Eric Kavanagh: Mine damer og herre, hei og velkommen tilbake til TechWise. Jeg heter Eric Kavanagh. Jeg vil være din moderator for Episode 3. Dette er et nytt show som vi har designet sammen med vennene våre fra Techopedia, et veldig kult nettsted som åpenbart fokuserer på teknologi, og selvfølgelig, her på The Bloor Group, fokuserer vi ganske veldig på enterprise teknologi. Så, bedriftsprogramvare av alle slag, og hele TechWise-formatet ble designet for å gi deltakerne et virkelig godt og hardt blikk på en bestemt plass. Så vi har gjort Hadoop for eksempel, vi analyserte i forrige show, og i dette bestemte showet snakker vi alt om sky.
Så det heter "The Cloud Imperative - What, Where, When and How." Vi skal snakke med et par analytikere i dag og deretter tre leverandører. Så, Qubole, Cloudant og Attunity er sponsorene for dagens show. En stor takk for dere for deres tid og oppmerksomhet i dag, og en stor takk, selvfølgelig, til alle dere der ute. Og husk at du som deltakere på disse forestillingene spiller en viktig rolle. Vi vil at du skal stille spørsmål, engasjere deg, bli interaktiv, gi oss beskjed om hva du synes, for helt åpenbart er hele hensikten med showet her å hjelpe dere til å forstå hva som skjer der ute i en verden av cloud computing.
Cloud Imperative Deck
Så la oss gå rett videre. Første vert, verten din der oppe, Eric Kavanagh, det er meg, og så har vi Dr. Robin Bloor til å kalle inn fra en flyplass, og vår gode venn Gilbert, Gilbert Van Cutsem, en uavhengig analytiker, kommer også til å dele noen tanker med deg. Så får vi høre fra Ashish Thusoo, administrerende direktør og medgründer av Qubole. Vi vil høre fra Mike Miller, sjefforsker hos Cloudant og til slutt fra Lawrence Schwartz, VP for Marketing at Attunity. Så, vi har en hel masse innhold stilt opp for deg i dag.
Så, skyen - edikt ovenfra - dette er et konsept som kom til meg forleden da jeg tenkte på dette. Virkelig, cloud computing er bare enormt i disse dager. Jeg mener, det er egentlig ganske fascinerende å se på utviklingen av disse tingene, og et av eksemplene jeg ofte gir er i selve webcasting-teknologien. De av dere som ringte inn tidlig hørte selvfølgelig noen interessante tekniske utfordringer. Det er ett problem med nettskyen er at det endres, formater endres, standarder endres, grensesnitt endres, og noen ganger når du prøver å koble sammen to forskjellige områder sammen, får du litt problemer, får du litt problemer. Så dette er faktisk en av tingene du kan bekymre deg for med cloud computing. Vær forsiktig med arkitektur! Det kan du se på det siste punktet.
Noe av det vi gjør, akkurat som en side-merknad her, for vår webcast, vi har en egen leverandør av telefonkonferanser. Da bruker vi WebEx. Vi bruker ikke WebEx-lyden fordi ærlig talt, en gang vi brukte WebEx-lyd for mange år siden, og den krasjet og brant på en mest ubehagelig måte. Dermed er vi ikke villige til å løpe den risikoen igjen. Så bruker vi vårt eget lydopptaksfirma som heter Arkadin som et faktum og vi sy sammen i sanntid alle disse forskjellige løsningene. Og ideen er at vi da kunne sendt deg en e-postapplikasjon med en egen e-postapplikasjon med tilfelle WebEx ville ha krasjet, vi forteller dere alle om å ringe inn, vi vil sende dere lysbildene og bare gå gjennom det mer eller mindre uten WebEx-miljøer. Så, slik du kan komme deg rundt slike problemer, men denne typen problemer er over alt.
Men det er mange fordeler med sky. Det er klart det er en liten hindring for innreise, du kan se på plakaten til cloud computing er selvfølgelig salesforce.com, som nettopp revolusjonerte virksomheten, nærmere bestemt salgsstyrke-automatisering. Men så har du ting som Marketo og iContact og Constant Contact og Sailthru og godhet, når det gjelder markedsføring og salgsautomatisering, det er mange verktøy, men det er ikke alt det er. HR får det til hele skyspillet, analytics er i skyspillet. Se på det lite kjente selskapet der ute, Amazon Web Services, hva de gjør med cloud computing - det er bare enormt. Og jeg hørte et godt tilbud forleden fra en fyr vi jobber mye med David som nå er over hos Cisco, som faktisk et selskap som kjøpte WebEx. Ikke sikker på at de har investert så mye som jeg skulle ønske at de skulle ha i WebEx, men det er egentlig ikke min beslutning, er det? Men han er på Cisco i disse dager, og han hadde et veldig morsomt, bare lite sitat, og det vil si, "det er ikke en sky, det er mange skyer, " og det er helt riktig. Det er mange skyer der ute. Faktisk er hver skyleverandør sin egen sky. Så en av utfordringene i disse dager er å koble til sky, ikke sant? Hvis du er salgsstyrker, ville det ikke være fint å koble seg direkte til iContact og Constant Contact og til LinkedIn, for eksempel, og kanskje til Twitter og andre miljøer, fikset andre skyer der ute bare forretningsløsninger som gir mening for deg og ditt selskap.
Så dette er noen problemer å huske på, men skyen er her for å bli. Bare vet at om dette er den lokale programvaren her for å bli. Så hva har vi å finne ut i bedriften eller noen til og med små til mellomstore bedrifter, hvordan definerer du arkitekturen din og opprettholder den slik at du kan utnytte skyen uten å skape en gigant et annet sted utenfor din kontroll? Så tydeligvis utviklet hele datavarehusindustrien seg rundt et behov for å konsolidere kritisk informasjon for å analysere den informasjonen og ta bedre beslutninger.
Nå, nå har Amazon Web Services Redshift. Det er en av de største webcastene vi noen gang har gjort var med Redshift. Det er en ganske stor avtale. De endrer dynamikken, de endrer prisstrukturene. Du kan se når prisene dine faller ned på tradisjonell lisensiering for bedriftsprogramvare delvis på grunn av skyberegning og del fordi disse menneskene er der ute og senker prispunktet og legger press på prisen. Så det er gode nyheter for sluttbrukerne. Det er noe å huske på absolutt for alle der ute som prøver å bruke noen av disse teknologiene. Så det er noe du må huske på, og vi vil snakke om det i dag på showet.
Så analytiker Dr. Robin Bloor blir vår første analytiker for dagen. Så jeg vil gå videre og skyve hans første lysbilde og overlate tastene til ham. Robin, jeg tror du er her et sted, der er du. Og med det skal jeg dele det ut, og gulvet er ditt!
Dr. Robin Bloor: Ok, Eric. Takk for introduksjonen. Jeg kom over … for et par dager siden kom jeg over en undersøkelse av forbrukere, som faktisk stilte spørsmålet - tror du at stormvær forstyrrer sky computing? Og mer enn 50 prosent av dem sa ja. Jeg tenkte bare at jeg ville gi deg beskjed om at det ikke gjør det, hvis du er en av de som tror på det. Og da, det er litt som å tro at du vet at når du har snø på TV-en, fordi det snør ute.
Cloud, du vet, en av tingene er at det er slags, du vet, en viktig, hvis du vil, enkel detalj av skyen er at skyen faktisk er et datasenter på en eller annen måte, eller at en bestemt skytjeneste er et datasenter. Det eneste er at det er et annet datasenter enn den tradisjonelle skyen. Så jeg skulle snakke i oversikt om skyen, slik at du som sikkerhetskopi skal gå nærmere inn på skybruken fordi det ikke er noe poeng i å dekke samme grunn.
Så det første slags poeng som jeg ønsker å si er at skyen er en tjeneste, vet du? Og en av tingene som faktisk skjer på grunn av cloud computing, er at det er en … vel, jeg kaller døden til merker, en hel serie programvaremerker hadde veldig mye krefter og fortsetter å ha krefter innen bedriftens databehandling. Når du først kommer til skyen, har de ikke mye krefter lenger, vet du? Når du kjøper en skytjeneste, bryr du deg om applikasjonen, selvfølgelig bryr du deg om servicenivået skyen kommer til å gi deg, du vil ikke at skytjenesten svikter ofte, du bryr deg om bruksomkostninger og bryr deg om disse ting fordi dette er en tjeneste, men det du ikke bryr deg om er at du ikke bryr deg om hvilken maskinvare den kjører på spesielt, du bryr deg ikke hva nettverksteknologien er, du bryr deg ikke hva operativsystemet det kjører er, du bryr deg ikke hva filsystemene er, du bryr deg ikke engang hva databasen er, og som faktisk brukes spesifikt av noen gitte databasetjenester ut av skyen, vet du? Og virkningen av det på en måte er at skyen er forferdelig mange programvaremerker har ingen reell verdi i skyen, fordi du vet at du går inn i skyen på en eller annen måte for noe som er en tjeneste og ikke lenger produkt. Så jeg trodde jeg kunne gjøre et par lysbilder av grunner til ikke å bruke skyen, du vet, og dette er alt, hvis du vil, du vet, blodige enkle, åpenbare grunner, men noen måtte oppgi dem, så jeg trodde jeg skulle gjøre det.
Så grunner ikke til meg … ikke å bruke skyen - hvis de ikke kan gi den type data og prosessstyring du vil ha dem, vet du, så oppfyller den rett og slett ikke kriteriene dine. Hvis de ikke kan gi deg den ytelsen du ønsker, vil den ikke oppfylle kriteriene. Hvis skyen gir deg fleksibiliteten når det gjelder hvordan du kan flytte ting rundt, vil den ikke oppfylle et kriterium. Det er bare åpenbare grunner til at spesielle skytjenester ikke vil passe for mange mennesker der ute, annet enn å gjøre bedriftens databehandling.
Du kan ikke gjøre det fordi du kan gjøre det billigere. Skyen er ikke alltid det billigste alternativet. Noen mennesker ser ut til å tro fordi det ofte er et billig alternativ at det alltid vil være billigere, det er ikke alltid billigere. Og den andre tingen er at hvis du tar en applikasjon fra en sky, integrerer den ikke godt med det du gjør, så har du sannsynligvis ikke tenkt å gå videre med det, og det er, du vet, grunner til å vende deg bort .
Her er grunnene til å adoptere. En av tingene du kan gjøre i skyen, ganske mye skuddsikker, er prototypingaktivitet. Hvis du enten kan prototype i skyen og implementere i datasenteret, er det helt levedyktig, og det er store mengder mennesker som gjør det. Du kan laste opp arbeid fra datasenteret med ikke-kritiske applikasjoner fordi de sannsynligvis vil være i stand til å finne noen slags skytjenester som vil oppfylle servicenivået ditt til de ukritiske tingene. Og du kan laste opp spesifikke applikasjoner som salesforce.com og lignende tilbud til det, du vet, standardapplikasjonene. Alle slags har en evne på dette området, og feltet er ikke spesialisert, og du vet, det tradisjonelle … hva som er tilgjengelig i skyen, vil sannsynligvis være det du går med.
Så den siste tingen som jeg ønsket å si, det er en ganske interessant ting, egentlig, er når du faktisk ser etter skyen, en måte å forstå er på samme måte som en rekke stordriftsfordeler. Hele poenget er at du, vet du, driver et datasenter der ute, og at du kommer til å ringe inn til det datasenteret fra et eller annet sted og bruke det, og derfor ville det være bedre, det er bedre å være i hovedsak billigere enn hvis du gjør det selv. Så, du vet, det handler egentlig om stordriftsfordeler.
Skyleverandørene, de velger datasenterplassering, og det beste stedet å lokalisere datasenteret ligger rett ved siden av en kraftstasjon, og spesielt rett ved siden av en billig kraftstasjon. Så en kraftstasjon nordover som tilfeldigvis er vannkraft eller noe sånt. Det er normalt det billigste, vet du? Du kan faktisk finne datasenteret der, og du vil synes det er enklere. Det er rimeligere å ansette folk på slike steder enn det er i sentrum av New York eller San Francisco. Du kan standardisere hele anlegget når det gjelder klimaanlegg og strøm. Det vil spare deg for mye fordi det betyr at du kan gi ut en hel bygning til det, og det er hva alle skyoperatørene gjør. De standardiserer nettverksmaskinvare, de standardiserer datamaskinvaren de bruker, vanligvis varer x86-brett, ofte vil de montere dem selv. Så noen bygger faktisk hele saken. De vil bruke Amazon-programvare som de kan fordi det faktisk ikke betyr noen kostnad å ta i bruk den. De vil standardisere i all programvare. Så de vil aldri oppgradere noe annet enn å oppgradere på en gang. De vil organisere støtten. Så de vil betale støtte til mange forskjellige leverandører som bare har sitt eget støtteapparat. De vil ha skalere- og skalereevne i den forstand at de vil kjøre mer enn du noen gang ville ha den typen tjenester, og de vil overvåke bruken på en måte som de fleste datasentre ikke kan fordi de kjører bare en standardisert tjeneste, men de fleste datasentre kjører en hel rekke ting. Og det er det skyen egentlig handler om, og som på en viss måte kan definere om den interesserer deg eller om den ikke gjør det for noen bestemt applikasjon. Så, du vet, min slags grove tommelfingerregel er at der stordriftsfordeler er mulig, skyen tar over før eller senere. Men måten innovasjon og fleksibilitet og en veldig spesifikk ting du selv går, kan virkelig ikke. Skyen blir alltid nest best.
Greit. La meg gi det tilbake til Eric, eller videre til Gilbert.
Eric Kavanagh: Ok, Gilbert, jeg gir deg nøklene til WebEx. Vent litt. Bare klikk hvor som helst på det lysbildet og bruk pil ned på tastaturet.
Gilbert Van Cutsem: Jeg tror jeg har kontroll.
Eric Kavanagh: Du har kontroll.
Gilbert Van Cutsem: OK. Her går vi. Skyimperativet - himmelen er grensen, er det en urban legende, eller hva ville du tro om det? Dette er bare noen få samtaler og ting du bør vurdere.
For det første, fra "hva" -fronten, vet du, som vi alle vet, jeg tror ikke noen tviler på dette. SaaS-ification er her for å bli fordi programvaren faktisk aldri dør, den flytter bare til skyen, ikke sant? Jeg tror jeg sa dette før i forrige utgave av dette. Å nei, eller Eric sa det for meg i en tidligere utgave. Og jeg tror den åpenbare grunnen, og dette går tilbake til Robin på en måte også, er at på bedriftens side av ting er bedriftens tidslinje ganske enkel. CMO trenger alltid det hele, og han trenger det nå. Så, han handler om å markedsføre seg. Så trist, det er en god unnskyldning for det på en måte for ham. CIO er imidlertid litt nervøs for SaaS og skyer fordi du vet, hele elastisitetsproblemet betyr at det som går opp også må komme ned. Du må være klar til å skalere ut, men også å skalere tilbake. Så det er han litt nervøs for. Finansdirektøren er ikke nervøs, ikke mer enn den vanlige, men han ser ut som: "Hei, dette er … hvor mye vil dette sette oss tilbake?" Det er, du vet, den beryktede investeringen kontra OPEX-diskusjonen. Den er ganske gammel, men den er veldig, du vet, veldig viktig i denne verden. Og sist, men ikke minst, er selvfølgelig administrerende direktør. Han ser ut som: "Å! Risikoredusering! Gutter, dere er alle glade, men er vi klare for dette?" Fordi risiko er det han tenker på.
Så, hva er risikoen? Bare noen få tanker, ikke sant? Vi har å gjøre med tankeledelse, men i en uferdig vei fordi dette er ganske nye ting, alt ganske nylig. Vi har ikke så mange datapunkter, egentlig, hvis du tenker på det. Og så, også, på risikosiden, må vi forholde oss til ombordstigning, du vet, folk som signerer avtaler, ser ut som: "Ja, det er det vi vil, veien å gå, " de melder seg på, men da det er ikke nok. Du vet, du må ombord folk og det, husker du filmene? Tilbake i oversettelse, det er litt av, du vet, hva ombordstigning handler om. Og også, som Robin nettopp sa, du vet, at on-prem ikke nødvendigvis går bort med en gang. Så du må integrere begge verdener. Det er en hybridverden. Og så, hvordan skal du gjøre det? Det er 80-20, 80-20-regelen Pareto, er det greit? Er det bra nok? Og så søppel inn / søppel ut når du kobler til systemene. Er det greit? Er det holdbart? Fordi, du vet, skal du migrere, skal du kartlegge bedriften din til rotsystemet, hvordan skal du gjøre det? Og så er den siste, som jeg synes er ekstremt viktig, multitenant-arkitekturer, noe som betyr at datasikkerhet på dine egne data, noen ganger kalles det "eie dine egne data", blir det veldig viktig, vet du? Hundre mennesker som bruker det samme systemet, en database sitter under systemet, hvem skal se dataene mine? Bare meg, ikke sant? Er du helt sikker på det? Datasikkerhet, datasikkerhet hjelper eksperter. Hvis du er CIO, bringer det "jeg" tilbake til CIO fordi du nå er ansvarlig for informasjon. Det er ganske interessant hvis du er CIO.
Så la oss snakke litt om "hvorfor." Så den strategiske hensikten med alt dette er veldig, veldig enkelt, tror jeg. Hvis du er abonnent, er det markedspress. Hvis du er en leverandør, er det konkurransepress. Hvis du har jevnaldrende, er det gruppepress. Hvis du er abonnent, er det bare markedspsykologien. Alle vil gå til skyen, SaaS eller hva du enn kaller det, sky SaaS, vi trenger alle og ønsker å dra dit. Og årsaken er vanligvis økonomisk. Det er den åpenbare grunnen, men hvis du tenker på det økonomiske aspektet, kommer du inn i det jeg kaller regningen-mot-budsjett-paradokset. Skal du gå for et abonnement, alt-du-kan-spise-systemer, $ 50, $ 500 i måneden eller noe sånt, eller drømmer du om bruk basert slik at du bare betaler for det du virkelig bruker? Og hvordan skal det fungere, bruksbasert, forbruksbasert? Skal du måle alle de tingene? Det kommer antagelig ikke til å skje med en gang. Så, du vil ende opp med en hybridmekanisme, det vil si at jeg betaler 200 i måneden og kanskje noen ganger 500 fordi jeg må betale for merforbruket. Retainer Plus, det kommer nok til å gå etter min mening.
Men det er også noe jeg kaller den skjulte hensikten på bred front, og jeg tror at, du vet, dette er helt ekte. Det er endring av kontroll, det er CIO versus CMO, maktskiftet eller maktkampen mellom CMO, "Jeg vil ha alt og jeg vil ha det nå, " og CIO, som sier som "Hei, dette er alt om data, vet du? Jeg kjørte for 20 år siden, det handlet om maskinvaresystemer. For ti år siden handlet det om applikasjoner. I dag handler det om data. Og siden jeg er CIO - informasjon - handler det om meg. Jeg har kontroll. " Så det er en slags maktforskyvning eller maktkamp jeg tror det pågår akkurat nå mellom disse to, CMO og CIO.
Så til slutt, alt er så ungt at ingen virkelig vet om vi er i innovatortypen miljø eller i den tidlige adoptertypen. Jeg tror vi er i den tidlige adoptertypen miljø, ikke den tidlige majoriteten, bare den tidlige adoptereren, men, du vet, slags halvveis. Og så, du vet, for kunden, sluttbrukeren, abonnenten, dette handler om å få et forsprang fordi CMO vil ha forsprang, ikke sant? Og så er det viktig å ikke ende opp med det vi kaller reduserende avkastning. Det begrensende forspranget kan føre til redusert avkastning. Det er grunnen til at det er ekstremt viktig å, du vet, stole på partene som kan sørge for at ett enkelt feil punkt ikke er et problem, og at datasikkerhet blir respektert. Så det vil kreve ganske mye endringsledelse. Og så til slutt - nesten ferdig, dette er det siste lysbildet - hvordan skal vi gjøre dette? Hvordan går flytten til skyen, flyttingen til SaaS, du vet, sømløs og enkel? Vel, ved å gjøre to ting: ta hensyn - levering - virkelig viktig, og ombordstigning, enda viktigere.
Eric Kavanagh: OK …
Gilbert Van Cutsem: Og i så fall er himmelen grensen. Takk skal du ha.
Eric Kavanagh: Ja. Det var bra. Jeg elsket de veldig provoserende ideene, jeg liker måten du ganske brakk ned. Det tror jeg gir mye mening. Og la oss gå videre og skyve Ashishs første lysbilde, så overlater jeg nøklene til WebEx til deg, Ashish. OK, gå videre. Bare klikk hvor som helst på det lysbildet og bruk pil ned på tastaturet. Der går du.
Ashish såledesoo: OK. Takk, Eric. Hei folkens, dette er Ashish og jeg skal fortelle dere om Qubole. Så, bare for å starte, Qubole, egentlig gir den store data som en tjenesteplattform. Det er en skybasert plattform som er vert i Amazon-skyen og Google-skyen, og vi leverer teknologi som Hadoop, Hive, Presto og en haug andre jeg skal snakke om, alt på en nøkkelferdig måte, slik at våre kunder i utgangspunktet kan komme seg ut av all forvirring i big data-infrastrukturverdenen eller gå ut av å faktisk drive en drift av denne infrastrukturen og virkelig fokusere mer på dataene deres og transformasjonene de vil gjøre på dataene sine. Så det er det Qubole handler om.
Når det gjelder de konkrete fordelene, en måte å tenke på Qubole på, du vet, selvfølgelig er det en totalentreprenør, selvbetjeningsplattform for big data-analyse og big data-integrasjon bygget rundt Hadoop, men mer grunnleggende, hva det gjør er at du vet, for alle big data-motorer som Hadoop, Hive, Presto, Spark, Chartly og så videre og så videre, gir det alle fordelene med skyen til disse big data-motorene og noen av de viktigste manifester som den bringer fra skyens perspektiv er, du vet, å gjøre infrastrukturen tilpasningsdyktig og ved å tilpasse, mener jeg både smidig og fleksibel arbeidsmengde som kjøres på noen av disse motorene, og også å gjøre disse motorene til mye mer selvbetjening og samarbeid i den forstand at du vet, Qubole gir grensesnitt der du kan bruke disse spesifikke teknologiene, ikke bare for din utvikling eller, du vet, utviklerorienterte oppgaver, men selv dine andre dataanalytikere kan også begynne å få fordelene med disse teknologiene til en selvbetjening grensesnitt.
Vi får mye, du vet, knyttet til nettopp dette, du vet, webinar, du vet, dette er et av våre perspektiver på hvilke fordeler med skyen som Qubole gir store data. Så hvis du bare gjør en sammenligning mellom hvordan du løper, sier Hadoop, og lar det arbeide i en innstilling på forhånd, i en forhåndsinnstilling, tenker du alltid når det gjelder statiske klynger, du vet, fikser du klynger, kan du størrelse dem til din høyeste bruk, og du holder dem der, og hvis du må endre dem, må du gå gjennom en hel prosess med anskaffelser, distribusjon, testing og så videre. Qubole endrer at ved å lage klynger helt på etterspørsel, er klyngene våre helt elastiske, vi bruker objektene som er lagret fra skyen for å faktisk lagre data, og klyngene kommer opp, og du vet, de kommer opp på bakgrunn av etterspørselen som genereres av brukerne, og de går bort når det ikke er etterspørsel. Så dette gjør infrastrukturen så mye mer smidig og fleksibel og tilpasningsdyktig til arbeidsmengdene dine.
Et annet eksempel på fleksibilitet er, du vet, i dag kan du ha opprettet dine statiske klynger her, du vet, med en viss arbeidsmengde i tankene, og hvis arbeidsmengden endres og infrastrukturen din nå må oppgraderes, trenger du kanskje mer minne på maskinene dine og sånt. Igjen, du vet, å gjøre dette på skyen gjennom Qubole for eksempel, gjør det enkelt. Du kan alltid leie nye, forskjellige typer maskiner og, du vet, få klynger, 100-knuteklynger opp og gå i løpet av et par minutter i motsetning til uker du måtte vente på Hadoop på forhånd.
Den andre viktige tingen som Qubole skiller seg fra på stedet er at Qubole egentlig er et tjenestetilbud, så alle verktøyene og infrastrukturen du trenger for å integrere tjenesten, trenger du ikke … uansett hvor du vet, det er først og fremst at du tar programvaren, du må kjøre den selv, du må integrere den selv og gjøre disse fordelene, alle fordelene med SaaS-modellen er en ledetråd til, du vet, hvordan Qubole tilbyr big data i motsetning til å kjøre Hadoop on-prem selv.
Dette lysbildet dekker vanligvis arkitekturen vår. Vi er selvfølgelig basert på skyen, vi lagrer dataene våre om objekter i skyen i skyen, Google sky og Google Compute Engine eller Amazon Web Services. Vi tar alle Hadoop-økosystemprosjektene, og rundt det har vi utviklet nøkkel-IP rundt autoskalering og selvstyring, vi har gjort mange skyoptimaliseringer for å få disse komponentteknologiene til å fungere veldig bra i skyen, som du vet, skyinfrastruktur er veldig forskjellig fra å bare kjøre ting på bare metall og en hel haug datakontakter for å gjøre det mulig å flytte data inn og ut av denne plattformen. Så det sammenligner skyplattformen og som gjør det mulig for deg, det er en nøkkel … nøkkelfunksjonen der, er hvordan du kan lage all selvbetjening slik at du ikke trenger å ha en sterk … du ikke har ikke et veldig stort operasjonelt fotavtrykk mens vi kjører dette, men vi slutter det sammen med data arbeidsbenken vår om dette er verktøy for analytikere, om dette er verktøy for datastyring, om dette er malverktøy og så videre og så videre slik at du kan gi fordelene med denne teknologien, ikke bare for utviklerne, men også andre forretningsbrukere og bedriften. Og selvfølgelig knytter vi også denne skyplattformen til verktøy som dere allerede bruker, enten disse er, du vet, bruksverktøy eller bare Tableau, eller om de bruker, vet du, mer datavarehus produkter som Redshift og også videre.
I dag kjører tjenesten i ganske stor skala, vi behandler faktisk nærmere 40 petabyte med data hver måned nå på tvers av vår kundebase. Våre klynger varierer i størrelse fra 10-node klynger til 1500 node klynger, og du vet, når det gjelder størrelsesområdet vi kan behandle og stort sett, etter beste kunnskap, kjører vi sannsynligvis noen av de største klynger på skyen når det gjelder Hadoop, og vi behandler til rundt 250 000 virtuelle maskiner i løpet av en måned over klyngene våre. Husk at modellen vår er klynger på forespørsel, som har enorme fordeler med tanke på å redusere driftsmengden din, forbedre din og så videre og så videre.
Til slutt, du vet, en av våre, du vet, dette er bare et utvalg av hvordan Qubole har vært transformerende for forskjellige selskaper. er et eksempel på vår klient. De var allerede på skyen, de kjørte for eksempel Elastic MapReduce på skyen, og databruken der var ganske begrenset. De vil ha omtrent 30 odde brukere som kunne bruke den teknologien. Med Qubole har de vært i stand til å utvide det til mer enn 200-odd brukere i selskapet som har sett utvidelse av store data-bruk tilfeller, og det er virkelig brakt, vet du, hva vi kaller definisjonen av en smidig big data-plattform og det har blitt veldig sentralt i mange av de analytiske arbeidsmengdene deres.
Så, bare for å stenge ute, vet du, det var en kort grunning på Qubole. I hovedsak er visjonen vår hvordan vi gjør bedrifter som er mye mer smidige rundt big data, og egentlig utnytter vi fordelene ved skyen og får dem til å bære store datateknologier rundt Hadoop, slik at våre kunder kan utnytte fordelene med smidighet og fordelene. av fleksibilitet og fordelene med selvbetjening i skyen for å bli så mye mer effektive for deres databehov. Så jeg vil stoppe der og overlate det tilbake til Eric.
Eric Kavanagh: OK. Det høres bra ut, og nå skal jeg overlevere det til Mike Miller fra Cloudant. Mike, jeg gir deg nøklene akkurat nå. Bare klikk på lysbildet, her går du. Ta den bort.
Mike Miller: Ser ut som om jeg har nøklene. Så jeg vil be om unnskyldning. Jeg mistet … Jeg tror jeg har glemt å sende noen skrifter med presentasjonen min. Så forhåpentligvis kan du se forbi det og forestille deg at det er vakkert. Men, ja, dette er gøy. Jeg har fått en lang liste her, provoserende ting som jeg hørte at jeg skrev ned at jeg er ivrig etter å komme tilbake til deg i panelet. Så jeg skal prøve å komme gjennom dette raskt.
Så jeg begynner med Cloudant. Cloudant er en database som en tjeneste, vår skyleverandør og faktisk har jeg ikke engang den nye logoen. Vi ble anskaffet av IBM for ikke så lenge siden. Og det er vi … Jeg skal snakke om tjenesten vår og spesielt fokusere på å prøve å gjøre brukerne og kundene våre smidige på en ganske annen måte enn forrige foredragsholder.
Cloudant leverer database som en tjeneste og andre datarelaterte tjenester for personer som bygger applikasjoner. Så vi engasjerer oss direkte med utviklere og vi fokuserer på operasjonelle eller OLTP-data i motsetning til analysene som vi har hørt fra Ashish tidligere. Og poenget der virkelig, hele verdien av Cloudant, som kan deles opp til å hjelpe brukerne våre å gjøre mer, og det er å bygge flere apper, vokse mer og sove mer. Jeg vil snakke om dem litt i detalj, men den generelle ideen her er at hvis du er en bruker, vet du, du er i et forretningsforetak, bygger du en ny applikasjon, legger en funksjon til eksisterende applikasjon eller nett oppstart av mobilen, bør du fokusere på kjernekompetansen din. Og tidligere, kanskje for opptil ti år siden, skulle IT være en særegen, du vet, konkurranse, beklager, konkurranseskader, selv å drive en database godt for å være et konkurransefortrinn. Er lettet over at de dagene er over! Og slik, måten vi virkelig prøver å samarbeide med brukerne våre er å oppmuntre dem til å bruke sammensatte tjenester, modulbaserte, gjenbrukbare, komposible med ideen som reduserer tid til markedsføring, øker skalerbarheten. Og den overordnede ideen her er at nettskyen ikke bare er, noe du skyver over på brukere, det er virkelig et marked … det er en markedsutvikling fordi måten folk bygger applikasjoner på, bruker applikasjoner, enhetene de kjører på og omfanget av data endres ganske radikalt de siste 5-10 årene. Det er virkelig understreket den eksisterende applikasjonsarkitekturen for å bygge apper, så vel som bare å håndtere dataene og analysenes arbeidsmengder offline. Og slik åpner det for en hel strøm av muligheter.
Så Cloudant er en distribuert database som en tjeneste, og den var unik, tror jeg, i starten at den virkelig ble levert med en mobilstrategi fra begynnelsen, og jeg vil snakke om dette i detalj, men tanken er at jeg skriver applikasjoner nå, du skriver ikke for bare en plattform, ikke sant? Du skriver for noe jeg kan kjøre en petabyte-skala i skyen, det må også kunne løpe jevnt på et skrivebord eller i en nettleser, og mer og mer vi ser ting, vi må kjøre på en mobil enhet eller en semi-tilkoblet enhet eller bærbar enhet eller noe vi omtaler som IOT. Og så tror jeg at, du vet, applikasjoner som kan takle godt og utnytte de forskjellige kundene, er utrolig konkurransedyktige i markedet, og det vi prøver å gjøre er å gjøre det enkelt for folk å enkelt API i en enkelt programmeringsmodell å skrive, til håndtere data på alle de forskjellige enhetene som har enormt forskjellig skala. 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. Hva tror du?
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. God. 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. Absolutt. 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. Yeah. Ikke noe problem. 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. Yeah. 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. Jeg vet ikke. 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. That's a very good question. 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. God. 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. Ha det fint. Ha det.
