Eric Kavanagh: Senyores i senyors, hola i benvinguts de nou a TechWise. Em dic Eric Kavanagh. Seré el vostre moderador per a l’episodi 3. Es tracta d’un nou espectacle que hem dissenyat amb els nostres amics de Techopedia, un lloc web molt maco que òbviament se centra en la tecnologia i, per descomptat, aquí al grup Bloor, ens centrem força en l’empresa. tecnologia Així doncs, es va dissenyar tot tipus de programes empresarials i tot el format TechWise per oferir als assistents una bona visió dura en un espai específic. Així, doncs, hem fet Hadoop per exemple, hem fet analítiques a l’últim espectacle i en aquest programa en particular, parlem tot sobre núvol.
Per tant, es diu "L'imperatiu del núvol: què, on, quan i com". Parlarem amb un parell d'analistes avui i tres venedors. Per tant, Qubole, Cloudant i Attunity són els patrocinadors de l’espectacle actual. Un gran agraïment per aquestes persones pel seu temps i atenció avui dia i un gran gràcies, per descomptat, a tots els que esteu allà fora. I tingueu en compte que, com a assistents a aquests espectacles, teniu un paper important. Volem que feu preguntes, que us impliqueu, que interactueu, que ens informeu del que penseu perquè, òbviament, tot el propòsit de l’espectacle aquí és ajudar-vos a comprendre el que hi ha al món del cloud computing.
El pont imperatiu del núvol
Per tant, anem cap al llarg. Primer amfitrió, el vostre amfitrió allà, Eric Kavanagh, sóc jo, i el doctor Robin Bloor ens va trucar des d'un aeroport. De fet, el nostre bon amic Gilbert, Gilbert Van Cutsem, analista independent, també compartirà alguns pensaments amb tu. A continuació, escoltarem Ashish Suchoo, CEO i cofundador de Qubole. Sentirem de Mike Miller, científic principal de Cloudant i finalment de Lawrence Schwartz, vicepresident de màrqueting de Attunity. Així, avui tenim una gran quantitat de continguts alineats.
Per tant, el núvol (edicte des de dalt) és un concepte que em va venir l’altre dia quan estava pensant en això. Realment, la informàtica en núvol és tan gran avui dia. Vull dir, és realment fascinant veure l'evolució d'aquestes coses i un dels exemples que solc donar és a la tecnologia de transmissió web. Per descomptat, els que vàreu marcar ja que vàreu escoltar alguns reptes tècnics interessants. Aquest és un problema amb el núvol, és que canvia, els formats canvien, canvien els estàndards, canvien les interfícies i, de vegades, quan intenteu connectar dues àrees diferents junts, teniu alguna dificultat, podreu tenir problemes. Per tant, aquesta és una de les coses que més us ha de preocupar amb la computació en núvol. Compte amb l’arquitectura! Podeu veure-ho a l’últim punt de bala.
Una de les coses que fem, tan sols com una nota lateral aquí, per a la nostra transmissió web, tenim un proveïdor independent de conferències de telèfon. Després fem servir WebEx. No utilitzem l’àudio WebEx perquè francament, una vegada que vam utilitzar l’àudio WebEx fa anys i es va estavellar i cremar d’una manera més desagradable. Per tant, no estem disposats a tornar a córrer aquest risc. Per tant, fem servir la nostra pròpia empresa de gravació d'àudio anomenada Arkadin i, en temps real, agrupem totes aquestes solucions diferents. I la idea és que després us puguem enviar un correu electrònic amb una aplicació de correu electrònic independent amb les diapositives per si, per exemple, WebEx s’hauria estavellat, us diem a tots que marqueu, us enviarem un correu electrònic a les diapositives i només hi passéssim més o menys sense el tipus d’ambients WebEx. Per tant, la manera com podeu trobar aquest tipus de problemes, però hi ha tot això.
Però, hi ha molts avantatges per al núvol. Viousbviament, és una barrera baixa per a l’entrada, es pot mirar el fill del cartell de la computació en núvol és salesforce.com, per descomptat, el que només va revolucionar el negoci, concretament l’automatització de la força de vendes, òbviament. Però, aleshores, teniu coses com Marketo i iContact i Constant Contact i Sailthru, i, per excel·lència, en termes d’automatització de màrqueting i vendes, hi ha tones d’eines, però no és tot el que hi ha. La RRHH arriba a tot el joc al núvol, les analítiques es troben en el joc del núvol. Mireu aquella empresa poc coneguda que hi ha a Amazon Services Web, el que fan amb la informàtica en núvol: és simplement massiu. I vaig escoltar una gran cita l’altre dia d’un home que fem molta feina amb David que ara acaba a Cisco, de fet, l’empresa que va comprar WebEx. No estic segur que hagin invertit tant com voldria que tinguessin a WebEx, però aquesta no és la meva decisió, no? Però, està a Cisco aquests dies i tenia una cita molt divertida, simplement pithy, i és a dir, "no hi ha un núvol, hi ha molts núvols", i és així. Hi ha molts núvols. De fet, cada proveïdor de núvols és el seu propi núvol. Aleshores, un dels reptes actuals és connectar el núvol, oi? Si sou força de vendes, no estaria bé connectar-vos directament amb iContact i el Contacto Constant i a LinkedIn, per exemple, i potser a Twitter i altres entorns, altres núvols allà només arreglen solucions empresarials que tenen sentit per a vosaltres. i la vostra empresa.
Així doncs, es tracta d’alguns problemes a tenir en compte, però el núvol està aquí per quedar-se. Només heu de saber que sobre això, el programari on-premissa és aquí per romandre. Així, què hem de descobrir en l'empresa o en empreses de mida petita o mitjana, com definiu la vostra arquitectura i la manteniu de manera que pugueu aprofitar el núvol sense crear un gegant més enllà del vostre control? Així, òbviament, tota la indústria d’emmagatzematge de dades va evolucionar entorn a la necessitat de consolidar informació crítica per analitzar aquesta informació i prendre millors decisions.
Bé, ara Amazon Web Services té Redshift. Aquesta és una de les transmissions web més grans que hem fet mai amb Redshift. És una cosa molt gran. Estan canviant la dinàmica, canvien les estructures de preus. Podeu veure com els vostres preus disminueixen en les llicències de programari empresarial tradicional, en part a causa de la computació en núvol i en part, perquè aquestes persones baixen el punt de preu, pressionant sobre el preu. Així doncs, aquesta és una bona notícia per als usuaris finals. Alguna cosa que cal tenir en compte és certament per a aquells que estiguin provant d’utilitzar algunes d’aquestes tecnologies. Per tant, és una cosa que cal tenir en compte i avui en parlarem al programa.
Per tant, l’analista Dr. Robin Bloor serà el nostre primer analista del dia. Per tant, seguiré endavant i empenyé la primera diapositiva i li lliuraré les tecles. Robin, crec que estàs aquí en algun lloc, hi ets. I amb això vaig a lliurar-ho, i el pis és teu!
Robin Bloor: D'acord, Eric. Gràcies per aquesta introducció. Vaig trobar-me … fa un parell de dies em vaig trobar amb una enquesta de consumidors, de fet, que va fer la pregunta: creieu que el clima tempestuós interfereix amb la informàtica en núvol? I més del 50 per cent d’ells van dir que sí. Només vaig pensar que us hauria de fer saber que no ho és, si sou dels que creieu en això. I, aleshores, és una mica com creure això, quan ja tens neu a la televisió és perquè neva a fora.
Núvol, ja sabeu, una de les coses és que és, com ho sabeu, un important, si voleu, un detall senzill del núvol és que el núvol és en realitat un centre de dades d’una manera o altra, o qualsevol servei en núvol en particular un centre de dades. L’única cosa és que és un centre de dades diferent del núvol tradicional. Per tant, anava a parlar de manera general sobre el núvol, de manera que, com a còpia de seguretat, aprofundiríeu sobre l'ús del núvol perquè no té sentit cobrir el mateix terreny.
Aleshores, el primer tipus que m'agradaria fer és que el núvol sigui un servei, saps? I una de les coses que passa actualment a causa de la computació en núvol és que hi ha un … bé, anomeno la mort de les marques, tota una sèrie de marques de programari tenien molt poder i continuen tenint competències en informàtica corporativa. Una vegada que arribeu al núvol, ja no tenen massa poder? Quan compres un servei en núvol, t'importa l'aplicació, és clar, t'importa el nivell de servei que et brindarà el núvol, no vols que el servei en núvol falli freqüentment, t'importi el cost d'ús i t'importin aquests coses perquè aquest és un servei, però el que ja no t’importa és que no t’importa el maquinari que funciona, especialment, no t’importa quina és la tecnologia de xarxa, no t’importa el sistema operatiu funciona, és que no t'importa què són els sistemes de fitxers, ni tan sols t'importa què és la base de dades i realment és utilitzat específicament per qualsevol servei de bases de dades fora del núvol, saps? I, en certa manera, l’impacte és que el núvol és una gran quantitat de marques de programari que no tenen cap valor real al núvol perquè, ja ho sabeu, aneu al núvol d’una manera o altra per alguna cosa que sigui un servei i no més. producte Així doncs, vaig pensar que podria fer un parell de diapositives de raons per no fer servir el núvol, ja ho sabeu, i aquestes són totes, si voleu, ja ho sabeu, raonades raons senzilles, òbvies, però algú les havia de declarar, així que jo vaig pensar que ho faria.
Per tant, raons per a mi … no fer servir el núvol: si no poden proporcionar el tipus de dades i el govern de processos que desitgeu, ja ho sabeu, simplement no compleix els vostres criteris. Si no us poden oferir el rendiment que voleu, no complirà els criteris. Si el núvol us ofereix la flexibilitat quant a com podeu moure les coses, no complireu els criteris. Aquestes són raons òbvies per les quals els serveis en particular del núvol no convindrien a molta gent que hi ha, a part de fer computació corporativa.
Potser no ho podeu fer perquè ho podeu fer més barat. El núvol no sempre és l’opció més barata. Hi ha qui sembla pensar perquè sovint és una opció barata, sempre serà més barata, no sempre és més barata. I l’altra cosa és que si esteu prenent una aplicació d’un núvol, no s’integra bé amb el que esteu fent, probablement no aneu a avançar i aquestes són les raons de desviar-vos. .
Aquí teniu els motius per adoptar. Ja sabeu, una de les coses que podeu fer al núvol, pràcticament a prova de bales, és l’activitat de prototipat. Si podeu prototipar al núvol i implementar-lo al centre de dades, és completament viable i hi ha moltes persones que ho fan. Podeu penjar treballs des del centre de dades amb aplicacions no crítiques perquè, probablement, podríeu trobar algun tipus de serveis al núvol que complissin el vostre nivell de servei a les coses poc crítiques. I podeu penjar aplicacions específiques com salesforce.com i ofertes similars a aquestes, ja ho sabeu, a les aplicacions estàndard. Tothom té una capacitat en aquest àmbit i el camp no està especialitzat i, ja ho sabeu, el tradicional … probablement el que hi hagi disponible al núvol serà amb el que aneu.
Així, l’últim que volia dir, és una cosa interessant, realment, és quan realment busqueu el núvol, una manera d’entendre és com una sèrie d’economies d’escala. Tot el tema és que, ja ho sabeu, amb un centre de dades que hi ha i que marqueu a aquest centre de dades des d’un lloc o un altre i l’utilitzeu i, per tant, seria millor, seria millor en el principal més barat que si tu ho fas tu mateix. Així que, ja ho sabeu, es tracta realment d’economies d’escala.
Els proveïdors de núvols, trien la ubicació del centre de dades i el millor lloc per ubicar el centre de dades es troba just al costat d’una central, i sobretot just al costat d’una central econòmica. Per tant, una central fins al nord que passa a ser hidroelèctrica o alguna cosa així. Normalment és el més barat, saps? En realitat podeu localitzar el centre de dades allà i us resultarà més fàcil. És menys costós contractar gent en aquestes ubicacions que al centre de Nova York o San Francisco. Podeu estandarditzar a tota la instal·lació en termes d’aire condicionat i potència. Això us estalviarà molt perquè significa, ja ho sabeu, que podeu donar tot un edifici i això és el que fan exactament tots els operadors del núvol. S’estandarditzen en maquinari de xarxa, s’estandarditzen en el maquinari d’ordinador que utilitzen, normalment taulers x86 de productes bàsics, sovint s’hi assemblaran. Així, fins i tot n'hi ha que estan construint tot el problema. Utilitzaran el programari d'Amazon que puguin, ja que realment no suposa cap cost per adoptar-lo. Es normalitzaran en tot el programari. Per tant, mai no actualitzaran res, excepte per actualitzar-les alhora. Organitzaran el suport. Així doncs, pagaran suport a multitud de proveïdors diferents que només tenen el seu propi suport. Disposaran de capacitats d’ampliació i escalada en el sentit que s’executaran més del que haguessis estat executant aquest tipus de servei i vetllaran pel seu ús de manera que la majoria de centres de dades no puguin ser perquè solen executar només un servei normalitzat, però la majoria de centres de dades funcionen amb una sèrie de coses. I això és el que es refereix al núvol, realment, i que, en certa manera, pot definir si t’interessa o no per a cap aplicació en concret. Per tant, ja sabeu, el meu tipus de regla general és que, quan les economies d’escala són possibles, el núvol s’apoderarà tard o d’hora. Però, la manera com la innovació i la flexibilitat i les coses molt específiques que es fan vostès no poden realment. El núvol sempre serà el segon millor.
Bé. Permetin-ho passar a Eric o a Gilbert.
Eric Kavanagh: D’acord, Gilbert, us donaré les claus aquí al WebEx. Espera. Feu clic a qualsevol lloc de la diapositiva i utilitzeu la fletxa cap avall del teclat.
Gilbert Van Cutsem: Crec que tinc control.
Eric Kavanagh: Tu tens el control.
Gilbert Van Cutsem: D'acord. Aqui venim. El núvol imperatiu: el cel és el límit, és una llegenda urbana, o què en pensaries? Aquestes són només algunes xerrades i coses a considerar.
Primer, des del front "què", ja ho sabeu, com tots sabem, no crec que ningú es dubti d'això. L’aplicació SaaS és aquí per quedar-se perquè el programari no mor mai, només es mou al núvol, oi? Crec que ho he dit abans a l’anterior edició d’aquest. Oh, no, o Eric ho va dir per a mi en una edició anterior. I crec que la raó òbvia, i això torna a Robin en certa manera és que, en el cas de les coses corporatives, la línia de temps corporativa és bastant fàcil. La OCM sempre ho necessita tot i ara ho necessita. Per tant, tot segueix el temps de comercialitzar. Tan trist, és una bona excusa per a ell en certa manera. El CIO, però, està una mica nerviós per SaaS i els núvols perquè, ja sabeu, tot el problema d’elasticitat significa que el que puja també ha de disminuir. Heu d’estar a punt per escalar, però també per escalar. Per tant, està una mica nerviós per això. El CFO no està nerviós, no més que l’habitual, però es diu: "Ei, això és … quant ens retornarà això?" Es tracta de la famosa despesa de capital enfront de la discussió sobre OPEX. És bastant antic, però és molt important, ja ho sabeu, molt important en aquest món. I després, per últim, però no per això menys important, és CEO, per descomptat. Es diu: "Ah! Mitigació del risc! Nois, tots esteu emocionats, però estem preparats per això?" Perquè el risc és el que pensa.
Quin és el risc? Només uns quants pensaments, oi? Estem tractant aquí amb el lideratge del pensament, però en un camí inacabat perquè es tracta de coses força noves, totes relativament recents. En realitat no tenim gaires punts de dades. I, per tant, també hem de fer front a l’embarcat, ja ho sabeu, les persones que signen acords van com: “Sí, això és el que volem, el camí a seguir”, s’inscriuen, però després no n'hi ha prou. Ja ho sabeu, heu de pujar a la gent i això, recordeu les pel·lícules? Tornem a la traducció, això és un poc, ja ho sabeu, de què es tracta de l’abordatge. I també, tal com acabava de dir Robin, ja ho sabeu, no és necessàriament anar a la premissa. Per tant, heu d’integrar els dos mons. És un món híbrid. I així, com ho faràs? És 80-20, la norma 80-20 de Pareto, està bé? És prou bo? I, a continuació, la brossa a / escombraries quan connecteu els sistemes. Està bé? És durable? Com que, ja, vés a migrar, vareu fer una correspondència a l'empresa per al sistema root, com podeu fer-ho? I després l’última, que crec que és extremadament important, és l’arquitectura multitenant, és a dir, que la privadesa de les dades a les vostres pròpies dades, de vegades es diu “posseeix les vostres pròpies dades”, és important? Un centenar de persones que utilitzen el mateix sistema, una base de dades se situa per sota del sistema, qui veurà les meves dades? Només jo, no? N’estàs del tot segur? Privacitat de dades, seguretat de dades ajuda els experts. Si sou els CIO, torneu el "jo" a CIO perquè ara us encarregueu d'informació. Això és força interessant si ets un CIO.
Per tant, parlem una mica del "per què". Així, crec, la intenció estratègica de tot això és molt senzilla. Si sou subscriptor, hi ha una pressió del mercat. Si sou un proveïdor, hi ha una pressió competitiva. Si teniu companys, hi ha pressió entre iguals. Si sou subscriptor, és només la psicologia del mercat. Tothom vol anar al núvol, SaaS o com ho anomenis, núvol SaaS, tots necessitem i volem anar-hi. I la raó sol ser financera. Aquesta és la raó òbvia, però si penseu en l’aspecte financer, introduireu el que jo anomeno paradoxa de factura i pressupost. Voleu obtenir una subscripció, sistemes de consumibles, 50 dòlars, 500 dòlars al mes o alguna cosa així, o somieu amb l'ús de manera que només pagueu el que realment feu servir? I, per tant, com funciona això, es basa en l’ús, en el consum? Vas a mesurar totes aquestes coses? Probablement no passarà de seguida. Així doncs, acabareu amb un mecanisme híbrid, és a dir, pagueu 200 al mes i potser ocasionalment 500 perquè he de pagar el consum addicional. Retainer Plus, probablement ha de seguir, segons la meva opinió, el camí a seguir.
Però, també hi ha alguna cosa que jo anomeno la intenció oculta al front ampli i crec que, ja ho sabeu, això és absolutament real. És el canvi de control, és el CIO versus l'OCM, el canvi de poder o la lluita de poder entre l'OCM, "ho vull tot i ho vull ara", i el CIO, que diu com: "Ei, això és tot Ja sabeu? Jo solia executar, fa vint anys, es tractava de sistemes de maquinari, fa deu anys que es tractava d’aplicacions. Avui es tracta de dades, i com que sóc el CIO, informació, tot jo. Tinc el control. " Així, doncs, aquest és el tipus de canvi de poder o de lluita de poder. Crec que s'està produint ara mateix entre aquests dos, l'OCM i la CIO.
Al final, tot això és tan jove que ningú sap realment si estem en el tipus d’entorn innovador o en el tipus d’entorn que s’adopta de forma primerenca. Crec que ens trobem en el tipus d’entorn d’adopció primerenca, no en la majoria primerenca, només en l’adopció primerenca, però, ja ho sabeu, una mica a mig camí. I, per tant, ja sabeu, per al client, l’usuari final, el subscriptor, es tracta d’obtenir un inici de capçalera perquè l’OVM vol el començament inicial, oi? Per tant, és important no acabar amb el que anomenem rendiments disminuïdors. La limitació d’inici del capçal pot comportar disminuir els rendiments. És per això que és extremadament important que, ja sabeu, trobeu, confieu en les parts que puguin assegurar-se que el punt de fracàs únic no és cap problema i que es respecti la seguretat de les dades. Per tant, caldrà una mica de gestió del canvi. I, al final, gairebé acabat, aquesta és la darrera diapositiva: com anem a fer això? Com serà, senzill i senzill, el trasllat al núvol, el pas a SaaS? Bé, fent dues coses: parar atenció (aprovisionament) realment important i embarcar, encara més important.
Eric Kavanagh: Bé …
Gilbert Van Cutsem: I, en aquest cas, el cel és el límit. Gràcies.
Eric Kavanagh: Sí. Va ser genial. Em van encantar les idees molt provocadores, m’agrada la forma en què es va trencar tot això. Crec que té molt sentit. Anem endavant i pressionem la primera diapositiva d’Ashish i us lliuraré les claus del WebEx, Ashish. D'acord, endavant. Feu clic a qualsevol lloc de la diapositiva i utilitzeu la fletxa cap avall del teclat. Allà vas.
Ashish Suchoo: D'acord. Gràcies, Eric. Hola, això és Ashish i vaig a parlar-te sobre Qubole. Així, només per començar, Qubole, bàsicament, proporciona dades grans com a plataforma de servei. Es tracta d’una plataforma basada en núvols que es troba al núvol d’Amazon i al núvol de Google i proporcionem tecnologia com Hadoop, Hive, Presto i molts altres que en parlaré, tot de forma clau per tal que els nostres clients puguin sortir bàsicament de tota la confusió que existeix en el món de les infraestructures de dades o sortir de l’executat realment que opera aquesta infraestructura i realment centrar-se més en les seves dades i en les transformacions que volen fer en les seves dades. Aleshores, això és Qubole.
Pel que fa als beneficis tangibles, una forma de pensar en Qubole, ja sabeu, és clar, és una plataforma clau en mà, d’autoservei per a l’anàlisi de dades de grans dades i la integració de grans dades construïda al voltant d’Hadoop, però més fonamentalment, el que fa és que, vosaltres. sabeu, perquè tots els motors de dades grans com Hadoop, Hive, Presto, Spark, Chartly, etcètera, aporten tots els avantatges del núvol a aquests motors de dades grans i alguns dels principals elements que aporta de La perspectiva del núvol és, ja sabeu, que s’adapti la infraestructura i, mitjançant una adaptació, vull dir que són àgils i flexibles a les càrregues de treball que s’executen en qualsevol d’aquests motors i també fan que aquests motors siguin molt més autoserveus i col·laboratius en el sentit que, Ja sabeu, Qubole proporciona interfícies on podeu utilitzar aquestes tecnologies específiques no només per al vostre desenvolupament o, ja ho sabeu, tasques orientades als desenvolupadors, sinó que fins i tot els vostres altres analistes de dades també poden començar a obtenir els avantatges d’aquestes tecnologies en un autoservei. interfície.
Tenim molts, ja ho sabeu, relacionats amb aquest particular, ja sabeu, el webinar, ja ho sabeu, aquesta és una de les nostres perspectives sobre quins avantatges aporta el núvol que Qubole aporta a les grans dades. De manera que, si només fas una comparació entre com executeu, per exemple, Hadoop i deixeu que es carreguen de treball en una configuració pre-prem, en una configuració pre-prem, sempre esteu pensant en termes de clústers estàtics. agrupaments, potser els midau al vostre màxim ús i els mantingueu allà mateix i, si els heu de canviar, haureu de passar per tot un procés de contractació, desplegament, proves i així successivament. Qubole canvia que al crear clústers completament sota demanda, els nostres clústers són completament elàstics, utilitzem els objectes emmagatzemats des del núvol per emmagatzemar dades i es produeixen els clústers i, ja ho sabeu, es basen en la demanda que genera. els usuaris i se’n van quan no hi ha demanda. Per tant, això fa que aquesta infraestructura sigui molt més àgil i flexible i adaptable a les seves càrregues de treball.
Un altre exemple de flexibilitat és, ja ho sabeu, que potser heu creat els vostres clústers estàtics aquí, ja ho sabeu, tenint en compte una certa càrrega de treball i si les vostres càrregues de treball canvien i ara cal millorar la vostra infraestructura, potser necessitareu més memòria a les màquines. i coses així. Un cop més, ja ho sabeu, fer això al núvol mitjançant Qubole, per exemple, és senzill. Sempre podeu llogar màquines noves i diferents i, ja sabeu, posar-vos en funcionament cúmuls, cúmuls de 100 nodes en un parell de minuts, a diferència de les setmanes que heu d’esperar a l’Hadoop pre-prem.
L’altra cosa clau en què Qubole es diferencia dels premis és que Qubole és essencialment, com a oferta de serveis, de manera que no cal que totes les eines i la infraestructura que necessiteu per integrar el servei … En qualsevol lloc, ja ho sabeu, principalment feu servir el programari, l’heu d’executar tu mateix, heu d’integrar-lo vosaltres mateixos i fer tots aquests avantatges, tots els avantatges del model SaaS són una pista per, ja ho sabeu, com Qubole ofereix grans dades en lloc de fer funcionar Hadoop en un lloc mateix.
Aquesta diapositiva generalment cobreix la nostra arquitectura. Per descomptat, basats en el núvol, emmagatzemem les nostres dades en objectes al núvol, al núvol de Google i al Google Compute Engine o a Amazon Web Services. Aprofitem tots els projectes de l’ecosistema Hadoop i al voltant d’això, hem desenvolupat una IP clau al voltant de l’escala automàtica i l’autogestió, hem realitzat moltes optimitzacions de núvols per fer que aquestes tecnologies components funcionin molt bé al núvol, ja que, ja sabeu, la infraestructura del núvol és molt diferent del fet de funcionar amb el metall nu i un conjunt de connectors de dades per permetre que les dades es puguin moure dins i fora d'aquesta plataforma. Així doncs, això compara la plataforma de núvols i això permet que, ja ho sabeu, és clau … la característica clau és la de fer tot el servei d’autoservei perquè no hagueu de tenir un fort … no No teniu una empremta operativa molt gran mentre s’executa, però vinculem que juntament amb el nostre banc de treball de dades, ja siguin eines per als analistes, tant si són eines de govern de dades, com si són eines de plantilla, etcètera, de manera que pugueu pot aportar els avantatges d’aquesta tecnologia, no només als desenvolupadors, sinó també a altres usuaris comercials i a l’empresa. I, per descomptat, també enllacem aquesta plataforma en núvol amb eines que els vostres usuaris ja podrien fer servir si són, ja sabeu, eines d’utilització o simplement Tableau o si utilitzen, ja sabeu, més tipus d’emmagatzematge de dades de productes com Redshift i etcètera.
Avui en dia, el servei funciona a gran escala, actualment processem prop de 40 petabytes de dades cada mes a través de la nostra base de clients. Els nostres clústers varien de mida, entre cúmuls de 10 nodes i cúmuls de 1500 nodes i, ja ho sabeu, en termes de l’amplitud d’escala que podem processar i, en general, segons el que he sabut, probablement tenim alguns dels més grans. clústers al núvol pel que fa a Hadoop i processem fins a 250.000 màquines virtuals en un sol mes a través dels nostres clústers. Recordeu que el nostre model és el clúster a la demanda, que té uns avantatges enormes quant a la reducció de les vostres càrregues de treball operatives, així com a la millora de les vostres coses, etc.
Finalment, ja sabeu, un dels nostres, ja sabeu, només es tracta d’un mostreig de com Qubole s’ha transformat en diverses empreses. és un exemple del nostre client. Ja eren al núvol, utilitzaven Elastic MapReduce al núvol, per exemple, i l'ús de les dades allà estava força restringit. Tenirien uns 30 usuaris estranys que podrien utilitzar aquesta tecnologia. Amb Qubole, han pogut ampliar això a més de 200 usuaris estranys de l'empresa que han vist expandir els casos d'ús de dades grans i realment, ja sabeu, el que anomenem la definició d'una plataforma àgil de dades. ha esdevingut realment fonamental per a moltes de les seves càrregues de treball d’analítica.
Així, només per tancar, ja ho sabeu, que va ser un resum primari sobre Qubole. Essencialment, la nostra visió és com fem que les empreses siguin molt més àgils al voltant de les grans dades i, fonamentalment, aprofitem els beneficis del núvol i els portem a suportar les tecnologies de dades grans al voltant de Hadoop perquè els nostres clients puguin aprofitar els avantatges de l’agilitat i aquests beneficis. de flexibilitat i aquells avantatges de la naturalesa d’autoservei al núvol per esdevenir molt més eficaços a les seves necessitats de dades. Per tant, m'aturaré allà i ho lliuraré a Eric.
Eric Kavanagh: Bé. Això sona molt bé i ara us ho lliuraré a Mike Miller de Cloudant. Mike, ara us passo les claus. Només cal que feu clic a la diapositiva, aquí hi aneu. Emporta-t'ho.
Mike Miller: Sembla que tinc les claus. Per tant, em disculparé. He perdut … Crec que m'he oblidat d'enviar alguns tipus de lletra amb la meva presentació. Per tant, esperem que pugueu mirar més enllà i imaginar que és bonic. Però sí, és divertit. Tinc una llarga llista aquí, coses provocatives que vaig sentir que vaig escriure que estic desitjós de tornar a vosaltres al plafó. Així doncs, intentaré fer-ho ràpidament.
Així doncs, començaré per Cloudant. Cloudant és una base de dades com a servei, el nostre proveïdor de núvols i, de fet, ni tan sols tinc el nou logotip. Fa molt de temps no l’hem adquirit per IBM. I així, estem … Parlaré del nostre servei i em centraré sobretot en intentar que els nostres usuaris i clients siguin àgils d’una manera força diferent a l’anterior altaveu.
Cloudant proporciona base de dades com a servei i altres serveis relacionats amb les dades per a persones que creen aplicacions. Així doncs, ens relacionem directament amb els desenvolupadors i ens centrem en les dades operatives o OLTP en contrast amb les analítiques que ja vam sentir de Ashish. I el punt que hi ha és realment, el valor sencer de Cloudant, que es pot desglossar en ajudar els nostres usuaris a fer més coses i, per tant, crear més aplicacions, créixer més i dormir més. Parlaré d’ells amb una mica de detall, però la idea general aquí és que si sou usuaris, ja ho sabeu, sou una empresa comercial, esteu construint una nova aplicació, afegint una funció a l’aplicació o web existents. engegar mòbil, us heu d’enfocar en la vostra competència bàsica. I anteriorment, potser fins fa una dècada, la IT hauria de ser un distintiu, ja ho sabeu, la competència, el perdó, els danys competitius, fins i tot executar bé una base de dades per ser un avantatge competitiu. Aliats que aquests dies s’han acabat! Així doncs, la manera en què realment intentem treballar amb els nostres usuaris és animar-los a utilitzar serveis compostos, modulars, reutilitzables, composables, amb la idea que redueixi el temps a la comercialització, augmentant l’escalabilitat. I la idea general aquí és que el núvol no és simplement, ja ho sabeu, que s’està impulsant als usuaris alguna cosa nova, és realment un mercat … és una evolució del mercat perquè la forma en què la gent crea aplicacions, consumeixen aplicacions, els dispositius on s’executen. i l'escala de dades canvia bastant radicalment en els darrers 5-10 anys. Això ha subratllat realment l'arquitectura d'aplicacions existent per a la creació d'aplicacions, a més de fer front a aquestes dades i a les càrregues de treball analítiques fora de línia Per tant, obre tot un flux d'oportunitats.
Així doncs, Cloudant és una base de dades distribuïda com a servei i va ser única, crec, des dels seus inicis que realment es va enviar amb una estratègia mòbil des del principi, i en parlaré en detall, però la idea és que escriure aplicacions ara, no esteu escrivint per a una sola plataforma, oi? Esteu escrivint per a alguna cosa que puc executar una escala de petabyte al núvol, també ha de ser capaç de funcionar sense problemes en un escriptori o en un navegador i cada vegada més veiem coses, hem de funcionar en un dispositiu mòbil o un dispositiu semi-connectat o un dispositiu que es pot dur o cosa que anomenem IOT. I, per tant, crec que, ja ho sabeu, les aplicacions que poden afrontar bé i potenciar aquells diferents clients són increïblement competitives en el mercat i el que intentem fer és que sigui senzill que la gent escrigui API en el model de programació única per escriure. manejar les dades de tots aquells dispositius que tenen una escala molt diferent. 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. Què penses?
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. Bé. 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. Absolutament. 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. Sí. No hi ha cap problema. We have one attendee asking about various types of use cases like logistics and specifically HR, so I threw up this website of Workday, wanted to make a couple of comments on that, and then Gilbert, maybe I will bring you in to comment on the whole concept of architecture. So, in terms of HR, I actually heard a rather well, I will call it, let's say comment from an analyst a couple of months ago, a few months ago I suppose, about going to the cloud for Human Resources. I have been doing some research on this to know lot of HR-type functions are being outsourced to the cloud, certainly stuff like payroll is fairly easy to outsource these days, benefits programs and insurance, that kind of thing, but there is a real serious caveat to keep in mind and Gilbert, this is what I want you to comment on from an architectural perspective, which is you have to be very careful about when you are moving to the cloud for some kind of critical business service because you either want to be very strategic and very thoughtful, meaning you go through the process of making sure that you understand what's going on in the cloud and what's staying on-premise, and there is the folk from Attunity will tell you that truly one of the things they specialize in is making those connections such that they provide the kind of connectivity you need because what's happening with some organizations is they go and they will use Workday for example, to put some of their HR stuff to the cloud, but they don't do it all or they don't do enough or they don't think through it enough, and what happens then? Then they want to happen to manage the cloud environment and their original on-premises environment as well, which means, guess what? He just increased your cost, you doubled your workload and you created lots and lots of headaches for people, and that's usually when someone gets fired and then the guy who comes in has a real mess to clean up. So, you really do have to think through the architecture of the data and the systems and the processes and make sure you dot all your i's and cross all your t's and with that, I will throw it over to Gilbert for comments. I am guessing it will be with that, but maybe not.
Gilbert Van Cutsem: Alright. Sí. 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. No ho sé. 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. Aquesta és una molt bona pregunta. 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. Bé. 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. Cuida't. Adeu.
