Cloud providers waste a lot of their customers’ cloud dollars, but enterprises can take action.
For years, private clouds pushed traditional on-prem hardware. Will the recent move towards specialized private clouds, especially for AI, be a win?
Will the new advances in serverless really address the problems enterprises have, or are they more hype to protect the public cloud providers’ investments?
Generative AI is causing excitement but not success for most enterprises. This needs to change quickly, but it will take some work that enterprises may not be willing to do.
Unsustainable demands for AI are on the horizon. People will soon have to stop fake-caring about cloud sustainability and give a damn for real.
IT management’s call for strategic alignment and cost efficiency is leading to a new era of choices that will drive cloud innovation and collaboration.
In some countries, the government is attempting to regulate cloud computing, and cloud providers are suing each other over competition and lock-in. Where does that leave enterprises?
AI and other forces are lessening the gravitational pull of public cloud platforms. This trend might be good for enterprises.
Despite soaring investments in artificial intelligence, the shortage of AI skills is stifling enterprise implementations.
We’re building too much complexity and are ill-trained to secure it. The result will be breach after breach, while enterprises wonder what happened. Get a clue now.
The construction of more data centers to support AI systems makes it hypocritical to discuss sustainability at the same time. Sustainable AI is an oxymoron right now.
How many enterprises are revisiting on-premises solutions in a cloud-dominated era for better cost management, security, and performance?
Too many businesses believe that adequate security is too expensive. Here are some ways to keep costs manageable.
Businesses are recognizing the benefits of specialized GPU clouds, general-purpose IaaS providers, and regional cloud options.
Companies think their only choices are repatriation or complaining about the high costs of the public cloud. There's a third option, but it takes work.
NIST recently published a report that garnered little attention, but it's a must-read document for people in business and law enforcement.
Companies suffer when cloud computing architects are not directly aligned with their business's overall goals. Let’s readjust our perspectives from purely technical.
The government’s intentions to promote cybersecurity for cloud-based AI are good, but its track record of successfully managing technology is poor.
As more enterprises leave the cloud or express real concern with rising prices, vendors must adapt to retain enterprise customers.
The idea of integrating data gathered from multiple sources is hardly new, but interest in digital transformation and AI is pushing enterprises to tackle it again.
We’ve known for years that application portability between public cloud providers is not easy or cheap. Here are a few approaches to try instead.
Does simulating attacks and failures help you harden your infrastructure, or is it a risky distraction for unprepared teams?
NIST has some recommendations for navigating the evolving cybersecurity landscape with quantum-resistant strategies, and they should absolutely be on your radar.
The expensive, painful lessons we learned from the early days of cloud computing are relevant to the generative AI era.
If enterprises want to sustain their digital transformation journeys, cloud operations must be a priority, with the funding to match.
Artificial intelligence will redefine cloud security with adaptive frameworks, enhanced threat intelligence, and predictive analytics to usher in an era of proactive protection.
Overshadowed by generative AI and GPUs, quantum computing still offers value for specialized applications.
Comprehensive strategies to attract, retain, and develop top talent in cloud computing to ensure sustainable growth and innovation.
We seem to have lost our ability to build efficient cloud systems, resulting in billions of dollars of lost business value. We need to find that metric again and find it now.
From cutting costs to boosting efficiency, lean AI is reshaping the business landscape and democratizing advanced technology for enterprises of all sizes.
Engineers are ideally placed to manage high cloud expenses but may not want one more thing on their plate. What role should finops teams play?
Distributing workloads among various providers offers protection from failure, but make sure your business can handle the complexity and costs.
AI agents benefit from the data sovereignty, customization, and lower costs of on-premises servers and other options outside the public clouds.
Until CIOs are ready to confront data that is siloed, redundant, or can’t be traced through the business process, generative AI will not pay off.
After all these years, we still haven’t implemented enough finops, automation, and governance to stop wasting money in the cloud.
Rapid cloud adoption has left many enterprises needing help with their technology infrastructure. These simple rules will keep the pain to a minimum.
There is widespread fear in the securities and finance sectors that using generative AI will force companies to rely on giant cloud companies.
CISOs are still hampered by bad assumptions and outdated approaches. They should be involved in decisions from day 1 to address unique business needs.
AI agents offer flexibility and autonomy as they plan and complete complex tasks that traditionally require human involvement.
The explosive growth of generative AI drives the multicloud model. But be prepared because it’s going to cost more money.
It's old news that no one in IT can find enough talent to build and run modern IT solutions. AI won’t save you, so start looking at other options.
Using edge systems to run elements of generative AI could be game-changing. It requires planning and skill, but this hybrid approach may be the future.
Leaving the cloud is not a matter of choosing between two clear-cut options. Few enterprises go completely data center or completely cloud.
The problems can be hard to find but easy to solve. With a proactive approach and best practices, you can avoid unhappy users and a damaged business reputation.
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