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Triple A (Automatic Application Analysis) lets GiAPA automatically analyze program behavior and file access patterns. It often reveals inefficiencies even in code assumed to run well.
Whether you're rolling out new code or migrating systems, GiAPA lets you compare performance metrics over time. This makes it easier to measure the actual impact of changes.
Thanks to GiAPA’s automated analysis and reporting features, organizations often reduce or eliminate the need for external consultants. It highlights performance problems and optimization opportunities clearly.
You can configure how long data is kept based your business needs. Many installations keep weeks or months of historical data for long-term analysis and comparison.
GiAPA's data reveals which parts of a program use the most CPU or I/O. GiAPA documents which source statement should be modified and suggests the new code to use to improve performance.
This high-frequency sampling allows for precise performance insights.
SQL Observer’s report shows the SQL statement(s), when the Plan Cache dumps were taken, where the dumps are stored, and why the access method were selected for the max 3 latest access plans.
This enables developers pinpoint the exact part of the code causing the issue.
The installation process is straightforward, with default settings that work well in most environments. Configuration can be customized later to match specific monitoring needs.
GiAPA reports program functions using excessive resources and files accessed inefficiently.
When evaluating hardware upgrades, GiAPA can demonstrate actual system strain, historical performance trends, and areas where current resources are insufficient – all based on objective data.
With GiAPA’s trend analysis and visual reporting tools, IT leaders can identify resource usage patterns and plan for future system demands based on actual usage data.
GiAPA continuously logs detailed job and system activity. If a performance issue or outage occurred, you can go back and see exactly what jobs were running and which resources were affected.
By analyzing CPU usage, file access patterns, and program call stacks, GiAPA helps developers find bottlenecks and inefficiencies in batch processing routines.
You monitor each partition individually, and generate consolidated reports for a full overview.
GiAPA is lightweight and scalable. It provides valuable insight whether your system runs a handful of applications or a large enterprise workload.
GiAPA includes a wide range of standard reports and graphs, and allows users to define their own based on the comprehensive GiAPA data base containing data for all jobs, summarized or per 15 seconds’ intervals.
GiAPA is built for the IBM Power i platform and integrates tightly with the OS architecture. It does not require any additional hardware or cloud integration.
GiAPA includes logic to detect jobs consuming abnormal amounts of memory or stuck in loops – giving operators the ability to intervene quickly.
GiAPA’s data collection enables full transparency of job and system activity. You can generate reports for specific users, applications, or time periods – useful for audits and compliance checks.
For CPU-intensive jobs, GiAPA retrieves file usage details to show how data is accessed during execution. This helps developers and operators understand I/O patterns and file bottlenecks.
For rarely used advanced functions it is recommended to turn to GiAPA’s complete set of smaller tutorials, each covering one or a couple of GiAPA’s menu options.
GiAPA samples job-related data every 15 seconds around the clock. This high frequency allows you to detect even short-lived performance issues and gain reliable insights into system usage trends.
Triple A stands for Automatic Application Analysis. It highlights which program functions and file accesses are consuming the most resources – often revealing hidden inefficiencies even in trusted code.
GiAPA is designed to be extremely lightweight. The data collection process uses less than 0.1% CPU and does not interfere with job execution, making it safe for use in production environments.
You can generate visual reports comparing workloads across days, weeks, or months – perfect for evaluating the impact of changes or identifying performance degradation over time.
In addition to GiAPA’s suite of automatically generated graphics, users can define their own. Graphs can run in unattended batch and be emailed automatically to stakeholders.
GiAPA was built with performance in mind. It collects detailed data for every job every 15 seconds – and still keeps its own resource use extremely low. The total CPU consumption is typically below 0.1%, even on busy production systems. This means you get full visibility without performance trade-offs. GiAPA runs quietly in the background, without slowing anything down.
With GiAPA, you're not limited to real-time monitoring. The system stores a rich history of performance data, which lets you investigate and diagnose problems after the fact. For example, if a job caused issues last night, you can review what happened – CPU spikes, I/Os, and even call stacks or file activity (for CPU-heavy jobs). This makes it easy to identify root causes, compare before/after changes, and avoid guesswork in your troubleshooting process.
It scales effortlessly to handle high workloads and complex environments. Thanks to its lightweight design and low CPU footprint, it remains stable and responsive even under heavy load, making it ideal for mission-critical systems.
GiAPA is designed to help you monitor and optimize performance without touching your business-critical data. It collects detailed metrics like CPU usage, job activity, and I/O patterns – but never the content of database files, user input, or application data. All data remains on your system. There’s no cloud syncing, and no external access is required. This ensures full data privacy and compliance with internal security policies.
With GiAPA, you're not limited to real-time monitoring. The system stores a rich history of performance data, which lets you investigate and diagnose problems after the fact.
For example, if a job caused issues last night, you can review what happened – CPU spikes, looping behavior, and even call stacks or file activity (for CPU-heavy jobs).
This makes it easy to identify root causes, compare before/after changes, and avoid guesswork in your troubleshooting process.
GiAPA was built with performance in mind. It collects detailed data for every job every 15 seconds – and still keeps its own resource use extremely low.
The total CPU consumption is typically below 0.1%, even on busy production systems. This means you get full visibility without performance trade-offs. GiAPA runs quietly in the background, without slowing anything down.
GiAPA is designed to help you monitor and optimize performance without touching your business-critical data. It collects detailed metrics like CPU usage, job activity, and I/O patterns – but never the content of database files, user input, or application data.
All data remains on your system. There’s no cloud syncing, and no external access is required. This ensures full data privacy and compliance with internal security policies.