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CA Technologies Enhances Management Solution for AWS

CA Technologies is offering enhanced management and governance capabilities powered by Amazon Web Services (AWS).

Enterprise customers rely on CA Technologies solutions — including CA Automation Suite for Clouds, CA Application Performance Management, CA Nimsoft Cloud Monitor and CA ARCserve — to manage, monitor and protect applications and services running on AWS.

At the AWS re: Invent customer and partner conference in Las Vegas, CA Technologies unveiled solutions developed on AWS within CA Automation Suite for Clouds. With this new integration, customers can streamline and govern the provisioning of AWS services, allowing them to rapidly move workloads to the cloud. This enables customers to realize even faster time to value for cloud deployments and greater agility as their resource needs change.

“While enterprises are moving computing resources to third-party cloud service providers to give them increased flexibility, scalability and responsiveness in meeting rapidly changing business demands; CIOs have been slower to consider cloud environments for their business-critical applications because of perceived concerns about the ability to manage or govern those resources,” said Roger Pilc, general manager, Industries, Solutions & Alliances, CA Technologies. “With our offerings developed on AWS, we’re helping to remove some of those barriers, giving enterprises the management, monitoring and governance capabilities they are accustomed to using in their on-premise systems and cloud environments.”

“As we work closely with our enterprise customers, we understand that they are looking for a wide range of options to manage and govern their applications, services and resources on AWS,” said Terry Wise, Head of Worldwide Partner Ecosystem, Amazon Web Services. “Many enterprise customers already use CA Technologies solutions on premise, and by enabling these customers to extend these capabilities to AWS, enterprises are able to deploy critical workloads in the cloud while maintaining similar operational and governance frameworks that they do on premise.”

Additional features of CA Automation Suite for Clouds Powered by Amazon Web Services include:

• Enterprise Lifecycle Management of AWS Services
- Pre-designed workflows and approvals for automated self-service delivery of infrastructure and application services within the AWS Cloud

• Governance and Administration
- Configurable processes to allow finance, compliance and configuration management for customers to establish approval and audit trails

• Holistic Portfolio Support
- Application performance management to deliver quality of experience for critical business services
- Data management for recovery and availability of data

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 ...

CA Technologies Enhances Management Solution for AWS

CA Technologies is offering enhanced management and governance capabilities powered by Amazon Web Services (AWS).

Enterprise customers rely on CA Technologies solutions — including CA Automation Suite for Clouds, CA Application Performance Management, CA Nimsoft Cloud Monitor and CA ARCserve — to manage, monitor and protect applications and services running on AWS.

At the AWS re: Invent customer and partner conference in Las Vegas, CA Technologies unveiled solutions developed on AWS within CA Automation Suite for Clouds. With this new integration, customers can streamline and govern the provisioning of AWS services, allowing them to rapidly move workloads to the cloud. This enables customers to realize even faster time to value for cloud deployments and greater agility as their resource needs change.

“While enterprises are moving computing resources to third-party cloud service providers to give them increased flexibility, scalability and responsiveness in meeting rapidly changing business demands; CIOs have been slower to consider cloud environments for their business-critical applications because of perceived concerns about the ability to manage or govern those resources,” said Roger Pilc, general manager, Industries, Solutions & Alliances, CA Technologies. “With our offerings developed on AWS, we’re helping to remove some of those barriers, giving enterprises the management, monitoring and governance capabilities they are accustomed to using in their on-premise systems and cloud environments.”

“As we work closely with our enterprise customers, we understand that they are looking for a wide range of options to manage and govern their applications, services and resources on AWS,” said Terry Wise, Head of Worldwide Partner Ecosystem, Amazon Web Services. “Many enterprise customers already use CA Technologies solutions on premise, and by enabling these customers to extend these capabilities to AWS, enterprises are able to deploy critical workloads in the cloud while maintaining similar operational and governance frameworks that they do on premise.”

Additional features of CA Automation Suite for Clouds Powered by Amazon Web Services include:

• Enterprise Lifecycle Management of AWS Services
- Pre-designed workflows and approvals for automated self-service delivery of infrastructure and application services within the AWS Cloud

• Governance and Administration
- Configurable processes to allow finance, compliance and configuration management for customers to establish approval and audit trails

• Holistic Portfolio Support
- Application performance management to deliver quality of experience for critical business services
- Data management for recovery and availability of data

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 ...