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Performance Management For the Cloud: The Cloud Service Provider View

Srinivas Ramanathan

In my previous blogs in this four-part blog series I discussed performance management from the deployment perspective and the Cloud consumer view. The third perspective is that of the provider of the cloud service – whether it is the public cloud provider or the private cloud provider.

Start with Part One: Performance Management Challenges for Cloud-Hosted Services

Start with Part Two: Performance Management from the Cloud: The Deployment Perspective

Start with Part Three: Performance Management of the Cloud: The Cloud Consumer View

If you are the IT manager of a cloud service provider, the cloud itself is a service that that you are delivering to users. Your primary concern is to make sure that users of the cloud service are happy. Cloud service users must be able to login at any time, provision new instances as required, be able to start and stop instances and deploy applications in these instances.

For applications deployed in your cloud infrastructure, the performance of these applications should match the performance they would have had if they had been hosted on-premise, on physical machines.

Performance management FOR the cloud helps you, the cloud provider, deliver better cloud performance, maximum service availability, and superior customer satisfaction. The performance management system also helps you right-size your infrastructure, so that you can achieve the necessary returns for your investment in the cloud infrastructure.

To manage your cloud infrastructure, look for a performance management solution with the following characteristics:

Monitors the cloud infrastructure end-to-end

Typically, cloud infrastructures are built on a virtualization platform (e.g., VMware vSphere, Citrix XenServer, Microsoft Hyper-V). There are specialized applications that handle security (e.g., VMware vShield), web applications that enable user self-service and the cloud platform (e.g., VMware vCloud, Citrix CloudStack) that powers your cloud service.

The underlying infrastructure components including Active Directory, SAN, network equipment, etc. also need to be monitored as a failure of any of these components can also impact the cloud service. A performance management solution for the cloud should be capable of handling all of these infrastructure tiers from a central console.

Scalability

Scalability, to ensure that the management solution can handle the workload as your infrastructure grows, is another key requirement.

Supports Automation

A key driving factor for cloud computing is agility – the ability to power-up and power-down instances rapidly, on-demand. To achieve the kind of agility that customers expect, cloud service providers must make their operations fully automated. This covers the management system as well.

When a new cloud instance is provisioned, it should be automatically added to the management system for monitoring. Agent-based or agentless monitoring should be enabled. If required, agents should be installed on the cloud instances automatically. Touch-free provisioning and configuration of the management system is a very key requirement. Likewise, once provisioning and configuration of the monitoring has been done, alerts generated from the management system should be automatically handled.

To support this level of automation, the management system should support open interfaces that can be integrated with toolsets already being used by the cloud service provider. For instance, cloud service providers are already using runbook automation tools like Dynamic Ops, HP Orchestration and others. The performance management system should offer APIs (application programming interfaces) or CLIs (Command Line Interfaces) to allow its integration with the existing automation/orchestration tools.

For alert management, service providers often use trouble ticketing systems such as HEAT, BMC Remedy, and others. The management system must support interfaces that allow trouble tickets to be automatically opened when a problem is detected and automatically closed when a problem is fixed.


Allows cloud service providers to offer monitoring

The right performance management system will not only allow you to oversee the operation of your cloud service, but it can also allow you - the cloud service provider - to offer monitoring as a value-added service to your customers. For this purpose, the management system should support multi-tenancy – i.e., the same management platform can be used to monitor networks, servers and applications for multiple enterprise customers.

In this case, each customer gets a personalized login and when he/she logs into the management system, they only get to see the parts of the infrastructure that they have been configured to access and get reports for. The monitoring service can offer monitoring of the cloud instances that the customer is using. Advanced monitoring can also be offered to customers, providing them in-depth insight into applications like databases, web servers, Java applications, etc. that customers are hosting in the cloud.


The key benefits to service providers from a management solution that monitors the cloud infrastructure are:

- Ensuring that the performance of the cloud infrastructure meets the expectation of users.

- Facilitates effective provisioning of the cloud infrastructure to deliver the expected ROI without compromising on performance.

- Enables the cloud service provider to provide performance metrics of the cloud as a value-added service to their customers.

In summary, cloud performance management needs to be considered from three different perspectives, each of which has unique needs. A comprehensive approach needs to incorporate performance management FROM the cloud, OF the cloud and FOR the cloud. This will provide IT operations management with a new best practice for cloud performance management via a much more holistic view into every tier of the cloud infrastructure than traditional silo-based approaches provide.

This blog is the final in a series of four on cloud management.

Part One: Performance Management Challenges for Cloud-Hosted Services

Part Two: Performance Management from the Cloud: The Deployment Perspective

Part Three: Performance Management of the Cloud: The Cloud Consumer View

Srinivas Ramanathan is CEO and Founder of eG Innovations.

Related Links:

www.eginnovations.com

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Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

Performance Management For the Cloud: The Cloud Service Provider View

Srinivas Ramanathan

In my previous blogs in this four-part blog series I discussed performance management from the deployment perspective and the Cloud consumer view. The third perspective is that of the provider of the cloud service – whether it is the public cloud provider or the private cloud provider.

Start with Part One: Performance Management Challenges for Cloud-Hosted Services

Start with Part Two: Performance Management from the Cloud: The Deployment Perspective

Start with Part Three: Performance Management of the Cloud: The Cloud Consumer View

If you are the IT manager of a cloud service provider, the cloud itself is a service that that you are delivering to users. Your primary concern is to make sure that users of the cloud service are happy. Cloud service users must be able to login at any time, provision new instances as required, be able to start and stop instances and deploy applications in these instances.

For applications deployed in your cloud infrastructure, the performance of these applications should match the performance they would have had if they had been hosted on-premise, on physical machines.

Performance management FOR the cloud helps you, the cloud provider, deliver better cloud performance, maximum service availability, and superior customer satisfaction. The performance management system also helps you right-size your infrastructure, so that you can achieve the necessary returns for your investment in the cloud infrastructure.

To manage your cloud infrastructure, look for a performance management solution with the following characteristics:

Monitors the cloud infrastructure end-to-end

Typically, cloud infrastructures are built on a virtualization platform (e.g., VMware vSphere, Citrix XenServer, Microsoft Hyper-V). There are specialized applications that handle security (e.g., VMware vShield), web applications that enable user self-service and the cloud platform (e.g., VMware vCloud, Citrix CloudStack) that powers your cloud service.

The underlying infrastructure components including Active Directory, SAN, network equipment, etc. also need to be monitored as a failure of any of these components can also impact the cloud service. A performance management solution for the cloud should be capable of handling all of these infrastructure tiers from a central console.

Scalability

Scalability, to ensure that the management solution can handle the workload as your infrastructure grows, is another key requirement.

Supports Automation

A key driving factor for cloud computing is agility – the ability to power-up and power-down instances rapidly, on-demand. To achieve the kind of agility that customers expect, cloud service providers must make their operations fully automated. This covers the management system as well.

When a new cloud instance is provisioned, it should be automatically added to the management system for monitoring. Agent-based or agentless monitoring should be enabled. If required, agents should be installed on the cloud instances automatically. Touch-free provisioning and configuration of the management system is a very key requirement. Likewise, once provisioning and configuration of the monitoring has been done, alerts generated from the management system should be automatically handled.

To support this level of automation, the management system should support open interfaces that can be integrated with toolsets already being used by the cloud service provider. For instance, cloud service providers are already using runbook automation tools like Dynamic Ops, HP Orchestration and others. The performance management system should offer APIs (application programming interfaces) or CLIs (Command Line Interfaces) to allow its integration with the existing automation/orchestration tools.

For alert management, service providers often use trouble ticketing systems such as HEAT, BMC Remedy, and others. The management system must support interfaces that allow trouble tickets to be automatically opened when a problem is detected and automatically closed when a problem is fixed.


Allows cloud service providers to offer monitoring

The right performance management system will not only allow you to oversee the operation of your cloud service, but it can also allow you - the cloud service provider - to offer monitoring as a value-added service to your customers. For this purpose, the management system should support multi-tenancy – i.e., the same management platform can be used to monitor networks, servers and applications for multiple enterprise customers.

In this case, each customer gets a personalized login and when he/she logs into the management system, they only get to see the parts of the infrastructure that they have been configured to access and get reports for. The monitoring service can offer monitoring of the cloud instances that the customer is using. Advanced monitoring can also be offered to customers, providing them in-depth insight into applications like databases, web servers, Java applications, etc. that customers are hosting in the cloud.


The key benefits to service providers from a management solution that monitors the cloud infrastructure are:

- Ensuring that the performance of the cloud infrastructure meets the expectation of users.

- Facilitates effective provisioning of the cloud infrastructure to deliver the expected ROI without compromising on performance.

- Enables the cloud service provider to provide performance metrics of the cloud as a value-added service to their customers.

In summary, cloud performance management needs to be considered from three different perspectives, each of which has unique needs. A comprehensive approach needs to incorporate performance management FROM the cloud, OF the cloud and FOR the cloud. This will provide IT operations management with a new best practice for cloud performance management via a much more holistic view into every tier of the cloud infrastructure than traditional silo-based approaches provide.

This blog is the final in a series of four on cloud management.

Part One: Performance Management Challenges for Cloud-Hosted Services

Part Two: Performance Management from the Cloud: The Deployment Perspective

Part Three: Performance Management of the Cloud: The Cloud Consumer View

Srinivas Ramanathan is CEO and Founder of eG Innovations.

Related Links:

www.eginnovations.com

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...