Eric Kavanagh: Dame in gospod, pozdravljeni in ponovno dobrodošli nazaj v TechWise. Ime mi je Eric Kavanagh. Jaz bom vaš moderator za Epizodo 3. To je nova oddaja, ki smo jo zasnovali s prijatelji iz Techopedije, zelo kul spletnega mesta, ki se očitno osredotoča na tehnologijo, in seveda, tukaj v The Bloor Group, se zelo osredotočamo na podjetništvo tehnologija. Torej, podjetniška programska oprema vseh vrst in celoten format TechWise je bil zasnovan tako, da je našim udeležencem omogočil resnično dober pogled na določen prostor. Tako smo na primer naredili Hadoop, v zadnji oddaji smo naredili analitiko in v tej konkretni oddaji govorimo o oblaku.
Torej, imenuje se "Oblak v oblaku - kaj, kje, kdaj in kako." Danes se bomo pogovarjali z nekaj analitiki in nato s tremi prodajalci. Qubole, Cloudant in Attunity so torej sponzorji današnje oddaje. Velika hvala tem ljudem za njihov čas in pozornost danes in velika hvala vsem, ki ste zunaj. In ne pozabite, da kot udeleženci teh oddaj igrate pomembno vlogo. Želimo, da postavite vprašanja, se vključite v interakcijo in nam sporočite, kaj mislite, ker je očitno, da je celoten namen oddaje, da vam pomagate razumeti, kaj se dogaja tam v svetu računalništva v oblaku.
Oblačni Imperative Paluba
Torej, pojdimo desno naprej. Prvi gostitelj, vaš gostitelj tam, Eric Kavanagh, to sem jaz, nato pa dr. Robin Bloor kliče z letališča, in pravzaprav bo tudi naš dober prijatelj Gilbert, Gilbert Van Cutsem, neodvisni analitik nekaj misli s seboj. Potem bomo slišali od Ashish-a Takoo, izvršnega direktorja in soustanovitelja Qubole-a. Slišali bomo od Mikea Millerja, glavnega znanstvenika pri Cloudantu in nazadnje od Lawrencea Schwartza, podpredsednika marketinga pri Attunity. Danes smo za vas pripravili cel kup vsebin.
Torej, oblak - edikt od zgoraj - to je koncept, ki mi je prišel drugi dan, ko sem razmišljal o tem. Res je, računalništvo v oblaku je prav danes ogromno. Hočem reči, resnično je fascinantno opazovati razvoj teh stvari in eden od primerov, ki ga pogosto navedem, je tehnologija samega oddajanja. Seveda ste tisti, ki ste se zgodaj oglasili, slišali nekaj zanimivih tehničnih izzivov. To je ena težava z oblakom, ali se spreminja, spreminjajo se formati, spreminjajo se standardi, spreminjajo se vmesniki in včasih, ko poskušate povezati dve različni področji skupaj, imate težave, imate nekaj težav. Torej, to je pravzaprav ena težava pri računalništvu v oblaku. Bodite previdni glede arhitekture! To lahko vidite na zadnji točki.
Ena izmed stvari, ki jo počnemo, kot pripomba pri našem spletnem prenosu, imamo ločenega prodajalca telefonskih konferenc. Nato uporabimo WebEx. Avdio WebEx ne uporabljamo, ker odkrito povedano, enkrat smo pred leti uporabljali avdio WebEx in se je zrušil in zažgal na najbolj neprijeten način. Zato tega tveganja nismo pripravljeni ponovno prevzeti. Tako dejansko uporabljamo lastno podjetje za snemanje zvokov Arkadin in v realnem času skupaj šivamo vse te različne rešitve. Ideja je, da bi vam nato lahko poslali e-pošto z ločeno e-poštno aplikacijo s diapozitivi, če bi se na primer WebEx zrušil, vsem vam povemo, da pokličete, vam pošljemo diapozitive in preprosto preberemo več ali manj brez WebExovih okolij. Torej, kako lahko odpravite tovrstne težave, ampak takšne težave so povsod.
Vendar pa je za oblake veliko koristi. Očitno je, da gre za nizko oviro za vstop, lahko pogledate, da je otrok plakatov v računalništvu v oblaku seveda salesforce.com, kar je očitno samo spremenilo poslovanje, natančneje avtomatizacijo prodajnih sil. Potem pa imate na voljo stvari, kot so Marketo in iContact, Constant Contact in Sailthru, in, na srečo milostno, kar zadeva avtomatizirano trženje in prodajo, obstaja veliko orodij, vendar to še ni vse. HR ga pripelje do celotne igre v oblaku, analitika je v igri v oblaku. Poglejte tisto malo znano podjetje Amazon Web Services, s čim se ukvarjajo z računalništvom v oblaku - prav veliko. Nekega dne sem slišal veliko citat od fanta, s katerim veliko delava z Davidom, ki je zdaj pri Ciscu konec, kot podjetje, ki je kupilo WebEx. Nisem prepričan, da so vložili toliko, kot bi želel, da imajo v WebEx, vendar to res ni moja odločitev, kajne? Ampak, danes je pri Ciscu in imel je zelo smešen, samo blazen citat, in to je, "ni enega oblaka, veliko je oblakov", in ravno to je tako. Tam je veliko in veliko oblakov. Pravzaprav je vsak ponudnik oblakov svoj oblak. Torej, eden od izzivov v teh dneh je povezati oblak, kajne? Če ste prodajna sila, ali ne bi bilo lepo, če se na primer povežete neposredno z iContact in nenehnim stikom ter s LinkedIn in morda s Twitterjem in drugimi okolji, so drugi oblaki tam le določili poslovne rešitve, ki so smiselne za vas in vaše podjetje.
Torej, to je nekaj vprašanj, ki jih morate upoštevati, toda oblak je tu, da ostane. Samo vedite, da je v zvezi s tem potrebna dodatna programska oprema, ki bo ostala. Torej, kaj moramo ugotoviti v podjetju ali kakšnih celo majhnih do srednjih podjetjih, kako definirati svojo arhitekturo in jo vzdrževati tako, da lahko vzvodite oblak, ne da bi ustvarili velikanko drugje zunaj svojega nadzora? Očitno se je celotna industrija skladiščenja podatkov razvijala okoli potrebe po konsolidaciji kritičnih informacij, da bi analizirali te informacije in sprejeli boljše odločitve.
No, zdaj Amazon Web Services ima Redshift. To je ena največjih spletnih oddaj, kar smo jih kdaj storili z Redshiftom. To je precej velika stvar. Spreminjajo dinamiko, spreminjajo strukture cen. Lahko opazujete, kako se vaše cene znižujejo na tradicionalno licenciranje programske opreme za podjetja, deloma zaradi računalništva v oblaku in deloma zato, ker ljudje tam znižujejo ceno in pritiskajo na ceno. To je dobra novica za končne uporabnike. Vsekakor je treba upoštevati vse, ki se trudijo uporabljati nekatere od teh tehnologij. Torej, nekaj je treba upoštevati in o tem bomo govorili danes v šovu.
Torej, analitik dr. Robin Bloor bo danes naš prvi analitik. Torej, šel bom naprej in mu potisnil prvi diapozitiv in mu predal ključe. Robin, mislim, da si nekje tukaj, tam si. In s tem ga bom oddal, tla pa so tvoja!
Dr. Robin Bloor: V redu, Eric. Hvala za uvod. Pred nekaj dnevi sem naletel na anketo potrošnikov, ki je postavila vprašanje - ali menite, da nevihtno vreme ovira računalništvo v oblaku? In več kot 50 odstotkov jih je odgovorilo pritrdilno. Samo pomislil sem, da vam sporočim, da ne gre, če ste eden tistih, ki verjamejo v to. In potem je malo podobno kot verjeti, da je, ko imaš sneg na televiziji, ker zunaj sneži.
Cloud, veste, ena od stvari je, da je nekakšna, veste, pomembna, če vam je všeč, preprosta podrobnost oblaka je, da je oblak na tak ali drugačen način podatkovni center, ali katera koli določena storitev v oblaku je podatkovni center. Edino je, da gre za drugačen podatkovni center kot tradicionalni oblak. Torej, nameraval bi govoriti o oblaku, da bi kot vaše varnostno kopijo podrobneje raziskovali uporabo oblaka, ker nima smisla pokrivati isto zemljo.
Torej, najprej bi rad poudaril, da je oblak storitev, veste? In ena od stvari, ki se dejansko dogaja zaradi računalništva v oblaku, je, da obstaja … no, jaz pravim smrti blagovnih znamk, cela serija blagovnih znamk programske opreme je imela ogromno moči in še naprej ima pooblastila v korporativnem računalništvu. Ko pridete v oblak, nimajo več moči, veste? Ko kupujete storitev v oblaku, vam je mar za aplikacijo, seveda vam je mar za raven storitve, ki jo bo oblak imel, ne želite, da storitev v oblaku pogosto odpove, skrbite za stroške uporabe in vam je mar za to stvari, ker je to storitev, toda tisto, kar vas ne zanima več, je, da vam ni vseeno, na kakšni strojni opremi deluje, ne zanima vas, kakšna je omrežna tehnologija, ne zanima vas, kakšen je operacijski sistem teče je, ne zanima vas, kakšni so datotečni sistemi, sploh vam ni vseeno, kakšna je baza podatkov, in to dejansko uporabljajo posebej katere koli dane baze podatkov iz oblaka, veste? In vpliv tega na nek način je, da je oblak zelo veliko blagovnih znamk programske opreme v oblaku nima prave vrednosti, ker veste, da grete v oblak tako ali drugače na nekaj, kar je storitev in ne več izdelek. Torej, mislil sem, da lahko naredim nekaj diapozitivov, da ne uporabljam oblaka, veš, in to so vsi, če hočeš, veš, krvavi preprosti, očitni razlogi, ampak nekdo jih je moral navesti, tako da, mislil, da bi.
Torej, razlogi, da ne … ne uporabljam oblaka - če ne morejo zagotoviti takšnih podatkov in upravljanja procesov, kot jih želite, veste, potem preprosto ne ustreza vašim kriterijem. Če vam ne morejo dati želene uspešnosti, ne bo zadostilo kriterijem. Če vam oblak daje prilagodljivost glede premikanja stvari, potem ne bo izpolnjeval meril. To so samo očitni razlogi, zakaj določene storitve v oblaku ne bi ustrezale ogromno ljudem, razen dela s korporativnim računalništvom.
Morda tega ne boste storili, ker lahko to storite ceneje. Oblak ni vedno najcenejša možnost. Nekateri se zdijo mnenja, ker je pogosto poceni možnost, vedno bo cenejša, ni vedno tudi cenejša. Druga stvar je, da če vzamete aplikacijo iz oblaka, se ta ne vključuje dobro s tem, kar počnete, potem verjetno ne boste šli naprej s tem in to so, veste, razlogi, da se obrnete .
Tu so razlogi za sprejetje. Veste, ena od stvari, ki jo lahko naredite v oblaku, je precej neprebojna, aktivnost prototipov. Če lahko prototirate v oblaku in jih implementirate v podatkovni center, je to povsem izvedljivo in veliko ljudi to počne. Delo lahko v podatkovni center naložite z nekritičnimi aplikacijami, ker bodo verjetno lahko našli neprimerne storitve v oblaku, ki bodo ustrezale vašemu nivoju storitev. In lahko naložite določene aplikacije, kot je prodajaforce.com, in podobne ponudbe na tiste, ki jih poznate, standardne aplikacije. Na tem področju so vsi sposobni in področje ni specializirano in, veste, tradicionalno … kar koli je na voljo v oblaku, bo verjetno tisto, s čimer greš.
Končna stvar, ki sem jo hotela povedati, je res zanimiva stvar, ko dejansko iščete oblak, je en način razumevanja le vrsta ekonomije obsega. Poanta je v tem, da zaženete podatkovni center tam in se od nekje ali drugega pokličete v ta podatkovni center in ga uporabite, zato bi bilo bolje, bolje bi bilo v glavnem ceneje, kot če to storite sami. Torej, veste, resnično gre za ekonomijo obsega.
Ponudniki oblakov izberejo lokacijo podatkovnega centra in najboljše mesto za iskanje podatkovnega centra je tik ob elektrarni, še posebej tik ob poceni elektrarni. Torej, ena elektrarna na severu, ki je hidroelektrična ali kaj podobnega. To je običajno najcenejše, veste? Tam lahko podatkovni center dejansko najdete in ugotovili boste, da je lažje. Nakupiti ljudi na takšnih lokacijah je manj drago, kot je to v središču New Yorka ali San Francisca. Celoten objekt lahko standardizirate glede na klimatsko napravo in moč. To vam bo prihranilo veliko, saj to pomeni, da lahko zanj daste celo zgradbo in to točno počnejo vsi operaterji v oblaku. Standardizirajo se na strojni opremi za mreženje, standardizirajo se na računalniški strojni opremi, ki jo uporabljajo, ponavadi so robne plošče x86, pogosto jih bodo sestavile same. Nekateri celo celo stvar gradijo. Uporabili bodo Amazonovo programsko opremo, ki jo lahko, ker to dejansko ne pomeni stroškov za njeno sprejetje. Standardizirali bodo vso programsko opremo. Torej, ne bodo nikoli ničesar nadgradili, razen da bi nadgradili vse naenkrat. Organizirali bodo podporo. Tako bodo plačevali podporo množici različnih ponudnikov, ki imajo samo svojo podporo. Imeli bodo možnost spreminjanja obsega in obsega v smislu, da bodo izvajali več, kot bi kdaj izvajali tovrstno storitev, in nadzirali bodo njihovo uporabo tako, kot večina podatkovnih centrov ne more, ker izvajajo samo eno standardizirano storitev, vendar večina podatkovnih centrov izvaja celo vrsto stvari. In v tem se oblak resnično ukvarja in na določen način lahko določa, ali vas zanima ali ne za kakšno posebno aplikacijo. Torej, veste, moje nekako grobo pravilo je, da tam, kjer so možne ekonomije obsega, prej ali slej prevzame oblak. Toda inovativnost in prilagodljivost ter zelo konkretne stvari, ki jih greste sami, resnično ne morejo. Oblak bo vedno drugi najboljši.
V redu. Naj ga vrnem Ericu ali Gilbertu.
Eric Kavanagh: V redu, Gilbert, tukaj bom dal ključe za WebEx. Ostani v pripravljenosti. Preprosto kliknite kjer koli na drsniku in uporabite puščico navzdol na tipkovnici.
Gilbert Van Cutsem: Mislim, da obvladam.
Eric Kavanagh: Vi imate nadzor.
Gilbert Van Cutsem: V redu. Tukaj gremo. Oblačni imperativ - nebo je meja, je to urbana legenda ali kaj bi si mislili o tem? To je le nekaj pogovorov in stvari, ki jih je treba upoštevati.
Najprej iz "kaj" spredaj veste, kot vsi vemo, mislim, da nihče ne dvomi v to. SaaS-ificationation je tu, da ostane, ker programska oprema dejansko nikoli ne umre, ampak se preprosto premakne v oblak, kajne? Mislim, da sem to že povedal v prejšnji izdaji tega. O ne, ali Eric je to rekel zame v prejšnji izdaji. Mislim, da je očiten razlog in to na nek način sega tudi do Robina v tem, da je na korporativni strani stvari korporativna časovnica precej enostavna. CMO vedno potrebuje vse in to zdaj potrebuje. Torej, ves čas je na trgu. Tako žalostno, da je to dober izgovor za to na nek način zanj. Kljub temu je CIO malce nervozen zaradi SaaS-a in oblakov, ker, saj veste, celotna težava z elastičnostjo pomeni, da mora iti tudi to, kar narašča. Pripravljeni morate biti na skali, vendar tudi na obseg nazaj. Torej, on je malo nervozen zaradi tega. CFO ni nervozen, ne bolj kot ponavadi, ampak pravi: "Hej, to je … koliko nas bo to vrnilo?" Veste, zloglasni kapitalski odhodki in razprava o OPEX. Precej je stara, vendar je na tem svetu zelo pomembna. In potem, nenazadnje, seveda izvršni direktor. Pojavlja se tako: "Oh! Zmanjševanje tveganja! Fantje, vsi ste navdušeni, a smo pripravljeni na to?" Ker je tveganje tisto, o čemer razmišlja.
Kakšno je torej tveganje? Samo nekaj misli, kajne? Tu se ukvarjamo z miselnim vodstvom, vendar na nedokončani poti, ker so to vse precej nove stvari, vse dokaj novejše stvari. V resnici nimamo veliko podatkovnih točk, če pomislite. In tako se tudi na tveganju moramo spoprijeti z vkrcanjem na ladjo, veste, ljudje, ki podpisujejo sporazume, gredo kot: "Da, to je tisto, kar si želimo, pot", se prijavijo, a potem to ni dovolj. Veste, morate vkrcati ljudi in se spomnite filmov? Nazaj v prevodu je to nekaj, kar veste, o čem se vkrcava. In potem tudi, kot je Robin ravnokar rekel, veste, da on-prem ne gre nujno takoj. Torej, morate integrirati oba sveta. To je hibridni svet. In tako, kako boš to storil? To je 80-20, Pareto pravilo 80-20, je to v redu? Je to dovolj dobro? In potem smeti v / smeti ven, ko povežete sisteme. Je to vredu? Je to trpežno? Ker se boste preselili, ali boste svoje podjetje preslikali v korenski sistem, kako boste to storili? In potem je zadnja, ki se mi zdi izjemno pomembna, večnamenske arhitekture, kar pomeni, da zasebnost podatkov na vaših lastnih podatkih, včasih se imenuje "lastni lastni podatki", postane zelo pomembna, veste? Sto ljudi, ki uporabljajo isti sistem, ena baza podatkov sedi pod sistemom, kdo bo videl moje podatke? Samo jaz, kajne? Ste glede tega popolnoma prepričani? Zasebnost podatkov in varnost podatkov pomagata strokovnjakom. Če ste CIO, vam vrne "jaz" v CIO, ker ste zdaj zadolženi za informacije. To je precej zanimivo, če si CIO.
Torej, pogovorimo se malo o "zakaj". Torej je strateški namen vsega tega zelo, zelo preprost. Če ste naročnik, obstaja tržni pritisk. Če ste ponudnik, obstaja pritisk konkurence. Če imate vrstnike, obstaja pritisk vrstnikov. Če ste naročnik, je to le tržna psihologija. Vsi želijo iti v oblak, SaaS ali kakorkoli že imenujete, oblak SaaS, vsi potrebujemo in želimo iti tja. In razlog je ponavadi finančni. To je očiten razlog, toda če razmišljate o finančnem vidiku, se lotite tega, čemur pravim paradoks med proračunom in proračunom. Ali boste šli na naročnino, vse, kar lahko jeste, 50 dolarjev, 500 dolarjev mesečno ali kaj podobnega, ali sanjate o uporabi, ki temelji na tem, da boste plačevali samo tisto, kar v resnici uporabljate? In kako je torej to delo, ki temelji na uporabi, temelji na potrošnji? Ali boste odmerili vse te stvari? Verjetno se to ne bo zgodilo takoj. Torej boste končali s hibridnim mehanizmom, to je, plačujem 200 na mesec in morda občasno 500, ker moram plačati za dodatno porabo. Retainer Plus, po mojem mnenju bo to verjetno šlo.
Toda obstaja tudi nekaj, čemur na široki sprednji strani pravim skrita namera, in verjamem, da je, veste, to povsem resnično. To je sprememba nadzora, to je CIO proti CMO, premik moči ali boj za moč med CMO, "hočem vse in hočem zdaj", in CIO, ki pravi kot: "Hej, to je vse o podatkih, veste? Včasih sem tekel pred 20 leti, je šlo za strojne sisteme. Pred desetimi leti je šlo za vse aplikacije, danes pa za podatke. In ker sem CIO - informacije - gre za vse jaz. Nadzorujem. " Torej, to je neke vrste premik moči ali boj za oblast, kar verjamem, da se trenutno dogaja med tema dvema skupnima organizacijama za trženje in skupino za konkurenco.
Torej, na koncu je vse to tako mlado, da nihče v resnici ne ve, ali smo v inovativnem okolju ali v zgodnjem usvojitvenem okolju. Verjamem, da smo v okolju zgodnjega posvojitelja, ne zgodnji večini, le zgodnji posvojitelj, ampak, veste, nekako na polovici. In tako, veste, za stranko, končnega uporabnika, naročnika, gre za to, da začnemo s tem, ker CMO želi začeti, kajne? In zato je pomembno, da ne dokončamo tistega, čemur pravimo zmanjševanje donosov. Omejevalni zagon lahko povzroči zmanjšanje donosov. Zato je izjemno pomembno, da veste, da najdete, da zaupate strankam, ki lahko poskrbijo, da enotna točka napake ni težava in da se spoštuje varnost podatkov. Torej, potrebno bo kar nekaj upravljanja sprememb. In na koncu - skoraj končano, to je zadnji diapozitiv - kako bomo to naredili? Kako poteka premik v oblak, premik v SaaS, veste, brezhibno in enostavno? No, če naredimo dve stvari: bodite pozorni - zagotovite - resnično pomembno, na krovu pa še bolj pomembno.
Eric Kavanagh: V redu …
Gilbert Van Cutsem: In v tem primeru je nebo meja. Hvala vam.
Eric Kavanagh: Ja. To je bilo super. Všeč so mi bile zelo provokativne ideje, všeč mi je, kako si nekako vse to podrl. Mislim, da ima to veliko smisla. In pojdimo naprej in potisnimo prvi drsnik Ashisha, jaz pa ti bom izročil ključe WebExa, Ashish. Ok, pojdi naprej. Preprosto kliknite kjer koli na drsniku in uporabite puščico navzdol na tipkovnici. Izvolite.
Ashish Takooo: V redu. Hvala, Eric. Pozdravljeni, to je Ashish in pripovedoval bom o Qubole. Torej, za začetek, Qubole v bistvu ponuja velike podatke kot storitveno platformo. Gre za platformo v oblaku, ki jo gosti Amazon in oblak Google in ponujamo tehnologije, kot so Hadoop, Hive, Presto in kup drugih, o katerih bom govoril, vse na ključ, tako da se lahko naše stranke v bistvu umaknejo vso zmedo v svetu velike podatkovne infrastrukture ali izstopite iz dejanskega vodenja te infrastrukture in se bolj osredotočite na svoje podatke in preobrazbe, ki jih želijo narediti v svojih podatkih. Torej, to je tisto, kar je Qubole.
Kar zadeva oprijemljive koristi, je en način razmišljanja o Qubole, seveda veste, da je na ključ samoplačniška platforma za analizo velikih podatkov in velika integracija podatkov, zgrajena okoli Hadoopa, ampak bolj bistveno, kaj počne, je to, ti vem, za vse velike podatkovne motorje, kot so Hadoop, Hive, Presto, Spark, Chartly in tako naprej, in tako naprej, prinaša vse prednosti oblaka tem velikim podatkovnim motorjem in nekaj ključnih manifestacij, ki jih prinaša iz V perspektivi oblak je, da infrastruktura postane prilagodljiva in s prilagajanjem mislim tako prožno kot prilagodljivo delovnim obremenitvam, ki se izvajajo na katerem koli od teh motorjev in tudi te motorje naredi veliko bolj samopostrežne in skupne v smislu, veste, Qubole ponuja vmesnike, kjer lahko uporabljate te posebne tehnologije ne samo za svoj razvoj ali, veste, naloge, usmerjene v razvijalce, ampak tudi vaši drugi analitiki podatkov lahko začnejo izkoristiti prednosti teh tehnologij za samopostrežno storitev vmesnik.
Dobimo veliko, veste, kar se tiče tega konkretnega, saj veste, webinarja, veste, to je ena od naših perspektiv glede prednosti oblaka, ki ga Qubole prinaša do velikih podatkov. Torej, če samo primerjate med tem, kako zaženete, recimo, Hadoop in ga pustite, da se obremenjuje v predhodni nastavitvi, v nastavitvi za vnaprej, vedno razmišljate o statičnih grozdih, veste, popravite svoje grozdov, morda jih nastavite na največjo raven in jih hranite tam, nato pa jih morate spremeniti, potem boste morali skozi celoten postopek nabave, uvajanja, testiranja in tako naprej. Qubole spreminja, da so z ustvarjanjem grozdov v celoti na zahtevo naši grozdi popolnoma elastični, predmete, shranjene iz oblaka, dejansko shranjujemo podatke in grozdi se pojavijo, in veste, nastanejo na podlagi povpraševanja, ki ga ustvari uporabniki in odidejo, kadar ni povpraševanja. Tako je zaradi tega infrastruktura toliko bolj prožna, prilagodljiva in prilagodljiva vašim delovnim obremenitvam.
Drug primer prilagodljivosti je, da veste, da ste danes morda ustvarili svoje statične grozde tukaj, veste, z določenim delovnim obremenitvam in če se vaše delovne obremenitve spremenijo in je treba zdaj nadgraditi vašo infrastrukturo, morda potrebujete več pomnilnika na svojih strojih in podobne stvari. Spet veste, da to na primer v oblaku prek Qubole naredi preprosto. Vedno lahko najamete nove, različne vrste strojev in, veste, v nekaj minutah dobite grozde, 100-vozliške grozde, v nasprotju s tedni, ki ste jih morali čakati na Hadoop.
Druga ključna stvar, pri kateri se Qubole razlikuje od on-prem je, da je Qubole v bistvu kot ponudba storitev, zato vseh orodij in infrastrukture, ki jih potrebujete za vključitev storitve, vam ni treba … kamor koli že, veš, predvsem jemlješ programsko opremo, jo moraš sam zagnati, sam jo moraš integrirati in narediti vse te prednosti, vse prednosti modela SaaS so namig, veš, kako Qubole ponuja velike podatke v nasprotju s tem, da sam Hadoop samodejno izvaja sam.
Ta diapozitiv običajno pokriva našo arhitekturo. Seveda na podlagi oblaka shranjujemo svoje podatke o predmetih v oblaku v oblaku, Google Cloud in Google Compute Engine ali Amazon Web Services. Vzamemo vse ekosistemske projekte Hadoop in okoli tega, razvili smo ključni IP glede samodejnega skaliranja in samostojnega upravljanja, naredili smo veliko optimizacij oblakov, da bodo te komponente komponent resnično dobro delovale v oblaku, saj veste, oblačna infrastruktura je se zelo razlikuje od samo izvajanja stvari na goli kovini in celega števila podatkovnih konektorjev, ki omogočajo premikanje podatkov s te platforme. Torej, to primerja platformo v oblaku in to omogoča, da je to, kar veste, ključno … ključna značilnost je, kako narediti vse samopostrežne storitve, da vam ne bo treba imeti močnih … ne Med izvajanjem tega nimam zelo velikega operativnega odtisa, vendar to povezujemo z našim delovnim sistemom za podatke, ali so to orodja za analitike, ali so to orodja za upravljanje podatkov, ali so to orodja za predloge in tako naprej, in tako naprej, tako da lahko prinese prednosti te tehnologije ne le razvijalcem, ampak tudi drugim poslovnim uporabnikom in podjetjem. In to platformo v oblaku seveda povezujemo tudi z orodji, ki jih ljudje že uporabljajo, ne glede na to, ali gre za orodja za uporabo ali samo Tableau ali pa uporabljajo, veste, več izdelkov za shranjevanje podatkov, kot so Redshift in tako naprej in tako naprej.
Danes storitev deluje v dokaj velikem obsegu, vsak mesec obdelamo približno 40 petabajtov podatkov v bazi strank. Naši grozdi se razlikujejo po velikosti od 10-vozliških grozdov do 1500-vozliških grozdov in, veste, glede na obseg obsega, ki ga lahko obdelujemo in na splošno, kolikor vem, izvajamo verjetno nekaj največjih grozdov v oblaku, kar zadeva Hadoop, in v enem mesecu obdelamo do približno 250.000 virtualnih strojev v naših grozdih. Ne pozabite, naš model so grozdi na zahtevo, kar ima ogromne koristi v smislu zmanjšanja operativnih delovnih obremenitev, pa tudi izboljšanja vašega in tako naprej in tako naprej.
Končno, eno od naših, veste, je to samo vzorčenje, kako se je Qubole preoblikoval v različna podjetja. je primer naše stranke. Bili so že v oblaku, na primer so v oblaku izvajali elastični MapReduce in uporaba podatkov je bila tam precej omejena. Imeli bi približno 30 nenavadnih uporabnikov, ki bi lahko uporabljali to tehnologijo. S Quboleom so to lahko razširili na več kot 200 nenavadnih uporabnikov v podjetju, ki so opazili širitev primerov uporabe velikih podatkov in res je prineslo, veste, temu, kar imenujemo definicija agilne platforme velikih podatkov in to postalo je resnično osrednje za veliko njihovih analitičnih delovnih obremenitev.
Torej, samo da bi zaključili, veste, to je bil kratek primer na Quboleu. V bistvu je naša vizija, kako narediti podjetja, ki so veliko bolj okretna okoli velikih podatkov, in v bistvu izkoriščamo prednosti oblaka in jih pripeljemo do uporabe velikih podatkovnih tehnologij v okolici Hadoopa, tako da lahko naše stranke izkoristijo te prednosti okretnosti in teh prednosti fleksibilnosti in tistih koristi samopostrežne narave v oblaku, da postanejo toliko učinkovitejše za njihove potrebe po podatkih. Tam se bom ustavil in ga predal Eriku.
Eric Kavanagh: V redu. To se sliši super in zdaj ga bom predal Mikeu Millerju iz Cloudanta. Mike, trenutno ti predajam ključe. Samo kliknite na diapozitiv, tukaj. Vzemi stran.
Mike Miller: Zdi se, da imam ključe. Torej, opravičil se bom. Izgubil sem se … Mislim, da sem s svojo predstavitvijo pozabil odposlati nekaj pisav. Torej, upajmo, da boste lahko pogledali mimo tega in si predstavljali, da je lepo. Ampak ja, to je zabavno. Tu imam dolg seznam, provokativne stvari, ki sem jih slišal, da sem si zapisal, da se nestrpno vrnem k vam v panel. Torej, poskusil bom hitro preiti to.
Torej, začel bom z Cloudantom. Cloudant je baza podatkov kot storitev, naš ponudnik oblakov in pravzaprav novega logotipa sploh nimam. IBM je prevzel ne tako dolgo nazaj. In tako smo … Govoril bom o naši storitvi in se še posebej osredotočil na to, da bomo poskušali uporabnike in stranke prilagoditi na dokaj drugačen način kot prejšnji govornik.
Cloudant ponuja bazo podatkov kot storitev in druge storitve, povezane s podatki, za ljudi, ki gradijo aplikacije. Torej neposredno sodelujemo z razvijalci in se osredotočamo na operativne ali OLTP podatke v nasprotju z analitiko, ki smo jo že slišali od Ashisha. In bistvo je v tem, da je Cloudant celoten vrednost, ki jo lahko razdelimo v pomoč našim uporabnikom, da naredijo več in tako ustvarijo več aplikacij, rastejo več in spijo več. O njih bom spregovoril nekoliko podrobneje, toda splošna ideja je, da če ste uporabnik, veste, da ste v poslovnem podjetju, gradite novo aplikacijo in dodate funkcijo obstoječi aplikaciji ali spletu mobilni zagon, se morate osredotočiti na svojo osnovno sposobnost. In prej, morda pred desetletjem, naj bi bila IT prepoznavna, konkurenca, žal, konkurenčna škoda, celo vodenje baze podatkov je konkurenčna prednost. Sproščeno, da je teh dni konec! Način, kako resnično poskušamo sodelovati z našimi uporabniki, je, da jih spodbudimo k uporabi sestavljenih storitev, modularnih, za večkratno uporabo, sestavljivih, saj ideja, ki zmanjšuje čas trženja, povečuje razširljivost. In splošna ideja tukaj je, da oblak ni samo, kar veste, nekaj novega se potiska na uporabnike, to je v resnici trg … To je razvoj trga, ker način, kako ljudje gradijo aplikacije, porabijo aplikacije, naprave, na katerih delujejo in obseg podatkov se v zadnjih 5–10 letih precej korenito spreminja. To je resnično poudarjeno obstoječo arhitekturo aplikacij za gradnjo aplikacij, pa tudi samo za spopadanje s temi podatki in delovno obremenitvijo analitike brez povezave. In tako se odpira cel kup priložnosti.
Torej je Cloudant distribuirana podatkovna baza kot storitev in verjamem, da je bila edinstvena po svojem nastanku, da je res že od začetka dobavljena z mobilno strategijo in o tem bom podrobno govorila, ampak ideja je, da zdaj pišem aplikacije, ne pišete samo za eno platformo, kajne? Pišete za nekaj, kar lahko zaprem petabajtno lestvico v oblaku, prav tako mora biti nemoteno teči na namizju ali brskalniku. Še več in več vidimo stvari, ki jih moramo izvajati na mobilni napravi ali polpovezana naprava ali nosljiva naprava ali nekaj, kar imenujemo IOT. In tako mislim, da veste, da so aplikacije, ki lahko dobro delujejo in vplivajo na te različne stranke, izjemno konkurenčne na trgu, in to, kar poskušamo narediti, je preprosto, da lahko ljudje enotnim API-jem v enotnem programskem modelu pišejo, ravnati s podatki v vseh tistih različnih napravah z zelo različnim obsegom. 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. Kaj misliš?
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. Dobro. 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. Vsekakor. 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. Ja. Brez 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. Ja. 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. Nevem. 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. To je zelo dobro vprašanje. 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. Dobro. 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. Great! 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. Pazite. Adijo.
