Posts Tagged Enterprise Cloud System

Best TCO—System z vs. x86 vs. Public Cloud

IBM recently analyzed various likely customer workload scenarios and found that the System z as an enterprise Linux server could consistently beat x86 machines and even public cloud providers like AWS in terms of TCO.  The analysis was reasonably evenhanded although, like automobile mileage ratings, your actual results may vary.

This blogger has long contended that the z Enterprise Linux Server acquired under the deeply discounted IBM System z Solution Edition program could beat comparable x86 systems not only in terms of TCO but even TCA. Algar, a Brazilian telecom, acquired its initial zEnterprise Linux server to consolidate a slew of x86 systems and lay a foundation for scalable growth. It reports cutting data center costs by 70%. Nationwide Insurance, no newcomer to mainframe computing, used the zEnterprise to consolidate Linux servers, achieving $46 million in savings.

The point: the latest IBM TCO analyses confirm what IBM has been saying. TCO advantage, IBM found, switches to the z Enterprise Linux Server at around 200 virtual servers compared to the public cloud and a bit more VMs compared to x86 machines. View the IBM z TCO presentation here.

IBM further advanced its cause in the TCO/TCA battle with the recent introduction of the IBM Enterprise Cloud System. This is a factory-built and integrated system—processor, memory, network, IFLs, virtualization management, cloud management, hypervisor, disk orchestration, Linux OS—priced (discounted) as a single solution. IBM promises to deliver it in 45 days and have it production ready within hours of hitting the organization’s loading dock. Of course, it comes with the scalability, availability, security, manageability, etc. long associated with the z, and IBM reports it can scale to 6000 VMs. Not sure how this compares in price to a Solution Edition Enterprise Linux Server.

The IBM TCO analysis compared the public cloud, x86 cloud, and the Enterprise Cloud System in terms power and space, labor, software/middleware, and hardware costs when running 48 diverse (a range of low, medium, and high I/O) workloads. In general it found an advantage for the z Enterprise Cloud System of 34-73%.  The z cost considerably more in terms of hardware but it more than made up for it in terms of software, labor, and power. Overall, the TCO examined more than 30 cost variables, ranging from blade/IFL/memory/storage amounts to hypervisor/cloud management/middleware maintenance.

In terms of hardware, the z included the Enterprise Linux Server, storage, z/VM, and IBM Wave for z/VM. Software included WebSphere Application Server middleware, Cloud Management Suite for z, and Tivoli for z/VM. The x86 cloud included HP hardware with a hypervisor, WebSphere Application Server, SmartCloud Orchestrator, SmartCloud Monitoring, and Tivoli Storage Manager EE. Both analyses included labor to manage both hardware and VMs, power and space costs, and SUSE Linux.

The public cloud assumptions were a little different. Each workload was deployed as a separate instance. The pricing model was for reserved instances. Hardware costs were based on instances in east US region with SUSE, EBS volume, data in/out, support (enterprise), free and reserved tier discounts applied. Software costs included WebSphere Application Server ND (middleware) costs for instances. A labor cost was included for managing instance.

When IBM applied its analysis to 398 I/O-diverse workloads the results were similar, 49-75% lower cost with the Cloud System on z. Again, z hardware was considerably more costly than either x86 or the public cloud. But z software and labor was far less than the others. In terms of 3-year TCO, the cloud was the highest at $37 M, x86 came in at $18.3 M, and the Cloud on z cost $9.4 M. With 48 workloads, the z again came in with lowest TCO at $1 M compared to $1.6 M for x86 systems, and $3.9 M for the public cloud.

IBM tried to keep the assumptions equivalent across the platforms. If you make different software or middleware choices or a different mix of high-mid-low I/O workloads your results will be different but the rankings probably won’t change all that much.

Also, there still is time to register for IBM Edge2014 in Las Vegas. This blogger will be there hanging around the bloggers lounge when not attending sessions. Please join me there.

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