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Infrastructure Management - Do You Still Care?

A few good reasons why you should ...

Infrastructure Management is so 1990s. Everyone has it. Could there be anything interesting left to say? Yes -- that it is more critical than ever. It may still be just the plumbing but the demands on it are only growing and yesterday’s point solutions won't do the job.

In a June 2011 article in CIOInsight, interestingly titled, “IT Investment Trends: Infrastructure Back in the Mix” they note, “CIO Insight’s latest IT Investment Trends study shows renewed interest in the fundamentals of the IT infrastructure. This is refreshing amid today’s ethereal talk about clouds and virtual machines.”

It is, in fact, those ethereal technologies that are driving Infrastructure Management solutions to grow up and meet the demands placed on them by combining integration, automation and intelligent analytics. These new, unified infrastructure management solutions can step up to the requirements for agility and the ability to handle the complexity that new technologies and higher expectations inflict on all organizations - enterprises, government agencies and service providers alike.

Here are four reasons why - in 2012 - you should still care:

Too big to fail infrastructures are the backbone of an organization’s bottom line. While the “infrastructure” was once a code word for “the network” and the applications running over it only impacted employees, infrastructures are now a growing conglomeration of the network, systems, databases and applications that affect customers and employees alike, with direct impact on your bottom line.

Managing the infrastructure as a whole is imperative. Attempting to manage with a mix of point products becomes part of the problem rather than the solution. Effort by IT staff or service network operators to manually correlate events from silo-focused management products and track impact to individuals and services is a practice that simply doesn’t scale. Integrated and unified infrastructure management solutions automatically correlate events between silos, identify root cause and track impact to individuals and business services, letting IT staff and service network operators practice rapid remediation. Performance and trend analysis even lets them get ahead of developing issues to avoid some problems altogether.

Voice and video are rapidly gaining acceptance into the infrastructure “club.” Once outside the data network, they now sit well within an organization’s infrastructure, even while requiring essentially different service qualities than standard IP data traffic. Isn’t that why we have Quality of Service (QoS) capabilities? However, manually creating QoS service classes and hoping they have the desired effect is risky without a clear view into traffic flows and performance. With good visibility, QoS classes can be fine tuned to support both business critical applications and the delay-sensitive voice and video services.

Virtualization is the perfect technology to take an infrastructure running close to the edge from bad to worse. If your IT staff is struggling to manually track systems capacity and utilization, adding virtualization will create the tipping point. With automated tools for infrastructure management they can keep up with the volume of workload and application movement while holding down capital costs, data center expansion and staff stress.

Private clouds bring many technologies together (server, network and storage virtualization, high availability, automation and self-service) to optimize an organization’s assets and provide a highly responsive infrastructure service environment, much like a data center on steroids. The private cloud is expected to scale to absorb utilization peaks and protect against outages and degradation, thereby making it a prime consumer of unified infrastructure management. Without the ability to manage the scope and complexity of the private cloud, it can become a single point of multiple, potential failures.

With these technologies resetting the bar for organizational competence and competitiveness, it is a good time to review your infrastructure management solution. Is it unified, managing performance and available for physical and virtual systems, the network, applications and databases and giving you a single view? Can it provide visibility into traffic flows so voice and video can safely co-exist in your infrastructure? Can it scale as your organization grows? Time to reconsider.

ABOUT Pam Snaith

Pam Snaith joined CA Technologies in 2005 as part of the Concord Communications acquisition. In her role in Product Marketing she is focused on solutions that drive business Service Assurance. Snaith has broad experience in the networking industry, from software engineering to product management and marketing for voice and data products at institutions and companies including the Federal Reserve Bank, Digital Equipment Corporation, Xyplex Networks, Lucent Technologies and Avaya. She has published magazine articles and numerous white papers. Snaith earned a B.A. from New York University and completed additional coursework at Cornell Medical College.

Related Links:

www.ca.com

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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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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

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 ...

Infrastructure Management - Do You Still Care?

A few good reasons why you should ...

Infrastructure Management is so 1990s. Everyone has it. Could there be anything interesting left to say? Yes -- that it is more critical than ever. It may still be just the plumbing but the demands on it are only growing and yesterday’s point solutions won't do the job.

In a June 2011 article in CIOInsight, interestingly titled, “IT Investment Trends: Infrastructure Back in the Mix” they note, “CIO Insight’s latest IT Investment Trends study shows renewed interest in the fundamentals of the IT infrastructure. This is refreshing amid today’s ethereal talk about clouds and virtual machines.”

It is, in fact, those ethereal technologies that are driving Infrastructure Management solutions to grow up and meet the demands placed on them by combining integration, automation and intelligent analytics. These new, unified infrastructure management solutions can step up to the requirements for agility and the ability to handle the complexity that new technologies and higher expectations inflict on all organizations - enterprises, government agencies and service providers alike.

Here are four reasons why - in 2012 - you should still care:

Too big to fail infrastructures are the backbone of an organization’s bottom line. While the “infrastructure” was once a code word for “the network” and the applications running over it only impacted employees, infrastructures are now a growing conglomeration of the network, systems, databases and applications that affect customers and employees alike, with direct impact on your bottom line.

Managing the infrastructure as a whole is imperative. Attempting to manage with a mix of point products becomes part of the problem rather than the solution. Effort by IT staff or service network operators to manually correlate events from silo-focused management products and track impact to individuals and services is a practice that simply doesn’t scale. Integrated and unified infrastructure management solutions automatically correlate events between silos, identify root cause and track impact to individuals and business services, letting IT staff and service network operators practice rapid remediation. Performance and trend analysis even lets them get ahead of developing issues to avoid some problems altogether.

Voice and video are rapidly gaining acceptance into the infrastructure “club.” Once outside the data network, they now sit well within an organization’s infrastructure, even while requiring essentially different service qualities than standard IP data traffic. Isn’t that why we have Quality of Service (QoS) capabilities? However, manually creating QoS service classes and hoping they have the desired effect is risky without a clear view into traffic flows and performance. With good visibility, QoS classes can be fine tuned to support both business critical applications and the delay-sensitive voice and video services.

Virtualization is the perfect technology to take an infrastructure running close to the edge from bad to worse. If your IT staff is struggling to manually track systems capacity and utilization, adding virtualization will create the tipping point. With automated tools for infrastructure management they can keep up with the volume of workload and application movement while holding down capital costs, data center expansion and staff stress.

Private clouds bring many technologies together (server, network and storage virtualization, high availability, automation and self-service) to optimize an organization’s assets and provide a highly responsive infrastructure service environment, much like a data center on steroids. The private cloud is expected to scale to absorb utilization peaks and protect against outages and degradation, thereby making it a prime consumer of unified infrastructure management. Without the ability to manage the scope and complexity of the private cloud, it can become a single point of multiple, potential failures.

With these technologies resetting the bar for organizational competence and competitiveness, it is a good time to review your infrastructure management solution. Is it unified, managing performance and available for physical and virtual systems, the network, applications and databases and giving you a single view? Can it provide visibility into traffic flows so voice and video can safely co-exist in your infrastructure? Can it scale as your organization grows? Time to reconsider.

ABOUT Pam Snaith

Pam Snaith joined CA Technologies in 2005 as part of the Concord Communications acquisition. In her role in Product Marketing she is focused on solutions that drive business Service Assurance. Snaith has broad experience in the networking industry, from software engineering to product management and marketing for voice and data products at institutions and companies including the Federal Reserve Bank, Digital Equipment Corporation, Xyplex Networks, Lucent Technologies and Avaya. She has published magazine articles and numerous white papers. Snaith earned a B.A. from New York University and completed additional coursework at Cornell Medical College.

Related Links:

www.ca.com

Hot Topics

The Latest

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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

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 ...