Awan imperatif - apa, mengapa, bila dan bagaimana - episod berteknologi episod 3

Eric Kavanagh: Tuan dan lelaki, hello dan selamat datang sekali lagi ke TechWise. Nama saya Eric Kavanagh. Saya akan menjadi moderator anda untuk Episod 3. Ini adalah pertunjukan baru yang kami telah direka dengan rakan-rakan kami dari Techopedia, sebuah laman web yang sangat keren yang jelas memberi tumpuan kepada teknologi, dan sudah tentu, di sini di The Bloor Group, kami menumpukan perhatian kepada perusahaan teknologi. Oleh itu, perisian perusahaan dari pelbagai jenis, dan format TechWise keseluruhan direka untuk memberi pengunjung kami pandangan keras yang baik pada ruang tertentu. Jadi, kami telah melakukan Hadoop sebagai contoh, kami melakukan analisis dalam pameran terakhir dan dalam pameran ini, kami bercakap tentang awan.

Jadi, ia dipanggil "The Cloud Imperative - Apa, Di mana, Kapan dan Bagaimana." Kami akan bercakap dengan beberapa penganalisis hari ini dan kemudian tiga vendor. Jadi, Qubole, Cloudant dan Attunity adalah penaja acara hari ini. Terima kasih banyak untuk orang-orang untuk masa dan perhatian mereka hari ini dan terima kasih besar, tentu saja, kepada anda semua di luar sana. Dan ingat bahawa sebagai peserta menunjukkan ini, anda memainkan peranan penting. Kami mahu anda bertanya, terlibat, berinteraksi, beritahu kami apa yang anda fikir kerana jelas, tujuan keseluruhan rancangan ini adalah untuk membantu anda memahami apa yang berlaku di dunia pengkomputeran awan.

Deck Imperatif Awan

Jadi, mari kita teruskan. Tuan rumah pertama, tuan rumah anda di sana, Eric Kavanagh itu saya dan kemudian kami mempunyai Dr Robin Bloor memanggil dari lapangan terbang, sebagai fakta dan rakan baik kami, Gilbert, Gilbert Van Cutsem, seorang penganalisis bebas, juga akan berkongsi beberapa pemikiran dengan anda. Kemudian kita akan mendengar dari Ashish Thusoo, Ketua Pegawai Eksekutif dan pengasas bersama Qubole. Kami akan mendengar dari Mike Miller, ketua saintis di Cloudant dan akhirnya dari Lawrence Schwartz, VP Pemasaran di Attunity. Oleh itu, kami mendapat banyak kandungan yang disediakan untuk anda hari ini.

Jadi, awan - edict dari atas - ini adalah konsep yang datang kepada saya hari yang lain ketika saya berfikir tentang ini. Benar, pengkomputeran awan hanya besar hari ini. Maksud saya, ia sangat menarik untuk melihat evolusi barangan ini dan salah satu contoh yang sering saya berikan ialah dalam teknologi webcanya sendiri. Sudah tentu, orang-orang yang menelefon anda pada awal mendengar beberapa cabaran teknikal yang menarik. Itu satu masalah dengan awan yang berubah, perubahan format, perubahan piawai, perubahan antara muka dan kadang kala apabila anda cuba menyambungkan dua kawasan yang berbeza bersama-sama, anda mendapat sedikit kesulitan, anda mendapat sedikit masalah. Jadi, ini sebenarnya salah satu perkara yang perlu dibimbangkan dengan pengkomputeran awan. Berhati-hati dengan seni bina! Anda dapat melihat bahawa pada titik peluru terakhir.

Salah satu perkara yang kami lakukan, sebagai nota sampingan di sini, untuk siaran web kami, kami mempunyai vendor persidangan telefon yang berasingan. Kemudian kita menggunakan WebEx. Kami tidak menggunakan audio WebEx kerana terus terang, satu kali kami menggunakan audio WebEx tahun lalu dan ia terhempas dan dibakar dengan cara yang paling tidak menyenangkan. Oleh itu, kami tidak bersedia untuk menjalankan risiko itu lagi. Oleh itu, kami menggunakan syarikat rakaman audio kami yang dipanggil Arkadin sebagai hakikatnya dan kami menjalin bersama, dalam masa nyata, semua penyelesaian yang berbeza ini. Dan ideanya ialah kami boleh menghantar e-mel kepada anda dengan aplikasi e-mel yang berasingan dengan slaid sekiranya contohnya, WebEx akan terhempas, kami memberitahu anda semua untuk mendail, kami akan menghantar e-mel kepada anda slaid dan hanya meneruskannya lebih atau kurang tanpa persekitaran WebEx. Jadi, cara anda boleh mendapatkan masalah-masalah seperti ini, tetapi isu-isu seperti ini adalah di seluruh tempat.

Tetapi, terdapat banyak faedah untuk awan. Sudah tentu, ia adalah halangan yang rendah untuk masuk, anda boleh melihat anak poster pengkomputeran awan adalah salesforce.com tentu saja, yang hanya merevolusikan perniagaan, khususnya automasi kuasa jualan, jelas. Tetapi, anda telah mendapat barangan seperti Marketo dan iContact dan Kenalan Tetap dan Sailthru dan, kebaikan yang baik, dari segi pemasaran dan automasi jualan, terdapat banyak alat, tetapi itu bukan semuanya. HR mendapatkannya ke permainan keseluruhan awan, analisis dalam permainan awan. Lihatlah syarikat kecil yang diketahui di luar sana Perkhidmatan Web Amazon, apa yang mereka lakukan dengan pengkomputeran awan - ia hanya besar. Dan saya mendengar petikan yang hebat pada hari yang lain dari seorang lelaki yang kami banyak bekerjasama dengan David yang kini berada di Cisco, sebagai fakta, syarikat yang membeli WebEx. Tidak pasti mereka telah melabur sebanyak yang saya ingin mereka miliki di WebEx, tapi itu bukan keputusan saya, bukan? Tetapi, dia berada di Cisco pada hari-hari ini dan dia mempunyai petikan yang sangat lucu dan tepat, dan itu, "tidak ada satu awan, terdapat banyak awan, " dan itu betul-betul betul. Terdapat banyak dan banyak awan di luar sana. Malah, setiap penyedia awan adalah awan sendiri. Oleh itu, salah satu cabaran hari ini ialah untuk menyambungkan awan, bukan? Sekiranya anda adalah tenaga jualan, tidakkah anda menyambung terus ke iContact dan Kenalan Tetap dan untuk LinkedIn, contohnya, dan mungkin ke Twitter dan persekitaran lain, awan lain di luar sana hanya menetapkan penyelesaian perniagaan yang masuk akal untuk anda dan syarikat anda.

Jadi, ini adalah beberapa isu yang perlu diingat, tetapi awan ada di sini untuk kekal. Hanya tahu bahawa, perisian premis di sini untuk kekal. Jadi, apa yang perlu kita fikirkan dalam perusahaan atau mana-mana perniagaan kecil atau sederhana, bagaimanakah anda menentukan seni bina dan mengekalkannya supaya anda boleh memanfaatkan awan tanpa membuat raksasa di tempat lain di luar kawalan anda? Oleh itu, jelasnya keseluruhan industri pergudangan data berkembang di sekitar keperluan untuk menyatukan maklumat kritikal untuk menganalisis maklumat tersebut dan membuat keputusan yang lebih baik.

Nah, sekarang Perkhidmatan Web Amazon mempunyai Redshift. Itulah salah satu webcast terbesar yang pernah kami lakukan adalah dengan Redshift. Itulah perjanjian yang cukup besar. Mereka mengubah dinamik, mereka mengubah struktur penetapan harga. Anda boleh menonton apabila harga anda turun pada pelesenan perisian perusahaan tradisional sebahagiannya kerana pengkomputeran awan dan sebahagiannya kerana orang-orang ini di luar sana menurunkan titik harga, meletakkan tekanan pada harga. Jadi, itu berita baik untuk pengguna akhir. Ia sesuatu yang perlu diingat untuk sesiapa sahaja di luar sana yang cuba menggunakan beberapa teknologi ini. Jadi, ia adalah sesuatu yang perlu diingat dan kita akan bercakap mengenai hari ini di pameran itu.

Oleh itu, penganalisis Dr Robin Bloor akan menjadi penganalisis pertama kami untuk hari itu. Jadi, saya akan pergi ke depan dan menolak slaid pertamanya dan menyerahkan kunci kepadanya. Robin, saya fikir anda berada di sini di suatu tempat, di sana anda berada. Dan dengan itu saya akan menyerahkannya, dan lantai adalah milik anda!

Dr Robin Bloor: Baiklah, Eric. Terima kasih kerana pengenalan itu. Saya jumpa … beberapa hari yang lalu, saya melihat tinjauan pengguna, sebenarnya, yang menanyakan soalan - adakah anda menganggap cuaca buruk yang mengganggu pengkomputeran awan? Dan lebih daripada 50 peratus daripada mereka berkata ya. Saya hanya fikir saya akan memberitahu anda bahawa tidak, jika anda adalah salah seorang yang percaya dalam hal itu. Dan kemudian, itu agak seperti mempercayai bahawa, anda tahu, apabila anda mempunyai salji di televisyen adalah kerana ia bersiaran di luar.

Awan, anda tahu, salah satu perkara itu adalah jenisnya, anda tahu, yang penting, jika anda suka, butiran sederhana awan ialah awan itu sebenarnya pusat data dalam satu cara atau yang lain, atau mana-mana perkhidmatan awan tertentu pusat data. Satu-satunya perkara adalah, ia adalah pusat data yang berbeza daripada awan tradisional. Oleh itu, saya akan bercakap dalam gambaran keseluruhan mengenai awan supaya cadangan anda untuk lebih terperinci mengenai kegunaan awan kerana tidak ada titik yang meliputi tanah yang sama.

Oleh itu, jenis titik pertama yang saya ingin buat ialah perkhidmatan awan itu, anda tahu? Dan salah satu daripada perkara yang sebenarnya berlaku kerana pengkomputeran awan ialah ada … baik, saya memanggil kematian jenama, satu siri jenama perisian mempunyai banyak kuasa yang besar dan terus mempunyai kuasa dalam pengkomputeran korporat. Sebaik sahaja anda sampai ke awan, mereka tidak mempunyai kuasa lagi, anda tahu? Apabila anda membeli perkhidmatan awan, anda mengambil berat mengenai aplikasi itu, sudah tentu, anda mengambil berat tentang tahap perkhidmatan awan akan memberi anda, anda tidak mahu perkhidmatan awan gagal sering, anda mengambil berat tentang kos penggunaan dan anda mengambil berat tentang perkara-perkara ini perkara-perkara kerana ini adalah perkhidmatan, tetapi apa yang anda tidak peduli lagi adalah bahawa anda tidak peduli apa perkakasan yang dijalankan pada khususnya, anda tidak peduli apa teknologi rangkaian itu, anda tidak peduli apa sistem operasi ia berjalan, anda tidak peduli apa sistem fail, anda tidak peduli apa pangkalan data dan itu sebenarnya digunakan secara khusus oleh mana-mana perkhidmatan pangkalan data yang diberikan keluar dari awan, anda tahu? Dan impaknya sedemikian ialah awan itu banyak jenama perisian yang tidak mempunyai nilai sebenar di awan kerana, anda tahu, anda pergi ke awan dalam satu cara atau yang lain untuk sesuatu yang merupakan perkhidmatan dan tidak lagi produk. Jadi, saya fikir saya dapat melakukan beberapa sebab mengapa tidak menggunakan awan, anda tahu, dan ini semua, jika anda suka, anda tahu, sebab mudah, berdarah jelas, tetapi ada yang menyatakannya, jadi, saya fikir saya akan.

Oleh itu, sebab tidak kepada saya … untuk tidak menggunakan awan - jika mereka tidak dapat menyediakan jenis data dan proses urus tadbir yang anda mahukan, anda tahu, maka ia hanya tidak memenuhi kriteria anda. Jika mereka tidak dapat memberikan prestasi yang anda mahu, itu tidak akan memenuhi kriteria. Sekiranya awan memberi anda fleksibiliti dari segi bagaimana anda boleh menggerakkan barangan di sekitar maka ia tidak akan memenuhi kriteria. Itulah alasan yang jelas mengapa perkhidmatan awan tertentu tidak sesuai dengan banyak orang di luar sana selain melakukan pengkomputeran korporat.

Anda mungkin tidak melakukannya kerana anda boleh melakukannya lebih murah. Awan tidak selalu pilihan yang paling murah. Sesetengah orang seolah-olah berfikir kerana selalunya pilihan yang murah itu akan menjadi lebih murah, ia tidak semestinya lebih murah. Dan perkara lain ialah jika anda mengambil aplikasi dari awan, ia tidak menggabungkan dengan baik dengan apa yang anda lakukan, maka anda mungkin tidak akan maju dengannya dan itu adalah, anda tahu, alasan untuk berpaling .

Inilah sebab-sebab untuk menerima pakai. Anda tahu, salah satu perkara yang boleh anda lakukan di awan, cukup peluru, adalah aktiviti prototyping. Jika anda sama ada anda boleh prototaip di awan dan melaksanakan di pusat data, ia sepenuhnya berdaya maju dan terdapat sejumlah besar orang yang melakukan itu. Anda boleh memuat naik kerja dari pusat data dengan aplikasi yang tidak kritikal kerana mungkin, anda akan dapat mencari beberapa jenis perkhidmatan awan yang akan memenuhi tahap perkhidmatan anda dengan perkara yang tidak kritikal. Dan anda boleh memuat naik aplikasi tertentu seperti salesforce.com dan persembahan yang serupa dengannya, anda tahu, aplikasi standard. Semua orang mempunyai keupayaan dalam bidang itu dan bidang itu tidak khusus dan, anda tahu, tradisional … apa sahaja yang terdapat di awan mungkin akan menjadi apa yang anda pergi.

Jadi, perkara akhir yang saya ingin katakan, itu sesuatu yang menarik, sebenarnya, apabila anda benar-benar mencari awan, satu cara pemahaman adalah seperti siri skala ekonomi. Maksudnya ialah, anda tahu, menjalankan pusat data di luar sana dan anda akan mendail ke pusat data itu dari suatu tempat atau yang lain dan menggunakannya dan oleh itu, ia akan menjadi lebih baik, lebih baik menjadi lebih murah daripada jika anda melakukannya sendiri. Jadi, anda tahu, itu benar-benar semua tentang skala ekonomi.

Penyedia awan, mereka memilih lokasi pusat data dan tempat terbaik untuk mencari pusat data adalah tepat di sebelah stesen kuasa, dan terutama di sebelah stesen kuasa yang murah. Oleh itu, satu stesen kuasa di utara yang berlaku menjadi hidroelektrik atau sesuatu seperti itu. Ia biasanya yang paling murah, anda tahu? Anda sebenarnya boleh mencari pusat data di sana dan anda akan mendapati ia lebih mudah. Ia lebih murah untuk menyewa orang di lokasi seperti itu di tengah-tengah New York atau San Francisco. Anda boleh menyeragamkan seluruh kemudahan dari segi penyaman udara dan kuasa. Ini akan menjimatkan banyak kerana ia bermakna, anda tahu, anda boleh memberikan keseluruhan bangunan kepadanya dan itulah yang sebenarnya dilakukan oleh semua pengendali awan. Mereka menyeragamkan perkakasan rangkaian, mereka menyeragamkan perkakasan komputer yang mereka gunakan, biasanya papan komoditi x86, selalunya mereka akan memasangnya sendiri. Jadi, ada yang benar-benar membina semuanya. Mereka akan menggunakan perisian Amazon yang mereka dapat kerana ia sebenarnya bermakna tidak ada kos untuk mengadopsi itu. Mereka akan menyeragamkan dalam semua perisian. Jadi, mereka tidak akan meningkatkan apa-apa kecuali menaik taraf sekaligus. Mereka akan menganjurkan sokongan. Oleh itu, mereka akan memberi sokongan kepada pelbagai pembekal yang hanya mempunyai kemudahan sokongan mereka sendiri. Mereka akan mempunyai keupayaan skala dan keciciran dalam erti kata bahawa mereka akan berjalan lebih daripada yang anda akan menjalankan perkhidmatan semacam itu dan mereka akan memantau penggunaan mereka dengan cara yang kebanyakan pusat data tidak dapat kerana mereka semacam menjalankan satu perkhidmatan standard sahaja, tetapi kebanyakan pusat data menjalankan pelbagai perkara. Dan itulah awan itu semua, benar-benar, dan dengan cara tertentu, boleh menentukan sama ada ia menarik minat anda atau sama ada ia tidak untuk sebarang aplikasi tertentu. Jadi, anda tahu, jenis praktikal kasar saya ialah apabila ekonomi skala mungkin, awan akan mengambil alih lambat laun. Tetapi, cara inovasi dan fleksibiliti dan perkara yang sangat spesifik yang anda pergi sendiri sebenarnya tidak boleh. Awan sentiasa akan menjadi yang terbaik kedua.

Baik. Izinkan saya lulus kembali kepada Eric, atau ke Gilbert.

Eric Kavanagh: Okay, Gilbert, saya akan memberikan kunci di sini ke WebEx. Bersiap sedia. Cuma klik di mana sahaja pada slaid itu dan gunakan panah bawah pada keyboard anda.

Gilbert Van Cutsem: Saya rasa saya terkawal.

Eric Kavanagh: Anda terkawal.

Gilbert Van Cutsem: Baiklah. Di sini kita pergi. Awan awan - langit adalah had, apakah itu legenda bandar, atau apa yang anda fikirkan? Ini hanya beberapa perbincangan dan perkara yang perlu dipertimbangkan.

Pertama, dari hadapan "apa", anda tahu, seperti yang kita semua tahu, saya tidak fikir ada orang yang meragui ini. SaaS-ification di sini untuk tinggal kerana perisian itu sebenarnya tidak pernah mati, ia hanya bergerak ke awan, kan? Saya fikir saya berkata demikian sebelum ini dalam edisi terdahulu ini. Oh tidak, atau Eric berkata bahawa untuk saya dalam edisi sebelumnya. Dan saya fikir sebab yang jelas, dan ini kembali kepada Robin dengan cara yang sama, adalah bahawa di sisi korporat perkara, garis masa korporat sangat mudah. CMO selalu memerlukannya dan dia memerlukannya sekarang. Oleh itu, dia sudah tiba masanya untuk memasarkan. Begitu sedih, itu adalah alasan yang baik untuk itu dengan cara baginya. CIO, bagaimanapun, agak gugup tentang SaaS dan awan kerana, anda tahu, masalah keanjalan keseluruhan bermakna bahawa apa yang naik juga mesti turun. Anda mesti bersiap sedia untuk skala, tetapi juga untuk skala kembali. Jadi, dia agak gugup tentang perkara itu. CFO tidak gementar, tidak lebih daripada yang biasa, tapi dia pergi seperti, "Hei, ini … berapa banyak ini akan membuatkan kita kembali?" Inilah, anda tahu, perbelanjaan modal yang terkenal berbanding perbincangan OPEX. Ia cukup tua, tapi sangat, anda tahu, sangat penting di dunia ini. Dan kemudian, yang terakhir tetapi yang paling tidak, adalah CEO, sudah tentu. Beliau pergi seperti, "Oh, pengurangan risiko! Guys, anda semua teruja, tetapi adakah kami bersedia untuk ini?" Kerana risiko adalah apa yang difikirkannya.

Jadi, apakah risiko? Hanya beberapa fikiran, bukan? Kami berurusan di sini dengan kepimpinan pemikiran, tetapi di jalan yang belum selesai kerana ini semua perkara yang baru, semuanya baru-baru ini. Kami tidak mempunyai banyak titik data, sememangnya, jika anda memikirkannya. Oleh itu, kita juga, pada sisi risiko, kita harus berurusan dengan orang lain, anda tahu, orang yang menandatangani perjanjian seperti, "Ya, itulah yang kita mahu, jalan untuk pergi, " mereka mendaftar, tetapi kemudian ini tidak cukup. Anda tahu, anda perlu orang-orang di papan dan itu, ingat filem? Kembali dalam terjemahan, itu sedikit, anda tahu, apa yang ada di kapal terbang adalah semua. Dan kemudian juga, seperti yang dikatakan oleh Robin, anda tahu, secara langsung tidak semestinya akan segera pergi. Jadi, anda perlu mengintegrasikan kedua-dua dunia. Ia adalah dunia hibrid. Jadi, bagaimana anda akan melakukannya? 80-20, Pareto 80-20, apakah itu baik? Adakah itu cukup baik? Dan kemudian sampah dalam / sampah apabila anda menyambungkan sistem. Adakah itu baik-baik saja? Adakah itu tahan lama? Kerana, anda tahu, adakah anda akan berhijrah, adakah anda akan memetakan perniagaan anda ke sistem akar, bagaimana anda akan melakukannya? Dan kemudian yang terakhir, yang saya fikir sangat penting, adalah seni bina multitenan, yang bermaksud bahawa privasi data pada data anda sendiri, kadangkala ia dipanggil "memiliki data sendiri, " menjadi sangat penting, anda tahu? Seratus orang menggunakan sistem yang sama, satu pangkalan data duduk di bawah sistem, siapa yang akan melihat data saya? Hanya saya, kan? Adakah anda benar-benar yakin tentang itu? Privasi data, keselamatan data membantu pakar. Jika anda CIO, ia membawa balik "I" ke CIO kerana sekarang anda bertanggungjawab terhadap maklumat. Itu cukup menarik jika anda adalah CIO.

Jadi, mari kita bercakap sedikit tentang "mengapa." Oleh itu, niat strategik semua ini sangat, sangat mudah, saya rasa. Sekiranya anda pelanggan, terdapat tekanan pasaran. Jika anda pembekal, terdapat tekanan kompetitif. Sekiranya anda mempunyai rakan sebaya, terdapat tekanan rakan sebaya. Jika anda seorang pelanggan, ia hanya psikologi pasaran. Semua orang mahu pergi ke awan, SaaS atau apa sahaja yang anda panggil, awan SaaS, kita semua perlukan dan mahu pergi ke sana. Dan sebab itu biasanya kewangan. Itulah alasan yang jelas, tetapi jika anda berfikir tentang aspek kewangan, anda masuk ke dalam apa yang saya panggil paradoks bil-versus-bajet. Adakah anda akan pergi untuk langganan, semua-anda-boleh-makan sistem, $ 50, $ 500 sebulan atau sesuatu seperti itu, atau adakah anda bermimpi tentang penggunaan berdasarkan supaya anda hanya membayar untuk apa yang anda benar-benar menggunakan? Dan bagaimana, bagaimanakah ia akan berfungsi, berasaskan penggunaan, berasaskan penggunaan? Adakah anda akan meter semua barangan itu? Ia mungkin tidak akan berlaku dengan serta-merta. Jadi, anda akan berakhir dengan mekanisme hibrid, iaitu, saya membayar 200 sebulan dan mungkin kadang-kadang 500 kerana saya terpaksa membayar untuk penggunaan tambahan. Retainer Plus, itu mungkin akan, pada pandangan saya, cara untuk pergi.

Tetapi, terdapat juga sesuatu yang saya sebut niat tersembunyi di bahagian depan, dan saya percaya bahawa, anda tahu, ini benar-benar nyata. Ia adalah perubahan kawalan, itu adalah CIO berbanding CMO, peralihan kuasa atau perjuangan kuasa antara CMO, "Saya mahu semuanya dan saya mahu sekarang, " dan CIO, yang berkata seperti, "Hei, ini semua kira-kira data, anda tahu saya pernah berlari, 20 tahun yang lalu, ia adalah mengenai sistem perkakasan.Sepuluh tahun yang lalu adalah semua tentang aplikasi.Sekarang, ini semua tentang data.Dan kerana saya adalah maklumat CIO - itu semua tentang saya berada dalam kawalan. " Jadi, itulah pergeseran kuasa atau perjuangan kuasa saya percaya yang berlaku sekarang antara kedua-dua, CMO dan CIO.

Jadi, pada akhirnya, ini semua sangat muda sehingga tiada siapa yang benar-benar mengetahui sama ada kita berada di dalam persekitaran jenis inovator atau di dalam persekitaran awal yang mengadopsi. Saya percaya kita berada di alam persekitaran awal, bukan majoriti awal, hanya penerimanya awal, tetapi, anda tahu, semacam separuh jalan. Jadi, anda tahu, untuk pelanggan, pengguna akhir, pelanggan, ini tentang mendapatkan permulaan bermula kerana CMO mahu permulaan bermula, bukan? Dan sebagainya, adalah penting untuk tidak berakhir dengan apa yang kita sebut pulangan berkurang. Permulaan yang mengehadkan mungkin membawa kepada pulangan yang semakin berkurangan. Itulah sebabnya ia sangat penting untuk, anda tahu, cari, mempercayai pihak-pihak yang boleh memastikan bahawa satu titik kegagalan bukan masalah dan keselamatan data yang dihormati. Jadi, ia memerlukan sedikit perubahan pengurusan. Dan akhirnya, pada akhirnya - hampir selesai, ini adalah slaid terakhir - bagaimana kita akan melakukan ini? Bagaimanakah langkah ke awan, bergerak ke SaaS akan menjadi, anda tahu, lancar dan mudah? Nah, dengan melakukan dua perkara: memberi perhatian - peruntukan - benar-benar penting, dan on-boarding, lebih penting lagi.

Eric Kavanagh: Alright …

Gilbert Van Cutsem: Dan dalam hal itu, langit adalah batas. Terima kasih.

Eric Kavanagh: Ya. Itu hebat. Saya menyukai idea-idea yang sangat provokatif, saya suka cara anda memecahkan semua itu. Saya fikir yang masuk akal. Dan mari kita teruskan dan tekankan slaid pertama Ashish dan saya akan menyerahkan kunci kepada WebEx kepada anda, Ashish. Baiklah, teruskan. Cuma klik di mana sahaja pada slaid itu dan gunakan panah bawah pada keyboard anda. Itupun dia.

Ashish Thusoo: Baiklah. Terima kasih, Eric. Hai orang-orang, ini Ashish dan saya akan memberitahu anda mengenai Qubole. Jadi, hanya untuk memulakan, Qubole, pada dasarnya ia menyediakan data besar sebagai platform perkhidmatan. Ia adalah platform berasaskan awan yang dihoskan di awan Amazon dan awan Google dan kami menyediakan teknologi seperti Hadoop, Hive, Presto dan sekumpulan orang lain yang saya akan bincangkan, semuanya dengan cara turnkey supaya pelanggan kami pada asasnya dapat keluar semua kekeliruan dalam dunia infrastruktur data yang besar atau keluar daripada sebenarnya menjalankan operasi infrastruktur ini dan benar-benar memberi tumpuan lebih kepada data mereka dan transformasi yang mereka mahu lakukan pada data mereka. Jadi, itulah yang dikehendaki oleh Qubole.

Dari segi faedah yang ketara, satu cara berfikir tentang Qubole, anda tahu, sudah tentu ia menjadi turnkey, platform layan diri untuk analisis data besar dan integrasi data besar yang dibina di sekitar Hadoop, tetapi lebih mendasar, apa yang dilakukannya adalah, anda Ketahui, untuk semua enjin data besar seperti Hadoop, Hive, Presto, Spark, Chartly dan sebagainya dan sebagainya, ia membawa semua faedah awan ke enjin data yang besar ini dan beberapa kunci yang menunjukkan bahawa ia membawa dari perspektif awan adalah, anda tahu, membuat infrastruktur menyesuaikan diri dan dengan menyesuaikan diri, saya bermaksud baik tangkas serta fleksibel untuk beban kerja yang dijalankan pada mana-mana enjin-enjin ini dan juga menjadikan enjin-enjin ini lebih banyak layan diri dan kolaboratif dalam erti kata bahawa, anda tahu, Qubole menyediakan antara muka di mana anda boleh menggunakan teknologi-teknologi tertentu bukan sahaja untuk pembangunan anda atau, anda tahu, tugas yang berorientasikan pemaju, tetapi juga penganalisis data anda yang lain juga boleh mula mendapat manfaat teknologi ini untuk layan diri antara muka.

Kami mendapat banyak, anda tahu, berkaitan dengan hal ini, anda tahu, webinar, anda tahu, ini adalah salah satu perspektif kita mengenai manfaat awan yang dibawa oleh Qubole ke data besar. Jadi, jika anda hanya melakukan perbandingan antara cara anda menjalankan, katakan, Hadoop dan biarkan beban kerja dalam tetapan awal, dalam tetapan awal, anda sentiasa berfikir dari segi kluster statik, anda tahu, anda membetulkan kluster, anda mungkin saiz mereka untuk kegunaan puncak anda dan anda menyimpannya di sana dan kemudian jika anda perlu menukarnya maka anda perlu melalui proses keseluruhan perolehan, penempatan, pengujian dan sebagainya dan sebagainya. Perubahan Qubole yang dengan mewujudkan kluster sepenuhnya pada permintaan, kluster kami sangat elastik, kami menggunakan objek yang tersimpan dari awan untuk benar-benar menyimpan data dan cluster muncul dan, anda tahu, mereka muncul berdasarkan permintaan yang dihasilkan oleh pengguna dan mereka pergi apabila tiada permintaan. Jadi, ini menjadikan infrastruktur yang lebih tangkas dan fleksibel dan menyesuaikan diri dengan beban kerja anda.

Satu lagi contoh fleksibiliti adalah, anda tahu, hari ini anda mungkin telah membuat kumpulan statik anda di sini, anda tahu, dengan beban kerja tertentu dan jika beban kerja anda berubah dan infrastruktur anda kini perlu dinaik taraf, mungkin anda memerlukan lebih banyak memori pada mesin anda dan perkara-perkara seperti itu. Sekali lagi, anda tahu, melakukan ini di awan melalui Qubole sebagai contoh, menjadikannya mudah. Anda boleh menyewa jenis mesin yang baru, dan, anda tahu, mendapatkan kelompok, cluster 100-nod dan berjalan dalam beberapa minit berbanding minggu yang anda perlu menunggu untuk Hadoop di-premi.

Perkara utama yang lain di mana Qubole membezakan dirinya dari pada premis adalah bahawa Qubole pada asasnya, sebagai tawaran perkhidmatan, jadi semua alat dan infrastruktur yang anda perlukan untuk mengintegrasikan perkhidmatan itu, anda tidak perlu … di mana-mana sahaja, anda tahu, terutamanya anda mengambil perisian, anda perlu menjalankannya sendiri, anda perlu mengintegrasikannya sendiri dan melakukan semua manfaat tersebut, semua manfaat model SaaS adalah petunjuk kepada, anda tahu, bagaimana Qubole menawarkan data besar berbanding dengan menjalankan Hadoop secara percuma.

Slide ini umumnya meliputi seni bina kami. Kami, tentu saja, berdasarkan awan, kami menyimpan data kami pada objek di awan di awan, awan Google dan Google Compute Engine atau Amazon Web Services. Kami mengambil semua projek ekosistem Hadoop dan sekitar itu, kami telah membangunkan IP utama di sekitar auto skala dan pengurusan diri, kami telah melakukan banyak pengoptimuman awan untuk menjadikan teknologi komponen ini berfungsi dengan baik di awan seperti, anda tahu, infrastruktur awan adalah sangat berbeza dari hanya menjalankan perkara-perkara di logam terdedah dan sekumpulan penyambung data untuk membolehkan data dipindahkan masuk dan keluar dari platform ini. Jadi, yang membandingkan platform awan dan yang membolehkan itu, anda tahu, itu adalah kunci … ciri utama ada cara untuk membuat semua perkhidmatan diri supaya anda tidak perlu mempunyai … kuat Kami tidak mempunyai jejak operasi yang sangat besar semasa menjalankan ini, tetapi kami mengikatnya bersama-sama dengan data kerja kami sama ada ini adalah alat untuk penganalisis, sama ada ini alat tadbir urus data, sama ada alat templat ini, dan sebagainya dan sebagainya supaya anda boleh membawa manfaat teknologi ini, bukan hanya kepada pemaju, tetapi pengguna perniagaan dan perusahaan lain juga. Dan tentu saja, kita juga mengikat platform awan ini kepada alat yang mungkin digunakan oleh orang-orang ini sama ada ini, anda tahu, alat utiliti atau hanya Tableau atau sama ada mereka menggunakan, anda tahu, jenis produk pergudangan data seperti Redshift dan sebagainya dan sebagainya.

Hari ini, perkhidmatan berjalan pada skala yang sangat besar, kami memproses sebenarnya hampir 40 petabytes data setiap bulan sekarang di seluruh pangkalan pelanggan kami. Kelompok kami bervariasi dalam saiz dari 10 kelompok nod ke kumpulan 1500-nod dan, anda tahu, dari segi skala skala yang dapat kami proses dan dengan serta-merta, dengan pengetahuan saya yang terbaik, kami menjalankan mungkin sebahagian terbesar clusters di awan sejauh Hadoop bimbang dan kami memproses sekitar 250, 000 mesin maya dalam satu bulan di seluruh kelompok kami. Ingatlah, model kami adalah kluster atas permintaan, yang mempunyai faedah yang sangat besar dari segi mengurangkan beban kerja operasi anda serta menambah baik dan seterusnya dan sebagainya.

Akhirnya, anda tahu, salah seorang dari kami, anda tahu, ini hanyalah satu percubaan bagaimana Qubole telah berubah menjadi pelbagai syarikat. adalah contoh pelanggan kami. Mereka sudah berada di atas awan, mereka sedang menjalankan Map ElasticReduce di atas awan, contohnya, dan penggunaan data di sana cukup dikekang. Mereka akan mempunyai kira-kira 30 orang pengguna yang boleh menggunakan teknologi itu. Dengan Qubole, mereka telah dapat memperluaskannya kepada lebih daripada 200 pengguna aneh di syarikat yang telah melihat perkembangan penggunaan data besar dan benar-benar dibawa, anda tahu, apa yang kita sebut definisi platform data besar tangkas dan itu ia menjadi sangat penting bagi banyak beban kerja analitik mereka.

Jadi, hanya untuk menutup, anda tahu, itu adalah buku ringkas mengenai Qubole. Pada dasarnya, visi kami adalah bagaimana kami membuat perusahaan yang lebih tangkas di sekitar data besar dan pada asasnya, kami memanfaatkan faedah awan dan membawa mereka untuk menanggung teknologi data besar di sekitar Hadoop supaya pelanggan kami boleh memanfaatkan manfaat ketangkasan dan faedah tersebut fleksibiliti dan faedah-faedah sifat layan diri di awan menjadi yang lebih berkesan untuk keperluan data mereka. Jadi, saya akan berhenti di sana dan menyerahkannya kepada Eric.

Eric Kavanagh: Baiklah. Itu terdengar hebat dan sekarang, saya akan menyerahkannya kepada Mike Miller of Cloudant. Mike, saya meluluskan kunci anda sekarang. Cuma klik pada slaid, di sini anda pergi. Mengambilnya.

Mike Miller: Sepertinya saya mempunyai kunci. Jadi, saya akan memohon maaf. Saya hilang … Saya fikir saya terlupa menghantar beberapa fon dengan pembentangan saya. Jadi, semoga anda dapat melihat masa lalu dan membayangkan ia cantik. Tetapi, ya, ini menyeronokkan. Saya telah mendapat senarai panjang di sini, perkara-perkara provokatif yang saya dengar bahawa saya menulis bahawa saya bersungguh-sungguh untuk kembali kepada anda dalam panel. Jadi, saya akan cuba melangkah dengan cepat.

Jadi, saya akan bermula dengan Cloudant. Cloudant adalah pangkalan data sebagai perkhidmatan, penyedia awan kami dan sebenarnya, saya tidak mempunyai logo baru. Kami telah diperoleh oleh IBM tidak lama dahulu. Oleh itu, kami … Saya akan bercakap mengenai perkhidmatan kami dan khususnya menumpukan usaha untuk menjadikan pengguna dan pelanggan kami tangkas dengan cara yang agak berbeza berbanding penceramah yang terdahulu.

Cloudant menyediakan pangkalan data sebagai perkhidmatan dan perkhidmatan berkaitan data lain untuk orang yang membina aplikasi. Oleh itu, kami terlibat terus dengan pemaju dan kami memberi tumpuan kepada data operasi atau OLTP berbanding dengan analisis yang kami dengar daripada Ashish sebelum ini. Dan intinya ada, nilai keseluruhan Cloudant, yang boleh dipecah untuk membantu pengguna kami berbuat lebih banyak dan supaya itu membina lebih banyak aplikasi, berkembang lebih banyak dan tidur lebih banyak. Saya akan membincangkannya dengan sedikit butiran, tetapi idea umum di sini ialah jika anda seorang pengguna, anda tahu, anda berada dalam perniagaan, anda sedang membina aplikasi baru, menambah ciri ke aplikasi atau web yang ada permulaan mudah alih, anda harus memberi tumpuan kepada kecekapan teras anda. Dan sebelum ini, mungkin sehingga sedekad yang lalu, IT adalah untuk membezakan, anda tahu, persaingan, maaf, kerosakan kompetitif walaupun menjalankan pangkalan data dengan baik untuk menjadi kelebihan daya saing. Relaks hari-hari sudah berakhir! Oleh itu, cara kita benar-benar berusaha untuk bekerja dengan pengguna kami adalah untuk menggalakkan mereka untuk menggunakan perkhidmatan komposit, modular, boleh diguna semula, komposibel dengan idea yang mengurangkan masa untuk pemasaran, meningkatkan skalabiliti. Dan idea keseluruhan di sini ialah awan bukan sahaja, anda tahu, sesuatu yang baru ditolak ke pengguna, itu benar-benar pasaran … ia evolusi pasaran kerana cara orang membina aplikasi, menggunakan aplikasi, peranti yang mereka jalankan dan skala data berubah cukup radikal dalam tempoh 5-10 tahun yang lalu. Itu benar-benar menekankan seni bina aplikasi yang sedia ada untuk membina aplikasi serta hanya berurusan dengan data dan analisis beban kerja di luar talian. Dan sebagainya, ia membuka peluang penuh.

Jadi, Cloudant adalah pangkalan data diedarkan sebagai perkhidmatan dan ia adalah unik, saya percaya, dalam penubuhannya ia benar-benar dihantar dengan strategi mudah alih dari awal, dan saya akan membincangkan perkara ini secara terperinci, tetapi ideanya ialah aplikasi penulisan sekarang, anda tidak menulis untuk hanya satu platform, kan? Anda menulis untuk sesuatu yang saya dapat menjalankan skala petabyte di awan, ia juga harus berjalan lancar pada desktop atau dalam pelayar dan semakin banyak kita melihat perkara, kita perlu berjalan pada peranti mudah alih atau peranti separuh bersambung atau peranti yang boleh pakai atau sesuatu yang kita rujuk sebagai IOT. Oleh itu, saya fikir, anda tahu, aplikasi yang dapat menangani dengan baik dan memanfaatkan pelanggan-pelanggan yang berbeza adalah sangat berdaya saing di pasaran dan apa yang kami cuba lakukan adalah menjadikannya mudah bagi orang untuk API tunggal dalam model pengaturcaraan tunggal untuk menulis, mengendalikan data dalam semua peranti yang berbeza yang mempunyai skala yang sangat berbeza. 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. Hebat. 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. Apa pendapat kamu?

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. Sudah tentu. So, I think, you know, there are two parts to… So, let me first talk about, you know, why YARN was done and then talk about how that potentially changes the game and what's fundamentally still is the same, you know, where it doesn't change the game. I think that's an important thing to realize also because many times you, you know, you get caught up on this hype of say, this is the new, shiny thing and, you know, everything is going to, you know, all the problems are going to go away and so on and so forth. So, but the primary thing is that, you know, the strength and the weakness of the MapReduce API was that it was a very simple API and essentially, any problem that you could structure around being a sorting problem could be represented in, you know, that API. And some problems are naturally, you know… can naturally be transformed into that and some problems, you know, you sort of, you know, once you have just MapReduce at your disposal then you try to fit into a sorting problem.

So, I think the latter is where YARN plays a role by expanding out those APIs by, you know, being able to compose, you know, maps and reductions and, you know, whole bunch of different types of APIs in terms of how the data can be distributed between these two stages, and so on and so forth. You just made that API that much more richer. So, now you have at your disposal, different ways of solving that same problem, right? So, you just don't have to, you know, be constrained by the API and the problem gets solved one way or the other like, you know, if you are, you know, trying to do an analytics, you know, workload, you can express that in MapReduce, you can express that in YARN. The big difference that happens, that starts to happen is, you know, in terms of, you know, the performance matrix that you start seeing, you know, once you start, say programming to YARN and in some cases, a newer set of things, for example, streaming analysis and so on and so forth starts becoming a reality when you start, you know, doing that, you know, those things in YARN.

So, those are the differences that, you know, that thing has brought into the ecosystem. I think it's much, the richness there is much more on the API side as opposed to it being another resource manager, especially in the cloud context. If you think about it in cloud context, the resource manager is actually your… the VMs that you bring up, you know, you have virt… you know, it's not necessarily… Again, this is a big difference between say, on-prem how you are running Hadoop clusters and how you are running in the cloud then, you know, you have like the constrained static set of machines, you want to distribute those machines amongst different resources and they were used for YARN there. But, in the cloud, you know, you can bring up machines left and right. And so, just from the perspective of being a resource manager, it probably doesn't have that, you know, that bigger need and specifically in the cloud, but from the perspective of providing these, you know, richness of APIs which allow you to, for example, the Hive is initiative they can now program Hive to not just to use MapReduce, but have much more richer plans of doing jobs and things like that. It brings those benefits to the ecosystem. I think that is where the true value of YARN belongs. And in the cloud context, definitely, it's not that interesting from the resource management point of view, but it's much more interesting in terms of what it enables other projects to do, in terms of, you know, workloads that now, it now can be used to be programmed on to your data or the previous workloads that can be done in a much more efficient way.

Eric Kavanagh: Right.

Ashish Thusoo: I had, you know, one more just, you know, adding to Mike, you know, there was another provocative thing which was said which is around and, you know, which was around, hey, treating the cloud as yet another data center. I think you… you know, that is one point of view which most companies, you know, look at and say, okay, you know, that's the easiest point of view actually to look at saying that, okay, you know, this is, you have bunch of machines on your, you know, you have compute, you have storage and you have networking on your on-prem data center and cloud provides the same thing out there. So, I am just going to do exactly the same thing that I am doing on my own on-prem data center and do the same thing in the cloud and viola - that's how it should work. What we have found out, you know, having been running the clouds for, the two clouds where, you know, you have the ability to provision VMs within a minute, the ability to use a highly scalable objects to store data and things like that. We have found that cloud actually, the cloud architecture and these inherent abilities actually enable different ways of doing things, you know, and this is what I have talked about in my slide as well, you know, the whole notion of… in just, you know, in… the perspective of just Hadoop, the whole notion of just running the static cluster versus on-demand dynamic clusters, that is something that you don't see happening in an on-prem data center, you know, versus, you know, true cloud where the, you know, there's a enough capacity to be able to support these types of workloads.

And so, I think there is definitely some shift needed. You know, the big fear for me is that if you just treat cloud as yet another data center, you actually… while you, you know, there are lot of other benefits, but there are lot of intrinsic benefits that you might ignore if you, you know, start doing that, security is another one, the way you deal with security and the cloud, there's a lot of differences in terms of how you would deal with, you know, in… from on-prem perspective and so on and so forth. Just wanted to add that in, from my perspective.

Eric Kavanagh: Sure. Yeah. Tiada 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. Yeah. So, just another example of something similar, just yesterday happened to me. So, I lost one of my doctors because he went out of business. 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. Itulah soalan yang sangat baik. 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. Great! Well, folks, we've burned through an hour and 15 minutes or so, a lot of great questions there and a lot of great presentations. Thank you so much to all of our vendors today and of course, to both of our analysts on the show today. A big thank you, of course, to Qubole, Cloudant and Attunity. We are gonna put the archive up at insideanalysis.com. I showed you where that goes, and big thanks to our friends at Techopedia as well.

So, folks, thank you again for your time and attention. This concludes Episode 3 of TechWise, our relatively new show. There is Episode 4 coming up pretty soon. It's gonna be on the big data ecosystem. So, watch for information on all that. And then till then, folks, thank you so much. We will catch up with you next time. Jaga diri. Selamat tinggal.