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2025 Cloud and FinOps Predictions - Part 2

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. Part 2 covers repatriation and more.

 

REPATRIATION

Most new production workloads are born in the cloud, this will continue. However, in the coming year, there will be an increase in customers who modernized applications in the public cloud, repatriating this data due to cost control. The adoption of cloud infrastructure will continue to grow, but a percentage of organizations will bring services back down to a self-hosted data center.
Simon Taylor
CEO and Co-Founder, HYCU

With rising IT costs driven by increased license fees from major vendors and soaring hyperscaler bills, many organizations are facing budget crises. In 2025, we predict a shift as companies begin moving workloads back from the cloud to on-premises or colocations to reduce operational expenses.
Sascha Giese
Global Tech Evangelist, Observability, SolarWinds

Repatriation is accelerating, but the cloud might respond by 2025, likely through more competitive pricing, and also technical advancements offering greater flexibility and security. We're still heavily moving to the cloud, and repatriation might take a few years to slow down. 
William McKnight
Analyst, GigaOm

MULTI-CLOUD REPATRIATION

Multi-cloud repatriation will persist: Although there is still a movement of enterprises moving from private to public clouds, in 2025 we will see AI adoption drive a wave of simultaneous multi-cloud repatriation. Rising cloud costs, security concerns and resource constraints caused by AI adoption are the main drivers behind this trend and cloud repatriation will emerge as the strategic solution for controlling it.
Karthik Ranganathan
Co-Founder and Co-CEO, Yugabyte

CLOUD REPATRIATION WON'T DELIVER COST SAVINGS

Cloud repatriation won't be the key to cost savings (for most): As budget continues to be a key concern for organizations, one approach to cutting costs people are talking about, but not executing on is organizations moving their workloads from cloud to on-prem, however, that won't be feasible (or strategic) for most. It's true that certain organizations with predictable workloads might benefit from hybrid or on-prem solutions — like large-scale social media networks. However, for most companies, the time, money, resources, and overall complexity of full-scale cloud repatriation won't offset cost. Instead, they should look into implementing a targeted optimization approach — instead of abandoning their cloud infrastructure, they can optimize it for cost, performance, and scalability. This requires a mix of FinOps, leveraging the right tools, and continuous monitoring of infrastructure economics, but teams that lean into this approach will see meaningful cost savings without sacrificing the agility and scalability that drew them to cloud platforms in the first place.
Richard "Richi" Hartmann
Director of Community & Office of the CTO, Grafana Labs

SOVEREIGN CLOUD

All Hail The Sovereign Cloud: In 2025, we're going to see a real push towards sovereign and private clouds. We're already seeing the largest hyperscalers pouring billions of dollars into constructing data centers around the world to offer these capabilities. This rush to build capacity will take a while to come online, in the meantime, demand will skyrocket fueled by a wave of legislation coming predominantly from the EU. Those with flexible, scalable and elastic cloud infrastructure will be able to adopt sovereign or private approaches quickly. Those with monolithic, rigid infrastructure will be putting themselves behind the curve.
Kevin Cochrane
CMO, Vultr

INFRASTRUCTURE-AS-CODE

The adoption of infrastructure-as-code will make multi-cloud deployment strategies more sophisticated, enabling organizations to avoid vendor lock-in and optimize costs. Advanced tooling will remove provider differences, allowing seamless deployment and management across cloud platforms while maintaining consistent security and compliance controls.
Tristan Stahnke
Principal Application Security Consultant, GuidePoint Security

CLOUD-NATIVE ANALYTICS

Scalability and agility demands will push cloud-native analytics to the forefront: By 2025, cloud-native architectures will be the go-to choice for businesses looking to keep pace with the need for agility and scalability. As intelligence-supported decision-making takes center stage across industries, cloud-native analytics will lead the way. Companies are increasingly adopting multi-cloud strategies to maintain flexibility and avoid vendor lock-in, and analytics platforms will need to support seamless interoperability across different cloud providers. Users will look for hyperscale-neutral solutions that integrate effortlessly with major players like AWS, GCP, and Azure, while also handling AI/ML/Generative workloads with ease. Cloud-native is set to become the foundation for analytics in the next phase of business intelligence.
Trevor Schulze
Chief Digital & Information Officer, Alteryx

GREENOPS

GreenOps will grab a greater foothold: Statistics show that the public cloud now has a larger carbon footprint than even the airline industry, and a single public data center uses as much electricity as 50,000 homes. Amid new regulations, particularly in Europe, coupled with consumer pressure, we predict more interest in the concept of GreenOps. Put simply, GreenOps is the practice of minimizing a cloud environment's carbon footprint by efficiently using cloud resources. This can only be done with visibility into an organization's true cloud spend and a deeper understanding of how resources are allocated. Optimizing cloud use to reduce waste will be a key part of this puzzle, leading organizations and individuals to take a closer look at their data usage.
Bill Buckley
SVP of Engineering, CloudZero

Cloud providers will prioritize energy-efficient data centers and sustainable practices: The amount of electricity consumed to power today's data centers is incredible. A Gemini query (Google's generative AI tool) needs nearly 10 times as much electricity to process as a traditional Google search. Large tech brands including IBM, AWS and Google are already looking for ways to reduce the amount of electricity usage through energy-efficient hardware, and green energy sources. Power management software will also rise in popularity. Low-power processors, solid-state drives and energy-efficient cooling systems are cloud features you want to look for in 2025.
Sashank Purighalla
Founder and CEO, BOS Framework

Go to: 2025 Cloud and FinOps Predictions - Part 3

Hot Topics

The Latest

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 ...

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.

2025 Cloud and FinOps Predictions - Part 2

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. Part 2 covers repatriation and more.

 

REPATRIATION

Most new production workloads are born in the cloud, this will continue. However, in the coming year, there will be an increase in customers who modernized applications in the public cloud, repatriating this data due to cost control. The adoption of cloud infrastructure will continue to grow, but a percentage of organizations will bring services back down to a self-hosted data center.
Simon Taylor
CEO and Co-Founder, HYCU

With rising IT costs driven by increased license fees from major vendors and soaring hyperscaler bills, many organizations are facing budget crises. In 2025, we predict a shift as companies begin moving workloads back from the cloud to on-premises or colocations to reduce operational expenses.
Sascha Giese
Global Tech Evangelist, Observability, SolarWinds

Repatriation is accelerating, but the cloud might respond by 2025, likely through more competitive pricing, and also technical advancements offering greater flexibility and security. We're still heavily moving to the cloud, and repatriation might take a few years to slow down. 
William McKnight
Analyst, GigaOm

MULTI-CLOUD REPATRIATION

Multi-cloud repatriation will persist: Although there is still a movement of enterprises moving from private to public clouds, in 2025 we will see AI adoption drive a wave of simultaneous multi-cloud repatriation. Rising cloud costs, security concerns and resource constraints caused by AI adoption are the main drivers behind this trend and cloud repatriation will emerge as the strategic solution for controlling it.
Karthik Ranganathan
Co-Founder and Co-CEO, Yugabyte

CLOUD REPATRIATION WON'T DELIVER COST SAVINGS

Cloud repatriation won't be the key to cost savings (for most): As budget continues to be a key concern for organizations, one approach to cutting costs people are talking about, but not executing on is organizations moving their workloads from cloud to on-prem, however, that won't be feasible (or strategic) for most. It's true that certain organizations with predictable workloads might benefit from hybrid or on-prem solutions — like large-scale social media networks. However, for most companies, the time, money, resources, and overall complexity of full-scale cloud repatriation won't offset cost. Instead, they should look into implementing a targeted optimization approach — instead of abandoning their cloud infrastructure, they can optimize it for cost, performance, and scalability. This requires a mix of FinOps, leveraging the right tools, and continuous monitoring of infrastructure economics, but teams that lean into this approach will see meaningful cost savings without sacrificing the agility and scalability that drew them to cloud platforms in the first place.
Richard "Richi" Hartmann
Director of Community & Office of the CTO, Grafana Labs

SOVEREIGN CLOUD

All Hail The Sovereign Cloud: In 2025, we're going to see a real push towards sovereign and private clouds. We're already seeing the largest hyperscalers pouring billions of dollars into constructing data centers around the world to offer these capabilities. This rush to build capacity will take a while to come online, in the meantime, demand will skyrocket fueled by a wave of legislation coming predominantly from the EU. Those with flexible, scalable and elastic cloud infrastructure will be able to adopt sovereign or private approaches quickly. Those with monolithic, rigid infrastructure will be putting themselves behind the curve.
Kevin Cochrane
CMO, Vultr

INFRASTRUCTURE-AS-CODE

The adoption of infrastructure-as-code will make multi-cloud deployment strategies more sophisticated, enabling organizations to avoid vendor lock-in and optimize costs. Advanced tooling will remove provider differences, allowing seamless deployment and management across cloud platforms while maintaining consistent security and compliance controls.
Tristan Stahnke
Principal Application Security Consultant, GuidePoint Security

CLOUD-NATIVE ANALYTICS

Scalability and agility demands will push cloud-native analytics to the forefront: By 2025, cloud-native architectures will be the go-to choice for businesses looking to keep pace with the need for agility and scalability. As intelligence-supported decision-making takes center stage across industries, cloud-native analytics will lead the way. Companies are increasingly adopting multi-cloud strategies to maintain flexibility and avoid vendor lock-in, and analytics platforms will need to support seamless interoperability across different cloud providers. Users will look for hyperscale-neutral solutions that integrate effortlessly with major players like AWS, GCP, and Azure, while also handling AI/ML/Generative workloads with ease. Cloud-native is set to become the foundation for analytics in the next phase of business intelligence.
Trevor Schulze
Chief Digital & Information Officer, Alteryx

GREENOPS

GreenOps will grab a greater foothold: Statistics show that the public cloud now has a larger carbon footprint than even the airline industry, and a single public data center uses as much electricity as 50,000 homes. Amid new regulations, particularly in Europe, coupled with consumer pressure, we predict more interest in the concept of GreenOps. Put simply, GreenOps is the practice of minimizing a cloud environment's carbon footprint by efficiently using cloud resources. This can only be done with visibility into an organization's true cloud spend and a deeper understanding of how resources are allocated. Optimizing cloud use to reduce waste will be a key part of this puzzle, leading organizations and individuals to take a closer look at their data usage.
Bill Buckley
SVP of Engineering, CloudZero

Cloud providers will prioritize energy-efficient data centers and sustainable practices: The amount of electricity consumed to power today's data centers is incredible. A Gemini query (Google's generative AI tool) needs nearly 10 times as much electricity to process as a traditional Google search. Large tech brands including IBM, AWS and Google are already looking for ways to reduce the amount of electricity usage through energy-efficient hardware, and green energy sources. Power management software will also rise in popularity. Low-power processors, solid-state drives and energy-efficient cooling systems are cloud features you want to look for in 2025.
Sashank Purighalla
Founder and CEO, BOS Framework

Go to: 2025 Cloud and FinOps Predictions - Part 3

Hot Topics

The Latest

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 ...

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.