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28 Ways to Ensure Application Performance in the Hybrid Cloud - Part 5

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. Part 5, the final installment, covers approaches you might not have thought about.

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

Start with 28 Ways to Ensure Application Performance in the Hybrid Cloud - Part 2

Start with 28 Ways to Ensure Application Performance in the Hybrid Cloud - Part 3

Start with 28 Ways to Ensure Application Performance in the Hybrid Cloud - Part 4

22. FOCUS ON PERFORMANCE DURING DEVELOPMENT

Tools don't ensure great performance in hybrid cloud environments. Tools help you in your testing phase to ensure that the application you push to production meets your performance requirements. Afterwards tools will help you to monitor the end user experience (performance and availability) and will help you to make sure you can guarantee the promised experience. The best way to ensure great performance is to make performance a requirement from day one. Make sure you're developers understand the performance of each line of code they write.
Coen Meerbeek
Online Performance Consultant and Founder of Blue Factory Internet

23. TEST AGAINST REAL NETWORK CONDITIONS

The biggest challenge with Hybrid Cloud is the switch between very different networks (often Lan to Wan) as the workload dynamically expands into the off-premises facilities. The network has a huge impact on application response time and performance and this must be mitigated in advance to prevent sharp increases in response time as the off-premises systems come into play during periods of high demand. The best way to do this is by utilizing Virtual test networks (network emulators) to try out (or test) these dynamic network changes prior to deployment of the solution. These products will replicate the real-world network conditions of both the private and public elements of the cloud solutions including transition between them. Taking this approach means you will have full insight into any potential issues before you commit time, money and resource to implementing a hybrid cloud solution.
Frank Puranik
Senior Technical Specialist, iTrinegy

24. KEEP MISSION CRITICAL APPLICATIONS IN-HOUSE

Hybrid cloud environments use a mix of on-premises, private cloud and third-party, public cloud services, allowing dynamic workload shifts as computing needs change. The major difference between the private and public cloud is that private clouds are not a shared resource, subject to overload from "neighbors" in the cloud. For this reason, when it comes to ensuring high performance for mission-critical, revenue-generating transactions, we recommend keeping these permanently in the private cloud, on mainframes (IBM's recently announced z13s is a strong option for mid-sized enterprises). Once that is established, organizations must include the mainframe as part of their overarching enterprise APM efforts. Today, an estimated 55 percent of enterprise applications touch mainframes, and IT managers need to be able to identify and address any mainframe bottlenecks that could impact performance.
Spencer Hallman
Product Manager, Compuware

25. FIND THE RIGHT SOLUTION PARTNER

Find the right partner. Invest in partners that bring the right added value to help you secure processes without the problem growing beyond your ability to handle it. Ensure your partner is aware of new technologies, trained and well-equipped to manage the breadth of various regulation requirements, and is able to provide (on your behalf) the tools customers need to answer market compliance. It's important that no component of what you choose to solve the business problem becomes the weak link.
Joan Groleau
Director, North America Channel Sales, Ipswitch

26. EXTEND TEAM SKILLS AND KNOWLEDGE

Today's IT professionals need to extend across traditional generalist or specialist roles and become polymaths in order to be successful in the hybrid IT world as they pivot across multiple technology domains. The most important skills and knowledge IT professionals need to develop or improve to successfully manage hybrid IT environments are service-oriented architectures, automation, vendor management, application migration, distributed architectures, API and hybrid IT monitoring and management tools and metrics.
Kong Yang
Head Geek, SolarWinds

27. ASSIGN APPLICATIONS TO THE RIGHT CLOUD ENVIRONMENT

Although there is a widening array of APM tools available to the challenges of the hybrid cloud alternatives, the key to ensure application performance is understanding the strengths and weaknesses of each cloud offering and properly assigning the application deployment to the appropriate cloud environment.
Jeffrey Kaplan
Managing Director of THINKstrategies and Founder of the Cloud Showplace

28. MANAGE THE FULL LIFECYCLE OF THE CLOUD SERVICE

Application performance in a cloud environment, whether public, private or hybrid, is about more than simply monitoring the application, it's about managing the full lifecycle of the cloud service from provisioning and maintaining the right configurations to remediating security vulnerabilities to planning for capacity growth. You need a cloud management platform that not only thrives in a hybrid environment but also enables applications to perform optimally.
Bill Berutti
President of the Cloud, Data Center and Performance Businesses at BMC Software

Hot Topics

The Latest

Production incidents rarely announce themselves as database problems. They appear as slow transactions, timeouts, rising response times, or an application struggling under a workload it previously handled. APM provides an essential starting point. It can identify a slow transaction path, highlight an affected service, and show that a database dependency is consuming more time than expected. But identifying the database as part of the problem is not the same as explaining what is happening inside it ...

Cloud teams are under constant pressure to reduce spend without slowing development or increasing operational risk. They are deploying autoscalers, rightsizing workloads, enforcing resource requests, reviewing utilization dashboards, and building FinOps processes around cloud-native environments. Yet the results often disappoint ...

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...

28 Ways to Ensure Application Performance in the Hybrid Cloud - Part 5

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. Part 5, the final installment, covers approaches you might not have thought about.

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

Start with 28 Ways to Ensure Application Performance in the Hybrid Cloud - Part 2

Start with 28 Ways to Ensure Application Performance in the Hybrid Cloud - Part 3

Start with 28 Ways to Ensure Application Performance in the Hybrid Cloud - Part 4

22. FOCUS ON PERFORMANCE DURING DEVELOPMENT

Tools don't ensure great performance in hybrid cloud environments. Tools help you in your testing phase to ensure that the application you push to production meets your performance requirements. Afterwards tools will help you to monitor the end user experience (performance and availability) and will help you to make sure you can guarantee the promised experience. The best way to ensure great performance is to make performance a requirement from day one. Make sure you're developers understand the performance of each line of code they write.
Coen Meerbeek
Online Performance Consultant and Founder of Blue Factory Internet

23. TEST AGAINST REAL NETWORK CONDITIONS

The biggest challenge with Hybrid Cloud is the switch between very different networks (often Lan to Wan) as the workload dynamically expands into the off-premises facilities. The network has a huge impact on application response time and performance and this must be mitigated in advance to prevent sharp increases in response time as the off-premises systems come into play during periods of high demand. The best way to do this is by utilizing Virtual test networks (network emulators) to try out (or test) these dynamic network changes prior to deployment of the solution. These products will replicate the real-world network conditions of both the private and public elements of the cloud solutions including transition between them. Taking this approach means you will have full insight into any potential issues before you commit time, money and resource to implementing a hybrid cloud solution.
Frank Puranik
Senior Technical Specialist, iTrinegy

24. KEEP MISSION CRITICAL APPLICATIONS IN-HOUSE

Hybrid cloud environments use a mix of on-premises, private cloud and third-party, public cloud services, allowing dynamic workload shifts as computing needs change. The major difference between the private and public cloud is that private clouds are not a shared resource, subject to overload from "neighbors" in the cloud. For this reason, when it comes to ensuring high performance for mission-critical, revenue-generating transactions, we recommend keeping these permanently in the private cloud, on mainframes (IBM's recently announced z13s is a strong option for mid-sized enterprises). Once that is established, organizations must include the mainframe as part of their overarching enterprise APM efforts. Today, an estimated 55 percent of enterprise applications touch mainframes, and IT managers need to be able to identify and address any mainframe bottlenecks that could impact performance.
Spencer Hallman
Product Manager, Compuware

25. FIND THE RIGHT SOLUTION PARTNER

Find the right partner. Invest in partners that bring the right added value to help you secure processes without the problem growing beyond your ability to handle it. Ensure your partner is aware of new technologies, trained and well-equipped to manage the breadth of various regulation requirements, and is able to provide (on your behalf) the tools customers need to answer market compliance. It's important that no component of what you choose to solve the business problem becomes the weak link.
Joan Groleau
Director, North America Channel Sales, Ipswitch

26. EXTEND TEAM SKILLS AND KNOWLEDGE

Today's IT professionals need to extend across traditional generalist or specialist roles and become polymaths in order to be successful in the hybrid IT world as they pivot across multiple technology domains. The most important skills and knowledge IT professionals need to develop or improve to successfully manage hybrid IT environments are service-oriented architectures, automation, vendor management, application migration, distributed architectures, API and hybrid IT monitoring and management tools and metrics.
Kong Yang
Head Geek, SolarWinds

27. ASSIGN APPLICATIONS TO THE RIGHT CLOUD ENVIRONMENT

Although there is a widening array of APM tools available to the challenges of the hybrid cloud alternatives, the key to ensure application performance is understanding the strengths and weaknesses of each cloud offering and properly assigning the application deployment to the appropriate cloud environment.
Jeffrey Kaplan
Managing Director of THINKstrategies and Founder of the Cloud Showplace

28. MANAGE THE FULL LIFECYCLE OF THE CLOUD SERVICE

Application performance in a cloud environment, whether public, private or hybrid, is about more than simply monitoring the application, it's about managing the full lifecycle of the cloud service from provisioning and maintaining the right configurations to remediating security vulnerabilities to planning for capacity growth. You need a cloud management platform that not only thrives in a hybrid environment but also enables applications to perform optimally.
Bill Berutti
President of the Cloud, Data Center and Performance Businesses at BMC Software

Hot Topics

The Latest

Production incidents rarely announce themselves as database problems. They appear as slow transactions, timeouts, rising response times, or an application struggling under a workload it previously handled. APM provides an essential starting point. It can identify a slow transaction path, highlight an affected service, and show that a database dependency is consuming more time than expected. But identifying the database as part of the problem is not the same as explaining what is happening inside it ...

Cloud teams are under constant pressure to reduce spend without slowing development or increasing operational risk. They are deploying autoscalers, rightsizing workloads, enforcing resource requests, reviewing utilization dashboards, and building FinOps processes around cloud-native environments. Yet the results often disappoint ...

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...

As an analyst who researches how IT organizations design, build, and operate their networks, I find that network data is a constant source of pain. Network teams struggle with data quality, fragmentation, authority, access, and trust. And these issues undermine everything they try to do. Here are the numbers: Only 45% of network teams are completely confident in the accuracy of their network source of truth, which documents the intent of their network ...

The 2026 Global Data Center Survey from Uptime Institute reveals an industry navigating workforce constraints, escalating outage expenses, even as rising costs remain the top concern for management teams ...

The next observability gap may not be in the code. It may be under the rack. That sounds strange until you think about how AI incidents actually feel in the middle of an investigation ... The application dashboard may be accurate. It may also be stopping at the wrong boundary. AI systems depend on software, but they also depend on a dense physical stack: racks, power paths, thermal margin, maintenance activity and, in many environments, liquid cooling. Those physical dependencies can change slowly before they look like a software incident ...

Certificate expiration is the rare outage you can see coming. Every TLS certificate carries the date it stops working, so the moment it will begin breaking connections is knowable in advance. That's what makes an expired certificate such a frustrating way to lose a service. What's changing now is how often that date comes around ...

Enterprises operate different combinations of workloads across cloud, hybrid and multicloud environments. For business-critical workloads, teams need to consider monitoring and observability early so they can detect health issues, investigate failures, and understand operational impact. Organizations place workloads on cloud platforms based on a combination of technical requirements, economics, existing dependencies, organizational standards, and business priorities. Their monitoring priorities therefore depend on what they operate and where those systems run. Those priorities will not look the same for every organization ...