Eric Kavanagh: Damer og herre, hej og velkommen igen til TechWise. Jeg hedder Eric Kavanagh. Jeg vil være din moderator for afsnit 3. Dette er et nyt show, som vi har designet sammen med vores venner fra Techopedia, et meget sejt websted, der åbenlyst fokuserer på teknologi, og selvfølgelig, her på The Bloor Group, fokuserer vi ganske meget på virksomheden teknologi. Så enterprise-software af alle slags, og hele TechWise-formatet blev designet til at give vores deltagere et rigtig godt hårdt kig på et specifikt rum. Så vi har for eksempel gjort Hadoop, vi analyserede i det sidste show og i dette særlige show, vi taler alt om sky.
Så det kaldes "The Cloud Imperative - Hvad, hvor, hvornår og hvordan." Vi skal tale med et par analytikere i dag og derefter tre leverandører. Så Qubole, Cloudant og Attunity er sponsorerne for dagens show. En stor tak for disse mennesker for deres tid og opmærksomhed i dag og en stor tak, selvfølgelig, til alle jer derude. Og husk, at som deltagere af disse shows spiller du en betydelig rolle. Vi vil have, at du stiller spørgsmål, engagerer dig, bliver interaktiv, fortæller os, hvad du synes, for helt klart hele formålet med showet her er at hjælpe jer med at forstå, hvad der sker derude i verdenen af cloud computing.
Cloud Imperativ Deck
Så lad os gå til højre. Første vært, din vært deroppe, Eric Kavanagh, det er mig, og så har vi Dr. Robin Bloor, der ringer ind fra en lufthavn, som en kendsgerning, og vores gode ven Gilbert, Gilbert Van Cutsem, en uafhængig analytiker, deler også med nogle tanker med dig. Så hører vi fra Ashish Thusoo, administrerende direktør og medstifter af Qubole. Vi hører fra Mike Miller, chefforsker hos Cloudant og endelig fra Lawrence Schwartz, VP for Marketing hos Attunity. Så vi har en hel masse indhold oprettet til dig i dag.
Så skyen - edikt ovenfra - dette er et koncept, der kom til mig den anden dag, da jeg tænkte på dette. Virkelig, cloud computing er bare enormt i disse dage. Jeg mener, det er virkelig ret fascinerende at se udviklingen af dette, og et af eksemplerne, jeg ofte giver, er i selve webcasting-teknologien. Selvfølgelig hørte de af jer, der ringede ind tidligt, nogle interessante tekniske udfordringer. Det er et problem med skyen, det ændrer formater, ændrer standarder, ændrer grænseflader, og nogle gange når du prøver at koble to forskellige områder sammen, får du nogle problemer, får du nogle problemer. Så dette er faktisk en af de ting, man skal bekymre sig om med cloud computing. Vær forsigtig med arkitektur! Det kan du se på det sidste kuglepunkt.
En af de ting, vi gør, ligesom en side-note her, til vores webcast, vi har en separat telefonkonference-leverandør. Så bruger vi WebEx. Vi bruger ikke WebEx-lyden, fordi ærligt talt, engang brugte vi WebEx-lyd for mange år siden, og den styrtede ned og brændte på en meget ubehagelig måde. Vi er således ikke villige til at løbe denne risiko igen. Så vi bruger vores eget lydoptagelsesfirma kaldet Arkadin som en kendsgerning, og vi sy sammen i realtid alle disse forskellige løsninger. Og ideen er, at vi så kunne sende dig en e-mail med en separat e-mail-applikation med diaserne, for eksempel WebEx ville være gået ned, vi fortæller jer alle at ringe ind, vi vil e-maile diaserne og bare gå igennem mere eller mindre uden WebEx-slags miljøer. Altså, den måde, du kan omgå denne slags problemer på, men disse slags problemer er overalt.
Men der er mange fordele ved sky. Det er klart, det er en lav adgangsbarriere, du kan se på plakatbarnet til cloud computing er selvfølgelig salesforce.com, der lige har revolutioneret forretningen, specifikt salgstyrkens automatisering. Men så har du ting som Marketo og iContact og Constant Contact og Sailthru, og, godhed elskværdig, hvad angår markedsføring og salgsautomatisering, der er mange værktøjer, men det er ikke alt, hvad der er. HR bringer det til hele skyspillet, analytics er i skyspillet. Se på det lidt kendte firma derude Amazon Web Services, hvad de laver med cloud computing - det er bare massivt. Og jeg hørte et godt citat her om dagen fra en fyr, vi laver en masse arbejde med David, som nu er over hos Cisco, faktisk det firma, der købte WebEx. Ikke sikker på, at de har investeret så meget, som jeg gerne vil have, at de skulle have i WebEx, men det er ikke rigtig min beslutning, er det? Men han er i Cisco i disse dage, og han havde et meget sjovt, bare lille bud, og det er, "der er ikke en sky, der er mange skyer, " og det er nøjagtigt rigtigt. Der er masser og masser af skyer derude. Faktisk er enhver skyudbyder sin egen sky. Så en af udfordringerne i disse dage er at forbinde sky, ikke? Hvis du er salgsstyrke, ville det ikke være rart at oprette forbindelse direkte til iContact og Constant Contact og til LinkedIn, for eksempel, og måske til Twitter og andre miljøer, fik andre skyer derude bare fast forretningsløsninger, der giver mening for dig og din virksomhed.
Så dette er nogle problemer, du skal huske på, men skyen er her for at blive. Bare ved, at on-premiss-software er her for at blive. Så hvad har vi at finde ud af i virksomheden eller nogen endda små til mellemstore virksomheder, hvordan definerer du din arkitektur og vedligeholder den sådan, at du kan udnytte skyen uden at skabe en kæmpe et andet sted uden for din kontrol? Så naturligvis udviklede hele datalagringsindustrien sig omkring et behov for at konsolidere kritisk information for at analysere denne information og træffe bedre beslutninger.
Nå, nu har Amazon Web Services Redshift. Det er en af de største webcasts, vi nogensinde har gjort, var med Redshift. Det er en ret stor aftale. De ændrer dynamikken, de ændrer prisstrukturer. Du kan se, når din prisfastsættelse går ned på traditionel licens til virksomhedssoftware til dels på grund af cloud computing og delvis fordi disse mennesker er derude og sænker prispointet og lægger pres på prisen. Så det er gode nyheder for slutbrugerne. Det er noget, man skal huske, bestemt for enhver derude, der prøver at bruge nogle af disse teknologier. Så det er noget at huske på, og vi vil tale om det i dag på showet.
Så analytiker Dr. Robin Bloor bliver vores første analytiker for dagen. Så jeg vil gå foran og skubbe hans første dias og overdrage tasterne til ham. Robin, jeg tror, du er her et sted, der er du. Og med det vil jeg aflevere det, og gulvet er dit!
Dr. Robin Bloor: Okay, Eric. Tak for introduktionen. Jeg stødte på… for et par dage siden stødte jeg på en undersøgelse af forbrugere, der faktisk stillede spørgsmålet - tror du, at stormvejr forstyrrer cloud computing? Og mere end 50 procent af dem sagde ja. Jeg tænkte bare, at jeg ville fortælle dig, at det ikke gør det, hvis du er en af dem, der tror på det. Og så er det lidt som at tro, at du ved, at når du har sne i fjernsynet, er det fordi det sneer udenfor.
Cloud, du ved, en af tingene er, at det er en slags, du ved, en vigtig, hvis du kan lide, en enkel detalje af skyen er, at skyen faktisk er et datacenter på en eller anden måde, eller en hvilken som helst særlig skytjeneste er et datacenter. Det eneste er, det er et andet datacenter end den traditionelle sky. Så jeg skulle tale i oversigt om skyen, så som din sikkerhedskopi for at gå nærmere ind på skybrugen, fordi det ikke er nogen mening i at dække den samme grund.
Så det første slags punkt, som jeg gerne vil gøre, er, at skyen er en tjeneste, ved du? Og en af de ting, der faktisk sker på grund af cloud computing, er, at der er en … ja, jeg kalder mærkenes død, en hel række softwaremærker havde en frygtelig masse magt og fortsætter med at have magt inden for virksomhedernes computing. Når du først kommer til skyen, har de ikke meget magt længere, ved du? Når du køber en skytjeneste, er du ligeglad med applikationen, selvfølgelig er du ligeglad med det serviceniveau, skyen vil give dig, du ønsker ikke, at skytjenesten svigter ofte, du er interesseret i brugsomkostninger, og du interesserer dig for disse ting, fordi dette er en service, men det, du ikke interesserer dig mere, er, at du ikke er interesseret i, hvilken hardware den kører på, du er ligeglad med, hvad netværksteknologien er, du er ligeglad med, hvad operativsystemet er det kører er, du er ligeglad med, hvad filsystemerne er, du er ikke engang ligeglad med, hvad databasen er, og som faktisk bruges specifikt af en given database-tjenester ud af skyen, ved du? Og virkningen af det på en måde er, at skyen er en frygtelig masse softwaremærker, der ikke har nogen reel værdi i skyen, fordi du ved, du går ind i skyen på en eller anden måde for noget, der er en service og ikke længere en produkt. Så jeg troede, jeg kunne gøre et par lysbilleder af grunde til ikke at bruge skyen, ved du, og dette er alt sammen, hvis du vil, du ved, blodige enkle, indlysende grunde, men nogen var nødt til at oplyse dem, så jeg tænkte jeg ville.
Så grunde til mig … ikke til at bruge skyen - hvis de ikke kan levere den slags data og processtyring, du vil have dem, ved du, så opfylder det simpelthen ikke dine kriterier. Hvis de ikke kan give dig den præstation, du ønsker, vil den ikke opfylde kriterierne. Hvis skyen giver dig fleksibiliteten med hensyn til, hvordan du kan flytte ting rundt, opfylder det ikke et kriterium. Det er bare åbenlyse grunde til, at bestemte skytjenester ikke ville passe til en frygtelig masse mennesker derude bortset fra at udføre virksomheds computing.
Du gør muligvis ikke det, fordi du kan gøre det billigere. Skyen er ikke altid den billigste mulighed. Nogle mennesker synes at tro, fordi det ofte er en billig mulighed, at det altid vil være billigere, det er ikke altid billigere. Og den anden ting er, at hvis du tager en applikation fra en sky, integrerer den ikke godt med det, du laver, så er du sandsynligvis ikke nødt til at gå videre med det, og det er, du ved, grunde til at vende dig væk .
Her er grundene til at vedtage. Du ved, en af de ting, du kan gøre i skyen, temmelig skudsikker, er prototyperaktivitet. Hvis du enten kan prototype i skyen og implementere i datacentret, er det helt levedygtigt, og der er enorme mængder af mennesker, der gør det. Du kan uploade arbejde fra datacenteret med ikke-kritiske applikationer, fordi de sandsynligvis vil være i stand til at finde en slags skytjenester, der opfylder dit serviceniveau til de ukritiske ting. Og du kan uploade specifikke applikationer som salesforce.com og lignende tilbud til det, du kender, standardapplikationerne. Alle slags har en kapacitet i dette område, og feltet er ikke specialiseret, og du ved, det traditionelle … uanset hvad der er tilgængeligt i skyen vil sandsynligvis være det, du går med.
Så den sidste ting, som jeg ønskede at sige, det er en ret interessant ting, er, når man faktisk ser efter skyen, en måde at forstå på er lige som en række stordriftsfordele. Hele pointen er, at du ved, at køre et datacenter derude, og at du kommer til at ringe til det datacenter fra et eller andet sted og bruge det, og derfor ville det være bedre, det er bedre at være i hovedsagen billigere end hvis du gør det selv. Så du ved, det handler virkelig om stordriftsfordele.
Cloududbydere, de vælger datacenters placering, og det bedste sted at finde datacenteret ligger lige ved siden af et kraftværk, og især lige ved siden af et billigt kraftværk. Så et kraftværk nordpå, der tilfældigvis er vandkraft eller lignende. Det er normalt det billigste, ved du? Du kan faktisk finde datacenteret der, og du finder ud af, at det er lettere. Det er billigere at ansætte folk på sådanne steder, end det er i centrum af New York eller San Francisco. Du kan standardisere hele anlægget med hensyn til aircondition og strøm. Det sparer dig meget, fordi det betyder, at du ved, du kan give ud en hel bygning til det, og det er hvad nøjagtigt alle skyoperatører gør. De standardiserer netværkshardware, de standardiserer den computerhardware, de bruger, normalt vare x86-kort, ofte samler de dem selv. Så nogle er endda faktisk ved at opbygge det hele. De vil bruge Amazon-software, som de kan, fordi det faktisk ikke betyder nogen omkostning at vedtage det. De vil standardisere i al software. Så de vil aldrig opgradere noget bortset fra at opgradere alt på én gang. De vil organisere støtten. Så de vil betale støtte til mange forskellige udbydere, der bare har deres egen supportfacilitet. De vil have skalere- og skalereevne i den forstand, at de vil køre mere, end du nogensinde ville køre den slags service, og de vil overvåge deres brug på en måde, som de fleste datacentre ikke kan, fordi de kører kun en standardiseret service, men de fleste datacentre kører en hel række ting. Og det er, hvad skyen egentlig handler om, og som på en bestemt måde kan definere, om den interesserer dig, eller om den ikke gør det til et bestemt program. Så du ved, min slags grove tommelfingerregel er, at hvor stordriftsfordele er mulige, overtager skyen før eller senere. Men den måde, innovation og fleksibilitet og en meget specifikke ting, du selv går på, kan virkelig ikke. Skyen bliver altid næstbedst.
Okay. Lad mig give det tilbage til Eric eller videre til Gilbert.
Eric Kavanagh: Okay, Gilbert, jeg giver dig nøglerne her til WebEx. Stå ved. Klik bare hvor som helst på diaset og brug pilen ned på dit tastatur.
Gilbert Van Cutsem: Jeg tror, jeg har kontrol.
Eric Kavanagh: Du har kontrol.
Gilbert Van Cutsem: Okay. Nu sker det. Skyimperativet - himlen er grænsen, er det en urban legende, eller hvad ville du synes om det? Dette er kun et par tal og ting at overveje.
For det første, ved "hvad" -fronten, ved du, som vi alle ved, jeg tror ikke, at nogen er i tvivl om dette. SaaS-ification er her for at forblive, fordi softwaren faktisk aldrig dør, den flytter blot til skyen, ikke? Jeg tror, jeg sagde det før i den forrige udgave af dette. Åh nej, eller Eric sagde det for mig i en tidligere udgave. Og jeg tror, at den åbenlyse grund, og dette også går tilbage til Robin på en måde, er, at virksomhedernes tidslinje er ret let. CMO har altid brug for det hele, og han har brug for det nu. Så han handler alt om tid til at markedsføre. Så trist, det er en god undskyldning for det på en måde for ham. CIO er dog lidt nervøs for SaaS og skyer, fordi du ved, hele elasticitetsproblemet betyder, at det, der går op, også skal komme ned. Du skal være klar til at skalere ud, men også til at skalere tilbage. Så han er lidt nervøs over det. Finansdirektøren er ikke nervøs, ikke mere end den sædvanlige, men han ligner: "Hej, dette er … hvor meget vil dette sætte os tilbage?" Det er, du ved, den berygtede kapitaludgift kontra OPEX-diskussionen. Det er temmelig gammelt, men det er meget, du ved, meget vigtigt i denne verden. Og så er sidst, men ikke mindst, CEO, selvfølgelig. Han siger: "Åh! Risikobegrænsning! Gutter, I er alle glade for, men er vi klar til dette?" Fordi risiko er det, han tænker på.
Så hvad er risikoen? Bare et par tanker, ikke? Vi beskæftiger os her med tankeledelse, men på en uafsluttet sti, fordi det hele er temmelig nye ting, alt forholdsvis nylige ting. Vi har ikke så mange datapunkter, hvis du tænker over det. Og så, også på risikosiden, er vi nødt til at beskæftige os med ind-boarding, du ved, folk, der underskriver aftaler, ser ud som, "Ja, det er det, vi vil have, vejen til at gå, " de tilmelder sig, men så det er ikke nok. Du ved, du er nødt til at komme ombord på folk, og det, kan du huske filmene? Tilbage i oversættelse, det er lidt af, ved du, hvad ind-boarding handler om. Og så, som Robin netop sagde, ved du, at on-prem ikke nødvendigvis forsvinder med det samme. Så du er nødt til at integrere begge verdener. Det er en hybrid verden. Og så, hvordan skal du gøre det? Det er 80-20, 80-20-reglen Pareto, er det okay? Er det godt nok? Og derefter affaldet ind / affald, når du tilslutter systemerne. Er det okay? Er det holdbart? Fordi, du ved, skal du migrere, skal du kortlægge din virksomhed til rotsystemet, hvordan skal du gøre det? Og så er den sidste, som jeg synes er ekstremt vigtig, multitenantarkitekturer, hvilket betyder, at databeskyttelse på dine egne data, nogle gange kaldes det "ejer dine egne data", bliver meget vigtig, ved du? Hundrede mennesker, der bruger det samme system, en database sidder under systemet, hvem skal se mine data? Bare mig, ikke? Er du helt sikker på det? Datasikkerhed, datasikkerhed hjælper eksperter. Hvis du er CIO, bringer det "jeg" tilbage til CIO, fordi du nu er ansvarlig for information. Det er ret interessant, hvis du er CIO.
Så lad os tale lidt om "hvorfor." Så den strategiske hensigt med alt dette er meget, meget enkelt, synes jeg. Hvis du er en abonnent, er der markedspress. Hvis du er en udbyder, er der et konkurrencepres. Hvis du har kammerater, er der gruppepress. Hvis du er en abonnent, er det bare markedspsykologien. Alle vil gå til skyen, SaaS eller hvad du end kalder det, sky SaaS, vi har alle brug for og vil hen dertil. Og årsagen er normalt økonomisk. Det er den åbenlyse grund, men hvis du tænker på det økonomiske aspekt, kommer du ind i det, jeg kalder regningen-mod-budgettet-paradokset. Skal du tage et abonnement, alt-du-kan-spise-systemer, $ 50, $ 500 om måneden eller lignende, eller drømmer du om brug baseret, så du kun betaler for det, du virkelig bruger? Og så, hvordan fungerer det, brugsbaseret, forbrugsbaseret? Skal du måle alle de ting? Det sker sandsynligvis ikke med det samme. Så du ender med en hybridmekanisme, dvs. at jeg betaler 200 om måneden og måske lejlighedsvis 500, fordi jeg er nødt til at betale for det ekstra forbrug. Retainer Plus, det går sandsynligvis efter min mening vejen at gå.
Men der er også noget, som jeg kalder den skjulte hensigt på den brede front, og jeg tror, at du ved, dette er absolut ægte. Det er ændringen af kontrol, det er CIO versus CMO, magtskiftet eller magtkampen mellem CMO, "Jeg vil have det hele og jeg vil have det nu, " og CIO, der siger ligesom, "Hej, dette er alt om data, ved du? Jeg plejede at køre for 20 år siden, det handlede om hardwaresystemer. For ti år siden handlede det om applikationer. I dag handler det om dataene. Og siden jeg er CIO - information - handler det om mig. Jeg har kontrol. " Så det er en slags magtskift eller magtkamp, som jeg mener, at der foregår lige nu mellem disse to, CMO og CIO.
I sidste ende er alt dette så ungt, at ingen rigtig ved, om vi er i innovatortypen miljø eller i den tidlige adoptertype miljø. Jeg tror, vi er i den tidlige adoptertype af miljø, ikke det tidlige flertal, bare den tidlige adopter, men, du ved, slags halvvejs. Og så, ved du, for kunden, slutbrugeren, abonnenten, dette handler om at få et forspring, fordi CMO vil have hovedstart, ikke? Og så er det vigtigt at ikke ende med det, vi kalder mindskende afkast. Det begrænsende hovedstart kan muligvis føre til formindsket afkast. Derfor er det ekstremt vigtigt at, du ved, finde, stole på parterne, der kan sikre sig, at et enkelt mislykkelsespunkt ikke er et problem, og at datasikkerhed overholdes. Så det kræver en hel del ændringsstyring. Og så til sidst - næsten færdig, dette er det sidste lysbillede - hvordan skal vi gøre det? Hvordan går bevægelsen til skyen, flytningen til SaaS, du ved, problemfri og let? Nå ved at gøre to ting: være opmærksom - levering - virkelig vigtig og ombordstigning, endnu vigtigere.
Eric Kavanagh: Okay …
Gilbert Van Cutsem: Og i så fald er himlen grænsen. Tak skal du have.
Eric Kavanagh: Ja. Det var godt. Jeg elskede de meget provokerende ideer, jeg kan godt lide den måde, du på en måde brækkede alt det ned på. Det synes jeg giver meget mening. Og lad os gå foran og skubbe Ashishs første lysbillede, så overleverer jeg nøglerne til WebEx til dig, Ashish. Okay, gå videre. Klik bare hvor som helst på diaset og brug pilen ned på dit tastatur. Værsgo.
Ashish såledesoo: okay. Tak, Eric. Hej folkens, dette er Ashish, og jeg vil fortælle jer om Qubole. Så bare for at starte, Qubole, det giver i det væsentlige big data som en serviceplatform. Det er en skybaseret platform, der er vært i Amazon skyen og Google skyen, og vi leverer teknologi som Hadoop, Hive, Presto og en masse andre, jeg skal tale om, alt sammen på nøglefærdige måde, så vores klienter i det væsentlige kan komme ud af al forvirring i verdenen med stor datainfrastruktur eller gå ud af at køre en infrastruktur, og virkelig fokusere mere på deres data og de transformationer, de vil gøre på deres data. Så det er hvad Qubole handler om.
Med hensyn til de konkrete fordele, en måde at tænke på Qubole på, ved du selvfølgelig, at det er en nøglefærdig, selvbetjeningsplatform til big data-analyse og big data-integration bygget omkring Hadoop, men mere grundlæggende, hvad det gør er, at du ved, for alle big data-motorer som Hadoop, Hive, Presto, Spark, Chartly og så videre og så videre, bringer det alle fordelene ved skyen til disse big data-motorer og nogle af de nøglemanifester, det bringer fra skyens perspektiv er, at du ved, at gøre infrastrukturen tilpasningsdygtig og ved at tilpasse, mener jeg både smidig som fleksibel over for arbejdsmængderne, der køres på en af disse motorer, og også at gøre disse motorer til meget mere selvbetjening og samarbejde i den forstand, ved du, Qubole leverer grænseflader, hvor du kan bruge disse bestemte teknologier ikke kun til din udvikling eller, du ved, udviklerorienterede opgaver, men selv dine andre dataanalytikere kan også begynde at få fordelene ved disse teknologier til en selvbetjening grænseflade.
Vi får meget, du ved, hvad angår netop denne, du ved, webinar, du ved, dette er et af vores perspektiver på, hvilke fordele ved skyen, som Qubole bringer til store data. Så hvis du bare foretager en sammenligning mellem hvordan du kører, siger Hadoop og lader det arbejde belastes i en on-prem-indstilling, i en on-prem-indstilling, tænker du altid med hensyn til statiske klynger, ved du, fikser du din klynger, måler du dem måske efter din maksimale anvendelse, og du holder dem der, og hvis du skal ændre dem, er du nødt til at gennemgå en hel proces med indkøb, distribution, test og så videre og så videre. Qubole ændrer, at ved at oprette klynger helt på efterspørgsel, er vores klynger helt elastiske, vi bruger objekter, der er gemt fra skyen til faktisk at gemme data, og klyngerne kommer op, og du ved, de kommer op på grundlag af den efterspørgsel, der genereres af brugerne, og de forsvinder, når der ikke er efterspørgsel. Så dette gør infrastrukturen så meget mere fleksibel og fleksibel og tilpasningsdygtig til dine arbejdsmængder.
Et andet eksempel på fleksibilitet er, ved du, i dag har du måske oprettet dine statiske klynger her, du ved, med en vis arbejdsbyrde i tankerne, og hvis dine arbejdsmængder ændres, og din infrastruktur nu skal opgraderes, har du måske brug for mere hukommelse på dine maskiner og lignende ting. Igen, ved du, at gøre dette på skyen gennem Qubole for eksempel gør det enkelt. Du kan altid leje nye, forskellige typer maskiner og, du ved, få klynger, 100-knudepunkter op og køre på et par minutter i modsætning til uger, som du var nødt til at vente på Hadoop på forhånd.
Den anden centrale ting, som Qubole adskiller sig fra i stedet, er, at Qubole i det væsentlige er som et servicetilbud, så alle de værktøjer og den infrastruktur, du har brug for for at integrere tjenesten, behøver du ikke … uanset hvor du er klar over det, er det først og fremmest du tager softwaren, du er nødt til at køre det selv, du er nødt til at integrere det selv og gøre disse alle disse fordele, alle fordelene ved SaaS-modellen er en ledetråd til, du ved, hvordan Qubole tilbyder big data i modsætning til at køre Hadoop on-prem af dig selv.
Denne dias dækker generelt vores arkitektur. Vi er selvfølgelig baseret på skyen, vi gemmer vores data om objekter i skyen i skyen, Google sky og Google Compute Engine eller Amazon Web Services. Vi tager alle Hadoop-økosystemprojekter, og omkring det har vi udviklet centrale IP omkring auto-skalering og selvstyring, vi har udført en masse skyoptimeringer for at få disse komponentteknologier til at fungere rigtig godt i skyen, da du ved, sky infrastruktur er meget forskellig fra bare at køre ting på bare metal og en hel masse datakonnektorer for at gøre det muligt at flytte data ind og ud af denne platform. Så det sammenligner skyplatformen, og det muliggør, at du ved, det er en nøgle … nøglefunktionen der er, hvordan man gør al den selvbetjening, så du ikke behøver at have en stærk … du don 't har et meget stort operationelt fodaftryk, mens du kører dette, men vi binder det sammen med vores dataarbejde, om dette er værktøjer til analytikere, om dette er værktøjer til datastyring, om dette er skabeloner og så videre og så videre, så du kan bringe fordelene ved denne teknologi, ikke kun for udviklerne, men også andre forretningsbrugere og virksomheden. Og selvfølgelig binder vi også denne skyplatform til værktøjer, som I måske allerede bruger, hvad enten disse er, du ved, brugsværktøjer eller bare Tableau, eller om de bruger, du ved, mere datalagringstype af produkter som Redshift og osv. og så videre.
I dag kører tjenesten i ret stor skala, vi behandler faktisk tæt på 40 petabyte med data hver måned nu på tværs af vores klientbase. Vores klynger varierer i størrelse fra 10-knude-klynger til 1500-knude-klynger, og du ved, hvad angår det skalaudvalg, som vi kan behandle og stort set, så vidt jeg ved, kører vi sandsynligvis nogle af de største klynger på skyen hvad Hadoop angår, og vi behandler til omkring 250.000 virtuelle maskiner i en enkelt måned på tværs af vores klynger. Husk, vores model er klynger på efterspørgsel, som har enorme fordele med hensyn til at reducere dine operationelle arbejdsmængder samt forbedre din og så videre og så videre.
Endelig ved du, en af vores, du ved, dette er blot en prøveudtagning af, hvordan Qubole har været transformerende til forskellige virksomheder. er et eksempel på vores klient. De var allerede på skyen, de kørte for eksempel Elastic MapReduce på skyen, og dataforbruget der var ret begrænset. De ville have omkring 30-ulige brugere, der kunne bruge denne teknologi. Med Qubole har de været i stand til at udvide det til mere end 200 ulige brugere i virksomheden, som har set udvidelse af big data-brugssager, og det er virkelig bragt, ved du, hvad vi kalder definitionen af en smidig big data-platform, og at det er blevet virkelig centralt for en masse af deres analytiske arbejdsmængder.
Så bare for at lukke ud, ved du, det var en kort grundmand på Qubole. I det væsentlige er vores vision, hvordan vi gør virksomheder, der er meget mere smidige omkring big data og i det væsentlige, vi udnytter fordelene ved skyen og bringer dem til at bære store datateknologier omkring Hadoop, så vores kunder kan udnytte fordelene ved agility og disse fordele af fleksibilitet og fordelene ved selvbetjening i skyen for at blive så meget mere effektive til deres databehov. Så jeg vil stoppe der og overlevere det tilbage til Eric.
Eric Kavanagh: Okay. Det lyder godt, og nu overleverer jeg det til Mike Miller fra Cloudant. Mike, jeg giver dig nøglerne lige nu. Klik bare på diaset, her går du. Tage det væk.
Mike Miller: Det ser ud til, at jeg har nøglerne. Så jeg vil undskylde. Jeg mistede … Jeg tror, jeg har glemt at sende nogle skrifttyper med min præsentation. Så forhåbentlig kan du se forbi det og forestille dig, at det er smukt. Men ja, det er sjovt. Jeg har en lang liste her, provokerende ting, som jeg hørte, at jeg skrev ned, at jeg er ivrig efter at vende tilbage til dig i panelet. Så jeg vil prøve at komme igennem dette hurtigt.
Så jeg begynder med Cloudant. Cloudant er en database som en tjeneste, vores skyudbyder og faktisk har jeg ikke engang det nye logo. Vi blev købt af IBM for ikke længe siden. Og så er vi … Jeg vil tale om vores service og især fokusere på at forsøge at gøre vores brugere og kunder smidige på en ret anden måde end den foregående taler.
Cloudant leverer database som en service og andre datarelaterede tjenester for personer, der bygger applikationer. Så vi samarbejder direkte med udviklere, og vi fokuserer på operationelle eller OLTP-data i modsætning til analyserne, som vi tidligere har hørt fra Ashish. Og pointen der virkelig, Cloudants hele værdi, der kan opdeles i at hjælpe vores brugere med at gøre mere, og så det er at opbygge flere apps, vokse mere og sove mere. Jeg vil tale om dem i en smule detaljer, men den generelle idé her er, at hvis du er en bruger, ved du, du er i en forretningsvirksomhed, bygger du en ny applikation, tilføjer en funktion til den eksisterende applikation eller web mobil opstart, skal du fokusere på din kernekompetence. Og tidligere, måske op til et årti siden, skulle IT være en kendetegnet, du ved, konkurrence, beklager, konkurrencebeskadigelse, selv køre en database godt for at være en konkurrencefordel. Er lettet over, at disse dage er forbi! Og så, hvordan vi virkelig forsøger at arbejde med vores brugere er at tilskynde dem til at bruge sammensatte tjenester, modulopbyggede, genanvendelige, komposible med ideen, der reducerer tid til markedsføring, øger skalerbarheden. Og den overordnede idé her er, at sky ikke bare, du ved, noget nyt bliver skubbet på brugerne, det er virkelig et marked … det er en markedsudvikling, fordi måden folk bygger applikationer, forbruger applikationer, de enheder, som de kører på og omfanget af data ændres temmelig radikalt i de sidste 5-10 år. Det er virkelig understreget den eksisterende applikationsarkitektur til opbygning af apps såvel som bare at håndtere disse data og analytiske arbejdsbelastninger offline. Og så åbner det en hel strøm af muligheder.
Så Cloudant er en distribueret database som en service, og den var unik, tror jeg, i starten, at den virkelig blev leveret med en mobil strategi fra begyndelsen, og jeg vil tale om det detaljeret, men tanken er, at der skrives applikationer nu, skriver du ikke kun for en enkelt platform, ikke? Du skriver for noget jeg kan køre en petabyte skala i skyen, det skal også være i stand til at køre glat på et skrivebord eller i en browser og mere og mere vi ser ting, vi er nødt til at køre på en mobilenhed eller en semi-tilsluttet enhed eller bærbar enhed eller noget, vi betegner som IOT. Og så tror jeg, at du ved, applikationer, der kan håndtere og udnytte de forskellige klienter, er utroligt konkurrencedygtige på markedet, og hvad vi forsøger at gøre, er at gøre det enkelt for folk at enkelt API i den enkelt programmeringsmodel at skrive, til håndtere data på alle disse forskellige enheder, der har meget forskellig 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. Hvad synes 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. Godt. 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. Absolut. 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. Intet 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. 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. Jeg ved 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. Det er et meget godt spørgsmål. 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. Godt. 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. Pas på. Hej hej.
