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Hybrid Management is Key Challenge

Hybrid IT is becoming a standard enterprise model, but there’s no single playbook to get there, according to a new report by Dimension Data entitled The Success Factors for Managing Hybrid IT.

Looking at the top motivators to move to hybrid IT by country, Hong Kong, UK and US companies highlighted end-user demand most often, while respondents in France, Singapore and South Africa most often noted cost. Malaysian firms listed hiring challenges, and German firms mentioned limited data center capacity as the most common motivating factors.

The report also shows that management of the hybrid IT environment (41 percent of respondents) is one of the top three challenges in deployment.

Dimension Data Group CEO, Jason Goodall said: “With data and processes shifting across multiple cloud and non-cloud environments, a new approach to management is called for. IT managers are under tremendous pressure to seek new ways to manage and secure multiple IT environments in an effective manner. Automation is important because it helps reduce the operating costs, as well as the pain caused by the growing complexity of business processes and management tasks. It is simply no longer appropriate or cost-effective for these tasks to be done manually.”

Data migration was another common deployment challenge, with 44 percent of the respondents saying they found it challenging to determine which option is the best for a particular workload and to migrate workloads to new locations.

While 38 percent of enterprises surveyed claimed that they use automation to accelerate application migration, 48 percent said that migration at their company is manual and labor-intensive or that they use in-house resources. Today’s application and data migration remains complex and expensive for most organizations.

According to Kelly Morgan, Research VP, Services at 451 Research, managed services have become a key component of service delivery across a range of infrastructure and application products.

“Service providers that can offer a comprehensive portfolio of managed services across the broadest set of infrastructure options are well positioned to meet the full set of enterprise cloud requirements,” said Morgan.

Other highlights in the report include:

■ Despite concerns about security, compliance, and integration issues, organizations are embracing next-generation networking technologies such as SDN and network functions virtualization.

■ Enterprises are using innovative/emerging technologies such as containers, big data solutions and software-defined networking (SDN) in productions scenarios.

■ Enterprises are spending a significant portion of their IT budgets with third-party service providers on managed and professional services for various reasons – to lower cost, to free IT staff to focus on other projects, to improve security, and to provide specialized technical expertise. The research reveals that 41 percent of organizations work with multiple vendors and manage them themselves, and another 37 percent work with a single vendor that can offer a broad range of products and services which it builds and manages.

The research involved 1,500 IT decision makers from multiple vertical industries across the US, Europe, Asia-Pacific and South Africa.

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Hybrid Management is Key Challenge

Hybrid IT is becoming a standard enterprise model, but there’s no single playbook to get there, according to a new report by Dimension Data entitled The Success Factors for Managing Hybrid IT.

Looking at the top motivators to move to hybrid IT by country, Hong Kong, UK and US companies highlighted end-user demand most often, while respondents in France, Singapore and South Africa most often noted cost. Malaysian firms listed hiring challenges, and German firms mentioned limited data center capacity as the most common motivating factors.

The report also shows that management of the hybrid IT environment (41 percent of respondents) is one of the top three challenges in deployment.

Dimension Data Group CEO, Jason Goodall said: “With data and processes shifting across multiple cloud and non-cloud environments, a new approach to management is called for. IT managers are under tremendous pressure to seek new ways to manage and secure multiple IT environments in an effective manner. Automation is important because it helps reduce the operating costs, as well as the pain caused by the growing complexity of business processes and management tasks. It is simply no longer appropriate or cost-effective for these tasks to be done manually.”

Data migration was another common deployment challenge, with 44 percent of the respondents saying they found it challenging to determine which option is the best for a particular workload and to migrate workloads to new locations.

While 38 percent of enterprises surveyed claimed that they use automation to accelerate application migration, 48 percent said that migration at their company is manual and labor-intensive or that they use in-house resources. Today’s application and data migration remains complex and expensive for most organizations.

According to Kelly Morgan, Research VP, Services at 451 Research, managed services have become a key component of service delivery across a range of infrastructure and application products.

“Service providers that can offer a comprehensive portfolio of managed services across the broadest set of infrastructure options are well positioned to meet the full set of enterprise cloud requirements,” said Morgan.

Other highlights in the report include:

■ Despite concerns about security, compliance, and integration issues, organizations are embracing next-generation networking technologies such as SDN and network functions virtualization.

■ Enterprises are using innovative/emerging technologies such as containers, big data solutions and software-defined networking (SDN) in productions scenarios.

■ Enterprises are spending a significant portion of their IT budgets with third-party service providers on managed and professional services for various reasons – to lower cost, to free IT staff to focus on other projects, to improve security, and to provide specialized technical expertise. The research reveals that 41 percent of organizations work with multiple vendors and manage them themselves, and another 37 percent work with a single vendor that can offer a broad range of products and services which it builds and manages.

The research involved 1,500 IT decision makers from multiple vertical industries across the US, Europe, Asia-Pacific and South Africa.

Hot Topics

The Latest

Reliability is no longer proven by uptime alone, according to the The SRE Report 2026 from LogicMonitor. In the AI era, it is experienced through speed, consistency, and user trust, and increasingly judged by business impact. As digital services grow more complex and AI systems move into production, traditional monitoring approaches are struggling to keep pace, increasing the need for AI-first observability that spans applications, infrastructure, and the Internet ...

If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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 ...