Driving More Value From OpenVMS Critical Infrastructure in Local and Global Datacenters: A CASE STUDY. Presented by: J. Barry Thompson, CTO Tervela
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1 Driving More Value From OpenVMS Critical Infrastructure in Local and Global Datacenters: A CASE STUDY Presented by: J. Barry Thompson, CTO Tervela
2 Case Study: Customer Challenges The Solution Overall Impact Summary Tervela Background General Discussion and Q&A
3 CASE STUDY
4 Background High-volume electronic trading Trading apps co-located at global exchanges Challenges Massive data distribution wasn t scalable No single view of transactional data Business risk management Auditing & compliance A Global Transaction Fabric: Summary Data Fabric Solution Primary data fabric for global data distribution Real-time global trading Online marketplace for fixed income and derivatives Global scale, high-speed, no-loss Reduce complexity of global architecture Reduce development efforts for new apps (+50%) Virtual appliance for low-volume sites 4
5 The Global Architecture 5
6 Challenges General Data Volumes Complexity Cost Time to Market OpenVMS Specific Application Scaling State Offload / Performance Bridging to Other Architectures Computing and Communication Capacity Infrastructure Spend $$$$$ Marginal Impact $$$$$ Middleware Networking 4,8,16 core processers 10GE, 100GE pipes but major barriers to scale, cost reduction, and new business opportunity. $ Total Capacity Business Opportunity Effective Capacity Major Inflection Point
7 Fabric Deployed as an Overlay Solution 7
8 The Solution: A Data Fabric Solution Addressed: Legacy Messaging Middleware Tier 1 Storage for Replication State Offload Dynamic WAN Acceleration Database Acceleration OpenVMS Process Parallelization 8
9 Traditional Middleware Messaging SOA Event Solutions Caching Pub/Sub Protocol BI State Offload Utilizing a Data Fabric as a Middleware Upgrade, Replacement, or Acceleration Backbone Creates a Unified Platform for Next Generation in Application Connectivity JMS RPC / IPC Signal Processing Data Synch Queuing Request Response Event Capture Data Buffering Data Fabric Impact of Middleware to Data Fabric Upgrade Technology Performance by 1000x Reliability beyond 5x9s WAN Performance by x (md-orders) Process Scalability across multiple OpenVMS Blades Business 3 Products decommissioned Unified Data Plant Time to Market by >50% Cost reduction 9
10 Impact of Database Selection & Performance The Data Fabric Integrates with Existing Database Solutions to: Accelerate database insert rate and data availability Reduced time to query Accelerate the number of row inserts per second Reduced hardware requirements Any Database TVA Cache Dynamic Data Fabric TVA Cache TVA Cache Any Database Any Database Global data replication Accelerated data replication x over traditional solutions Significant cost savings on Tier 1 storage solutions for replication Do more with limited bandwidth Drive global synchronization in a BASE model with zero loss Migrate to Less Expensive, More Scalable Database Solution Time To Query / Insert Acceleration Global Data Replication 10
11 Detailed Impact on Replication Apps / DB / Files Replication / Synch Layer Without Data Fabric With Data Fabric Apps / DB / Files NYC Singapore London Scale/Complexity: Point to Point Only Static Routing Control/Manageability: No Security in Data Flow No visibility into the status of data movement Scale/Complexity: Fan in / Fan Out: 1:1; 1:N; N:M; N:1 Dynamic Routing Control/Manageability: Pinpoint Data Deliver and Security / Entitlements on Flow Visibility into all data flows globally. NYC Singapore Data Fabric London Performance: Synchronous Forced WAN Fetch External / non optimized WAN Acceleration Reliability/Availability: Active Cold Only Manual Activation Limited by slowest consumer Feature Set: Unidirectional replication Synchronous Only No ordering Limited to block or per transaction Restore from backup only Performance: Parallelization / Guaranteed Async data transfer Local Replay and Caching WAN acceleration optimized for Dynamic Data Reliability/Availability: Active Active: high availability for all Data Producers and Consumers BCP: Immediate, fully automated/seamless failover regardless of the complexity of the production environment Elastic: with the ability to deliver data to multiple targets, each with its own performance characteristics, without loss. Feature Set: Multi directional, multi target replication/data movement Ordering within a single or across ALL replication streams Data Ingress Acceleration with increased rows / second and time to query Rapidly rebuild a DB as of a specific point in time. 11
12 WAN Performance 40x Medium WAN Improvement 50 90x Long Haul WAN Improviement 10x MAN Improvement Estimated >200x Satellite WAN Improvement The Longer the distance, the Better the performance gains. Even >90x for low quality network links 12
13 SUMMARY
14 Approach Comparison Technology Global Real time Reliable Best suited for Tervela Data Fabric High High High real time big data Traditional Messaging Medium High Low volatile data WAN Optimization TCP Acceleration High Low Medium remote office file sharing, collaboration Caching Low Medium Medium historical or static unstructured DB Replication Medium Medium Medium historical or static structured data SAN Low Medium High local data Conclusions: 1. Solution architects must choose a technology based on their app and write code to circumvent deficiencies. 2. Without a Data Fabric If solutions have multiple requirements, multiple types of technologies must be used. 14
15 Approach Comparison Industries Financial Services Governments and Intelligence Agencies Telcos and Service Providers Logistics and Retail Payment Processing Use Cases Capital Markets: Trading Infrastructure Banking: Payments, Balances, Statements Asset Management: Portfolio Reporting & Analysis Sensor Data Collection and Monitoring Analysis & Compliance Cyber security Infrastructure: SaaS, PaaS, IaaS Value add Services: Location based Services Applications: Gaming, Social Media Product Catalogues Inventory and Pricing Real time Decision Support Mobile, Real time Payments 15
16 TERVELA OVERVIEW
17 About Tervela: Data In Motion The Tervela Data Fabric The fastest, most reliable, and cost effective data transport system for globally distributed, mission-critical applications x performance increase over traditional solutions Beyond 5x9 s built-in fault tolerance & high availability 50% faster to deliver new apps simple development tools & embedded services End-to-end manageability & security integrated data entitlements & protection 17
18 Big Data Movement for Scalable Applications Cloud REAL TIME Web & Mobile SaaS, IaaS, PaaS Enterprise / Cloud Data Cloud DR & Replication Real time Analytics Interactive Media & Devices Mobile Payments, Banking Facebook & Twitter Feeds Enterprise Trading Fabrics and Exchanges File & DB Replication Middleware Replacement Real time Analytics 18
19 Products TMX: Message Switch Message transport through the fabric High volume throughput Multi protocol intelligent routing Low latency Built in security model Operational predictability Integrated, decoupled caching TPE: Persistence Engine Embedded storage and caching within the fabric System wide caching Built in record & playback Burst management Optimized retrieval High performance spindle or SSD High availability TPM: Provisioning & Management Central management of the fabric Access control System provisioning Visual monitoring System health tracking SNMP alerting Comprehensive reporting Messaging System Optimized for Multi App Networks Client API C, C++, C#, Java, JMS Virtual Appliances 100% Interoperable 19
20 Why Companies Buy Tervela Flexibility Available in both HW and SW (virtual) Appliances Global Agility Need big data delivered in real time to data centers all over the world Reliability Guaranteed /no loss delivery, zero production outages Ease of Use The Tervela TMX is installed and running in weeks, not months Centralized Management and Visibility Less time to develop applications 20
21 GENERAL DISCUSSION / Q&A
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