Eric Kavanagh: Damas y caballeros, hola y bienvenidos nuevamente a TechWise. Me llamo Eric Kavanagh. Seré su moderador para el Episodio 3. Este es un nuevo programa que hemos diseñado con nuestros amigos de Techopedia, un sitio web genial que obviamente se enfoca en la tecnología y, por supuesto, aquí en The Bloor Group, nos enfocamos bastante en la empresa. tecnología. Por lo tanto, el software empresarial de todo tipo y todo el formato TechWise se diseñó para brindar a nuestros asistentes una buena mirada a un espacio específico. Entonces, hemos hecho Hadoop, por ejemplo, hicimos análisis en el último programa y en este programa en particular, estamos hablando de la nube.
Entonces, se llama "El imperativo de la nube: qué, dónde, cuándo y cómo". Hablaremos hoy con un par de analistas y luego con tres proveedores. Entonces, Qubole, Cloudant y Attunity son los patrocinadores del programa de hoy. Un gran agradecimiento a esas personas por su tiempo y atención hoy y un gran agradecimiento, por supuesto, a todos ustedes. Y tenga en cuenta que, como asistentes de estos espectáculos, usted juega un papel importante. Queremos que haga preguntas, que se involucre, que sea interactivo, que nos haga saber lo que piensa porque, obviamente, todo el propósito del programa aquí es ayudarlos a comprender lo que está sucediendo en el mundo de la computación en la nube.
El mazo imperativo de la nube
Entonces, sigamos adelante. Primero anfitrión, tu anfitrión allí, Eric Kavanagh, ese soy yo y luego tenemos al Dr. Robin Bloor llamando desde un aeropuerto, de hecho, y nuestro buen amigo Gilbert, Gilbert Van Cutsem, un analista independiente, también compartirá algunos pensamientos contigo Luego escucharemos a Ashish Thusoo, CEO y cofundador de Qubole. Escucharemos a Mike Miller, científico jefe de Cloudant y finalmente a Lawrence Schwartz, vicepresidente de marketing de Attunity. Entonces, tenemos una gran cantidad de contenido preparado para ti hoy.
Entonces, la nube, edicto desde arriba, este es un concepto que se me ocurrió el otro día cuando estaba pensando en esto. Realmente, la computación en la nube es enorme en estos días. Quiero decir, es realmente fascinante ver la evolución de estas cosas y uno de los ejemplos que a menudo doy es en la tecnología de transmisión web en sí. Por supuesto, aquellos de ustedes que marcaron temprano escucharon algunos desafíos técnicos interesantes. Ese es un problema con la nube: si cambia, los formatos cambian, los estándares cambian, las interfaces cambian y, a veces, cuando intentas conectar dos áreas diferentes juntas, tienes algunas dificultades, tienes algunos problemas. Entonces, esta es una de las cosas de las que preocuparse con la computación en la nube. ¡Cuidado con la arquitectura! Puedes ver eso en la última viñeta.
Una de las cosas que hacemos, solo como una nota al margen aquí, para nuestro webcast, tenemos un proveedor de conferencias telefónicas por separado. Luego usamos WebEx. No utilizamos el audio de WebEx porque, francamente, una vez utilizamos el audio de WebEx hace años y se bloqueó y se quemó de la manera más desagradable. Por lo tanto, no estamos dispuestos a correr ese riesgo nuevamente. Entonces, utilizamos nuestra propia compañía de grabación de audio llamada Arkadin de hecho y unimos, en tiempo real, todas estas soluciones diferentes. Y la idea es que luego podríamos enviarle un correo electrónico con una aplicación de correo electrónico separada con las diapositivas en caso de que, por ejemplo, WebEx se hubiera bloqueado, le decimos a todos que marquen, le enviaremos las diapositivas por correo electrónico y simplemente revisaremos más o menos sin el tipo de entornos WebEx. Entonces, la forma en que puede sortear este tipo de problemas, pero este tipo de problemas están por todas partes.
Pero, hay muchos beneficios para la nube. Obviamente, es una barrera de entrada baja, puede ver que el elemento secundario de la computación en la nube es salesforce.com, por supuesto, que solo revolucionó los negocios, específicamente la automatización de la fuerza de ventas, obviamente. Pero, entonces tienes cosas como Marketo e iContact y Constant Contact y Sailthru y, gracias a Dios, en términos de marketing y automatización de ventas, hay toneladas de herramientas, pero eso no es todo lo que hay. RRHH está llegando a todo el juego en la nube, la analítica está en el juego en la nube. Mire a esa compañía poco conocida de Amazon Web Services, lo que están haciendo con la computación en la nube: es enorme. Y escuché una gran cita el otro día de un tipo con el que trabajamos mucho con David, que ahora está en Cisco, de hecho, la compañía que compró WebEx. No estoy seguro de que hayan invertido tanto como me gustaría que tuvieran en WebEx, pero esa no es realmente mi decisión, ¿verdad? Pero, él está en Cisco en estos días y tenía una cita muy divertida y concisa, y es que "no hay una sola nube, hay muchas nubes", y eso es exactamente correcto. Hay montones y montones de nubes por ahí. De hecho, cada proveedor de la nube es su propia nube. Entonces, uno de los desafíos en estos días es conectar la nube, ¿verdad? Si usted es la fuerza de ventas, ¿no sería bueno conectarse directamente a iContact y Constant Contact y a LinkedIn, por ejemplo, y tal vez a Twitter y otros entornos, otras nubes por ahí solo arreglaron soluciones comerciales que tienen sentido para usted? y tu empresa
Por lo tanto, estos son algunos problemas a tener en cuenta, pero la nube está aquí para quedarse. Solo sé que sobre eso, el software local está aquí para quedarse. Entonces, lo que tenemos que descubrir en la empresa o en cualquier empresa pequeña o mediana, ¿cómo define su arquitectura y la mantiene de modo que pueda aprovechar la nube sin crear un gigante en otro lugar fuera de su control? Entonces, obviamente, toda la industria del almacenamiento de datos evolucionó en torno a la necesidad de consolidar la información crítica para analizar esa información y tomar mejores decisiones.
Bueno, ahora Amazon Web Services tiene Redshift. Esa es una de las transmisiones web más grandes que hicimos con Redshift. Eso es un gran problema. Están cambiando la dinámica, están cambiando las estructuras de precios. Puede ver cómo su precio baja en las licencias de software empresarial tradicionales, en parte debido a la computación en la nube y en parte porque estas personas están bajando el precio, presionando el precio. Entonces, esas son buenas noticias para los usuarios finales. Es algo a tener en cuenta, ciertamente, para cualquiera que esté tratando de usar algunas de estas tecnologías. Entonces, es algo a tener en cuenta y hablaremos de eso hoy en el programa.
Entonces, el analista Dr. Robin Bloor será nuestro primer analista del día. Entonces, seguiré adelante y empujaré su primer tobogán y le entregaré las llaves. Robin, creo que estás aquí en alguna parte, allí estás. Y con eso lo voy a entregar, ¡y el piso es tuyo!
Dr. Robin Bloor: De acuerdo, Eric. Gracias por esa presentación. Me encontré … hace un par de días, me encontré con una encuesta de consumidores, de hecho, que hizo la pregunta: ¿crees que el clima tormentoso interfiere con la computación en la nube? Y más del 50 por ciento de ellos dijo que sí. Solo pensé en hacerte saber que no es así, si eres de los que creen en eso. Y luego, es un poco como creer que, sabes, cuando tienes nieve en la televisión es porque está nevando afuera.
La nube, ya sabes, una de las cosas es que es un tipo de detalle importante, si lo desea, simple de la nube es que la nube es en realidad un centro de datos de una manera u otra, o cualquier servicio en la nube en particular es Un centro de datos. Lo único es que es un centro de datos diferente al de la nube tradicional. Entonces, iba a hablar en general sobre la nube para que, como su copia de seguridad, entrara en más detalles sobre el uso de la nube porque no tenía sentido cubrir el mismo terreno.
Entonces, el primer tipo de punto que me gustaría hacer es que la nube es un servicio, ¿sabes? Y una de las cosas que realmente está sucediendo debido a la computación en la nube es que hay una … bueno, llamo la muerte de las marcas, toda una serie de marcas de software tenían muchísimo poder y continúan teniendo poderes en la computación corporativa. Una vez que llegas a la nube, ya no tienen mucho poder, ¿sabes? Cuando compra un servicio en la nube, le importa la aplicación, por supuesto, le importa el nivel de servicio que le proporcionará la nube, no quiere que el servicio en la nube falle con frecuencia, le importa el costo de uso y le importan estos cosas porque este es un servicio, pero lo que ya no te importa es que no te importa en qué hardware se está ejecutando en particular, no te importa cuál es la tecnología de red, no te importa cuál es el sistema operativo se está ejecutando, no te importa cuáles son los sistemas de archivos, ni siquiera te importa cuál es la base de datos y eso es realmente utilizado específicamente por cualquier servicio de base de datos dado fuera de la nube, ¿sabes? Y el impacto de eso es que la nube es una gran cantidad de marcas de software que no tienen valor real en la nube porque, ya sabes, entras en la nube de una forma u otra por algo que es un servicio y ya no producto. Entonces, pensé que podría hacer un par de diapositivas de razones para no usar la nube, ya sabes, y estas son todas, si quieres, sabes, razones sangrientas, simples, obvias, pero alguien tenía que decirlas, así que, yo Pensé que lo haría.
Entonces, las razones no son para mí … no usar la nube: si no pueden proporcionar el tipo de datos y la gobernanza de procesos que desea, ya sabes, entonces simplemente no cumple con sus criterios. Si no pueden darle el rendimiento que desea, no va a cumplir con los criterios. Si la nube le brinda la flexibilidad en términos de cómo puede mover las cosas, entonces no cumplirá con un criterio. Esas son razones obvias por las que los servicios en la nube en particular no se adaptarían a una gran cantidad de personas que no sean informática corporativa.
Es posible que no lo haga porque puede hacerlo más barato. La nube no siempre es la opción más barata. Algunas personas parecen pensar porque a menudo es una opción económica, siempre será más barata, no siempre es más barata. Y la otra cosa es que si está tomando una aplicación desde una nube, no se integra bien con lo que está haciendo, entonces probablemente no va a seguir adelante y esas son, ya sabes, razones para rechazar .
Aquí están las razones para adoptar. Ya sabes, una de las cosas que puedes hacer en la nube, prácticamente a prueba de balas, es la actividad de creación de prototipos. Si puedes crear un prototipo en la nube e implementarlo en el centro de datos, es completamente viable y hay grandes cantidades de personas que lo hacen. Puede cargar el trabajo desde el centro de datos con aplicaciones no críticas porque, probablemente, podrá encontrar algún tipo de servicios en la nube que cumplan con su nivel de servicio a las cosas no críticas. Y puede cargar aplicaciones específicas como salesforce.com y ofertas similares a las aplicaciones estándar. Todo el mundo tiene una capacidad en esa área y el campo no está especializado y, ya sabes, lo tradicional … lo que sea que esté disponible en la nube probablemente sea con lo que vayas.
Entonces, lo último que quería decir, es algo realmente interesante, es que cuando realmente buscas la nube, una forma de entender es simplemente como una serie de economías de escala. El punto es que, ya sabes, ejecutar un centro de datos por ahí y que vas a llamar a ese centro de datos desde algún lugar u otro y usarlo y, por lo tanto, sería mejor, sería mejor en general más barato que si lo haces tu mismo Entonces, ya sabes, realmente se trata de economías de escala.
Los proveedores de la nube, eligen la ubicación del centro de datos y el mejor lugar para ubicar el centro de datos es justo al lado de una estación de energía, y especialmente al lado de una estación de energía económica. Entonces, una estación de energía en el norte que resulta ser hidroeléctrica o algo así. Normalmente es el más barato, ¿sabes? En realidad, puede ubicar el centro de datos allí y encontrará que es más fácil. Es menos costoso contratar personas en esos lugares que en el centro de Nueva York o San Francisco. Puede estandarizar toda la instalación en términos de aire acondicionado y energía. Eso le ahorrará mucho porque significa, ya sabe, que puede entregarle todo un edificio y eso es exactamente lo que hacen todos los operadores de la nube. Se estandarizan en el hardware de red, se estandarizan en el hardware de la computadora que usan, normalmente placas x86 de productos básicos, a menudo las ensamblan ellos mismos. Entonces, algunos incluso están construyendo todo. Utilizarán el software de Amazon que puedan porque en realidad significa que su adopción es gratuita. Se estandarizarán en todo el software. Por lo tanto, nunca actualizarán nada excepto para actualizar todo a la vez. Ellos organizarán el apoyo. Por lo tanto, pagarán soporte a multitud de proveedores diferentes que solo tienen su propio servicio de soporte. Tendrán la capacidad de escalar y escalar en el sentido de que estarán ejecutando más de lo que usted estaría ejecutando ese tipo de servicio y monitorearán su uso de una manera que la mayoría de los centros de datos no pueden porque están ejecutando un solo servicio estandarizado, pero la mayoría de los centros de datos ejecutan una serie completa de cosas. Y de eso se trata la nube, realmente, y eso de cierta manera, puede definir si le interesa o no para una aplicación en particular. Entonces, ya sabes, mi tipo de regla general es que, donde las economías de escala son posibles, la nube se hará cargo tarde o temprano. Pero, la forma en que la innovación y la flexibilidad y las cosas muy específicas que uno hace realmente no pueden. La nube siempre será la segunda mejor.
Bueno. Déjame pasarlo a Eric, o a Gilbert.
Eric Kavanagh: Bien, Gilbert, te daré las llaves aquí para el WebEx. Colocarse. Simplemente haga clic en cualquier lugar de esa diapositiva y use la flecha hacia abajo en su teclado.
Gilbert Van Cutsem: Creo que tengo el control.
Eric Kavanagh: Tú tienes el control.
Gilbert Van Cutsem: Muy bien. Aquí vamos. El imperativo de la nube: el cielo es el límite, ¿es una leyenda urbana o qué pensarías de él? Estas son solo algunas charlas y cosas a considerar.
Primero, desde el frente del "qué", ya sabes, como todos sabemos, no creo que nadie dude de esto. SaaS-ification está aquí para quedarse porque el software en realidad nunca muere, simplemente se mueve a la nube, ¿verdad? Creo que dije esto antes en la edición anterior de esto. Oh no, o Eric dijo eso por mí en una edición anterior. Y creo que la razón obvia, y esto también se remonta a Robin, es que en el lado corporativo de las cosas, el cronograma corporativo es bastante fácil. El CMO siempre lo necesita todo y lo necesita ahora. Entonces, él tiene que ver con el tiempo de comercialización. Muy triste, es una buena excusa para eso de alguna manera para él. Sin embargo, el CIO está un poco nervioso por SaaS y las nubes porque, ya sabes, todo el problema de elasticidad significa que todo lo que sube también debe bajar. Debe estar listo para escalar, pero también para volver a escalar. Entonces, está un poco nervioso por eso. El director financiero no está nervioso, no más de lo habitual, pero dice: "Oye, esto es … ¿cuánto nos retrasará?" Es el, ya sabes, el infame gasto de capital versus la discusión OPEX. Es bastante viejo, pero es muy importante en este mundo. Y luego, por último pero no menos importante, es el CEO, por supuesto. Él dice: "¡Oh! ¡Mitigación de riesgos! Chicos, ustedes están emocionados, pero ¿estamos listos para esto?" Porque el riesgo es lo que piensa.
Entonces, ¿cuál es el riesgo? Solo unos pocos pensamientos, ¿verdad? Estamos tratando con liderazgo de pensamiento, pero en un camino inacabado porque todo esto es bastante nuevo, todo bastante reciente. En realidad, no tenemos muchos puntos de datos, si lo piensas. Y así, también, en el lado del riesgo, tenemos que lidiar con la incorporación, ya sabes, las personas que firman acuerdos dicen: "Sí, eso es lo que queremos, el camino a seguir", se registran, pero luego eso no es suficiente. Sabes, tienes que incorporar gente y eso, ¿recuerdas las películas? De vuelta en la traducción, eso es un poco, ya sabes, de qué se trata la incorporación. Y luego, como Robin acaba de decir, ya sabes, on-prem no necesariamente desaparecerá de inmediato. Entonces, tienes que integrar ambos mundos. Es un mundo híbrido. Y entonces, ¿cómo vas a hacer eso? Es 80-20, la regla 80-20 Pareto, ¿está bien? ¿Es eso lo suficientemente bueno? Y luego la basura entra / sale cuando conecta los sistemas. Esta bien? ¿Es eso duradero? Porque, ya sabes, vas a migrar, vas a mapear tu empresa al sistema raíz, ¿cómo vas a hacer eso? Y luego, la última, que creo que es extremadamente importante, son las arquitecturas de múltiples inquilinos, lo que significa que la privacidad de los datos en sus propios datos, a veces se llama "poseer sus propios datos", se vuelve muy importante, ¿sabes? Cien personas que usan el mismo sistema, una base de datos se encuentra debajo del sistema, ¿quién verá mis datos? Solo yo, ¿verdad? ¿Estás absolutamente seguro de eso? La privacidad de los datos, la seguridad de los datos ayuda a los expertos. Si usted es el CIO, trae de vuelta el "I" al CIO porque ahora está a cargo de la información. Eso es bastante interesante si eres un CIO.
Entonces, hablemos un poco sobre el "por qué". Entonces, la intención estratégica de todo esto es muy, muy simple, creo. Si es suscriptor, existe presión del mercado. Si usted es un proveedor, existe una presión competitiva. Si tienes pares, hay presión de grupo. Si está suscrito, es solo la psicología del mercado. Todos quieren ir a la nube, SaaS o como se llame, SaaS en la nube, todos necesitamos y queremos ir allí. Y la razón suele ser financiera. Esa es la razón obvia, pero si piensas en el aspecto financiero, entras en lo que yo llamo la paradoja del proyecto de ley contra el presupuesto. ¿Vas a obtener una suscripción, sistemas de todo lo que puedas comer, $ 50, $ 500 al mes o algo así, o sueñas con un uso basado en lo que solo pagas por lo que realmente usas? Y entonces, ¿cómo va a funcionar eso, basado en el uso, basado en el consumo? ¿Vas a medir todas esas cosas? Probablemente no va a suceder de inmediato. Entonces, terminarás con un mecanismo híbrido, es decir, pago 200 al mes y quizás ocasionalmente 500 porque tengo que pagar por el consumo adicional. Retainer Plus, probablemente sea, en mi opinión, el camino a seguir.
Pero también hay algo que llamo la intención oculta en el frente amplio, y creo que esto es absolutamente real. Es el cambio de control, es el CIO versus el CMO, el cambio de poder o la lucha de poder entre el CMO, "Lo quiero todo y lo quiero ahora", y el CIO, que dice: "Oye, esto es todo sobre datos, ¿sabes? Solía correr, hace 20 años, todo se trataba de sistemas de hardware. Hace diez años todo se trataba de aplicaciones. Hoy, todo se trata de datos. Y como soy el CIO, la información, todo se trata yo. Estoy en control ". Entonces, eso es una especie de cambio de poder o lucha de poder, creo que está sucediendo en este momento entre estos dos, el CMO y el CIO.
Entonces, al final, todo esto es tan joven que nadie sabe realmente si estamos en el entorno innovador o en el adoptante temprano. Creo que estamos en el entorno de tipo de adoptante temprano, no en la mayoría temprana, solo en el adoptante temprano, pero, ya sabes, a medio camino. Entonces, ya sabes, para el cliente, el usuario final, el suscriptor, se trata de obtener una ventaja inicial porque el CMO quiere la ventaja, ¿verdad? Por lo tanto, es importante no terminar con lo que llamamos rendimientos decrecientes. La ventaja inicial limitante puede conducir a rendimientos decrecientes. Es por eso que es extremadamente importante, ya sabes, encontrar y confiar en las partes que pueden asegurarse de que el punto único de falla no sea un problema y que se respete la seguridad de los datos. Por lo tanto, requerirá bastante gestión de cambios. Y así, al final, casi terminado, esta es la última diapositiva, ¿cómo vamos a hacer esto? ¿Cómo va el cambio a la nube, el cambio a SaaS será, ya sabes, fácil y sin problemas? Bueno, al hacer dos cosas: prestar atención - aprovisionamiento - realmente importante, y la incorporación, aún más importante.
Eric Kavanagh: Muy bien …
Gilbert Van Cutsem: Y en ese caso, el cielo es el límite. Gracias.
Eric Kavanagh: Sí. Eso fue genial. Me encantaron las ideas muy provocativas, me gusta cómo rompiste todo eso. Creo que eso tiene mucho sentido. Y sigamos adelante, empujemos la primera diapositiva de Ashish y te entregaré las llaves del WebEx, Ashish. Está bien, adelante. Simplemente haga clic en cualquier lugar de esa diapositiva y use la flecha hacia abajo en su teclado. Ahí tienes.
Ashish Thusoo: Muy bien. Gracias Eric Hola amigos, soy Ashish y les voy a contar sobre Qubole. Entonces, solo para comenzar, Qubole, esencialmente proporciona grandes datos como plataforma de servicio. Es una plataforma basada en la nube alojada en la nube de Amazon y Google y proporcionamos tecnología como Hadoop, Hive, Presto y muchas otras de las que hablaré, todo de una manera llave en mano para que nuestros clientes puedan esencialmente salir de toda la confusión en el mundo de la infraestructura de big data o salir de la operación de esta infraestructura y realmente enfocarse más en sus datos y las transformaciones que quieren hacer en sus datos. Entonces, de eso se trata Qubole.
En términos de los beneficios tangibles, una forma de pensar acerca de Qubole, por supuesto, es una plataforma de autoservicio llave en mano para el análisis de big data y la integración de big data construida en torno a Hadoop, pero más fundamentalmente, lo que hace es que usted sepa, para todos los motores de big data como Hadoop, Hive, Presto, Spark, Chartly, etc., trae todos los beneficios de la nube a estos motores de big data y algunos de los manifiestos clave que trae La perspectiva de la nube es, ya sabes, hacer que la infraestructura sea adaptativa y al adaptarme, me refiero a ser ágil y flexible a las cargas de trabajo que se ejecutan en cualquiera de estos motores y también a hacer que estos motores sean mucho más autoservicios y colaborativos en el sentido de que, ya sabes, Qubole proporciona interfaces donde puedes usar estas tecnologías particulares no solo para tu desarrollo o, ya sabes, tareas orientadas al desarrollador, sino que incluso tus otros analistas de datos también pueden comenzar a obtener los beneficios de estas tecnologías para un autoservicio interfaz.
Obtenemos mucho, ya sabes, relacionado con este seminario web en particular, ya sabes, esta es una de nuestras perspectivas sobre los beneficios de la nube que Qubole aporta a los grandes datos. Entonces, si solo hace una comparación entre cómo ejecuta, digamos, Hadoop y deja que se cargue en una configuración local, en una configuración local, siempre está pensando en términos de grupos estáticos, ya sabe, arregla su clústeres, puede dimensionarlos para su uso máximo y mantenerlos allí y luego, si tiene que cambiarlos, debe pasar por un proceso completo de adquisición, despliegue, prueba, etc. Qubole cambia que al crear clústeres completamente a pedido, nuestros clústeres son completamente elásticos, usamos los objetos almacenados desde la nube para almacenar datos y los clústeres surgen y, ya sabes, surgen en función de la demanda generada por los usuarios y ellos se van cuando no hay demanda. Por lo tanto, esto hace que esa infraestructura sea mucho más ágil, flexible y adaptable a sus cargas de trabajo.
Otro ejemplo de flexibilidad es, ya sabe, hoy podría haber creado sus clústeres estáticos aquí, ya sabe, con una cierta carga de trabajo en mente y si sus cargas de trabajo cambian y su infraestructura ahora necesita ser actualizada, tal vez necesite más memoria en sus máquinas y cosas asi. De nuevo, ya sabes, hacer esto en la nube a través de Qubole, por ejemplo, lo hace simple. Siempre puede alquilar máquinas nuevas y de diferentes tipos y, ya sabe, obtener clústeres, clústeres de 100 nodos en funcionamiento en un par de minutos en lugar de semanas en las que tuvo que esperar Hadoop en las instalaciones.
La otra cosa clave en la que Qubole se diferencia del local es que Qubole es esencialmente, como una oferta de servicio, por lo que todas las herramientas y la infraestructura que necesita para integrar el servicio, no tiene que … donde sea que sea local, ya sabes, es principalmente que tomas el software, tienes que ejecutarlo tú mismo, tienes que integrarlo tú mismo y aprovechar todos esos beneficios, todos los beneficios del modelo SaaS son una pista para saber cómo Qubole ofrece grandes datos en lugar de ejecutar Hadoop en las instalaciones usted mismo.
Esta diapositiva generalmente cubre nuestra arquitectura. Por supuesto, estamos basados en la nube, almacenamos nuestros datos en objetos en la nube en la nube, la nube de Google y Google Compute Engine o Amazon Web Services. Tomamos todos los proyectos del ecosistema Hadoop y, en torno a eso, hemos desarrollado IP clave en torno al autoescalado y la autogestión, hemos realizado muchas optimizaciones en la nube para hacer que estas tecnologías de componentes funcionen realmente bien en la nube, ya que la infraestructura de la nube es muy diferente de simplemente ejecutar cosas en metal desnudo y un montón de conectores de datos para permitir que los datos se muevan dentro y fuera de esta plataforma. Entonces, eso compara la plataforma en la nube y eso permite que, ya sabes, esa sea una clave … la característica clave es cómo hacer todo el autoservicio para que no tenga que tener un fuerte … no No tenemos una huella operativa muy grande al ejecutar esto, pero lo vinculamos con nuestro banco de trabajo de datos, ya sea que se trate de herramientas para analistas, si se trata de herramientas de gobernanza de datos, si se trata de herramientas de plantillas, y así sucesivamente para que usted puede aportar los beneficios de esta tecnología, no solo a los desarrolladores, sino también a otros usuarios comerciales y a la empresa. Y, por supuesto, vinculamos también esta plataforma en la nube a las herramientas que ustedes ya podrían estar utilizando, ya sean herramientas de utilización o solo Tableau o si están utilizando, ya sabes, más productos de almacenamiento de datos como Redshift y Y así sucesivamente.
Hoy, el servicio se está ejecutando a una escala bastante grande, procesamos actualmente cerca de 40 petabytes de datos cada mes en nuestra base de clientes. Nuestros grupos varían en tamaño, desde grupos de 10 nodos hasta grupos de 1500 nodos y, en términos del rango de escala que podemos procesar y, en general, según mi conocimiento, ejecutamos probablemente algunos de los más grandes. en lo que respecta a Hadoop, agrupamos clústeres en la nube y procesamos alrededor de 250, 000 máquinas virtuales en un solo mes en nuestros clústeres. Recuerde, nuestro modelo es clústeres bajo demanda, lo que tiene enormes beneficios en términos de reducir sus cargas de trabajo operativas, así como mejorar su y así sucesivamente.
Finalmente, ya sabes, uno de nuestros, ya sabes, esto es solo una muestra de cómo Qubole ha transformado a varias compañías. Es un ejemplo de nuestro cliente. Ya estaban en la nube, ejecutaban Elastic MapReduce en la nube, por ejemplo, y el uso de datos allí era bastante limitado. Tendrían unos 30 usuarios que podrían usar esa tecnología. Con Qubole, han podido expandir eso a más de 200 usuarios de la compañía que han visto la expansión de los casos de uso de big data y realmente ha traído, ya sabes, lo que llamamos la definición de una plataforma ágil de big data y eso se ha vuelto realmente central para muchas de sus cargas de trabajo de análisis.
Entonces, para cerrar, ya sabes, esa fue una breve introducción a Qubole. Esencialmente, nuestra visión es cómo hacer que las empresas sean mucho más ágiles en torno a big data y, esencialmente, aprovechamos los beneficios de la nube y los aplicamos a las tecnologías de big data en Hadoop para que nuestros clientes puedan aprovechar esos beneficios de agilidad y esos beneficios de flexibilidad y los beneficios de la naturaleza de autoservicio en la nube para ser mucho más efectivos para sus necesidades de datos. Entonces, me detendré allí y se lo devolveré a Eric.
Eric Kavanagh: Muy bien. Eso suena genial y ahora, se lo entregaré a Mike Miller de Cloudant. Mike, te estoy pasando las llaves ahora mismo. Simplemente haz clic en la diapositiva, aquí tienes. Llevatelo.
Mike Miller: Parece que tengo las llaves. Entonces, me disculpo. Perdí … Creo que olvidé enviar algunas fuentes con mi presentación. Entonces, espero que puedas ver más allá de eso e imaginar que es hermoso. Pero sí, esto es divertido. Tengo una larga lista aquí, cosas provocativas que escuché que escribí y que estoy ansioso por volver a ver en el panel. Entonces, intentaré superar esto rápidamente.
Entonces, comenzaré por Cloudant. Cloudant es una base de datos como servicio, nuestro proveedor de la nube y, de hecho, ni siquiera tengo el nuevo logotipo. Fuimos adquiridos por IBM no hace mucho tiempo. Y entonces, estamos … Voy a hablar sobre nuestro servicio y en particular centrarme en tratar de agilizar a nuestros usuarios y clientes de una manera bastante diferente a la del orador anterior.
Cloudant proporciona una base de datos como servicio y otros servicios relacionados con los datos para las personas que crean aplicaciones. Por lo tanto, nos relacionamos directamente con los desarrolladores y nos enfocamos en datos operativos u OLTP en contraste con los análisis que escuchamos de Ashish anteriormente. Y el punto allí es realmente, el valor total de Cloudant, que se puede dividir en ayudar a nuestros usuarios a hacer más y eso es construir más aplicaciones, crecer más y dormir más. Hablaré de ellos con un poco de detalle, pero la idea general aquí es que si usted es un usuario, ya sabe, está en una empresa comercial, está creando una nueva aplicación, agregando una característica a la aplicación o web existente inicio móvil, debe centrarse en su competencia central. Y anteriormente, tal vez hasta hace una década, la TI debía ser una distinción, ya sabes, competencia, perdón, daño competitivo, incluso ejecutar una base de datos bien para ser una ventaja competitiva. ¡Aliviada de que esos días hayan terminado! Por lo tanto, la forma en que realmente intentamos trabajar con nuestros usuarios es alentarlos a usar servicios compuestos, modulares, reutilizables, compostables, con la idea de que reduce el tiempo de comercialización y aumenta la escalabilidad. Y la idea general aquí es que la nube no es solo, ya sabes, algo nuevo que se empuja a los usuarios, es realmente un mercado … es una evolución del mercado porque la forma en que las personas crean aplicaciones, consumen aplicaciones, los dispositivos en los que se ejecutan y la escala de datos cambia bastante radicalmente en los últimos 5-10 años. Eso realmente enfatizó la arquitectura de aplicaciones existente para crear aplicaciones, así como solo lidiar con esas cargas de trabajo de datos y análisis fuera de línea. Y así, se abre todo un flujo de oportunidades.
Entonces, Cloudant es una base de datos distribuida como un servicio y creo que fue único desde el principio que realmente se envió con una estrategia móvil desde el principio, y hablaré sobre esto en detalle, pero la idea es que escribir aplicaciones ahora, no estás escribiendo para una sola plataforma, ¿verdad? Estás escribiendo para algo en lo que puedo ejecutar una escala de petabytes en la nube, también tiene que poder ejecutarse sin problemas en un escritorio o en un navegador y cada vez vemos más cosas, tenemos que ejecutar en un dispositivo móvil o un dispositivo semi-conectado o dispositivo portátil o algo que llamamos IOT. Por lo tanto, creo que, ya sabes, las aplicaciones que pueden funcionar bien y aprovechar esos diferentes clientes son increíblemente competitivas en el mercado y lo que intentamos hacer es simplificar que la gente escriba API en el modelo de programación único para escribir manejar datos en todos esos dispositivos diferentes que tienen una escala muy diferente. Lo interesante es, ya sabes, la aceptación inicial en la web y los dispositivos móviles, aquí es donde vimos nuestra gran resta, pero incluso ahora antes de la adquisición, vemos un número cada vez mayor de usuarios empresariales, incluso en cosas como lo que digo como conservador 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. Excelente. 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. ¿Qué piensas?
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. Bueno. 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. Absolutamente. 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. Si. No hay 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. Si. 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 lo 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. Está todo bien. 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. Eso no es bueno.
Gilbert Van Cutsem: So, I don't know where my data is and assume she gets really mad, right? She goes like, "Oh, this is impossible. I pay you money and my customers are, my patients, sorry, are unhappy and with the data is gone, I wanna get away from you. I wanna go to a different system maybe also in the cloud, right?" How do you then move the data of your patients in this case, the data your business owns, to another system? How do I get it out first of all and then load it again? I am sure ETL in the cloud is an answer somehow and we have experts on that, but it's not that easy.
Eric Kavanagh: Yeah, but that's exactly right and folks, I threw up this other slide here, this other, another screen to show you where you can find the archives. So, anytime you want to check out - oh, there's the inside of our website, I don't want to show you that. So, here is the main website and on the right column here you can see a different show. So, TechWise is right here. You click on that and on these different pages where we will actually post the archives. So, we do archive all these webcasts.
Actually, I wanna throw back over to Mike, I suppose, and then also to Lawrence to kinda comment on this story that Gilbert just told. So, Mike, there is some, kind of, now this is kind of a small-business concern. You guys are more focused on big business, but nonetheless, if a large company who works with you and they want to go somewhere else, how do you manage that movement of the data and securing the data and so forth?
Mike Miller: Yeah. That's a very good question. It's one that used to come up a lot more often than it does now in sales calls, which I find to be an interesting anecdotal piece of evidence for a call. You know, I think that first of all, we are talking about a lot technologies, or at least employment models that are relatively new. This is very early in the cloud, right? We are talking about things like cloud, or in the case of data, we are talking about analytics services like Hadoop for databases and then NoSQL or NewSQL formats. You know, these are fundamentally new technologies and especially around things like, Hadoop and NoSQL, all of the ancillary services, the connectors, right, the… you know, if I want to find somebody that consults on Oracle, that's something I can find, but that entire ecosystem is just kinda spinning up right now.
So, it's getting easier day over day to say, okay, you know, give me a service that can read from 'x' traditional system, put it into Cloudant and do something with it and then put it back into 'y' traditional system, right? So, now they are very, you know, there are quite a few those things and it's actually more challenging, I think, for a typical user to understand what is the best choice, right, if I want to connect all the new technologies on-prem and then in the cloud.
So, I think as a cloud vendor, it's really on us to be very opinionated about that and to help walk users through the landscape of possibilities because the shift's a lot of new and I think that the average user, whether it's a CTO, CIO or whether it's actually developer, is coming up that learning curve fairly quickly. I think that a lot of the kind of baseline stuff is being worked out, cross-cloud connectors and, you know, taking away the really most basic worries about say, you know, bandwidth cost and whether or not you are going out on the wide area network versus staying on, you know, VPN the entire time. A lot of those things have been kinda abstracted away and what is the true promise of the cloud.
But, in general, I think you are also seeing, you know, that anecdote that we heard was, you know, something that is probably isomorphic to, you know, what will happen to your buying into a brand, you know, in a past lifetime, you know, what happens if that brand doesn't deliver, how much can I really trust that brand? I think you are seeing exactly the same thing happen in the cloud and, you know, I think that companies like Microsoft, Amazon, IBM and Google are, you know, very much stepping up and saying that there will at least be multiple pillars of trust and making sure that you are not going in with a company that's going to dry up and swallow your data, or worse, lose it or distribute it, right? And so, they are, at least, they are independable and they are anchoring, you know, the development of such ecosystem. But, I say to close, it's very early and a lot of that tooling is just getting started and, you know, I think you are going to see consulting services, you know, really putting a lot of focus on that in the very near term.
Eric Kavanagh: Yeah. That's a really, really good comment you just made there. I like that "pillars of trust" concept because the other thing to keep in mind here is you do once again have a number of fierce competitors vying for market share and for IT span, it's just like the old days all over again. Really, in the old days, by which I mean last year, you had IBM and Oracle and Microsoft and SAP and then Computer Associates and Informatica and all these companies, Teradata, etc. In the new world, now you have got, of course, Microsoft with their Du Jour, you have got Google, you have got Amazon Web Services, you know, you have Facebook in certain context. So, you have all these companies that are not necessarily so excited about working with each other, but you do have things like APIs. And so, one of the nice things that APIs really are crystallizing into the connectors that hold together the larger cloud, I suppose, and I want to throw up a slide for Lawrence to kinda comment on all this.
Yeah, Lawrence, obviously, you guys have specialized in the space for a while. So, I think you do have awesome advantage over maybe some newcomers. But, nonetheless, these are all very serious concerns because how data gets stored in the cloud is different than how it gets stored on-premise. Then I think that Mike makes a really good point that this whole space is just starting to take shape and it's gonna take a while for things to seriously fall into place and to crystallize. So, what's some advice that you have for companies that you… I guess, you basically concur with Mike, or what do you think?
Lawrence Schwartz: Yeah. I think it's, you know, what we see is when people are taking advantage of the cloud for a lot of use cases as compared to on-premise, you know, they are looking at kind of, you know, two different things. One is, they are looking at, you know, as we talked about this a little bit earlier, how do I… how does it incrementally add value to what I do, how do I, you know, how is it kind of an add-on? And so, you know, when back to when I talked about the Etix as a company where, you know, they are not moving all their operations over to Redshift, you know, yet per say, but they're saying, "I do a lot of work on Oracle, I wanna offer some of this to some kind of analytics from different environments, you know, kinda figure out, maybe do some sandbox stuff there, and, you know, and then learn about my business that way, and that way they can kind of carve out what they want, move it over there and do the work and, you know, it's less of a concern with moving, you know, everything over and all the records and whatnot. So, I think they look at that as one way that to take advantage of it with having less issues.
I think the other thing is people are also looking at these cases that are and aren't excellent fit for the cloud that are very, very hard to do in other ways. So, I will take another example, you know, we work with a company called, you know, iN DEMAND. They are video on-demand player. They do this work for Comcast and all of this and they will actually, you know, take the data that they are working with, they will take the media files and they will supply it to the cloud for doing their processing, do their processing there, and then they will consume it back for their on-premise customers. And then, you know, that gets upstairs to third parties that consume reviews. So, it's, you know, if you want to think about how the company is approaching it, it's, you know, how do I get my… how do I add value, how do I maybe not move the whole business at first, how do I get the right use cases, how do I add incremental value to what I do? And that helps kinda build about the confidence on what they are doing and as part of the process, and of course, you know, a key piece of that is, you know, making sure that they can do that securely and reliably and, you know, we make sure to the latest levels of encryption and other things to take care of that as much as we can on the transport side. But, that's how I think a lot of companies are approaching the problem.
Eric Kavanagh: Okay. Bueno. 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. ¡Excelente! 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. Cuídate. Adiós.
