Lessons from IBM Eagle TCO Analyses

A company running an obsolete z890 mainframe with what amounted to 0.88 processors (332 MIPS) planned a migration to a distributed system consisted of 36 distributed UNIX servers. The production workload consisted of applications, database, testing, development, security, and more.  Five years later, the company was running the same in the 36-server, multi-core (41x more cores than the z890) distributed environment except that its 4-year TCO went from $4.9 million to $17.9 million based on an IBM Eagle study.  The lesson, the Eagle team notes: cores drive platform costs in distributed systems.

Then there is the case of a 3500 MIPS mainframe shop that budgeted $10 million for a 1-year migration to a distributed environment. Eighteen months into the project, now six months behind schedule, the company had spent $25 million and only managed to offload 350 MIPS. In addition, it had to increase staff to cover the  over-run, implement steps to replace mainframe automation, had to acquire additional distributed capacity over the initial prediction (to support only 10% of total MIPS offloaded), and had to extend the period of running the old and the new systems in parallel at even more cost due to the schedule overrun. Not surprisingly, the executive sponsor is gone.

If the goal of a migration to the distributed environment is cost savings, the IBM Eagle team has concluded after 3 years of doing such analyses, most migrations are a failure. Read the Eagle FAQ here.

The Eagle TCO team was formed in 2007 and since then reports completing over 300 user studies.  Often its studies are used to determine the best platform among IBM’s various choices for a given set of workloads, usually as part of a Fit for Purpose. In other cases, the Eagle analysis is aimed at enabling a System z shop to avoid a migration to a distributed platform. The Eagle team, in fact, is platform agnostic until it completes its quantitative analysis, when the resulting numbers generally make the decisions clear.

Along the way, the Eagle team has learned a few lessons.  For example:  re-hosting projects tend to be larger than anticipated. The typical one-year projection will likely turn into a two- or three-year project.

The Eagle team also offers the following tips, which can help existing shops that aren’t necessarily looking to migrate but just want to minimize costs:

  • Update hardware and software; new systems generally are more cost-efficient. For example one bank upgraded from z/OS 1.6 to 1.8 and reduced each LPAR’s MIPS by 5% (monthly software cost savings paid for the upgrade almost immediately)
  • Schedule workloads to take advantage of sub-capacity software pricing for platforms that offer it, which may produce free workloads
  • Consolidate workloads on Linux, which invariably saves money, especially when consolidating many Linux virtual servers on a mainframe IFL. (A recent debate raged on LinkedIn focused on how many virtual instances can run on an IFL with some suggesting a max of 20. The official IBM figure:  you can consolidate up to 60 distributed cores or more on a single System z core; a single System z core = an IFL.)
  • Changing the database can impact capacity requirements and therefore costs, resulting in lower hardware and software costs
  • Consider the  IBM mainframe Solution Edition program, which is the best mainframe deal going, enabling you to acquire a new mainframe for workloads you’ve never run on a mainframe for a deeply discounted package price including hardware, software, middleware, and 3 years of maintenance.

 BottomlineIT generally is skeptical of TCO analyses from vendors. To be useful the analysis needs to include full context, technical details (components, release levels, and prices), and specific quantified benchmark results.  In addition, there are soft costs that must be considered.  Eagle analyses generally do that.

In the end, the lowest acquisition cost or even the lowest TCO isn’t necessarily the best platform choice for a given situation or workload. Determining the right platform requires both quantifiable analysis and judgment.

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