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.
Many enterprises are dusting off the private cloud strategies that lost out to the allure of the public cloud. Is this the right move?
There’s definitely more uncertainty in going with a microcloud provider, but choosing a smaller company for your GPU services may pay off big in the end.
The idea of decentralizing cloud computing has been overshadowed by AI, but frustration with high cloud prices has boosted interest in other options.
It seems to be fair game now to label cloud security as risky even though your data is likely safer there than on premises.
Using the generic architecture you saw at a conference for your company's unique business needs is a surefire way to waste money and time.
New data reveals some interesting information about cloud cost management and the fear of being fired. Should we rethink our approaches?
Enterprises may find it faster and easier to deploy their AI models in a public cloud that runs them as a service. AWS is jumping on this trend.
With public cloud providers chasing generative AI, it may be a surprise when dollars flow in other directions. Vendors and customers have a lot to consider.
Let’s not make the same mistakes we did 10 years ago. It is possible to deploy large language models in the cloud more cost-effectively and with less risk.
A recent study shows that the cloud benefits the IT department more than other business areas. That’s not enough to make it a success.
ESG scores can be a helpful tool in the pursuit of sustainability. But they won’t look deep into your architecture to see if poor design is wasting money and energy.
It’s no surprise that AI will be a gold mine for cloud providers. However, if vendors and customers move too far in the wrong direction, we’ll waste business value for years.
Many systems architects already see too much focus on processors for generative AI systems and not enough attention on other vital components.
How much carbon is your software responsible for? Awareness of power consumption and accountability for it are the first steps in a green development cycle.
Interest in doing the right thing is extending to IT systems beyond AI. This is good, even if mainly motivated by the fear of legal or financial consequences.
A dirty little secret in the cloud world is that container workloads have a higher total cost of ownership than they should.
AI models that use data where it exists rather than centralizing it require stronger privacy and security measures. Introducing the RoPPFL framework.
Enterprise IT sees these fees as arbitrary and annoying, and cloud providers are taking notice. However, it’s not all about customer goodwill.