also to Lawrence to kinda comment on this story that Gilbert just told. So, Mike, there is some, kind of, now this is kind of a small-business concern. You guys are more focused on big business, but nonetheless, if a large company who works with you and they want to go somewhere else, how do you manage that movement of the data and securing the data and so forth?

Mike Miller: Yeah. Napakagandang tanong na iyon. It's one that used to come up a lot more often than it does now in sales calls, which I find to be an interesting anecdotal piece of evidence for a call. You know, I think that first of all, we are talking about a lot technologies, or at least employment models that are relatively new. This is very early in the cloud, right? We are talking about things like cloud, or in the case of data, we are talking about analytics services like Hadoop for databases and then NoSQL or NewSQL formats. You know, these are fundamentally new technologies and especially around things like, Hadoop and NoSQL, all of the ancillary services, the connectors, right, the… you know, if I want to find somebody that consults on Oracle, that's something I can find, but that entire ecosystem is just kinda spinning up right now.

So, it's getting easier day over day to say, okay, you know, give me a service that can read from 'x' traditional system, put it into Cloudant and do something with it and then put it back into 'y' traditional system, right? So, now they are very, you know, there are quite a few those things and it's actually more challenging, I think, for a typical user to understand what is the best choice, right, if I want to connect all the new technologies on-prem and then in the cloud.

So, I think as a cloud vendor, it's really on us to be very opinionated about that and to help walk users through the landscape of possibilities because the shift's a lot of new and I think that the average user, whether it's a CTO, CIO or whether it's actually developer, is coming up that learning curve fairly quickly. I think that a lot of the kind of baseline stuff is being worked out, cross-cloud connectors and, you know, taking away the really most basic worries about say, you know, bandwidth cost and whether or not you are going out on the wide area network versus staying on, you know, VPN the entire time. A lot of those things have been kinda abstracted away and what is the true promise of the cloud.

But, in general, I think you are also seeing, you know, that anecdote that we heard was, you know, something that is probably isomorphic to, you know, what will happen to your buying into a brand, you know, in a past lifetime, you know, what happens if that brand doesn't deliver, how much can I really trust that brand? I think you are seeing exactly the same thing happen in the cloud and, you know, I think that companies like Microsoft, Amazon, IBM and Google are, you know, very much stepping up and saying that there will at least be multiple pillars of trust and making sure that you are not going in with a company that's going to dry up and swallow your data, or worse, lose it or distribute it, right? And so, they are, at least, they are independable and they are anchoring, you know, the development of such ecosystem. But, I say to close, it's very early and a lot of that tooling is just getting started and, you know, I think you are going to see consulting services, you know, really putting a lot of focus on that in the very near term.

Eric Kavanagh: Yeah. That's a really, really good comment you just made there. I like that "pillars of trust" concept because the other thing to keep in mind here is you do once again have a number of fierce competitors vying for market share and for IT span, it's just like the old days all over again. Really, in the old days, by which I mean last year, you had IBM and Oracle and Microsoft and SAP and then Computer Associates and Informatica and all these companies, Teradata, etc. In the new world, now you have got, of course, Microsoft with their Du Jour, you have got Google, you have got Amazon Web Services, you know, you have Facebook in certain context. So, you have all these companies that are not necessarily so excited about working with each other, but you do have things like APIs. And so, one of the nice things that APIs really are crystallizing into the connectors that hold together the larger cloud, I suppose, and I want to throw up a slide for Lawrence to kinda comment on all this.

Yeah, Lawrence, obviously, you guys have specialized in the space for a while. So, I think you do have awesome advantage over maybe some newcomers. But, nonetheless, these are all very serious concerns because how data gets stored in the cloud is different than how it gets stored on-premise. Then I think that Mike makes a really good point that this whole space is just starting to take shape and it's gonna take a while for things to seriously fall into place and to crystallize. So, what's some advice that you have for companies that you… I guess, you basically concur with Mike, or what do you think?

Lawrence Schwartz: Yeah. I think it's, you know, what we see is when people are taking advantage of the cloud for a lot of use cases as compared to on-premise, you know, they are looking at kind of, you know, two different things. One is, they are looking at, you know, as we talked about this a little bit earlier, how do I… how does it incrementally add value to what I do, how do I, you know, how is it kind of an add-on? And so, you know, when back to when I talked about the Etix as a company where, you know, they are not moving all their operations over to Redshift, you know, yet per say, but they're saying, "I do a lot of work on Oracle, I wanna offer some of this to some kind of analytics from different environments, you know, kinda figure out, maybe do some sandbox stuff there, and, you know, and then learn about my business that way, and that way they can kind of carve out what they want, move it over there and do the work and, you know, it's less of a concern with moving, you know, everything over and all the records and whatnot. So, I think they look at that as one way that to take advantage of it with having less issues.

I think the other thing is people are also looking at these cases that are and aren't excellent fit for the cloud that are very, very hard to do in other ways. So, I will take another example, you know, we work with a company called, you know, iN DEMAND. They are video on-demand player. They do this work for Comcast and all of this and they will actually, you know, take the data that they are working with, they will take the media files and they will supply it to the cloud for doing their processing, do their processing there, and then they will consume it back for their on-premise customers. And then, you know, that gets upstairs to third parties that consume reviews. So, it's, you know, if you want to think about how the company is approaching it, it's, you know, how do I get my… how do I add value, how do I maybe not move the whole business at first, how do I get the right use cases, how do I add incremental value to what I do? And that helps kinda build about the confidence on what they are doing and as part of the process, and of course, you know, a key piece of that is, you know, making sure that they can do that securely and reliably and, you know, we make sure to the latest levels of encryption and other things to take care of that as much as we can on the transport side. But, that's how I think a lot of companies are approaching the problem.

Eric Kavanagh: Okay. Mabuti. And maybe Ashish, I will throw one last question over to you. I am just throwing up, actually, I like your architecture slide. Even this slide I think is pretty neat. So, one of the questions in, you know, HDFS of course, by design the default is to save every piece of data three times. You can adjust that, of course, you can make it twice, you can make it four times, that does provide some overhead over time, obviously, but it is a way of backing up data. Anyway, that was the whole idea, one of the key ideas, right, from HDFS originally is redundancy, is not wanting to lose data. I've kind of been wondering how that's going to affect things like replication servers, quite frankly, when Hadoop does that natively.

But, one of the attendees is asking - "Can you request physical backups like tape for your cloud data? I read of a company that had their cloud management console hacked and their data and online backups trashed."

You know, we are hearing about these breaches all the time, they are getting more and more serious, they are killing major brands like Target, like Home Depot, etc. So, security is an issue and backup and restore is an issue. Can you kinda talk about how you guys address things like backup and restore and security?

Ashish Thusoo: Yeah, sure. So, we… So, I will talk about that and talk about HDFS first. So, as far as Qubole is concerned, you know, we… since we work on the cloud, we use the objects store there to store data. So, again, this is one of the other key differences why, you know, big data service on the cloud becomes different from on-prem. On-prem, we have always talked about, you know, HDFS and so on and so forth, but if you go to the cloud, a lot of the data is actually stored in their object stores. For example, that could be an S3 on AWS, Google cloud storage on Google Cloud, on Google Compute Engine, and so on and so forth.

Now, many of these object stores have built-in capabilities of providing you things, you know, these object stores, by the way, you know, one of the big differentiators from real clouds to actually your own data center is the presence of these object stores and the reason that these object stores are cool pieces of technology, you know, they are able to provide you very cheap storage and along with that they are able to provide you things like, you know, having the ability to actually have a disaster recovery thing built in and, you know, as part of that interface, you don't have to think about it. And also, they have tiered, you know, there is tiering there as well. For example, S3 has high availability and it's online access, but it's much more expensive. It's more expensive than say, a glacier storage on AWS, which is low, you know, it gives you, you know, the turnaround time is like four hours or something like that and it's much cheaper. So, you start thinking of, you know, those types of services. I think cloud providers are essentially providing those types of services to augment the need for things like tapes and so on and so forth. And also, to provide you disaster recovery or rather, you know, replication built in into these systems so that, you know, you are protected from disasters, regional disasters and things like that.

So, that is what Qubole heavily, you know, depends upon and the great thing is that a lot of… all the cloud providers are providing this. These are fundamentally very difficult problems to solve and by being built into some of the object stores that these cloud providers provide, you know, that is one more additional reason of, you know, storing this data, you know, in some of these object stores and using the cloud for that as opposed to trying to, you know, figure out, you know, replication, running two Hadoop clusters across different, you know, regions and, you know, trying to replicate data from HDFS from one region to the other, which is doable, we did that a lot when I was back at Facebook running this stuff there, but, you know, fundamentally, the object stores in the cloud just made it that much more easy.

Eric Kavanagh: Okay. Malaki! Well, folks, we've burned through an hour and 15 minutes or so, a lot of great questions there and a lot of great presentations. Thank you so much to all of our vendors today and of course, to both of our analysts on the show today. A big thank you, of course, to Qubole, Cloudant and Attunity. We are gonna put the archive up at insideanalysis.com. I showed you where that goes, and big thanks to our friends at Techopedia as well.

So, folks, thank you again for your time and attention. This concludes Episode 3 of TechWise, our relatively new show. There is Episode 4 coming up pretty soon. It's gonna be on the big data ecosystem. So, watch for information on all that. And then till then, folks, thank you so much. We will catch up with you next time. Ingat. Paalam.