Cloud Computing, Docker, Mesos, DCOS, Container, Big Data, Paas
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An overview of Xavient and approach to PaaS using Mesos, Cloud Foundry
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Cloud Computing, Docker, Mesos, DCOS, Container, Big Data, Paas
- 2. © 2016 Xavient Information Systems Agenda ü IaaS ü PaaS ü Technology Overview
- 4. © 2016 Xavient Information Systems Infrastructure as a Serviceis a form of cloud computing that provides virtualized computing resources. Public Cloud • AWS • Azure • GCE Private Cloud • VMWare • OpenStack • Apache CloudStack IaaS
- 6. © 2016 Xavient Information Systems • Platform as a service (PaaS) is a category of cloud computing services that provides a platform allowing customers to develop, run, and manage applications without the complexity of building and maintaining the infrastructure typically associated with developing and launching an app • DCOS is a new kind of operating system that organizes all of your machines, VMs, and cloud instances into a single pool of intelligently and dynamically shared resources. It runs on top of and enhances any modern version of Linux Paas and DCOS
- 7. © 2016 Xavient Information Systems No to Static Partitioning • Underutilize • Does not scale • Hard to deal with failures
- 11. © 2016 Xavient Information Systems Software on Mesos Aurorais a service scheduler that runs on top of Mesos, enabling you to run long- running services that take advantage of Mesos' scalability, fault-tolerance, and resource isolation. Marathonis a private PaaS built on Mesos. It automatically handles hardware or software failures and ensures that an app is “always on”. Hadoop Running Hadoop on Mesos distributes MapReduce jobs efficiently across an entire cluster. Spark is a fast and general-purpose cluster computing system which makes parallel jobs easy to write. Chronos is a distributed job scheduler that supports complex job topologies. It can be used as a more fault-tolerant replacement for Cron. Jenkins is a continuous integration server. The mesos-jenkinsplugin allows it to dynamically launch workers on a Mesos cluster depending on the workload. Cassandrais a performant and highly available distributed database. Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data. ElasticSearchis a distributed search engine. Mesos makes it easy to run and scale.
- 15. © 2016 Xavient Information Systems • Reservation problem • Data Persistence problem • Where is the security ? Authentication and Authorization • Monitoring • Framework Rate Limiting • Vendor support • Managed services Let’s get practical
- 16. © 2016 Xavient Information Systems • Resources are reserved for roles and roles used to reserve resources • Static Reservation mesos-slave --master=<ip>:<port> --resources="cpus:4;mem:2048;cpus(ads):8;mem(ads):4096” “8 CPUs and 4096 MB of RAM reserved for adson this slave.” • Dynamic reservation in Mesos >= 0.23.0 • Create through Frameworkand Operator API Framework Operator Reservation - mechanisms to reserve resources in specific slaves
- 17. © 2016 Xavient Information Systems • A mechanism to create a persistent volume from disk resources • Persistent volumes enable stateful services such as HDFS and Cassandra to store their data within Mesos • Authorization is must to create persistent volumes • Persistent volumes can only be created from reserveddisk resources, whether it be statically reserved or dynamically reserved - Important • Create through Framework and Operator API (Same as Dynamic Reservation) https://mesosphere.github.io/marathon/docs/persistent-volumes.html https://mesosphere.github.io/marathon/docs/external-volumes.html An external storage service enables your apps to be more fault-tolerant. If a host fails, Marathon reschedules your app on another host, along with its associated data, without user intervention. https://github.com/emccode/rexray Persistent Volumes
- 19. © 2016 Xavient Information Systems • Authentication is disabled by default. When authentication is enabled, operators can configure Mesos to either use the default authentication module or to use a customauthentication module. • Authentication permits only trusted entities to interact with a Mesos cluster • Authentication can be used at framework, agent and operator level • Configure authentication during the mesos master and slave start • Authorization , local and custom • Configure the actions that certain principals are allowed to perform http://mesos.apache.org/documentation/latest/authentication/ http://mesos.apache.org/documentation/latest/authorization/ * The default Mesos authentication module uses the Cyrus SASLlibrary. SASL is a flexible framework that allows two endpoints to authenticate with each other using a variety of methods. By default, Mesos usesCRAM-MD5 authentication. Security
- 21. © 2016 Xavient Information Systems Mesos and Containers "If a Docker application is a Lego brick, Kubernetes would be like a kit for building the Millennium Falcon and the Mesos cluster would be like a whole Star Wars universe made of Legos." ~ Solomon
- 25. © 2016 Xavient Information Systems • Aurora vs. Marathon http://code.hootsuite.com/marathon-vs-aurora-a-high-level- comparison/ • Mesos and Kubernetes http://stackoverflow.com/questions/26705201/whats-the- difference-between-apaches-mesos-and-googles-kubernetes • Jenkins and Mesos http://www.slideshare.net/carlossg/ci-and-cd-at-scale-scaling-jenkins- with-docker-and-apache-mesos • Bloomberg and Monitoring http://schd.ws/hosted_files/mesosconna2016/98/SeamlessMonitoringForMesosClusters.pd f • Uber and Cassandra http://schd.ws/hosted_files/mesosconna2016/60/mesoscon-uber.pdf • Mesoscon 2016 https://www.youtube.com/playlist?list=PLGeM09tlguZQVL7ZsfNMffX9h1rGNVqnC • Jenkins alternate solution https://github.com/HubSpot/Blazar • Mesos oversubscription http://mesos.apache.org/documentation/latest/oversubscription/ • https://support.mesosphere.com/hc/en-us/categories/200383389-Technical Read
- 33. © 2016 Xavient Information Systems Agenda ü Xavient Introduction • Company Snapshot • Global Presence • Our Differentiators ü Xavient Big Data & BI Capabilities ü Case Studies
- 34. © 2016 Xavient Information Systems Company Snapshot Who We Are • Founded in US in 2002 | Global Scale | ExponentialGrowth • Fortune 200 clientele | Partner of choice for 4 out of Top 5 CSPs inUS • Comprehensive Technology Coverage & Personalized Service What We Do • Enable Enterprise Class Solutions on Web, Mobility, Open Source, Cloud, BigData • Focus on Telecom, Retail, Healthcare & Banking • Optimize BAU SDLC Practices How We Deliver • Customer First Approach - Long term ongoing engagements are testimony to our success • Talent Farming – Thought leadership | Bootcamps | Embedded Factory • Maturity & Agility – Technology Innovation | Reusable Best Practices | Early Adopters
- 35. © 2016 Xavient Information Systems Global Presence Tampa, FL Atlanta, GA Herndon, VA Sterling, VA Bethpage, NY Frisco, TX Englewood, CO Denver, CO St. Louis, MO Bellevue, WA Simi Valley, CA (Headquarters) Noida Bengaluru OnshoreDelivery Center / Client Location OffshoreDelivery Center Mississauga, Canada
- 36. © 2016 Xavient Information Systems Xavient – Enabling Digital Transformation Mobility Open Source Big Data IoT UI/UX • Data ingestion and analysis from sensors, edges devices and smart phone apps. • Transition heavyweight, costly and composite systems to Open Source Stack based Enterprise class solutions • Custom UI/UX based on the business needs. • Delivered innovative solutions handling large volume of data • Mobility solution accelerators & frameworks to reduce costs & go-to-market faster
- 37. © 2016 Xavient Information Systems Our Differentiators People Pricing Processes Partnerships Productivity Amongst the best global IT talent Mature & Agile processes In-house R&D center, TSG® for innovationand automation Leveraging partnerships and strategic alliances Customer centric Global Delivery Highly-skilled consultants & SMEs Low attrition Excel in DevOps methodologies Extra bandwidth of 10-15% Big enough to scale, small enough to align Lead with Solutions and Value Turning client challenges into success stories Flexible pricing models for cost efficiency
- 42. © 2016 Xavient Information Systems Xavient’s Big Data Team Developer and Data Scientist 10+ years industry Experience 3 years Big Data experience Data Architect/Engineer 10+ years industry Experience 3 years Big Data experience Sr. Engagement Manager 8+ years industry Experience 2+ years Big Data experience Sr. Consultant 6+ years industry Experience 2 years Big Data experience • Develop data ingestion flow in batch and real time • Design and develop statistical procedures and algorithms around data sources • Recommend and build models for various data studies, data discovery and hypothesis • Work with developers to integrate and pre-process data for inputs into models • Data cleanup and transformation as preparation for analysis • Focus areas include: statistics, applied math, machine learning, model design and development • Configure and setup various development and data science tools. • Platform architecture analysis and design, including: data center layout, hardware and network considerations • Security model design and implementation for authentication, authorization, administration and audit • Define recommended processes for data ingestion, management, transformation and egress. • Perform installation for enterprise- scale cluster environments. • Resource management at cluster and infrastructure level. • Facilitate the selection of appropriate Big Data technology and tools • Conduct technical workshops • Define the overall architecture for the solutions/business applications and prepare the environment • Initial day-to-day cluster operations • Overall responsibility for project success • Primary management contact for the customer. • Coordinate all the Professional Services resources • Ensure the project is delivered according to schedule and budget • Report status and manage escalations. • Lead the implementation of business use case(s). • Provide expertise and guidance during the project lifecycle. • Provide design and development expertise for large-scale, clustered data processing systems • Develop ingest, transformation and egress capabilities leveraging latest tools such as Kafka, Storm, Pig, Hive, etc. • Resolve technical issues in the environment • Assist with the preparation of technical deliverables, and review and demonstrate the system and applications • Provide technical support either onsite or remote.
- 44. © 2016 Xavient Information Systems Big Data Case 1 : Enterprise Social Networking and Collaboration Platform • Real time data streaming • Search capability • Front end UI • Build recommendationmodel based on user search Xavient’s SolutionXavient’s Solution • End to end design and implementation of enterprise ready solution/app to provide social networking platform • Mobile app solution • Chat, Message exchange capabilities by leveraging NoSQL databases • Resource management at the enterpriselevel Technologies: Kafka, Storm, HDFS, Hive, HBase, Elastic Search, Java, ApacheMesos/Mesosphere, Apache Myraid Xavient’s Solution • Real time reports& analyticswith granular data • Health checkand monitoringofkeyareas • Informed and quickdecisions • Both online & offline mode access • Multiple Currencyselection (USD& local currency) Key Benefits Business Requirement An Enterprise Social Networking and Collaboration Platform
- 46. © 2016 Xavient Information Systems Big Data Case 2 : Implementing a True Enterprise Data Lake Business Requirement • Store all the data at one place • Eliminate datasilos • Build COE Xavient’s SolutionXavient’s Solution • Developed overall roadmap and design for enterprise ‘data lake.’ • POC and Hadoop knowledge sharing sessions • Security setup for strong authentication and authorization • Data ingestion from RDBMS to HDFS/Hive. H • Defined plan and helped implement a CoE Technologies used: HDP, Hive, Sqoop, AWS, Oozie Xavient’s Solution • Nomore silosof data • Fast response time delivered for long running queries • Cost per TB dropped • Internal Hadoop asa Service cloud • Store data for longer period oftime • New technologystackincreasesemployeeretention Key Benefits About Client Client is a leading Satellite TV Service Provider in US
- 47. © 2016 Xavient Information Systems • Operational dashboards • Customer scorecards • CDR analysis • Proactive Maintenance • Infrastructure investment • Bandwidth allocation • Product development EDW MPP CRM ERP DATA SOURCES DATA REPOS ANALYSIS Billing Data Subscriber Data Product Catalog Network Data Clickstream Online Chat Sensor Data Server Logs Call Detail Records Merchant Listing DMP Social Media Ingest Sqoop Flume HDFS Put WEB HDFS Hadoop Cluster Batch Map Reduce Script Pig SQL Hive Online Hbase Accumulo Real-Time Storm In-Memory Spark Others Metadata Management HCatalog Multitenant Processing: YARN Hadoop Operating System Linear Scale Compute & HDFS Storage Governance tag, filter & process Operations (Ambari) Security (Knox, Kerberos, Apache Ranger) 1 N . . . . . . . . . . . . . . . . . . . . . . . . . .. . . .. . . Big Data Case 2 : Enterprise Data Lake (Contd..)
- 48. © 2016 Xavient Information Systems Big Data Case 3 : Drop call and network change monitoring in Real Time . Business Requirement • Xavient’s SolutionXavient’s Solution Xavient’s SolutionKey Benefits • Store all the CDR data at one place “Data Lake” • Real time monitoring of dropped calls • Real time monitoring of network changes • Data ingestion flow was built using flume, kafka and storm to store data in HDFS, Hive and HBase in combination with Apache Phoenix • Solr and Banana delivered the dashboard capabilities • Apache Phoenix was to used to run queries against HBase to find drop calls and network change • Longer data retention • Faster response time from the larger data set • Cost reduced per TB because of Hadoop stack • Effective and fast alerting during the outages • Ability to run predictive analysis based on real time alerting . About Client Client is a leading wireless networkoperator in the US
- 51. © 2016 Xavient Information Systems BI Case 1 : Executive Dashboard For Strategic Insights Business Challenges Business Requirement Xavient’s Solution Xavient’s SolutionXavient’s Solution Key Benefits • Multi-channel dashboard • Real time analytics on Cross-functional data with visual representation • Quicker decision making for Senior Executives • Cross platform dashboard reporting application • Configurable background sync for offline data access • Customized KPIs providing bird’s eye view • Dynamic reporting from multiple digital marketing channels viz. revenue, billings, costs and number of campaigns Technologies used: Informatica, Oracle, HTML5, Jquery, Java, Objective C • Real time reports & analytics with granular data • Health check and monitoring of key areas • Informed and quick decisions • Both online & offline mode access • Multiple Currency selection (USD & local currency) About Client The client is a Digital Marketing & Advertising ServiceProvider
- 52. © 2016 Xavient Information Systems BI Case 2: Inventory and Merchandising App Business Challenges Business Requirement Xavient’s SolutionXavient’s Solution Key Benefits • Cross-Platform mobile application that gives at-a-glance view of all Sales, Inventory and Gross margin for all products in a store from anywhere • Performance dashboard for associates to measure, monitor and act on the sellable articles • Extend platform to cater to corporate vendors for various products • Interface the mobile app with SAP for metrics and reporting • developed a mobile application to: • Browse product catalogue • Check inventory reports and status • Track sales (actual and planned) • Read customer reviews • Find a store • View current promotions of retailer Technologies used: PHP/ Java Script /MySQL Objective C (for iOS app) Java (for Android app) • Convenient and Better customer service • Simple user friendly design layout • Customized platforms • Competitive pricing • Better Sales and Stock management • Speed scripting to increase Time to Market • More value added services About Client One of the leading retail chains the in US.