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Proactive Capacity Planning: Turn Your Mainframe Into a Growth Driver
Mainframe capacity planning has grown significantly more complex over the past several years—and with it, the effort needed to maintain and maximize your mainframe investments while driving innovation. Between seasonal peaks, new digital services, cloud integration, increasing AI workloads, and changing transaction volumes, business demand is anything but linear.
Even so, accurately forecasting capacity is critical to budget predictability, confident strategic decision-making, and long-term success. So, how can you ensure your investments will last or further elevate the outcomes, if you are already going through upgrades (like upgrading to z17, for example)? Or what can you do when your mainframe capacity planning strategy is no longer effective? It’s time for a proactive approach: COBOL workload redistribution with JOPAZ. Read on to learn:
- What JOPAZ is and how it compares to other mainframe resource management and modernization strategies
- How JOPAZ helps maximize mainframe ROI on new or existing infrastructure
- How proactive capacity planning can benefit your whole organization (and turn your mainframe into a growth driver)
Why is it important to get mainframe resource management right?
Because your mainframe capacity impacts your entire organization—including your ability to execute on strategic initiatives. A lack of planning can lead to performance issues, lead to unexpected software charges, and hinder progress. As a result, developers are often left managing unpredictable batch windows instead of working on forward-looking projects. By the same token, overestimating could mean capacity is taking up more of your budget than necessary, leaving modernization and innovation behind.
Accurate forecasting helps you find the right balance between business demand and mainframe capacity, so you can proactively optimize mainframe investments instead of constantly reacting to capacity issues in an unpredictable environment—or accruing surprise charges when contract renewal season rolls around.
Three signs your capacity planning strategy is no longer effective
How do you know when it’s time for a new approach? Look for these common signs:
Frequent under- or overprovisioning of GP capacity
Deliberately maintaining excess capacity may help avoid risk, but it often comes at the expense of resource optimization. On the other hand, a constant need for more capacity or a small number of batch jobs consuming a majority of your processing resources can also be signs of inefficiency.
Lack of visibility
If your organization can’t clearly identify which applications, business units, or workload changes are driving capacity growth, it’s difficult to make informed decisions about where optimization efforts will have the greatest impact.
Slow progress on growth initiatives.
Are your developers struggling to keep up with business growth and the resulting increase in workload demands? Are your infrastructure and operations teams being asked to do more with the same amount of resources? A lack of time for strategic initiatives could be a sign that your mainframe capacity forecasting strategy is no longer serving your business needs.
What’s more: Even if you’re operating under a tailor-fit pricing model, changes in usage can still lead to surprises when contract negotiations come around. This is why it’s important to closely monitor and control GP usage. So, how do you ensure your strategy not only meets your teams’ current needs but also leaves room for growth initiatives (all without hurting the bottom line)? That’s where JOPAZ comes in.
JOPAZ vs. other mainframe optimization strategies
As your business grows, so does the need for capacity—and the pressure to modernize. For many organizations, this could mean time- and resource-intensive code rewrites, migrations, or rearchitecting that carry several potential risks, including:
- Business disruption and downtime
- Loss of existing business logic and COBOL developer knowledge
- Unexpected technical debt and scope creep
- Performance issues and security vulnerabilities
- Increased complexity
Unlike other mainframe workload optimization or modernization strategies, JOPAZ doesn’t put your operational business at risk. Instead, it’s modernization in place—no rewrites, code or data changes, increased technical debt, or replatforming required.
How it works: Redistributing COBOL batch workloads off the GP
JOPAZ optimizes mainframe capacity by recompiling COBOL batch workloads into zIIP-eligible Java bytecode. By increasing zIIP utilization, JOPAZ frees capacity on your general processor. The results: an incremental approach to modernization, the ability to retain existing business logic, and more time and resources for strategic initiatives without the need for additional training or increased technical debt. This approach not only helps when you need additional capacity in the short-term, but it can also give you more headroom for future workload changes and upgrades.
From reactive to proactive capacity planning
Here’s the thing: While increasing zIIP utilization is a clear benefit, JOPAZ isn’t just about solving for capacity shortages. Mainframe workload optimization also helps your teams meet or exceed SLAs more consistently, prepare for growth without unnecessary resource expansion, and optimize batch windows so less time is spent on day-to-day optimization. In other words: JOPAZ helps you do more and create more value with what you already have.
Organizations that take a proactive approach to mainframe resource management are better positioned to modernize, reduce long-term operational risks, and increase agility by freeing up capacity before it becomes an emergency. Your mainframe doesn’t have to drain your resources with constant need for maintenance. Instead, performing COBOL workload redistribution with JOPAZ turns your mainframe into a growth driver and a competitive advantage, priming your infrastructure and teams for future innovation.
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