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Optimizing enterprise cloud infrastructure in a rapidly evolving digital landscape: A renewed approach

By Peter Chambers, Managing Director (APAC), AMD | Friday, July 11, 2025, 2:39 PM Asia/Singapore

Optimizing enterprise cloud infrastructure in a rapidly evolving digital landscape: A renewed approach

Explore practical steps for aligning cloud infrastructure with business needs, supporting efficiency, security, and sustainability in enterprise environments.

Enterprise cloud demands have evolved beyond the early drivers of adoption. Now, more than ever, businesses need to be prepared to scale at a moment’s notice.

At the same time, cloud workloads are becoming increasingly specialized, requiring optimized computing solutions to fully harness cloud-native architectures and frameworks.

Yet, not all modernization strategies lead to the same destination. Recent compute and workload trends highlight the importance of right-sizing cloud solutions.

How can enterprises ensure that their infrastructure is optimized for their specific business needs and workload requirements?

Rethinking cloud optimization
Without a cloud-optimized infrastructure, organizations risk losing operational advantages that could reduce the benefits of cloud-native adoption.

In addition, running AI workloads at scale without an optimized cloud infrastructure may lead to unnecessary energy consumption, increasing both operational costs and environmental impact. This inefficiency can strain financial resources and affect corporate sustainability goals.

Beyond performance gains, security is another critical consideration when selecting cloud-optimized hardware that is sometimes underappreciated. This is particularly important as organizations in the region face intensified cyber risks. Modern cloud infrastructure can incorporate advanced security features, such as confidential computing. These technologies can help ensure that sensitive data remains encrypted while in use, reducing the risk of physical memory attacks or virtual threats in hyperconverged infrastructure environments.

A cloud optimization checklist for 2025
As industries move forward with the adoption and deployment of AI technologies, IT leaders should ensure that their cloud infrastructure can support compute-intensive workloads while balancing cost, security, and efficiency considerations. While each organization’s computing needs are unique, IT teams embarking on hardware modernization may consider the following;

  • Performance: Are your cloud instances equipped for the level of compute performance your business requires? Cloud infrastructure should support a range of workloads, from web front-end applications to in-memory analytics and heavy transactional processing.
  • Cost and efficiency:  Can you reduce your cloud footprint by running the same workloads on fewer servers? Prioritizing instances with high compute density allows businesses to run more VMs or containers per server, which can lead to cost and energy efficiency benefits.
  • Security: Does your cloud instance provide the level of data protection you require? Confidential computing can help mitigate security risks by protecting data in use, reducing vulnerabilities in virtualized environments.
  • Ecosystem: Selecting cloud solutions based on widely supported standards can simplify environments, making it easier to develop, maintain, and migrate applications with minimal disruption.

Unseen optimization, tangible impact
For IT decision-makers, understanding the cost implications of each “unit of work” is important when selecting cloud instances. Traditional infrastructure may force enterprises to choose between overprovisioning resources — leading to unnecessary expenses —or under provisioning, which can cause performance bottlenecks.

Cloud-optimized hardware can help by enabling businesses to achieve more with fewer resources while maintaining high levels of performance, security, and efficiency.

It is also important to note that not all cloud offerings are powered by the same class of technologies, and this difference may become more apparent as AI workloads continue to require more compute, memory, and speed. For example, some cloud providers’ latest bare metal instances reportedly deliver higher compute and memory, and greater network bandwidth, while other providers’ new virtual machines can deliver increased throughput per vCPU, according publicly available benchmarks, which should be independently evaluated for relevance and accuracy.

Ultimately, cloud optimization should not be regarded as a destination, but an ongoing journey.

As cloud technologies continue to evolve, enterprises that prioritize modernization are more likely to benefit from scalability, improved sustainability, and a resilient digital foundation for future innovation.

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