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CA Technologies Powers StratITsphere’s New Cloud Services and Data Center

CA Technologies announced that StratITsphere, an IT consulting and data center services provider, will use CA Technologies cloud computing, energy management and service assurance solutions as the backbone for Nimbus, its new package of cloud-based services, as well as other offerings.

Nimbus was developed with and will be delivered on the CA AppLogic cloud platform and will include virtual private data centers (VPDC) with full failover and disaster recovery capabilities. StratITsphere’s Fortune 1000 customers will be able to access dynamically provisioned and secure cloud services, providing agile and highly available infrastructures with a lower capital investment than traditional computing solutions.

StratITsphere plans to use CA ecoSoftware to enable customers in its co-location facility to help lower their electricity costs and to help make the entire facility more energy efficient. By being able to see energy consumption patterns at the device and system levels, StratITsphere can make adjustments to help improve its power usage effectiveness (PUE) metric, a measure of how efficiently the facility uses electricity. CA ecoSoftware also allows StratITsphere to provide automatic billing to customers based on real energy use, rather than relying on error-prone estimates or time-consuming manual data collection.

To proactively manage the performance and availability of the service delivery infrastructure, and to monitor the composition and behavior of network traffic in real-time, StratITsphere relies on CA Technologies Service Assurance portfolio, including CA eHealth Performance Manager, CA Spectrum Infrastructure Manager and CA NetQoS ReporterAnalyzer software.

StratITsphere provides data center services and IT infrastructure and security advice to Fortune 1000 companies. The company’s data center facility in Houston, Texas is a Tier IV design, the highest level of certification available, and provides customers with access to mission-critical systems and data at all times.

The Latest

Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...

44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

77% of leaders say their teams need AI skills urgently. 64% say their organization plans to train current employees rather than hire new ones. So far, so reasonable. The part that surprised me is who's been put in charge: 34% of those leaders say IT and engineering own the AI skills mandate. Learning and Development or HR own it at 7% of organizations. That's roughly five-to-one in favor of the people who understand the tools, over the people whose actual job is teaching adults how to learn new ones ...

In the ever-evolving digital landscape, enterprises are increasingly focused on enhancing their observability stacks to gain deeper insights into their IT environments. Observability has become a cornerstone of modern IT operations, enabling organizations to monitor, diagnose, and optimize their systems with unprecedented precision. However, a critical piece of the puzzle often goes unnoticed in this transformation: IBM i ...

CA Technologies Powers StratITsphere’s New Cloud Services and Data Center

CA Technologies announced that StratITsphere, an IT consulting and data center services provider, will use CA Technologies cloud computing, energy management and service assurance solutions as the backbone for Nimbus, its new package of cloud-based services, as well as other offerings.

Nimbus was developed with and will be delivered on the CA AppLogic cloud platform and will include virtual private data centers (VPDC) with full failover and disaster recovery capabilities. StratITsphere’s Fortune 1000 customers will be able to access dynamically provisioned and secure cloud services, providing agile and highly available infrastructures with a lower capital investment than traditional computing solutions.

StratITsphere plans to use CA ecoSoftware to enable customers in its co-location facility to help lower their electricity costs and to help make the entire facility more energy efficient. By being able to see energy consumption patterns at the device and system levels, StratITsphere can make adjustments to help improve its power usage effectiveness (PUE) metric, a measure of how efficiently the facility uses electricity. CA ecoSoftware also allows StratITsphere to provide automatic billing to customers based on real energy use, rather than relying on error-prone estimates or time-consuming manual data collection.

To proactively manage the performance and availability of the service delivery infrastructure, and to monitor the composition and behavior of network traffic in real-time, StratITsphere relies on CA Technologies Service Assurance portfolio, including CA eHealth Performance Manager, CA Spectrum Infrastructure Manager and CA NetQoS ReporterAnalyzer software.

StratITsphere provides data center services and IT infrastructure and security advice to Fortune 1000 companies. The company’s data center facility in Houston, Texas is a Tier IV design, the highest level of certification available, and provides customers with access to mission-critical systems and data at all times.

The Latest

Pilots are everywhere, stakeholders are seeking results, businesses are pushing for new tools, and IT teams are being asked to make AI secure, reliable, and useful at scale. But as organizations move from testing AI to operationalizing it, many are discovering that the biggest barrier is not the model, the use case, or even the budget. It is the file data foundation within ...

Fast or cheap? For most of my career in engineering, speed and quality sat on opposite ends of a seesaw. The "OR" in "fast or cheap" was non-negotiable. It was expected that pushing for faster releases meant that something in quality would give way. Tightening quality controls meant the schedule slipped. Every engineering leader I know has lived some version of that tradeoff ... The seesaw is starting to level out ...

I have been building enterprise software for more than 20 years ... One thing stays true across all of it: You do not find out your foundation is wrong during the crisis. You find out when the debt comes due. For a lot of organizations, that bill is arriving now. New research ... puts hard numbers on something practitioners have been sensing for a while. The telemetry problem isn't coming. It's already here ...

The rapid growth of AI workloads is pushing traditional log management approaches to their limits, according to The State of Log Management 2026 report from Dynatrace. Modern logs have become critical to understanding, validating, and securing AI-driven decisions, helping organizations ensure reliability, compliance, and performance at scale. However, the volume and complexity of AI telemetry are overwhelming legacy tools ...

For years, secure connectivity has relied on a familiar pattern: route traffic back to centralized gateways, inspect it, and then allow access. This model worked when applications lived in a handful of data centers and users were largely confined to offices. That model is now under strain. Applications are distributed across clouds, users connect from everywhere, and real-time workloads demand performance that centralized inspection points struggle to deliver. As traffic volumes grow and latency expectations shrink, routing everything through a small number of control points has become both a performance bottleneck and a resilience risk. The future of secure connectivity requires a different approach ...

The AI experimentation phase is over, and the private cloud is where enterprise AI workloads are being deployed for security and scale, according to Private Cloud Outlook 2026, a new report from Broadcom ... 2026 marks an acceleration into a full AI tipping point. The shift is being shaped by three forces — costs, complexity, and control — that public cloud environments are increasingly failing to address for production AI at scale. Key findings from the report include ...

44% of organizations have reported an outage in the past year tied to suppressed or ignored alerts, and 78% had at least one incident where no alert was fired at all ... Engineers learned about failures from customers. That gap between what our tools report and what our customers experience is the problem DevOps teams have been quietly solving with GenAI tooling, even as most enterprises continue to run their NOCs on manual alert triage ...

Cloud outages are usually described as technical failures. When a service goes down, a dependency breaks, or a region has issues, the focus immediately shifts to infrastructure. But if you look closely at how these incidents actually unfold, the root cause is rarely the technology itself. It is almost always tied to decisions made earlier, during design, implementation, or day-to-day operations. The system behaves the way it was built. The real question is how it was built ...

77% of leaders say their teams need AI skills urgently. 64% say their organization plans to train current employees rather than hire new ones. So far, so reasonable. The part that surprised me is who's been put in charge: 34% of those leaders say IT and engineering own the AI skills mandate. Learning and Development or HR own it at 7% of organizations. That's roughly five-to-one in favor of the people who understand the tools, over the people whose actual job is teaching adults how to learn new ones ...

In the ever-evolving digital landscape, enterprises are increasingly focused on enhancing their observability stacks to gain deeper insights into their IT environments. Observability has become a cornerstone of modern IT operations, enabling organizations to monitor, diagnose, and optimize their systems with unprecedented precision. However, a critical piece of the puzzle often goes unnoticed in this transformation: IBM i ...