2025 Cloud and FinOps Predictions - Part 1

As part of APMdigest's 2025 Predictions Series, industry experts offer predictions on how Cloud, FinOps and related technologies will evolve and impact business in 2025.
 

CLOUD: ESSENTIAL INFRASTRUCTURE

In 2025, the cloud will evolve into a core platform prioritizing simplicity, security, and compliance. By integrating AI-driven insights and automation, cloud environments will empower diverse teams — not just developers — to drive efficient, secure, and compliant workflows. This growth will solidify the cloud as essential infrastructure, supporting seamless digital operations and driving strategic business growth. 
Gab Menachem
VP ITOM, ServiceNow

AI DRIVES CLOUD UTILIZATION

AI will significantly increase cloud utilization in 2025. The latest advancements in AI hardware, which come at a premium, require the use of hundreds of GPUs for model training. In addition, the demand for these GPUs has led them to be sold out for the next 12 months. If organizations are looking to train their own model or operationalize it with inference, there may be no other choice than to purchase it as a service from a cloud provider. As an alternative, they can utilize existing models and managed services from the cloud providers to make the deployment and management of a model simpler. Regardless of the method, AI is cost prohibitive as a DIY venture. The power of the cloud will enable customers to use the AI services and tools at the scale and flexibility that they need. Purchasing it as a service allows more organizations to access the technology and innovate, benefiting us all.
Jason Bright
Product Marketing Manager at Hyland

AI-DRIVEN AUTOMATION

AI in the cloud moves from simply "spotting things" to actually "doing things." Beyond data crunching and spitting out insights, AI-driven automation that turns insights into actions, automatically optimizes cloud performance and spend, and reduces the insight to action gap becomes the new table stakes by the end of 2025. Agentic AI gains rapid adoption and is integrated into workflows to accelerate AI impact such that the industry begins seeing "near-realtime FinOps" for the first time. And AI begins playing a bigger role in spotting anomalies and making decisions at moments of truth at the edge as organizations continue finding ways to shift left.
Kyle Campos
Chief Technology & Product Officer at CloudBolt

HYBRID CLOUD

In 2025, we will see an even greater push toward diversified IT infrastructure. It's no longer about being all on-prem, all-cloud, or all-SaaS — companies are finding a need to balance across these platforms to drive efficiency and better manage costs. We've had enough time with these technologies to know what works where, and we're getting smarter about budgeting for them.
Chrystal Taylor
Evangelist, SolarWinds

AI DRIVES HYBRID CLOUD

Thanks to AI, Hybrid Cloud is Here to Stay: Only about two years ago, it was a very cloud-only environment with some companies ready to get rid of their data centers altogether. The reality is, many businesses still have over half their data living outside of the cloud, and it will likely stay there based on what makes the most sense for their use case (in high stakes environments such as healthcare, for example). Therefore, hybrid cloud strategies are alive and well, especially with the proliferation of AI. Organizations can maintain on-premises GPU infrastructure for consistent, high-priority workloads while using cloud GPUs for burst capacity. This avoids complete lock-in to cloud providers' premium GPU pricing and grants better control over total cost of ownership for expensive AI infrastructure.
Haseeb Budhani
Co-Founder and CEO, Rafay

MULTI-CLOUD

In 2025, enterprises that initially made big bets on a single cloud hyperscaler will begin to diversify by introducing secondary providers, adding competition, and unlocking capabilities their primary provider may not offer. While the major cloud players still dominate enterprise spend, there will be a noticeable shift toward multi-cloud strategies as businesses seek to complement their existing investments.
Steve Ellis
Division President, Cloud Business Unit, Amdocs

AI DRIVES MULTI-CLOUD

I expect, due to AI-focused development, we'll see engineering and IT teams increasingly using more than one public cloud solution (AWS, Azure, etc.). By adopting this type of multi-cloud approach as part of a DevOps strategy, you can train your distributed AI workloads and models across multiple environments. For instance, there could be a benefit to using Azure's computing power to train one AI model and AWS for another. Or you could keep your legacy cloud workloads on one public cloud and then your AI workloads on a separate public cloud. This approach enables development teams to tailor their cloud environment to the needs of each AI application.
Faiz Khan
CEO of Wanclouds

MULTI-CLOUD CHAOS

The Forecast Calls for Multi-cloud Chaos: By 2025, multi-cloud environments will become the "new normal," but with a twist — organizations will be navigating clouds with as much finesse as a game of Twister. A recent Gartner report found that by 2024, over 75% of midsize and large organizations will have adopted a multicloud or hybrid IT strategy, but managing these clouds will resemble herding digital cats.
Ravi Ithal
GVP and CTO, Proofpoint DSPM

ALTERNATIVE CLOUD PROVIDERS

AI - The Catalyst For The Alt-cloud: AI will become smarter and more dependable in the next year, but businesses will require agile, scalable, open, composable ecosystems to unlock its full potential – something Big Tech's cloud titans aren't capable of delivering. Enterprises will increasingly look to alternative cloud providers to supply the kind of infrastructure that supports the rapid deployment of new AI models without skyrocketing overheads. These open ecosystems will supplant the monolithic, rigid, and costly single-vendor paradigm that has disproportionately favored enterprises operating closer to the traditional tech heartlands, leveling the playing field for AI innovation across all regions of the world.
JJ Kardwell
CEO, Vultr

DISTRIBUTED CLOUD

Enterprises Rethink Cloud Choices Amid New Regulations: 
As businesses seek greater flexibility and control, 2025 will see a shift away from legacy cloud providers toward more adaptable, distributed cloud solutions. Cloud concentration risk, privacy laws and data management regulations will be the primary drivers. Distributed cloud will enable companies to move compute and data closer to users and improve performance while staying responsive to compliance needs as regulations evolve. The focus will be on finding cloud solutions that balance innovation with agility.
Ari Weil
VP of Product Marketing, Akamai

Go to: 2025 Cloud and FinOps Predictions - Part 2

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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 ...

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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 ...

Why ITOps Need Right-Sized AI, Not Bigger Models

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 ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

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 ...

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2025 Cloud and FinOps Predictions - Part 1

As part of APMdigest's 2025 Predictions Series, industry experts offer predictions on how Cloud, FinOps and related technologies will evolve and impact business in 2025.
 

CLOUD: ESSENTIAL INFRASTRUCTURE

In 2025, the cloud will evolve into a core platform prioritizing simplicity, security, and compliance. By integrating AI-driven insights and automation, cloud environments will empower diverse teams — not just developers — to drive efficient, secure, and compliant workflows. This growth will solidify the cloud as essential infrastructure, supporting seamless digital operations and driving strategic business growth. 
Gab Menachem
VP ITOM, ServiceNow

AI DRIVES CLOUD UTILIZATION

AI will significantly increase cloud utilization in 2025. The latest advancements in AI hardware, which come at a premium, require the use of hundreds of GPUs for model training. In addition, the demand for these GPUs has led them to be sold out for the next 12 months. If organizations are looking to train their own model or operationalize it with inference, there may be no other choice than to purchase it as a service from a cloud provider. As an alternative, they can utilize existing models and managed services from the cloud providers to make the deployment and management of a model simpler. Regardless of the method, AI is cost prohibitive as a DIY venture. The power of the cloud will enable customers to use the AI services and tools at the scale and flexibility that they need. Purchasing it as a service allows more organizations to access the technology and innovate, benefiting us all.
Jason Bright
Product Marketing Manager at Hyland

AI-DRIVEN AUTOMATION

AI in the cloud moves from simply "spotting things" to actually "doing things." Beyond data crunching and spitting out insights, AI-driven automation that turns insights into actions, automatically optimizes cloud performance and spend, and reduces the insight to action gap becomes the new table stakes by the end of 2025. Agentic AI gains rapid adoption and is integrated into workflows to accelerate AI impact such that the industry begins seeing "near-realtime FinOps" for the first time. And AI begins playing a bigger role in spotting anomalies and making decisions at moments of truth at the edge as organizations continue finding ways to shift left.
Kyle Campos
Chief Technology & Product Officer at CloudBolt

HYBRID CLOUD

In 2025, we will see an even greater push toward diversified IT infrastructure. It's no longer about being all on-prem, all-cloud, or all-SaaS — companies are finding a need to balance across these platforms to drive efficiency and better manage costs. We've had enough time with these technologies to know what works where, and we're getting smarter about budgeting for them.
Chrystal Taylor
Evangelist, SolarWinds

AI DRIVES HYBRID CLOUD

Thanks to AI, Hybrid Cloud is Here to Stay: Only about two years ago, it was a very cloud-only environment with some companies ready to get rid of their data centers altogether. The reality is, many businesses still have over half their data living outside of the cloud, and it will likely stay there based on what makes the most sense for their use case (in high stakes environments such as healthcare, for example). Therefore, hybrid cloud strategies are alive and well, especially with the proliferation of AI. Organizations can maintain on-premises GPU infrastructure for consistent, high-priority workloads while using cloud GPUs for burst capacity. This avoids complete lock-in to cloud providers' premium GPU pricing and grants better control over total cost of ownership for expensive AI infrastructure.
Haseeb Budhani
Co-Founder and CEO, Rafay

MULTI-CLOUD

In 2025, enterprises that initially made big bets on a single cloud hyperscaler will begin to diversify by introducing secondary providers, adding competition, and unlocking capabilities their primary provider may not offer. While the major cloud players still dominate enterprise spend, there will be a noticeable shift toward multi-cloud strategies as businesses seek to complement their existing investments.
Steve Ellis
Division President, Cloud Business Unit, Amdocs

AI DRIVES MULTI-CLOUD

I expect, due to AI-focused development, we'll see engineering and IT teams increasingly using more than one public cloud solution (AWS, Azure, etc.). By adopting this type of multi-cloud approach as part of a DevOps strategy, you can train your distributed AI workloads and models across multiple environments. For instance, there could be a benefit to using Azure's computing power to train one AI model and AWS for another. Or you could keep your legacy cloud workloads on one public cloud and then your AI workloads on a separate public cloud. This approach enables development teams to tailor their cloud environment to the needs of each AI application.
Faiz Khan
CEO of Wanclouds

MULTI-CLOUD CHAOS

The Forecast Calls for Multi-cloud Chaos: By 2025, multi-cloud environments will become the "new normal," but with a twist — organizations will be navigating clouds with as much finesse as a game of Twister. A recent Gartner report found that by 2024, over 75% of midsize and large organizations will have adopted a multicloud or hybrid IT strategy, but managing these clouds will resemble herding digital cats.
Ravi Ithal
GVP and CTO, Proofpoint DSPM

ALTERNATIVE CLOUD PROVIDERS

AI - The Catalyst For The Alt-cloud: AI will become smarter and more dependable in the next year, but businesses will require agile, scalable, open, composable ecosystems to unlock its full potential – something Big Tech's cloud titans aren't capable of delivering. Enterprises will increasingly look to alternative cloud providers to supply the kind of infrastructure that supports the rapid deployment of new AI models without skyrocketing overheads. These open ecosystems will supplant the monolithic, rigid, and costly single-vendor paradigm that has disproportionately favored enterprises operating closer to the traditional tech heartlands, leveling the playing field for AI innovation across all regions of the world.
JJ Kardwell
CEO, Vultr

DISTRIBUTED CLOUD

Enterprises Rethink Cloud Choices Amid New Regulations: 
As businesses seek greater flexibility and control, 2025 will see a shift away from legacy cloud providers toward more adaptable, distributed cloud solutions. Cloud concentration risk, privacy laws and data management regulations will be the primary drivers. Distributed cloud will enable companies to move compute and data closer to users and improve performance while staying responsive to compliance needs as regulations evolve. The focus will be on finding cloud solutions that balance innovation with agility.
Ari Weil
VP of Product Marketing, Akamai

Go to: 2025 Cloud and FinOps Predictions - Part 2

Related Links

Hot Topics

The Latest

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

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 ...

AI Deepfakes: Rethinking Trust in the Workplace

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 ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

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 ...

Why ITOps Need Right-Sized AI, Not Bigger Models

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 ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

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 ...

5 Takeaways from the Observability Forecast for Media and Entertainment

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 ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

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 ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

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

Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

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 ...

5 Security Principles Every Entrepreneur Should Apply to Leadership

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...