Agentic AI applications are built with various platforms based on specific requirements including scalability, latency, security, and cost-efficiency. Hyperscalers are ideal for dynamic, global agentic AI systems but incur high operational costs. Private Clouds and Sovereign Clouds provide secure environments suitable for compliance-heavy applications at moderate costs. Co-location providers are cost-effective for predictable workloads, while Edge Computing Servers support latency-critical applications like IoT and autonomous vehicles. GPU Clouds ensure optimal performance for computationally intensive tasks, though they are expensive in the long run. The right platform selection depends on workload characteristics and long-term cost considerations.

Successful multicloud deployment isn’t about adopting multiple clouds—it’s about using them strategically while addressing hidden challenges. Most enterprises underestimate data gravity costs, integration complexities, and governance differences across providers. Security protocols, automation, and FinOps also require cloud-specific approaches, and network costs can quickly spiral without proper planning.

The reality? Multicloud often costs 2x the budget and takes far longer than expected. Success demands clear business objectives, independent cloud expertise, and a focus on loose coupling between platforms. Plan for redundancy and embrace the complexities upfront—ignorance will cost you far more later. Multicloud done right requires pragmatism, not marketing hype.

The cloud computing industry provides numerous paths to wealth, as outlined by thought leader David Linthicum. One lucrative option is becoming a partner in a consulting firm, where you can earn six to seven figures by driving revenue and delivering strategic leadership for enterprise clients navigating cloud transformations. Alternatively, starting your own consulting business allows you to focus on niche cloud areas like multi-cloud, FinOps, or managed services, building recurring revenue through contracts and scaling with unique service offerings.

Joining a cloud computing startup is another opportunity, offering significant financial upside if you negotiate equity and work in innovative, high-growth environments. Developing in-demand cloud-centric skills, such as expertise in cloud security, AI, or Kubernetes, can secure roles with annual salaries of $150,000 to $250,000, with additional income from freelancing or training. Lastly, investing in cloud-based products like SaaS platforms or niche solutions provides scalable, recurring revenue, though it requires upfront capital and keen market awareness.

David Linthicum emphasizes that cloud-savvy individuals who innovate, strategically adapt, and continuously specialize can achieve extraordinary financial success in this rapidly growing field. Combining technical expertise, business acumen, and foresight is key to unlocking wealth in cloud computing.

Nearly 40% of companies post fake "ghost jobs" in cloud computing, with no intention to hire. These deceptive listings serve multiple purposes: building talent pools, testing market rates, appearing to grow, and pressuring current employees. One in five online job postings are either fake or never filled, particularly affecting specialized tech roles. Companies justify this practice through claimed benefits - 70% report revenue boosts and 77% note increased worker productivity. For job seekers, warning signs include vague descriptions, prolonged posting periods, and lack of response to applications.

David Linthicum highlights three red flags for moving workloads off the public cloud: rising costs, diminished performance, and data governance challenges. These insights empower organizations to avoid over-commitment to public cloud providers and pursue alignment between IT needs and business objectives, often through hybrid solutions or on-premises repatriation.  Make informed choices to optimize both performance and cost-efficiency in your cloud/computing strategy!

Something remarkable is happening in the world of cloud computing. After years of dominance by AWS, Azure, and Google Cloud, enterprises are quietly orchestrating a shift that's reshaping the industry. They're turning to alternative cloud providers – and it's not just a cost-cutting move. Picture a GPU-intensive AI startup using Hyperstack for machine learning while keeping sensitive customer data in a sovereign cloud like OVHcloud. Or consider a healthcare provider combining private cloud infrastructure with specialized platforms for medical imaging processing. These aren't hypothetical scenarios – they're becoming the norm.

What's driving this change? The pain points of working with hyperscalers have become too real: unpredictable costs, compliance headaches, and the dreaded vendor lock-in. Alternative providers saw these gaps and pounced, offering transparent pricing, sovereign data centers, and specialized performance for demanding workloads like AI and ML. The result? A new cloud ecosystem is emerging, one where enterprises mix and match providers like artists blend colors on a palette. While the tech giants aren't going anywhere, their role is evolving. The future of cloud computing isn't about choosing one provider – it's about choosing the right providers for each specific need. And that's a game-changing shift that's only just beginning.

Google has announced a landmark $32 billion acquisition of cloud security startup Wiz, marking its largest purchase to date. This move highlights Google’s push to strengthen its cloud services amid growing demand for secure and scalable cloud platforms, fueled by advancements in artificial intelligence and increased cloud adoption by enterprises.

Wiz, founded in 2020, has rapidly become a dominant player in the cloud security market. Its agentless, multicloud platform is used by nearly half of Fortune 100 companies, offering organizations the ability to detect vulnerabilities and secure workloads seamlessly across multiple cloud environments. Wiz’s technology aligns perfectly with Google’s strategy of improving multicloud operability and addressing the complex security needs of modern enterprises.

The acquisition positions Google Cloud to better compete with Microsoft Azure and Amazon Web Services, both of which currently outperform Google in cloud revenue. Importantly, Wiz will continue to operate as a multicloud platform, ensuring compatibility with other cloud providers, which will appeal to enterprises leveraging diverse cloud strategies.

This deal demonstrates Google’s increasing emphasis on enterprise security solutions and its commitment to innovation in cloud computing. Expected to close in 2026, the acquisition could redefine Google’s role in the cloud ecosystem while accelerating advancements in multicloud security capabilities.

This video explores how enterprises are wasting $44.5 billion annually on unnecessary cloud spending and what can be done to reduce it. It begins by identifying the primary issue: 21% of cloud budgets go underutilized, often due to a disconnect between FinOps (Financial Operations) and engineering teams. Over 50% of engineers blame insufficient collaboration, with many assuming that cost management isn’t their responsibility. This lack of synergy leads to costly inefficiencies like over-provisioned resources, idle infrastructure, and mismanaged cloud environments.

The video also dives into the challenges of visibility and tooling. Many developers lack the real-time data to identify inefficiencies, with only 43% able to see idle resources and 39% able to track orphaned or unused components. Even though 62% of engineers want more control over cloud costs, inadequate tools and automation prevent proactive cost management.

The host emphasizes the need for cultural change, advocating for a "shift-left" approach where cost awareness becomes an integral part of the development process. Developers must take ownership of cost decisions during the design and deployment phases and collaborate closely with FinOps teams. The video highlights practical recommendations, such as automating cost-management processes, increasing visibility through better tools, and implementing proactive cost strategies at the architecture stage.

Finally, the video concludes by stressing the importance of breaking silos between teams and enabling shared accountability for cloud costs. By fostering collaboration, adopting real-time monitoring, and embracing automation, enterprises can reclaim billions of wasted dollars, optimize cloud performance, and unlock the full potential of the cloud. The video provides actionable insights for any organization looking to turn cloud chaos into cost efficiency.

AWS, once considered the gold standard of cloud innovation, seems to be faltering as it joins the race for agentic AI far later than its competitors. The announcement of a new team dedicated to building autonomous AI agents feels more like a response to external pressure than a proactive step forward. This delay raises unsettling questions about whether AWS is still the innovative force it once was or if it's beginning to lag behind in an industry that demands rapid adaptation.

For years, AWS set the pace for innovation in the cloud and enterprise tech industries. But the lack of urgency in pursuing agentic AI has left observers and enterprises wondering if AWS is growing complacent. While other major players aggressively define the future of AI-driven automation, AWS now looks like a reluctant participant rather than a visionary leader. By the time AWS fully ramps up its efforts, the market may have already shifted, leaving them at a competitive disadvantage.

More troubling is what this indicates about AWS’s overall trajectory. Enterprises depend on AWS not just for cloud infrastructure, but for innovation—the ability to stay ahead of trends and deliver cutting-edge solutions. This tardy embrace of agentic AI has cast doubt on its ability to do so, leaving many to wonder if AWS is no longer pushing boundaries but merely trying to keep up. In a field moving as fast as AI, being late is more than a misstep—it’s a signal of declining leadership.

In this engaging video, we dive into the revolutionary impact of Agentic AI on cloud technology and system deployment, specifically tailored for cloud professionals. Discover how Agentic AI signifies a significant shift in automation and operational intelligence, allowing systems to make autonomous decisions that improve efficiency and adapt to real-time data.

We explore the evolving role of cloud architecture and the crucial need for agility and flexibility when deploying microservices that seamlessly integrate with Agentic AI components. Learn how this innovative environment encourages continuous monitoring and feedback loops, fostering a dynamic web of interconnectivity between AI-driven decisions and traditional operations.

In addition, we highlight the importance of effective data management, emphasizing that high-quality, accessible data is essential for the success of Agentic AI systems. As we navigate this technological evolution, understand how the future of cloud technology is not just about supporting AI, but about co-creating a new paradigm where AI and non-AI systems work together harmoniously.

Whether you're an industry veteran or a tech enthusiast, this video provides valuable insights on positioning yourself at the forefront of this exciting new era in cloud technology and AI. Don’t miss this opportunity to learn how Agentic AI is set to redefine how we build and deploy systems in the digital age!