28 Ways to Ensure Application Performance in the Hybrid Cloud - Part 1

For years the IT industry debated about whether and when IT organizations would move everything to the cloud. Today's answer to this question is the hybrid cloud or hybrid IT – a combination of private and public clouds with traditional on-premise infrastructure, leveraging the best of all three worlds. A recent survey conducted by IDG Research Services for EMC revealed that 83% of respondents currently use or plan to use a hybrid cloud environment, and 73% agree that a hybrid cloud model creates a path to digital business.

It is clear that hybrid cloud offers many advantages. In a blog on APMdigest, Kong Yang of Solarwinds said, "The top three hybrid IT benefits by weighted rank are infrastructure cost-reduction, increased infrastructure flexibility/agility and relieving internal IT personnel of day-to-day management of some infrastructure, respectively."

However, as more enterprises move to hybrid cloud, they face new challenges for managing the performance of applications, such as limited visibility and control. Referencing a survey on public cloud, Antonio Piraino of ScienceLogic said, "A staggering 82 percent are unable to ensure optimum performance, health and availability of public cloud workloads due to lack of advanced visibility into the public cloud infrastructure."

In a recent blog on hybrid cloud, Shamus McGillicuddy, Senior Analyst, Network Management at Enterprise Management Associates (EMA), warns, "Enterprises who are implementing hybrid clouds will need to evaluate the readiness of their performance management to support these new cloud environments."

To address this new set of challenges, APMdigest asked experts from across the industry – including consultants, analysts and the leading vendors – for recommendations on the best way to ensure application performance in the hybrid cloud. The result is a detailed list of tools and approaches, and related insights, to guide enterprises as they migrate to hybrid cloud.

Some of the recommendations are new twists on tools you are familiar with or combinations of tools that our experts say are essential in the new world of hybrid cloud, but all of them require a new way of looking at the challenge of application performance.

The list will be posted in installments all week. Part 1 covers APM and End-User Experience Monitoring.

1. APPLICATION PERFORMANCE MANAGEMENT (APM)

There is often a misconception that hybrid cloud implies that an application (or components of an application) are running in two places concurrently. At least today, this is rarely the case, although in a future that increasingly includes things like containers and microservices this duality of execution may become more of a reality. Another way of saying this is that we don't need to make this more complex than it is. Today I would simply state that you should start with ensuring that you have visibility into the end user experience for both the cloud and on-premise applications. Use this point of observability to provide early warning indicators of potential problems. Depending upon the application type, you may be able to add instrumentation to help with localization of the problem domain through tracing and other activity (you may be able to substitute a network-based approach for this as well, if for example, cloud-based instrumentation proved to somehow be problematic). Then, through the same or additional agent technology you may have to delve more deeply into application and/or system internals to move closer to a root cause analysis. Of course, what I've basically described is the need for several of the elements that go into our 5 dimensional model of APM. All of this can be performed today with many existing SaaS or on-premise-based APM products as we point out in our latest Magic Quadrant. As I indicated earlier, this gets more complicated if in future hybrid cloud environments we start encountering more cloud native applications which have the twin challenges of scale and ephemerality, among other things, to deal with.
Cameron Haight
Research VP, IT Operations, Gartner

2. CLOUD-READY APM

Application Performance Management Platforms/Suites are becoming increasingly important as more companies roll out complex hybrid services. However one key factor to remember in choosing such a platform is that support for hybrid cloud also means support for the integration platforms that are intrinsic to creating hybrid services. In other words, APM solutions must be able to support the integration points that are foundational elements to hybrid delivery. Specifically, the APM solution needs to be "cloud ready" in its ability to consume and analyze metrics from API Gateways, messaging platforms, and/or other integration points to consolidate that information into APM dashboards and reports.
Julie Craig
Research Director, Application Management, Enterprise Management Associates (EMA)

Today's applications can have components spread across cloud, on premises, in containers and accessed through APIs and more. A modern approach to Application Performance Management allows you to see all of the elements and more importantly, reduce the complexity of what you are seeing so that you can quickly address performance issues, no matter where they reside.
Aruna Ravichandran
VP, DevOps Product and Solutions Marketing, CA Technologies

With the evolution of hybrid cloud, applications can now span across environments. For example, an application could be running on a public cloud platform to take advantage of autoscaling and be accessing data from a database that is running in an on-premises data center. An Application Performance Management tool that can discover ALL application dependencies no matter where they are located and give end-to-end visibility into transactions running across hybrid environments would be critical.
Payal Chakravarty
Offering Leader, APM Cloud Initiatives, IBM Cloud Integration

As workloads and applications shift from private to public clouds, application performance is liable to be impacted due to changes in the compute and network infrastructure. To monitor, manage and deliver the best end user experience, Application Performance Management tools must seamlessly instrument the edge device and the infrastructure to measure application reachability, availability and performance; integrate the data from different users and locations and present in a simple intuitive interface to different stakeholders, including the application owner and service delivery.
Balaji Venkatraman
Director of Product Management, IT Operations Management, Hewlett Packard Enterprise

3. END USER EXPERIENCE MONITORING

Without access to public cloud infrastructure, IT Ops teams face challenges in ensuring excellent end user experience for applications delivered via hybrid cloud environments, and cloud vendors' SLAs cover only the infrastructure under their control. Monitoring the actual end user experience from the point of consumption, the user's device, overcomes the limitations faced by other approaches which require access to the application code, involve proxy servers or load balancers, or which only emulate end user experience.
Mike Marks
Chief Product Evangelist, Aternity

According to reviews of APM solutions on IT Central Station, the best way to ensure app performance in a hybrid cloud environment is to start with end user experience management. Reviewers talk about the success they have with real user monitoring, synthetic monitoring, and other tools for monitoring end user experience across public and private clouds.
Russell Rothstein
Founder and CEO, IT Central Station

Click here to read the latest APM product reviews on IT Central Station

A primary driver for hybrid cloud deployments is the ability to retain critical systems of record that are not candidates to move off-premise or to a public cloud environment. Enterprise customers need to have deep visibility into "modern" application tiers, where an agent can be deployed within an application or server and dynamically discover and configure itself, as well as the need to provide agent-less deep visibility into applications and end users where agents are not allowed or not technically possible to deploy. The critical element, therefore, in addressing application performance within a hybrid cloud deployment is to tackle all types of application environments, including ones that require agent-less instrumentation, while focusing on end user experience as the critical measure of performance.
Michael Masterson
Director, Strategic Business Development, Dynatrace

In hybrid cloud architectures it is critical to understand everything you measure in the context of what it means to the user experience. While it's easy to collect mountains of data from each cloud provider about response times, availability, and resource consumption, none of this matters if we can't understand how changes in these metrics affect the user's satisfaction with our application.
Buddy Brewer
SVP of Products, SOASTA

Hybrid cloud environments offer organizations a great deal of flexibility, by allowing them to move workloads across public and private cloud resources as computing needs and costs change. However, it's important to remember that the public portion of hybrid cloud environments is a shared utility. This means when an organization relying on the public cloud is experiencing a peak traffic period, chances are their "neighbors" in the cloud could be experiencing peaks as well – which could mean degraded performance for everyone. Organizations that depend on the public cloud in any way need to constantly measure their own end users' experience of cloud applications, which requires monitoring from inside the firewall. In addition to maintaining visibility into the performance of systems that are critical for productivity, monitoring from within the organization's network can play a valuable role in SLA enforcement for cloud services.
Dennis Callaghan
Director of Industry Innovation, Catchpoint

4. INTEGRATED USER EXPERIENCE DATA FROM MULTIPLE SOURCES

Hybrid cloud argues for a strategic approach to application performance and user experience monitoring and management as suggested in the PADS Framework. Integration is essential in an environment where the user traverses multiple domains. Integrated user experience data brings context to cloud metrics. This begins with left-shifting application performance in DevOps, and extends to having visibility Into the repositories where containers reside. The objective is to significantly reduce the friction of cloud-to-cloud deployment and migration.
Gabe Lowy
Technology Analyst and Founder of TechTonics Advisors

Read 28 Ways to Ensure Application Performance in the Hybrid Cloud - Part 2, covering NPM, ITOA and BTM.

Related Links

Hot Topics

The Latest

Keys to Building a Partner Ecosystem That Scales

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

AI Deepfakes: Rethinking Trust in the Workplace

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Why ITOps Need Right-Sized AI, Not Bigger Models

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

5 Takeaways from the Observability Forecast for Media and Entertainment

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

28 Ways to Ensure Application Performance in the Hybrid Cloud - Part 1

For years the IT industry debated about whether and when IT organizations would move everything to the cloud. Today's answer to this question is the hybrid cloud or hybrid IT – a combination of private and public clouds with traditional on-premise infrastructure, leveraging the best of all three worlds. A recent survey conducted by IDG Research Services for EMC revealed that 83% of respondents currently use or plan to use a hybrid cloud environment, and 73% agree that a hybrid cloud model creates a path to digital business.

It is clear that hybrid cloud offers many advantages. In a blog on APMdigest, Kong Yang of Solarwinds said, "The top three hybrid IT benefits by weighted rank are infrastructure cost-reduction, increased infrastructure flexibility/agility and relieving internal IT personnel of day-to-day management of some infrastructure, respectively."

However, as more enterprises move to hybrid cloud, they face new challenges for managing the performance of applications, such as limited visibility and control. Referencing a survey on public cloud, Antonio Piraino of ScienceLogic said, "A staggering 82 percent are unable to ensure optimum performance, health and availability of public cloud workloads due to lack of advanced visibility into the public cloud infrastructure."

In a recent blog on hybrid cloud, Shamus McGillicuddy, Senior Analyst, Network Management at Enterprise Management Associates (EMA), warns, "Enterprises who are implementing hybrid clouds will need to evaluate the readiness of their performance management to support these new cloud environments."

To address this new set of challenges, APMdigest asked experts from across the industry – including consultants, analysts and the leading vendors – for recommendations on the best way to ensure application performance in the hybrid cloud. The result is a detailed list of tools and approaches, and related insights, to guide enterprises as they migrate to hybrid cloud.

Some of the recommendations are new twists on tools you are familiar with or combinations of tools that our experts say are essential in the new world of hybrid cloud, but all of them require a new way of looking at the challenge of application performance.

The list will be posted in installments all week. Part 1 covers APM and End-User Experience Monitoring.

1. APPLICATION PERFORMANCE MANAGEMENT (APM)

There is often a misconception that hybrid cloud implies that an application (or components of an application) are running in two places concurrently. At least today, this is rarely the case, although in a future that increasingly includes things like containers and microservices this duality of execution may become more of a reality. Another way of saying this is that we don't need to make this more complex than it is. Today I would simply state that you should start with ensuring that you have visibility into the end user experience for both the cloud and on-premise applications. Use this point of observability to provide early warning indicators of potential problems. Depending upon the application type, you may be able to add instrumentation to help with localization of the problem domain through tracing and other activity (you may be able to substitute a network-based approach for this as well, if for example, cloud-based instrumentation proved to somehow be problematic). Then, through the same or additional agent technology you may have to delve more deeply into application and/or system internals to move closer to a root cause analysis. Of course, what I've basically described is the need for several of the elements that go into our 5 dimensional model of APM. All of this can be performed today with many existing SaaS or on-premise-based APM products as we point out in our latest Magic Quadrant. As I indicated earlier, this gets more complicated if in future hybrid cloud environments we start encountering more cloud native applications which have the twin challenges of scale and ephemerality, among other things, to deal with.
Cameron Haight
Research VP, IT Operations, Gartner

2. CLOUD-READY APM

Application Performance Management Platforms/Suites are becoming increasingly important as more companies roll out complex hybrid services. However one key factor to remember in choosing such a platform is that support for hybrid cloud also means support for the integration platforms that are intrinsic to creating hybrid services. In other words, APM solutions must be able to support the integration points that are foundational elements to hybrid delivery. Specifically, the APM solution needs to be "cloud ready" in its ability to consume and analyze metrics from API Gateways, messaging platforms, and/or other integration points to consolidate that information into APM dashboards and reports.
Julie Craig
Research Director, Application Management, Enterprise Management Associates (EMA)

Today's applications can have components spread across cloud, on premises, in containers and accessed through APIs and more. A modern approach to Application Performance Management allows you to see all of the elements and more importantly, reduce the complexity of what you are seeing so that you can quickly address performance issues, no matter where they reside.
Aruna Ravichandran
VP, DevOps Product and Solutions Marketing, CA Technologies

With the evolution of hybrid cloud, applications can now span across environments. For example, an application could be running on a public cloud platform to take advantage of autoscaling and be accessing data from a database that is running in an on-premises data center. An Application Performance Management tool that can discover ALL application dependencies no matter where they are located and give end-to-end visibility into transactions running across hybrid environments would be critical.
Payal Chakravarty
Offering Leader, APM Cloud Initiatives, IBM Cloud Integration

As workloads and applications shift from private to public clouds, application performance is liable to be impacted due to changes in the compute and network infrastructure. To monitor, manage and deliver the best end user experience, Application Performance Management tools must seamlessly instrument the edge device and the infrastructure to measure application reachability, availability and performance; integrate the data from different users and locations and present in a simple intuitive interface to different stakeholders, including the application owner and service delivery.
Balaji Venkatraman
Director of Product Management, IT Operations Management, Hewlett Packard Enterprise

3. END USER EXPERIENCE MONITORING

Without access to public cloud infrastructure, IT Ops teams face challenges in ensuring excellent end user experience for applications delivered via hybrid cloud environments, and cloud vendors' SLAs cover only the infrastructure under their control. Monitoring the actual end user experience from the point of consumption, the user's device, overcomes the limitations faced by other approaches which require access to the application code, involve proxy servers or load balancers, or which only emulate end user experience.
Mike Marks
Chief Product Evangelist, Aternity

According to reviews of APM solutions on IT Central Station, the best way to ensure app performance in a hybrid cloud environment is to start with end user experience management. Reviewers talk about the success they have with real user monitoring, synthetic monitoring, and other tools for monitoring end user experience across public and private clouds.
Russell Rothstein
Founder and CEO, IT Central Station

Click here to read the latest APM product reviews on IT Central Station

A primary driver for hybrid cloud deployments is the ability to retain critical systems of record that are not candidates to move off-premise or to a public cloud environment. Enterprise customers need to have deep visibility into "modern" application tiers, where an agent can be deployed within an application or server and dynamically discover and configure itself, as well as the need to provide agent-less deep visibility into applications and end users where agents are not allowed or not technically possible to deploy. The critical element, therefore, in addressing application performance within a hybrid cloud deployment is to tackle all types of application environments, including ones that require agent-less instrumentation, while focusing on end user experience as the critical measure of performance.
Michael Masterson
Director, Strategic Business Development, Dynatrace

In hybrid cloud architectures it is critical to understand everything you measure in the context of what it means to the user experience. While it's easy to collect mountains of data from each cloud provider about response times, availability, and resource consumption, none of this matters if we can't understand how changes in these metrics affect the user's satisfaction with our application.
Buddy Brewer
SVP of Products, SOASTA

Hybrid cloud environments offer organizations a great deal of flexibility, by allowing them to move workloads across public and private cloud resources as computing needs and costs change. However, it's important to remember that the public portion of hybrid cloud environments is a shared utility. This means when an organization relying on the public cloud is experiencing a peak traffic period, chances are their "neighbors" in the cloud could be experiencing peaks as well – which could mean degraded performance for everyone. Organizations that depend on the public cloud in any way need to constantly measure their own end users' experience of cloud applications, which requires monitoring from inside the firewall. In addition to maintaining visibility into the performance of systems that are critical for productivity, monitoring from within the organization's network can play a valuable role in SLA enforcement for cloud services.
Dennis Callaghan
Director of Industry Innovation, Catchpoint

4. INTEGRATED USER EXPERIENCE DATA FROM MULTIPLE SOURCES

Hybrid cloud argues for a strategic approach to application performance and user experience monitoring and management as suggested in the PADS Framework. Integration is essential in an environment where the user traverses multiple domains. Integrated user experience data brings context to cloud metrics. This begins with left-shifting application performance in DevOps, and extends to having visibility Into the repositories where containers reside. The objective is to significantly reduce the friction of cloud-to-cloud deployment and migration.
Gabe Lowy
Technology Analyst and Founder of TechTonics Advisors

Read 28 Ways to Ensure Application Performance in the Hybrid Cloud - Part 2, covering NPM, ITOA and BTM.

Related Links

Hot Topics

The Latest

Keys to Building a Partner Ecosystem That Scales

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

AI Deepfakes: Rethinking Trust in the Workplace

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Why ITOps Need Right-Sized AI, Not Bigger Models

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

5 Takeaways from the Observability Forecast for Media and Entertainment

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...