The cloud imperative - apa, mengapa, kapan dan bagaimana - transkrip episode 3 techwise

Eric Kavanagh: Hadirin sekalian, halo dan selamat datang kembali ke TechWise. Nama saya Eric Kavanagh. Saya akan menjadi moderator Anda untuk Episode 3. Ini adalah pertunjukan baru yang telah kami rancang dengan teman-teman kami dari Techopedia, situs web yang sangat keren yang jelas berfokus pada teknologi, dan tentu saja, di sini di The Bloor Group, kami sangat fokus pada perusahaan teknologi. Jadi, perangkat lunak perusahaan dari semua jenis, dan seluruh format TechWise dirancang untuk memberikan peserta kami tampilan yang sangat bagus di ruang tertentu. Jadi, kami telah melakukan Hadoop misalnya, kami melakukan analitik pada pertunjukan terakhir dan dalam pertunjukan khusus ini, kami berbicara tentang cloud.

Jadi, ini disebut "The Cloud Imperative - Apa, Di Mana, Kapan dan Bagaimana." Kami akan berbicara dengan beberapa analis hari ini dan kemudian tiga vendor. Jadi, Qubole, Cloudant, dan Attunity adalah sponsor acara hari ini. Terima kasih banyak untuk orang-orang itu atas waktu dan perhatian mereka hari ini dan terima kasih yang besar, tentu saja, untuk kalian semua di luar sana. Dan perlu diingat bahwa sebagai peserta acara ini, Anda memainkan peran penting. Kami ingin Anda mengajukan pertanyaan, terlibat, berinteraksi, beri tahu kami apa yang Anda pikirkan karena jelas, seluruh tujuan pertunjukan di sini adalah untuk membantu kalian memahami apa yang terjadi di dunia komputasi awan.

Dek Awan Imperatif

Jadi, mari kita terus. Tuan rumah pertama, tuan rumah Anda di sana, Eric Kavanagh itu saya dan kemudian kita memanggil Dr. Robin Bloor dari bandara, dan teman baik kita Gilbert, Gilbert Van Cutsem, seorang analis independen, juga akan berbagi beberapa pemikiran dengan kamu. Kemudian kita akan mendengar dari Ashish Thusoo, CEO dan salah satu pendiri Qubole. Kita akan mendengar dari Mike Miller, kepala ilmuwan di Cloudant dan akhirnya dari Lawrence Schwartz, Wakil Presiden Pemasaran di Attunity. Jadi, kami mendapat banyak konten yang disiapkan untuk Anda hari ini.

Jadi, awan - dekrit dari atas - ini adalah konsep yang datang kepada saya tempo hari ketika saya memikirkan hal ini. Sungguh, komputasi awan sangat besar akhir-akhir ini. Maksud saya, sangat menarik untuk menyaksikan evolusi dari hal ini dan salah satu contoh yang sering saya berikan adalah dalam teknologi webcasting itu sendiri. Tentu saja, Anda yang menelepon lebih awal mendengar beberapa tantangan teknis yang menarik. Itu adalah satu masalah dengan cloud apakah itu berubah, format berubah, standar berubah, antarmuka berubah dan kadang-kadang ketika Anda mencoba untuk menghubungkan dua area yang berbeda bersama-sama, Anda mendapatkan beberapa kesulitan, Anda mendapatkan masalah. Jadi, ini sebenarnya salah satu hal yang perlu dikhawatirkan dengan cloud computing. Berhati-hatilah dengan arsitektur! Anda dapat melihat itu pada poin terakhir.

Salah satu hal yang kami lakukan, seperti catatan di sini, untuk siaran web kami, kami memiliki vendor konferensi telepon terpisah. Lalu kami menggunakan WebEx. Kami tidak menggunakan audio WebEx karena terus terang, suatu kali kami menggunakan audio WebEx tahun yang lalu dan jatuh dan terbakar dengan cara yang paling tidak menyenangkan. Jadi, kami tidak mau menanggung risiko itu lagi. Jadi, kami menggunakan perusahaan rekaman audio kami sendiri yang disebut Arkadin sebagai fakta dan kami menjahit bersama, secara real time, semua solusi berbeda ini. Dan idenya adalah bahwa kami kemudian dapat mengirim email kepada Anda dengan aplikasi email terpisah dengan slide dalam kasus misalnya, WebEx akan crash, kami memberitahu Anda semua untuk memanggil, kami akan mengirimkan email kepada Anda slide dan hanya pergi melalui itu lebih atau kurang tanpa jenis lingkungan WebEx. Jadi, cara Anda dapat mengatasi masalah seperti ini, tetapi masalah seperti ini ada di mana-mana.

Tapi, ada banyak manfaat untuk cloud. Jelas, itu penghalang rendah untuk masuk, Anda dapat melihat anak poster cloud computing adalah salesforce.com tentu saja, yang baru saja merevolusi bisnis, khususnya otomatisasi tenaga penjualan, jelas. Tetapi, Anda sudah mendapatkan hal-hal seperti Marketo dan iContact dan Constant Contact serta Sailthru dan, ya ampun, dalam hal pemasaran dan otomasi penjualan, ada banyak alat, tetapi tidak semuanya ada. SDM membawanya ke seluruh game cloud, analitik ada di game cloud. Lihatlah perusahaan kecil yang dikenal di luar sana, Amazon Web Services, apa yang mereka lakukan dengan komputasi awan - ini sangat besar. Dan saya mendengar kutipan yang bagus kemarin dari seorang lelaki yang banyak melakukan pekerjaan dengan David yang sekarang sudah berakhir di Cisco, faktanya, perusahaan yang membeli WebEx. Tidak yakin mereka telah berinvestasi sebanyak yang saya ingin mereka miliki di WebEx, tapi itu bukan keputusan saya, bukan? Tapi, dia ada di Cisco akhir-akhir ini dan dia punya kutipan yang sangat lucu, hanya bernas, dan itu adalah, "tidak ada satu awan, ada banyak awan, " dan itu tepat sekali. Ada banyak sekali awan di luar sana. Bahkan, setiap penyedia cloud adalah cloud sendiri. Jadi, salah satu tantangan saat ini adalah menghubungkan cloud, bukan? Jika Anda tenaga penjualan, bukankah menyenangkan untuk terhubung langsung ke iContact dan Kontak Konstan dan ke LinkedIn, misalnya, dan mungkin ke Twitter dan lingkungan lain, cloud lain di luar sana hanya menyatukan solusi bisnis yang masuk akal bagi Anda dan perusahaan Anda.

Jadi, ini adalah beberapa masalah yang perlu diingat, tetapi cloud ada di sini untuk tetap. Ketahuilah bahwa tentang hal itu, perangkat lunak di tempat akan tetap ada. Jadi, apa yang harus kita pahami di perusahaan atau bisnis skala kecil hingga menengah, bagaimana Anda mendefinisikan arsitektur Anda dan mempertahankannya sedemikian rupa sehingga Anda dapat memanfaatkan cloud tanpa menciptakan raksasa di tempat lain di luar kendali Anda? Jadi, jelas seluruh industri pergudangan data berkembang di sekitar kebutuhan untuk mengkonsolidasikan informasi penting untuk menganalisis informasi itu dan membuat keputusan yang lebih baik.

Nah, sekarang Amazon Web Services memiliki Redshift. Itu salah satu siaran web terbesar yang pernah kami lakukan adalah dengan Redshift. Itu masalah yang cukup besar. Mereka mengubah dinamika, mereka mengubah struktur harga. Anda dapat menyaksikan harga Anda turun pada lisensi perangkat lunak perusahaan tradisional sebagian karena cloud computing dan sebagian karena orang-orang ini di luar sana menurunkan titik harga, menekan harga. Jadi, itu kabar baik bagi pengguna akhir. Ini sesuatu yang perlu diingat tentunya bagi siapa pun di luar sana yang mencoba menggunakan beberapa teknologi ini. Jadi, ada sesuatu yang perlu diingat dan kita akan membicarakannya hari ini di acara itu.

Jadi, analis Dr. Robin Bloor akan menjadi analis pertama kami untuk hari itu. Jadi, saya akan pergi ke depan dan mendorong slide pertamanya dan menyerahkan kunci kepadanya. Robin, saya pikir Anda ada di sini di suatu tempat, di sana Anda. Dan dengan itu aku akan menyerahkannya, dan lantai milikmu!

Robin Bloor: Oke, Eric. Terima kasih untuk pengantar itu. Saya menemukan … beberapa hari yang lalu, saya menemukan survei konsumen, pada kenyataannya, yang mengajukan pertanyaan - apakah Anda berpikir bahwa cuaca badai mengganggu komputasi awan? Dan lebih dari 50 persen dari mereka menjawab ya. Saya hanya berpikir saya akan memberi tahu Anda bahwa itu tidak benar, jika Anda salah satu dari mereka yang meyakini hal itu. Dan kemudian, itu agak seperti percaya bahwa, Anda tahu, ketika Anda mendapat salju di televisi adalah karena salju turun di luar.

Cloud, Anda tahu, salah satu halnya adalah jenis, Anda tahu, yang penting, jika Anda suka, detail sederhana dari cloud adalah bahwa cloud sebenarnya adalah pusat data dengan satu atau lain cara, atau layanan cloud tertentu adalah pusat data. Satu-satunya hal adalah, ini adalah pusat data yang berbeda dari cloud tradisional. Jadi, saya akan berbicara dalam ikhtisar tentang cloud sehingga sebagai cadangan Anda untuk masuk ke lebih detail tentang penggunaan cloud karena tidak ada gunanya menutupi tanah yang sama.

Jadi, poin pertama yang ingin saya sampaikan adalah bahwa cloud adalah layanan, Anda tahu? Dan salah satu hal yang sebenarnya terjadi karena cloud computing adalah ada … yah, saya sebut kematian merek, serangkaian merek perangkat lunak memiliki banyak sekali kekuatan dan terus memiliki kekuatan dalam komputasi korporat. Begitu Anda sampai ke cloud, mereka tidak memiliki banyak kekuatan lagi, Anda tahu? Ketika Anda membeli layanan cloud, Anda peduli dengan aplikasi tersebut, tentu saja, Anda peduli dengan level layanan yang akan diberikan cloud kepada Anda, Anda tidak ingin layanan cloud sering gagal, Anda peduli dengan biaya penggunaan dan Anda peduli tentang ini hal-hal karena ini adalah layanan, tetapi apa yang tidak Anda pedulikan lagi adalah bahwa Anda tidak peduli apa perangkat keras yang berjalan pada khususnya, Anda tidak peduli apa teknologi jaringan, Anda tidak peduli apa sistem operasinya itu berjalan adalah, Anda tidak peduli apa sistem file, Anda bahkan tidak peduli apa database itu dan itu benar-benar digunakan secara khusus oleh setiap layanan database yang diberikan dari cloud, Anda tahu? Dan dampaknya adalah bahwa cloud adalah banyak sekali merek perangkat lunak tidak memiliki nilai nyata di cloud karena, Anda tahu, Anda pergi ke cloud dengan satu atau lain cara untuk sesuatu yang merupakan layanan dan bukan lagi produk. Jadi, saya pikir saya bisa melakukan beberapa slide alasan untuk tidak menggunakan cloud, Anda tahu, dan ini semua, jika Anda suka, Anda tahu, berdarah sederhana, alasan yang jelas, tetapi seseorang harus menyatakannya, jadi, saya pikir saya akan.

Jadi, alasan tidak bagi saya … untuk tidak menggunakan cloud - jika mereka tidak dapat memberikan jenis data dan proses tata kelola yang Anda inginkan, Anda tahu, maka itu sama sekali tidak memenuhi kriteria Anda. Jika mereka tidak dapat memberikan kinerja yang Anda inginkan, itu tidak akan memenuhi kriteria. Jika cloud memberi Anda fleksibilitas dalam hal bagaimana Anda bisa memindahkan barang, maka itu tidak akan memenuhi kriteria. Itu hanya alasan yang jelas mengapa layanan cloud tertentu tidak cocok untuk banyak orang di luar sana selain melakukan komputasi korporat.

Anda mungkin tidak melakukannya karena Anda bisa melakukannya dengan lebih murah. Cloud tidak selalu merupakan opsi termurah. Beberapa orang tampaknya berpikir karena ini seringkali merupakan pilihan yang tidak mahal dan akan selalu lebih murah, tidak selalu lebih murah. Dan hal lainnya adalah bahwa jika Anda mengambil aplikasi dari cloud, itu tidak terintegrasi dengan baik dengan apa yang Anda lakukan, maka Anda mungkin tidak akan maju dengan itu dan itu, Anda tahu, alasan untuk berpaling .

Inilah alasan untuk mengadopsi. Anda tahu, salah satu hal yang dapat Anda lakukan di cloud, cukup antipeluru, adalah aktivitas prototyping. Jika Anda bisa prototipe di cloud dan mengimplementasikannya di pusat data, itu sepenuhnya layak dan ada banyak orang yang melakukan itu. Anda dapat mengunggah pekerjaan dari pusat data dengan aplikasi yang tidak penting karena mereka mungkin akan, Anda akan dapat menemukan beberapa jenis layanan cloud yang akan memenuhi tingkat layanan Anda ke hal-hal yang tidak penting. Dan Anda dapat mengunggah aplikasi spesifik seperti salesforce.com dan penawaran serupa dengan itu, Anda tahu, aplikasi standar. Setiap orang memiliki kemampuan di bidang itu dan bidangnya tidak terspesialisasi dan, Anda tahu, tradisional … apa pun yang tersedia di cloud mungkin akan sesuai dengan keinginan Anda.

Jadi, hal terakhir yang ingin saya katakan, itu adalah hal yang agak menarik, sungguh, adalah ketika Anda benar-benar mencari awan, salah satu cara memahami adalah hanya sebagai serangkaian skala ekonomi. Intinya adalah bahwa, Anda tahu, menjalankan pusat data di luar sana dan Anda akan menghubungi pusat data itu dari suatu tempat atau yang lain dan menggunakannya dan oleh karena itu, akan lebih baik, lebih baik berada di main lebih murah daripada jika kamu melakukannya sendiri. Jadi, Anda tahu, ini benar-benar tentang skala ekonomi.

Penyedia cloud, mereka memilih lokasi pusat data dan tempat terbaik untuk menemukan pusat data tepat di sebelah pembangkit listrik, dan terutama tepat di sebelah pembangkit listrik murah. Jadi, satu pembangkit listrik di utara yang kebetulan hidroelektrik atau sesuatu seperti itu. Ini biasanya yang termurah, Anda tahu? Anda benar-benar dapat menemukan pusat data di sana dan Anda akan merasa lebih mudah. Lebih murah untuk mempekerjakan orang di lokasi seperti itu daripada di pusat New York atau San Francisco. Anda dapat menstandarkan seluruh fasilitas dalam hal AC dan daya. Itu akan menyelamatkan Anda banyak karena itu berarti, Anda tahu, Anda dapat memberikan seluruh bangunan untuk itu dan itulah yang persisnya dilakukan oleh semua operator cloud. Mereka membakukan pada perangkat keras jaringan, mereka membakukan pada perangkat keras komputer yang mereka gunakan, biasanya papan x86 komoditas, seringkali mereka akan merakitnya sendiri. Jadi, beberapa bahkan benar-benar membangun semuanya. Mereka akan menggunakan perangkat lunak Amazon yang mereka bisa karena itu sebenarnya berarti tidak ada biaya untuk mengadopsinya. Mereka akan distandarisasi dalam semua perangkat lunak. Jadi, mereka tidak akan pernah meningkatkan apa pun kecuali untuk memutakhirkan sekaligus. Mereka akan mengatur dukungan. Jadi, mereka akan membayar dukungan kepada banyak penyedia yang berbeda yang hanya memiliki fasilitas pendukung mereka sendiri. Mereka akan, memiliki peningkatan dan peningkatan kemampuan dalam arti bahwa mereka akan berjalan lebih dari yang pernah Anda jalankan layanan semacam itu dan mereka akan memantau penggunaannya dengan cara yang sebagian besar pusat data tidak dapat lakukan karena mereka semacam menjalankan hanya satu layanan standar, tetapi sebagian besar pusat data menjalankan serangkaian hal. Dan itulah yang dimaksud dengan cloud, sungguh, dan dengan cara tertentu, dapat menentukan apakah itu menarik minat Anda atau tidak untuk aplikasi tertentu. Jadi, Anda tahu, aturan dasar saya yang kasar adalah bahwa di mana skala ekonomi dimungkinkan, awan akan mengambil alih cepat atau lambat. Tapi, cara inovasi dan fleksibilitas serta hal-hal yang sangat spesifik yang Anda jalani benar-benar tidak bisa. Awan selalu menjadi yang terbaik kedua.

Baik. Biarkan saya memberikannya kembali ke Eric, atau ke Gilbert.

Eric Kavanagh: Oke, Gilbert, saya akan memberi Anda kunci di sini untuk WebEx. Bersiap. Cukup klik di mana saja pada slide itu dan gunakan panah bawah pada keyboard Anda.

Gilbert Van Cutsem: Saya pikir saya memegang kendali.

Eric Kavanagh: Anda memegang kendali.

Gilbert Van Cutsem: Baiklah. Kita mulai. Imperatif awan - langit adalah batasnya, apakah itu legenda urban, atau apa yang akan Anda pikirkan? Ini hanya beberapa pembicaraan dan hal-hal yang perlu dipertimbangkan.

Pertama, dari front "apa", Anda tahu, seperti kita semua tahu, saya tidak berpikir ada yang meragukan ini. SaaS-ification ada di sini untuk tetap karena perangkat lunak sebenarnya tidak pernah mati, itu hanya bergerak ke cloud, kan? Saya pikir saya mengatakan ini sebelumnya di edisi sebelumnya ini. Oh tidak, atau Eric mengatakan itu untuk saya di edisi sebelumnya. Dan saya pikir alasan yang jelas, dan ini kembali ke Robin juga, adalah bahwa di sisi korporat, timeline perusahaan cukup mudah. CMO selalu membutuhkan semuanya dan dia membutuhkannya sekarang. Jadi, dia sudah waktunya untuk pasar. Sedih sekali, itu alasan yang bagus untuknya. CIO, bagaimanapun, sedikit gugup tentang SaaS dan awan karena, Anda tahu, seluruh masalah elastisitas berarti bahwa apa yang naik juga harus turun. Anda harus siap untuk skala, tetapi juga untuk skala. Jadi, dia sedikit gugup tentang itu. CFO tidak gugup, tidak lebih dari biasanya, tetapi dia berkata, "Hei, ini … berapa banyak yang akan membuat kita kembali?" Ini, Anda tahu, belanja modal yang terkenal versus diskusi OPEX. Ini cukup tua, tetapi sangat, Anda tahu, sangat penting di dunia ini. Dan kemudian, yang tak kalah pentingnya, adalah CEO, tentu saja. Dia berkata, "Oh! Mitigasi risiko! Kawan, kalian semua bersemangat, tapi apakah kita siap untuk ini?" Karena risiko adalah apa yang dia pikirkan.

Jadi, apa risikonya? Hanya beberapa pemikiran, bukan? Kita berurusan di sini dengan kepemimpinan pemikiran, tetapi di jalan yang belum selesai karena ini semua adalah hal yang cukup baru, semua hal yang cukup baru. Kami tidak memiliki banyak titik data, sungguh, jika Anda memikirkannya. Jadi, kita juga, di sisi risiko, kita harus berurusan dengan naik pesawat, Anda tahu, orang-orang yang menandatangani perjanjian pergi seperti, "Ya, itulah yang kita inginkan, cara untuk pergi, " mereka mendaftar, tetapi kemudian itu tidak cukup. Anda tahu, Anda harus menyatukan orang dan itu, ingat filmnya? Kembali dalam terjemahan, itu adalah sedikit tentang, Anda tahu, apa itu on-boarding. Dan kemudian, seperti yang baru saja dikatakan Robin, Anda tahu, on-prem belum tentu langsung hilang. Jadi, Anda harus mengintegrasikan kedua dunia. Ini adalah dunia hybrid. Jadi, bagaimana Anda akan melakukannya? 80-20, aturan 80-20 Pareto, apakah itu oke? Apakah itu cukup baik? Dan kemudian sampah di / sampah keluar ketika Anda menghubungkan sistem. Apakah itu tidak apa apa? Apakah itu tahan lama? Karena, Anda tahu, apakah Anda akan bermigrasi, apakah Anda akan memetakan perusahaan Anda ke sistem root, bagaimana Anda akan melakukannya? Dan yang terakhir, yang saya pikir sangat penting, adalah arsitektur multitenant, yang berarti bahwa privasi data pada data Anda sendiri, kadang-kadang disebut "miliki data Anda sendiri, " menjadi sangat penting, Anda tahu? Seratus orang menggunakan sistem yang sama, satu database berada di bawah sistem, siapa yang akan melihat data saya? Hanya saya, bukan? Apakah Anda benar-benar yakin tentang itu? Privasi data, keamanan data membantu para ahli. Jika Anda adalah CIO, itu akan mengembalikan "I" ke dalam CIO karena sekarang Anda bertanggung jawab atas informasi. Itu cukup menarik jika Anda seorang CIO.

Jadi, mari kita bicara sedikit tentang "mengapa." Jadi, maksud strategis dari semua ini sangat, sangat sederhana, saya pikir. Jika Anda seorang pelanggan, ada tekanan pasar. Jika Anda penyedia, ada tekanan kompetitif. Jika Anda memiliki teman sebaya, ada tekanan teman sebaya. Jika Anda pelanggan, itu hanya psikologi pasar. Semua orang ingin pergi ke cloud, SaaS atau apa pun namanya, cloud SaaS, kita semua perlu dan ingin pergi ke sana. Dan alasannya biasanya finansial. Itulah alasan yang jelas, tetapi jika Anda berpikir tentang aspek keuangan, Anda masuk ke dalam apa yang saya sebut paradoks tagihan versus anggaran. Apakah Anda akan berlangganan, sistem all-you-can-eat, $ 50, $ 500 sebulan atau semacamnya, atau apakah Anda bermimpi tentang penggunaan sehingga Anda hanya membayar untuk apa yang benar-benar Anda gunakan? Jadi, bagaimana cara kerjanya, berbasis penggunaan, berbasis konsumsi? Apakah Anda akan mengukur semua hal itu? Itu mungkin tidak akan terjadi segera. Jadi, Anda akan berakhir dengan mekanisme hybrid, yaitu, saya membayar 200 sebulan dan mungkin kadang-kadang 500 karena saya harus membayar untuk konsumsi tambahan. Retainer Plus, mungkin akan, menurut saya, cara untuk pergi.

Tapi, ada juga sesuatu yang saya sebut maksud tersembunyi di depan yang luas, dan saya percaya, Anda tahu, ini benar-benar nyata. Ini adalah perubahan kontrol, CIO versus CMO, pergantian kekuasaan atau perebutan kekuasaan antara CMO, "Saya ingin semuanya dan saya ingin sekarang, " dan CIO, yang mengatakan seperti, "Hei, ini semua tentang data, Anda tahu? Saya dulu menjalankan, 20 tahun yang lalu, itu semua tentang sistem perangkat keras. Sepuluh tahun yang lalu adalah semua tentang aplikasi. Hari ini, semua tentang data. Dan karena saya adalah CIO - informasi - ini semua tentang saya. Saya memegang kendali. " Jadi, itu semacam pergantian kekuasaan atau perebutan kekuasaan yang saya percaya sedang terjadi saat ini antara keduanya, CMO dan CIO.

Jadi, pada akhirnya, ini semua sangat muda sehingga tidak ada yang benar-benar tahu jika kita berada dalam tipe inovator lingkungan atau pada tipe lingkungan adopter awal. Saya percaya kita berada dalam jenis lingkungan pengadopsi awal, bukan mayoritas awal, hanya pengadopsi awal, tetapi, Anda tahu, agak setengah jalan. Jadi, Anda tahu, untuk pelanggan, pengguna akhir, pelanggan, ini tentang memulai, karena CMO ingin memulai, bukan? Jadi, penting untuk tidak berakhir dengan apa yang kita sebut pengembalian berkurang. Start head yang terbatas mungkin menyebabkan hasil yang menurun. Itulah mengapa sangat penting untuk, Anda tahu, menemukan, memercayai pihak-pihak yang dapat memastikan bahwa satu titik kegagalan bukanlah masalah dan keamanan data dihormati. Jadi, itu akan membutuhkan sedikit perubahan manajemen. Jadi, pada akhirnya - hampir selesai, ini adalah slide terakhir - bagaimana kita akan melakukan ini? Bagaimana pindah ke cloud, pindah ke SaaS akan menjadi, Anda tahu, mulus dan mudah? Nah, dengan melakukan dua hal: memperhatikan - penyediaan - benar-benar penting, dan on-boarding, bahkan lebih penting.

Eric Kavanagh: Baiklah …

Gilbert Van Cutsem: Dan dalam hal ini, langit adalah batasnya. Terima kasih.

Eric Kavanagh: Ya. Tadi sangat menyenangkan. Saya menyukai ide-ide yang sangat provokatif, saya suka cara Anda memecahkan semua itu. Saya pikir itu masuk akal. Dan mari kita lanjutkan dan dorong slide pertama Ashish dan saya akan menyerahkan kunci ke WebEx kepada Anda, Ashish. OK silahkan. Cukup klik di mana saja pada slide itu dan gunakan panah bawah pada keyboard Anda. Ini dia.

Ashish Thusoo: Baiklah. Terima kasih, Eric. Hai teman-teman, ini Ashish dan saya akan bercerita tentang Qubole. Jadi, sebagai permulaan saja, Qubole, pada dasarnya ia menyediakan data besar sebagai platform layanan. Ini adalah platform berbasis cloud yang dihosting di cloud Amazon dan Google cloud dan kami menyediakan teknologi seperti Hadoop, Hive, Presto, dan banyak lainnya yang akan saya bicarakan, semuanya dengan cara turnkey sehingga klien kami pada dasarnya dapat keluar dari semua kebingungan di dunia infrastruktur data besar atau keluar dari benar-benar menjalankan operasi infrastruktur ini dan benar-benar lebih fokus pada data mereka dan transformasi yang ingin mereka lakukan pada data mereka. Jadi, itulah tujuan dari Qubole.

Dalam hal manfaat nyata, salah satu cara berpikir tentang Qubole, Anda tahu, tentu saja itu adalah turnkey, platform swalayan untuk analisis data besar dan integrasi data besar yang dibangun di sekitar Hadoop, tetapi lebih mendasar lagi, apa yang dilakukannya adalah bahwa, Anda tahu, untuk semua mesin data besar seperti Hadoop, Hive, Presto, Spark, Chartly, dan sebagainya, itu membawa semua manfaat cloud ke mesin data besar ini dan beberapa manifes kunci yang dibawa dari Perspektif cloud adalah, Anda tahu, membuat infrastruktur adaptif dan dengan beradaptasi, maksud saya lincah sekaligus fleksibel terhadap beban kerja yang dijalankan pada salah satu mesin ini dan juga membuat mesin ini lebih mandiri dan kolaboratif dalam arti bahwa, Anda tahu, Qubole menyediakan antarmuka di mana Anda dapat menggunakan teknologi-teknologi khusus ini tidak hanya untuk pengembangan Anda atau, Anda tahu, tugas-tugas yang berorientasi pengembang, tetapi bahkan analis data Anda yang lain juga dapat mulai mendapatkan manfaat dari teknologi ini untuk layanan mandiri antarmuka.

Kami mendapatkan banyak, Anda tahu, mengenai hal ini, Anda tahu, webinar, Anda tahu, ini adalah salah satu dari perspektif kami tentang manfaat awan apa yang dibawa Qubole ke data besar. Jadi, jika Anda hanya melakukan perbandingan antara bagaimana Anda menjalankan, katakanlah, Hadoop dan biarkan itu bekerja dalam pengaturan on-prem, dalam pengaturan on-prem, Anda selalu berpikir dalam hal cluster statis, Anda tahu, Anda memperbaiki cluster, Anda mungkin mengukur mereka untuk penggunaan puncak Anda dan Anda menyimpannya di sana dan kemudian jika Anda harus mengubahnya maka Anda harus melalui seluruh proses pengadaan, penyebaran, pengujian dan sebagainya dan seterusnya. Perubahan Qubole bahwa dengan membuat cluster sepenuhnya berdasarkan permintaan, cluster kami sepenuhnya elastis, kami menggunakan objek yang disimpan dari cloud untuk benar-benar menyimpan data dan cluster muncul dan, Anda tahu, mereka muncul berdasarkan permintaan yang dihasilkan oleh para pengguna dan mereka pergi ketika tidak ada permintaan. Jadi, ini menjadikan infrastruktur itu jauh lebih gesit dan fleksibel serta adaptif dengan beban kerja Anda.

Contoh lain dari fleksibilitas adalah, Anda tahu, hari ini Anda mungkin telah membuat cluster statis Anda di sini, Anda tahu, dengan beban kerja tertentu dan jika beban kerja Anda berubah dan infrastruktur Anda sekarang perlu ditingkatkan, mungkin Anda perlu lebih banyak memori pada mesin Anda dan hal-hal seperti itu. Sekali lagi, Anda tahu, melakukan ini di cloud melalui Qubole misalnya, membuatnya menjadi sederhana. Anda selalu dapat menyewa jenis mesin baru yang berbeda dan, Anda tahu, mendapatkan klaster, kluster 100-simpul dan berjalan dalam beberapa menit sebagai lawan dari berminggu-minggu Anda harus menunggu Hadoop di tempat.

Hal penting lainnya yang membedakan Qubole dari on-prem adalah bahwa Qubole pada dasarnya, sebagai penawaran layanan, jadi semua alat dan infrastruktur yang Anda perlukan untuk mengintegrasikan layanan, Anda tidak perlu … dimanapun on-prem, Anda tahu, itu terutama Anda mengambil perangkat lunak, Anda harus menjalankannya sendiri, Anda harus mengintegrasikannya sendiri dan melakukan semua manfaat itu, semua manfaat dari model SaaS adalah petunjuk untuk, Anda tahu, bagaimana Qubole menawarkan data besar sebagai lawan menjalankan Hadoop sendiri.

Slide ini biasanya mencakup arsitektur kita. Kami, tentu saja, berdasarkan pada cloud, kami menyimpan data kami pada objek-objek di cloud di cloud, Google cloud dan Google Compute Engine atau Amazon Web Services. Kami mengambil semua proyek ekosistem Hadoop dan sekitar itu, kami telah mengembangkan IP kunci seputar penskalaan otomatis dan manajemen mandiri, kami telah melakukan banyak optimasi cloud untuk membuat teknologi komponen ini bekerja sangat baik di cloud seperti, Anda tahu, infrastruktur cloud adalah sangat berbeda dari hanya menjalankan hal-hal pada logam kosong dan sejumlah besar konektor data untuk memungkinkan data untuk dipindahkan dan keluar dari platform ini. Jadi, yang membandingkan platform cloud dan yang memungkinkan itu, Anda tahu, itu adalah kunci … fitur utama ada cara membuat semua layanan mandiri sehingga Anda tidak harus memiliki yang kuat … Anda tidak perlu tidak memiliki jejak operasional yang sangat besar saat menjalankan ini, tetapi kami mengaitkannya dengan meja kerja data kami apakah ini adalah alat untuk analis, apakah ini adalah alat tata kelola data, apakah ini adalah alat templating, dan seterusnya dan seterusnya sehingga Anda dapat membawa manfaat dari teknologi ini, tidak hanya untuk pengembang, tetapi pengguna bisnis lain dan perusahaan juga. Dan tentu saja, kami juga menyatukan platform cloud ini dengan alat-alat yang mungkin sudah Anda gunakan apakah ini adalah, Anda tahu, alat pemanfaatan atau hanya Tableau atau apakah mereka menggunakan, Anda tahu, lebih banyak jenis data pergudangan produk seperti Redshift dan seterusnya dan sebagainya.

Saat ini, layanan ini berjalan pada skala yang cukup besar, kami memproses hampir 40 petabyte data setiap bulan sekarang di seluruh basis klien kami. Cluster kami bervariasi dalam ukuran dari 10-node cluster hingga 1500-node cluster dan, Anda tahu, dalam hal rentang skala yang dapat kami proses dan pada umumnya, sesuai pengetahuan saya, kami mungkin menjalankan beberapa yang terbesar cluster di cloud sejauh yang menyangkut Hadoop dan kami memproses sekitar 250.000 mesin virtual dalam satu bulan di seluruh cluster kami. Ingat, model kami adalah kelompok berdasarkan permintaan, yang memiliki manfaat luar biasa dalam hal mengurangi beban kerja operasional Anda serta meningkatkan Anda dan seterusnya dan seterusnya.

Akhirnya, Anda tahu, salah satu dari kami, Anda tahu, ini hanyalah contoh bagaimana Qubole telah transformatif ke berbagai perusahaan. adalah contoh dari klien kami. Mereka sudah ada di cloud, mereka menjalankan Elastic MapReduce di cloud, misalnya, dan penggunaan data di sana terbatasi. Mereka akan memiliki sekitar 30 pengguna aneh yang bisa menggunakan teknologi itu. Dengan Qubole, mereka telah mampu mengembangkannya menjadi lebih dari 200-aneh pengguna di perusahaan yang telah melihat perluasan kasus penggunaan data besar dan itu benar-benar membawa, Anda tahu, apa yang kita sebut definisi platform data besar yang gesit dan bahwa itu menjadi sangat penting bagi banyak beban kerja analitik mereka.

Jadi, untuk menutup, Anda tahu, itu adalah primer singkat tentang Qubole. Pada dasarnya, visi kami adalah bagaimana kami membuat perusahaan yang jauh lebih lincah di sekitar data besar dan pada dasarnya, kami memanfaatkan manfaat cloud dan membawa mereka untuk menanggung teknologi data besar di sekitar Hadoop sehingga klien kami dapat memanfaatkan manfaat kelincahan dan manfaat tersebut. fleksibilitas dan manfaat yang bersifat swalayan di cloud untuk menjadi yang jauh lebih efektif untuk kebutuhan data mereka. Jadi, saya akan berhenti di sana dan menyerahkannya kembali kepada Eric.

Eric Kavanagh: Baiklah. Kedengarannya hebat dan sekarang, saya akan menyerahkannya kepada Mike Miller dari Cloudant. Mike, aku memberikanmu kuncinya sekarang. Cukup klik pada slide, ini dia. Bawa pergi.

Mike Miller: Sepertinya saya punya kuncinya. Jadi, saya akan minta maaf. Saya kehilangan … Saya pikir saya lupa mengirim beberapa font dengan presentasi saya. Jadi, semoga Anda bisa melihat masa lalu dan membayangkannya indah. Tapi, ya, ini menyenangkan. Saya punya daftar panjang di sini, hal-hal provokatif yang saya dengar yang saya tuliskan bahwa saya ingin kembali kepada Anda di panel. Jadi, saya akan mencoba untuk melewati ini dengan cepat.

Jadi, saya akan mulai dengan Cloudant. Cloudant adalah basis data sebagai layanan, penyedia cloud kami dan sebenarnya, saya bahkan tidak memiliki logo baru. Kami diakuisisi oleh IBM belum lama ini. Jadi, kami … Saya akan berbicara tentang layanan kami dan terutama fokus pada upaya membuat pengguna dan pelanggan kami gesit dengan cara yang cukup berbeda dari pembicara sebelumnya.

Cloudant menyediakan basis data sebagai layanan dan layanan terkait data lainnya untuk orang yang membangun aplikasi. Jadi, kami terlibat langsung dengan pengembang dan kami fokus pada data operasional atau OLTP berbeda dengan analitik yang kami dengar dari Ashish sebelumnya. Dan intinya benar-benar, seluruh nilai Cloudant, yang dapat dipecah menjadi membantu pengguna kami melakukan lebih banyak dan itu membangun lebih banyak aplikasi, tumbuh lebih banyak dan lebih banyak tidur. Saya akan berbicara tentang mereka dengan sedikit detail, tetapi ide umum di sini adalah bahwa jika Anda adalah pengguna, Anda tahu, Anda berada di perusahaan bisnis, Anda sedang membangun aplikasi baru, menambahkan fitur ke aplikasi atau web yang ada startup seluler, Anda harus fokus pada kompetensi inti Anda. Dan sebelumnya, mungkin hingga satu dekade yang lalu, TI menjadi pembeda, Anda tahu, persaingan, maaf, kerusakan kompetitif bahkan menjalankan database dengan baik untuk menjadi keunggulan kompetitif. Lega bahwa hari-hari itu sudah berakhir! Jadi, cara kami benar-benar mencoba untuk bekerja dengan pengguna kami adalah mendorong mereka untuk menggunakan layanan komposit, modular, dapat digunakan kembali, dapat disusun dengan gagasan bahwa mengurangi waktu pemasaran, meningkatkan skalabilitas. Dan gagasan keseluruhan di sini adalah bahwa cloud bukan hanya, Anda tahu, sesuatu yang baru didorong ke pengguna, itu benar-benar sebuah pasar … itu adalah evolusi pasar karena cara orang membangun aplikasi, mengkonsumsi aplikasi, perangkat yang mereka jalankan dan skala data berubah secara radikal dalam 5-10 tahun terakhir. Itu benar-benar menekankan arsitektur aplikasi yang ada untuk membangun aplikasi serta hanya berurusan dengan data dan beban kerja analitik secara offline. Jadi, itu membuka seluruh aliran peluang.

Jadi, Cloudant adalah database terdistribusi sebagai layanan dan itu unik, saya percaya, pada permulaannya benar-benar dikirim dengan strategi mobile sejak awal, dan saya akan membicarakan hal ini secara rinci, tetapi idenya adalah menulis aplikasi sekarang, Anda tidak menulis hanya untuk satu platform, bukan? Anda menulis untuk sesuatu yang saya dapat menjalankan skala petabyte di cloud, itu juga harus dapat berjalan dengan lancar di desktop atau di browser dan semakin banyak kita melihat sesuatu, kita harus berjalan di perangkat seluler atau perangkat semi-terhubung atau perangkat yang dapat dipakai atau sesuatu yang kita sebut sebagai IOT. Jadi, saya pikir, Anda tahu, aplikasi yang dapat menangani dengan baik dan memanfaatkan klien yang berbeda sangat kompetitif di pasar dan apa yang kami coba lakukan adalah membuatnya mudah bagi orang untuk menggunakan satu API dalam model pemrograman tunggal untuk menulis, untuk menangani data di semua perangkat berbeda yang memiliki skala yang sangat berbeda. 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. Bagus. 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. Bagaimana menurut anda?

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. Baik. 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. Benar. 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. Ya. Tidak masalah. 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. Ya. 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. Saya tidak tahu 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. Itu pertanyaan yang sangat bagus. 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. Baik. 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. Bagus! 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. Hati hati. Sampai jumpa.