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20 Technologies to Support APM - Part 2

APMdigest continues the list, cataloging the many valuable tools available – beyond what is technically categorized as Application Performance Management (APM) – to support the goals of improving application performance and business service.

Start with Part 1

6. Synthetic Monitoring

Understanding Web and mobile app performance starts with the end-user experience, no matter how and when a customer accesses the application. And while today's IT departments are facing enormous pressure to deliver a flawless end-user experience, they must also drive down costs. These competing forces create a compelling case for adding a synthetic-transaction SaaS solution to the APM mix. IT pros responsible for application performance can understand the health and availability of key applications, and track global and local end-user experience, with a cost-effective, easy-to-use and fast-to-implement solution.
Aruna Ravichandran
VP Product and Solution Marketing, APM and DevOps, CA Technologies

Active, or synthetic, monitoring of applications, services, and websites 24/7 is an essential component of an enterprise-wide APM strategy. It ensures that online properties are fast and reliable for end users, helping to protect brand image and drive revenue. While passive monitoring provides a view into end user experience, it cannot detect downtime or get a full picture of what end users see outside of your datacenter(s) or cloud.
Mehdi Daoudi
CEO and Founder, Catchpoint

7. Infrastructure Monitoring

While APM solutions and corresponding strategy is critical for modern enterprises it's essential to also adopt an appropriate infrastructure monitoring solution. Applications sit on top of increasingly complex infrastructure workloads (server, network, storage) brought about by innovations in areas cloud architecture, mobile and non-relational data stores. This means that a unified infrastructure monitoring solution that is able to cover these areas is an essential component of a strategic monitoring strategy.
John Rakowski
Analyst, Infrastructure and Operations, Forrester Research

While APM provides great insight into service delivery from a user perspective, it alone isn't sufficient to properly identify and resolve performance or availability issues pertaining to the back-end infrastructure. Service-centric unified monitoring tools are the key to ensuring the health of applications and all the infrastructure components needed for consistent and reliable delivery of the service.
Deepak Kanwar
Senior Manager, Zenoss

8. Load Testing

APM is a cornerstone of delivering a quality user experience. To supplement the 360 degree view of your APM solution it is important to also implement and obtain correlation between your APM and Load Testing solutions. This combination provides a clear perspective of your application and your application environment, allowing you to use load to help predict application performance prior to seeing real life behavior through your APM solution.
Denis Goodwin
Director of Product Management, AlertSite by SmartBear

Among the thousands of product reviews by real users on IT Central Station – aka the "Yelp for IT" – we find numerous cross-references between APM and testing tools. Our community of IT professionals evidently find that investment in testing tools is complimentary to APM.
Russell Rothstein
Founder and CEO, IT Central Station

9. Log Management

While APM tools are definitely widely used for a view into how your own application code is performing, in many cases APM alone is not enough to give an end-to-end perspective of your system - especially in cloud environments where you no longer have the same level of access and it can be more difficult to apply instrumentation. We are seeing a huge increase in users sending more and more performance metrics into their log data – giving them the ability to use "logs as data" along side their APM tools, and providing deeper log-level insights into key business metrics.
Trevor Parsons, Phd
Co-founder & Chief Scientist, Logentries

Combining unified monitoring with log analysis provides faster trouble-shooting, improved root cause analysis, and more effective IT event correlation and forensic analysis.
David Dennis
VP of Marketing & Business Development, GroundWork

10. Middleware Management

Middleware Infrastructure Visibility is a necessity for application and business service performance. Enterprise applications are inherently complex and built on a combination of technologies including middleware systems (e.g., WebSphere MQ, IBM Data Power, TIBCO, and Oracle BPEL), packaged applications, and other legacy technologies. Middleware, in particular, serves as the plumbing connecting a multitude of heterogeneous systems. In this way, middleware management complements traditional APM offerings because it provides deep visibility into the infrastructure these applications depend on to deliver data and business services.
April Hickel
Product Manager, APM, BMC Software

20 Technologies to Support APM - Part 3

Hot Topics

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 ...

20 Technologies to Support APM - Part 2

APMdigest continues the list, cataloging the many valuable tools available – beyond what is technically categorized as Application Performance Management (APM) – to support the goals of improving application performance and business service.

Start with Part 1

6. Synthetic Monitoring

Understanding Web and mobile app performance starts with the end-user experience, no matter how and when a customer accesses the application. And while today's IT departments are facing enormous pressure to deliver a flawless end-user experience, they must also drive down costs. These competing forces create a compelling case for adding a synthetic-transaction SaaS solution to the APM mix. IT pros responsible for application performance can understand the health and availability of key applications, and track global and local end-user experience, with a cost-effective, easy-to-use and fast-to-implement solution.
Aruna Ravichandran
VP Product and Solution Marketing, APM and DevOps, CA Technologies

Active, or synthetic, monitoring of applications, services, and websites 24/7 is an essential component of an enterprise-wide APM strategy. It ensures that online properties are fast and reliable for end users, helping to protect brand image and drive revenue. While passive monitoring provides a view into end user experience, it cannot detect downtime or get a full picture of what end users see outside of your datacenter(s) or cloud.
Mehdi Daoudi
CEO and Founder, Catchpoint

7. Infrastructure Monitoring

While APM solutions and corresponding strategy is critical for modern enterprises it's essential to also adopt an appropriate infrastructure monitoring solution. Applications sit on top of increasingly complex infrastructure workloads (server, network, storage) brought about by innovations in areas cloud architecture, mobile and non-relational data stores. This means that a unified infrastructure monitoring solution that is able to cover these areas is an essential component of a strategic monitoring strategy.
John Rakowski
Analyst, Infrastructure and Operations, Forrester Research

While APM provides great insight into service delivery from a user perspective, it alone isn't sufficient to properly identify and resolve performance or availability issues pertaining to the back-end infrastructure. Service-centric unified monitoring tools are the key to ensuring the health of applications and all the infrastructure components needed for consistent and reliable delivery of the service.
Deepak Kanwar
Senior Manager, Zenoss

8. Load Testing

APM is a cornerstone of delivering a quality user experience. To supplement the 360 degree view of your APM solution it is important to also implement and obtain correlation between your APM and Load Testing solutions. This combination provides a clear perspective of your application and your application environment, allowing you to use load to help predict application performance prior to seeing real life behavior through your APM solution.
Denis Goodwin
Director of Product Management, AlertSite by SmartBear

Among the thousands of product reviews by real users on IT Central Station – aka the "Yelp for IT" – we find numerous cross-references between APM and testing tools. Our community of IT professionals evidently find that investment in testing tools is complimentary to APM.
Russell Rothstein
Founder and CEO, IT Central Station

9. Log Management

While APM tools are definitely widely used for a view into how your own application code is performing, in many cases APM alone is not enough to give an end-to-end perspective of your system - especially in cloud environments where you no longer have the same level of access and it can be more difficult to apply instrumentation. We are seeing a huge increase in users sending more and more performance metrics into their log data – giving them the ability to use "logs as data" along side their APM tools, and providing deeper log-level insights into key business metrics.
Trevor Parsons, Phd
Co-founder & Chief Scientist, Logentries

Combining unified monitoring with log analysis provides faster trouble-shooting, improved root cause analysis, and more effective IT event correlation and forensic analysis.
David Dennis
VP of Marketing & Business Development, GroundWork

10. Middleware Management

Middleware Infrastructure Visibility is a necessity for application and business service performance. Enterprise applications are inherently complex and built on a combination of technologies including middleware systems (e.g., WebSphere MQ, IBM Data Power, TIBCO, and Oracle BPEL), packaged applications, and other legacy technologies. Middleware, in particular, serves as the plumbing connecting a multitude of heterogeneous systems. In this way, middleware management complements traditional APM offerings because it provides deep visibility into the infrastructure these applications depend on to deliver data and business services.
April Hickel
Product Manager, APM, BMC Software

20 Technologies to Support APM - Part 3

Hot Topics

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 ...