Superior Cloud Economics with IBM Power Systems
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IBM Power Systems is working to decrease costs, improve performance and use the open community to help competitive enterprises put data to work in the cloud.
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Superior Cloud Economics with IBM Power Systems
- 1. Superior cloud economics, made with IBM. Introducing the most secure, quick-to-deploy converged infrastructure for cloud with open choice. With a consistent strategy thats building momentum, Power Systems supports more open innovation to put data to work.
- 2. Power Systems from IBM enables digital transformation on the cloud. IBM is helping customers manage data-intensive workloads on public and private clouds. Using Power, one of the industrys most advanced open- server architectures, organizations can extend their infrastructure quickly and economically and embark on their own digital transformation. 2
- 3. Expanding SoftLayer with POWER8. OpenPOWER-based bare metal with SoftLayer provides unparalleled data-mining, processing and open-source capabilities with cloud functionality. That combination can help enterprises store data on POWER8 servers with enough scalability to adapt to an ever-changing landscape of data and achieve twice the hybrid cloud performance. 3 1.4x more transaction per second at 61% lower cost per transaction for MariaDB workloads compared with Amazon Web Services.1 1.59x more users per hour at 65% lower cost for LAMP application stack.2 Sonny Fulkerson, CIO, Softlayer
- 4. 4 The path to a more open platform includes 1. using innovations from an open- community ecosystem. 2. increasing interoperability using open standards. 3. simplifying migration to Linux. 4. enabling Little Endian across the entire Power Systems Line. A more open innovation platform. Using feedback from the ever-expanding community of developers who contribute to the Power ecosystem, and independent software vendors who are migrating applications from x86 to Power-based linux architectures, IBM is developing an OpenPOWER platform featuring the wisdom of the most open of crowds. Doug Balog, General Manager, Power Systems, IBM Systems
- 5. Features: 1. Readily expandable systems to accommodate future change. 2. Built-in workload elasticity for automated workload scalability. 3. Single point of management with pre- integrated software and hardware. 4. Single point of contact for system service and integrated updates. 5. Scalable in-memory analytics platform. Scalability and security. The IBM PurePower System helps enterprises support a security-enhanced, converged cloud infrastructure for both Linux and AIX workloads right out of the box to meet the needs of growing mobile, social and Big Data workloads. An open Linux environment, PurePowers Integrated Infrastructure Management and IBM Storwize V7000 Storage offering combines security-enhanced, converged cloud infrastructure with open choice. 5 Stephen Leonard General Manager Sales IBM Systems
- 6. Lower total cost of operation for enterprise clouds. IBM delivers superior cloud economics with secure and open choices to help solve cloud-and mobile- computing challenges. With better performance per dollar for data and analytics workloads, the capacity to support more users on a LAMP stack and lower cost per transaction for MariaDB workloads, IBM Power Systems gets more done with less for enterprise clouds. However, there are additional cost advantages beyond those inherent in the capacity of the technology: migration pricing and support from IBM Global Financing. pay-as-you- go flexibility. automated workload management to reduce operating costs. 6 Jeff Barber VP-High End Storage, IBM Systems
- 7. IBM Power Systems works to decrease costs, improve performance and use the open community to help competitive enterprises put data to work in the cloud. Click here to learn more about IBM Power Systems. 7 1. Projections are based performance results measured by IBM as of February 13, 2015. Individual results will vary depending on individual workloads, configurations and conditions. IBM Power System S822L with (per socket) 8 cores / 64 threads, POWER8; 3.4GHz, 128 GB memory, Ubuntu 14.04 IBM; Linux速 kernel: 3.13.0-35-generic with MariaDB 10.0.14 compared to Competitive stack: Dell Power Edge R420 with (per socket) 8 cores / 16 threads; Intel E5-2450; 2.0 GHz; 128 GB , CentOS, OpenSource MySQL; OpenSourcePHPh Engine. S822L results were extrapolated to an C812L-M based 8c@ 3.86 GHz / 1-socket / 32 GB memory / 2x4TB drive system. The x86 results were extrapolated to Amazon r3.4xlarge offering E5-2670 v2: 8c @ 2.5 Ghz ; 122 GB memory / 1x4TB drives. The results were obtained under laboratory conditions, and not in an actual customer environment. IBMs internal workload studies are not benchmark applications, nor are they based on any benchmark standard. As such, customer applications, differences in the stack deployed, and other systems variations or testing conditions may produce different results and may vary based on actual configuration, applications, specific queries and other variables in a production environment. Pricing is based on estimated Softlayer pricing and published Amazon On-Demand pricing. 2. Projections are based performance results reported in https://www-304.ibm.com/partnerworld/wps/servlet/ContentHandler/stg_ast_sys_wp_ibm-power-systems-solution-for-mariadb/lc=en_ALL_ZZ. Individual results will vary depending on individual workloads, configurations and conditions. IBM Power System S822L with (per socket) 10 cores / 80 threads, POWER8; 3.67GHz, 128 GB memory, Ubuntu 14.04 IBM; Linux速 kernel: 3.13.0-35-generic with MariaDB 10.0.14 compared to Competitive stack: IBM System x3650 M4 with (per socket) 12 cores / 24 threads; Intel E5-2697 v2; 2.7 GHz; 128 GB , Ubuntu 14.04 IBM; Linux速 kernel: 3.13.0-35-generic with MariaDB 10.0.14. S822L results were extrapolated to an C812L-M based 10c@ 3.5 GHz / 1-socket / 256 GB memory / 2x4TB drive system. The HP DL380p results were extrapolated to Amazon r3.8xlarge offering with E5-2670 v2: 16c @ 2.5 Ghz; 244 GB memory / 2x320GB drives. The results were obtained under laboratory conditions, and not in an actual customer environment. IBMs internal workload studies are not benchmark applications, nor are they based on any benchmark standard. As such, customer applications, differences in the stack deployed, and other systems variations or testing conditions may produce different results and may vary based on actual configuration, applications, specific queries and other variables in a production environment.