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Balancing the Rising Costs of Public Cloud

Ahsan Siddiqui
Arcserve

The spiraling cost of energy is forcing public cloud providers to raise their prices significantly. A recent report by Canalys predicted that public cloud prices will jump by around 20% in the US and more than 30% in Europe in 2023. These steep price increases will test the conventional wisdom that moving to the cloud is a cheap computing alternative.

Indeed, many organizations are already looking at their higher cloud bills and assessing whether it still makes sense to keep moving their infrastructure to the cloud. They do have alternatives.

For instance, for solutions used regularly and persistently, it might make financial sense to bring those in-house rather than host them in the cloud. Owning the infrastructure and managing it yourself could be more cost-effective in the long run.

On the other hand, more complex technologies, and solutions with a high entry cost, such as artificial intelligence, remain good candidates for cloud hosting because they require so much infrastructure and personnel to run in-house. The cloud also remains an excellent option for specific services and solutions where more elasticity is required. This includes technologies that need to be scaled up quickly for a defined period, such as the last few days of each month or quarter when closing the books, then scaled back down.

These are just some issues that organizations should assess when determining if they should keep their data and infrastructure in the cloud. Moving them back on-premises or transitioning to a hybrid infrastructure entails keeping some data and applications in the cloud while returning others to an on-premises infrastructure. From now on, all organizations must take a step back and assess what will work best for them to find the right balance.

The Benefits of Hybrid Cloud

A hybrid cloud has a lot of advantages. Organizations adopting a hybrid cloud approach can more easily control costs and manage their data wherever it resides — on-premises, in a public or private cloud. Many organizations now face a range of emerging trends and threats that impact how they run their business and find the flexibility of a hybrid cloud essential.

A hybrid data center is adaptable. It's a viable and practical system that enables companies to meet the growing threat of ransomware attacks while taking on today's evolving business demands — all in real time. A hybrid data center provides strong security, efficient performance, reliability, scalability, agility, and cost-efficiency.

But a hybrid data center requires work. Implementing and operating one presents several IT-management challenges. Yes, a hybrid data center allows a business to efficiently store and shift workloads according to need and better protect its sensitive data. But a hybrid data center brings more complexity to managing servers, networks, storage, and software across the IT landscape.

For instance, organizations running a hybrid cloud must secure their data and applications both on-premises and in the cloud. They also must be able to recover data and applications on-premises or in the cloud, wherever the company initially hosted the data and applications. And they must handle backup and recovery across a hybrid environment. To do all this, they must have a data management and storage solution that meets the needs of a hybrid data center.

The Rise of Data Repatriation

As the cost of the cloud continues to balloon, many companies will take the dramatic step of "repatriating" workloads to preserve precious IT budgets. Already, rising energy prices are forcing organizations to rethink their cloud strategy and start repatriating their data from the cloud to on-premises.

Indeed, market intelligence firm IDC research shows that most organizations are now shifting workloads from the cloud back to on-premises data centers. In the IDC survey, 71% of respondents said they plan to move some or all of the workloads they're now running in public clouds back to on-premises environments in the next two years. A mere 13% said they plan to run all their workloads in the cloud.

There are many reasons why companies are repatriating their workloads from the cloud to on-premises. These include security, performance, regulatory compliance, and a desire for better control of the IT infrastructure. Another reason is cost, which can rise quickly and unexpectedly. Workloads often start small and demand a manageable expenditure, but when workloads jump — which they frequently do — so does the spending, which a company may not have anticipated.

Data volumes in the cloud have increased to a point where they're often not manageable. Moving some of this data back on premises can bring benefits beyond lower costs, such as better security and enhanced performance.

But as companies move their data back on-premises, they face several challenges. They need a data-storage solution that can protect their data wherever it resides — on-premises, offsite, or in the cloud. They also need a storage solution that ensures their data is available 24/7/365, even in unforeseen circumstances.

Ideally, they also need a storage solution that provides analytics that can rapidly decide what sets of data are critical to operations and what sets are not. With these analytics, organizations can efficiently determine which datasets they can place in the cloud, which can be stored locally, and which they should bring back on-premises. Analytics also enables companies to decide which data they must back up and which doesn't. With this, organizations can maintain an intelligent, tiered data architecture that ensures quick access to critical data and saves costs by identifying data they can store in less expensive, less readily accessible media.

Your To-Do List for Cloud Deployment in 2023

As cloud costs rise, organizations must reexamine their data storage systems. They must implement solutions that enable them to manage their workloads cost-effectively and, at the same time, ensure that their data is always accessible and secure.

Ahsan Siddiqui is Director of Product Management at Arcserve

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Balancing the Rising Costs of Public Cloud

Ahsan Siddiqui
Arcserve

The spiraling cost of energy is forcing public cloud providers to raise their prices significantly. A recent report by Canalys predicted that public cloud prices will jump by around 20% in the US and more than 30% in Europe in 2023. These steep price increases will test the conventional wisdom that moving to the cloud is a cheap computing alternative.

Indeed, many organizations are already looking at their higher cloud bills and assessing whether it still makes sense to keep moving their infrastructure to the cloud. They do have alternatives.

For instance, for solutions used regularly and persistently, it might make financial sense to bring those in-house rather than host them in the cloud. Owning the infrastructure and managing it yourself could be more cost-effective in the long run.

On the other hand, more complex technologies, and solutions with a high entry cost, such as artificial intelligence, remain good candidates for cloud hosting because they require so much infrastructure and personnel to run in-house. The cloud also remains an excellent option for specific services and solutions where more elasticity is required. This includes technologies that need to be scaled up quickly for a defined period, such as the last few days of each month or quarter when closing the books, then scaled back down.

These are just some issues that organizations should assess when determining if they should keep their data and infrastructure in the cloud. Moving them back on-premises or transitioning to a hybrid infrastructure entails keeping some data and applications in the cloud while returning others to an on-premises infrastructure. From now on, all organizations must take a step back and assess what will work best for them to find the right balance.

The Benefits of Hybrid Cloud

A hybrid cloud has a lot of advantages. Organizations adopting a hybrid cloud approach can more easily control costs and manage their data wherever it resides — on-premises, in a public or private cloud. Many organizations now face a range of emerging trends and threats that impact how they run their business and find the flexibility of a hybrid cloud essential.

A hybrid data center is adaptable. It's a viable and practical system that enables companies to meet the growing threat of ransomware attacks while taking on today's evolving business demands — all in real time. A hybrid data center provides strong security, efficient performance, reliability, scalability, agility, and cost-efficiency.

But a hybrid data center requires work. Implementing and operating one presents several IT-management challenges. Yes, a hybrid data center allows a business to efficiently store and shift workloads according to need and better protect its sensitive data. But a hybrid data center brings more complexity to managing servers, networks, storage, and software across the IT landscape.

For instance, organizations running a hybrid cloud must secure their data and applications both on-premises and in the cloud. They also must be able to recover data and applications on-premises or in the cloud, wherever the company initially hosted the data and applications. And they must handle backup and recovery across a hybrid environment. To do all this, they must have a data management and storage solution that meets the needs of a hybrid data center.

The Rise of Data Repatriation

As the cost of the cloud continues to balloon, many companies will take the dramatic step of "repatriating" workloads to preserve precious IT budgets. Already, rising energy prices are forcing organizations to rethink their cloud strategy and start repatriating their data from the cloud to on-premises.

Indeed, market intelligence firm IDC research shows that most organizations are now shifting workloads from the cloud back to on-premises data centers. In the IDC survey, 71% of respondents said they plan to move some or all of the workloads they're now running in public clouds back to on-premises environments in the next two years. A mere 13% said they plan to run all their workloads in the cloud.

There are many reasons why companies are repatriating their workloads from the cloud to on-premises. These include security, performance, regulatory compliance, and a desire for better control of the IT infrastructure. Another reason is cost, which can rise quickly and unexpectedly. Workloads often start small and demand a manageable expenditure, but when workloads jump — which they frequently do — so does the spending, which a company may not have anticipated.

Data volumes in the cloud have increased to a point where they're often not manageable. Moving some of this data back on premises can bring benefits beyond lower costs, such as better security and enhanced performance.

But as companies move their data back on-premises, they face several challenges. They need a data-storage solution that can protect their data wherever it resides — on-premises, offsite, or in the cloud. They also need a storage solution that ensures their data is available 24/7/365, even in unforeseen circumstances.

Ideally, they also need a storage solution that provides analytics that can rapidly decide what sets of data are critical to operations and what sets are not. With these analytics, organizations can efficiently determine which datasets they can place in the cloud, which can be stored locally, and which they should bring back on-premises. Analytics also enables companies to decide which data they must back up and which doesn't. With this, organizations can maintain an intelligent, tiered data architecture that ensures quick access to critical data and saves costs by identifying data they can store in less expensive, less readily accessible media.

Your To-Do List for Cloud Deployment in 2023

As cloud costs rise, organizations must reexamine their data storage systems. They must implement solutions that enable them to manage their workloads cost-effectively and, at the same time, ensure that their data is always accessible and secure.

Ahsan Siddiqui is Director of Product Management at Arcserve

Hot Topics

The Latest

For decades, traditional observability tools have forced IT professionals to sift through endless dashboards, turning a flood of alerts into actionable insight and driving widespread burnout. While enterprises adopted AI to eliminate this friction, most still deploy it reactively rather than proactively ... As systems become more complex and IT moves to the center of business strategy, a reactive posture is unsustainable ...

Ask an operations team what they monitor and you will hear a familiar list: latency, errors, throughput, uptime. Those signals still matter for AI, but they no longer answer the most important question. As Krishna Sai, CTO of SolarWinds, puts it: "Traditional observability tells you a system is running. AI observability tells you whether it's still reasoning soundly. Those are completely different questions" ...

AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...