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Q&A Part Two: CA Technologies Talks About APM

Pete Goldin
APMdigest

In Part Two of APMdigest's exclusive interview, Aruna Ravichandran, CA Technologies Vice President, Product and Solution Marketing, Application Performance Management & DevOps, discusses the benefits of APM and APM SaaS, and the differences between standard APM and APM for the cloud.

Start with Part One of the interview

APM: What are the top benefits of APM?

AR: APM is all about providing an outstanding customer or end-user experience. A positive customer experience improves customer satisfaction and brand perception thereby creating inspired users that directly impact business performance. It helps organizations reduce cost, increase brand loyalty, improve operational efficiency, and accelerate delivery of new business services to grow revenue.

APM: What do you see as the benefits of SaaS, in terms of APM?

AR: SaaS is all about ease of deployment, ease of use, and reduced cost. Looking at technology and business macro trends today, SaaS as a licensing and delivery model continues to show aggressive growth, and is pushing into the mainstream with enterprise IT organizations.

On the road to broad adoption, SaaS APM is following the path set in different markets (i.e. CRM), but is resolving its own unique maturity challenges. For example, what we have learned is that a SaaS APM solution has to be purposely designed to resolve specific APM problems, and with specific user personas in mind. A great example of a well-targeted product that is addressing a real need in the market is CA APM Cloud Monitor. This solution is used by many of our customers as a simple and easy to deploy End User Experience solution for Tier 2 and Tier 3 application, or to provide a complimentary synthetic monitoring component as part of a comprehensive CA APM solution for T1 applications.

Users expect an APM SaaS solution that delivers not only a cost optimized model that is easy to deploy with a quick time-to-value, but also one that is flexible and provides a persona-centric set of advanced capabilities that do not require a change in the platform or going on-premise. Not all of our customers' business and their applications are the same, but they all agree that SaaS APM should not just be some lightweight intro or “hook” to an APM solution that can completely resolve their problem. SaaS solutions need to be user centric, designed for specific personas, and have the ability to comprehensively resolve targeted APM challenges.

APM: What are the main differences between standard APM and APM for the cloud?

AR: Once again I will start answering with the customer needs in mind. The difference between APM and APM for Cloud solutions depends on the customer business, and the needs of their business models. For example, a Cloud providers' main focus is in exceptional customer experience. Performance of their applications is the cornerstone of the End User Experience and has direct impact on revenue streams. Their requirements are having a deep and scalable APM solution that will help them preemptively resolve issues, continue improving performance over time, and the ability to infinitely scale with their deployed solution. This is APM for the cloud.

A different example might include a business model where IT is bursting into the Public Cloud at times of peak load. They want to be able to make sure that transactions that are partially traversing applications in the Public Cloud will continue providing exceptional customer experience. In that case, they might deploy an APM solution that is running synthetic transactions to alert on any application issue.
This is just one simple use case, depicting the difference between customer needs that are driving APM and APM for Cloud requirements.

APM: With this in mind, what is the difference between CA APM vs. CA APM Cloud Monitor?

AR: When it comes to CA solutions, customers' needs are driving the solution and expected benefits. With CA APM you can ensure that every customer interaction with your applications is driving your business, by collecting on-premise information about applications, infrastructure, and end user experience and then taking action to optimize each user interaction with your applications. CA APM is an on-premise solution for datacenters, private clouds, and public clouds that require deep 20/20 vision of their applications.

CA APM Cloud Monitor is different in that it is a SaaS-based solution that runs synthetic transactions to emulate what a real-user might experience from over 96 monitoring stations across the globe. CA APM Cloud Monitor enables IT Operations teams to quickly identify and resolve performance issues and proactively manage the end-user experience of their applications around the world, even when there are no users on the system.

CA APM Cloud Monitor complements the on-premise CA APM solution for a more comprehensive solution and provides a SaaS-based option for applications that don't require full APM. This approach can help you optimize your organization's investments by employing the right level of synthetic monitoring so that you consistently deliver high service levels and an exceptional end-user experience.

Q&A Part Three: CA Technologies Talks About APM

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Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...

Q&A Part Two: CA Technologies Talks About APM

Pete Goldin
APMdigest

In Part Two of APMdigest's exclusive interview, Aruna Ravichandran, CA Technologies Vice President, Product and Solution Marketing, Application Performance Management & DevOps, discusses the benefits of APM and APM SaaS, and the differences between standard APM and APM for the cloud.

Start with Part One of the interview

APM: What are the top benefits of APM?

AR: APM is all about providing an outstanding customer or end-user experience. A positive customer experience improves customer satisfaction and brand perception thereby creating inspired users that directly impact business performance. It helps organizations reduce cost, increase brand loyalty, improve operational efficiency, and accelerate delivery of new business services to grow revenue.

APM: What do you see as the benefits of SaaS, in terms of APM?

AR: SaaS is all about ease of deployment, ease of use, and reduced cost. Looking at technology and business macro trends today, SaaS as a licensing and delivery model continues to show aggressive growth, and is pushing into the mainstream with enterprise IT organizations.

On the road to broad adoption, SaaS APM is following the path set in different markets (i.e. CRM), but is resolving its own unique maturity challenges. For example, what we have learned is that a SaaS APM solution has to be purposely designed to resolve specific APM problems, and with specific user personas in mind. A great example of a well-targeted product that is addressing a real need in the market is CA APM Cloud Monitor. This solution is used by many of our customers as a simple and easy to deploy End User Experience solution for Tier 2 and Tier 3 application, or to provide a complimentary synthetic monitoring component as part of a comprehensive CA APM solution for T1 applications.

Users expect an APM SaaS solution that delivers not only a cost optimized model that is easy to deploy with a quick time-to-value, but also one that is flexible and provides a persona-centric set of advanced capabilities that do not require a change in the platform or going on-premise. Not all of our customers' business and their applications are the same, but they all agree that SaaS APM should not just be some lightweight intro or “hook” to an APM solution that can completely resolve their problem. SaaS solutions need to be user centric, designed for specific personas, and have the ability to comprehensively resolve targeted APM challenges.

APM: What are the main differences between standard APM and APM for the cloud?

AR: Once again I will start answering with the customer needs in mind. The difference between APM and APM for Cloud solutions depends on the customer business, and the needs of their business models. For example, a Cloud providers' main focus is in exceptional customer experience. Performance of their applications is the cornerstone of the End User Experience and has direct impact on revenue streams. Their requirements are having a deep and scalable APM solution that will help them preemptively resolve issues, continue improving performance over time, and the ability to infinitely scale with their deployed solution. This is APM for the cloud.

A different example might include a business model where IT is bursting into the Public Cloud at times of peak load. They want to be able to make sure that transactions that are partially traversing applications in the Public Cloud will continue providing exceptional customer experience. In that case, they might deploy an APM solution that is running synthetic transactions to alert on any application issue.
This is just one simple use case, depicting the difference between customer needs that are driving APM and APM for Cloud requirements.

APM: With this in mind, what is the difference between CA APM vs. CA APM Cloud Monitor?

AR: When it comes to CA solutions, customers' needs are driving the solution and expected benefits. With CA APM you can ensure that every customer interaction with your applications is driving your business, by collecting on-premise information about applications, infrastructure, and end user experience and then taking action to optimize each user interaction with your applications. CA APM is an on-premise solution for datacenters, private clouds, and public clouds that require deep 20/20 vision of their applications.

CA APM Cloud Monitor is different in that it is a SaaS-based solution that runs synthetic transactions to emulate what a real-user might experience from over 96 monitoring stations across the globe. CA APM Cloud Monitor enables IT Operations teams to quickly identify and resolve performance issues and proactively manage the end-user experience of their applications around the world, even when there are no users on the system.

CA APM Cloud Monitor complements the on-premise CA APM solution for a more comprehensive solution and provides a SaaS-based option for applications that don't require full APM. This approach can help you optimize your organization's investments by employing the right level of synthetic monitoring so that you consistently deliver high service levels and an exceptional end-user experience.

Q&A Part Three: CA Technologies Talks About APM

Hot Topic
The Latest
The Latest 10

The Latest

Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...