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!

This video explores the critical signs of incompetent cloud leadership and its devastating impact on business success. We examine how poor leadership manifests through unclear strategy, ignored technical expertise, and mismanaged resources. Key warning signs include spiraling costs, declining team morale, and missed market opportunities.

The discussion outlines specific business impacts: financial waste, operational inefficiency, talent loss, and diminished competitive advantage. As organizations struggle with unreliable systems and mounting technical debt, competitors leveraging proper cloud strategies pull ahead.

We provide practical steps for addressing leadership issues, from documenting problems and building business cases to forming strategic alliances across departments. While fixing leadership problems internally is preferred, we acknowledge when it's time to consider career changes.  The message is clear: in today's digital economy, effective cloud leadership isn't optional - it's essential for business survival. Addressing leadership incompetence early is crucial to prevent long-term damage to your organization's future.

The cloud computing arena is a whirlwind of innovation, with the market swelling to a massive $330 billion in 2024. This impressive growth spurt is largely fueled by the rise of generative AI, a technology that has captured the imaginations of businesses worldwide.

While giants like AWS, Microsoft Azure, and Google Cloud still hold court, a new breed of agile competitors is emerging, disrupting the established order. These smaller, nimbler players are laser-focused on delivering tailored solutions for the specific demands of AI workloads, attracting enterprises hungry for flexibility and cost-effectiveness.

The battle for cloud dominance is no longer solely about size and scale, but about agility, specialization, and a deep understanding of the evolving needs of AI-driven businesses. As the lines between the physical and digital worlds blur, the cloud is transforming into a dynamic battleground where innovation and adaptability are the keys to survival.

Cloud migration projects frequently fail (70% rate) due to poor architecture decisions, underestimated data complexity, and inadequate planning. The key to recovery involves immediate action: stopping the migration, conducting a thorough assessment, and rebuilding with proper planning. Critical steps include rebuilding data models, mapping dependencies, implementing DevOps practices, and establishing a cloud center of excellence. Success requires honest communication with leadership, proper security measures, and sometimes temporarily reverting to previous systems while rebuilding the migration strategy. With the right approach and decisive action, failed cloud migrations can be transformed into success stories.           

In this video, we explore the growing frustration enterprises have with cloud service providers. Despite the cloud market's continued growth, companies are increasingly concerned about unexpected costs, lack of control, and vendor lock-in. Many organizations are now considering repatriating workloads back to on-premises solutions, particularly for resource-intensive applications like generative AI. While mega-conferences like AWS Re:Invent continue to draw crowds, there's a disconnect between the marketing hype and enterprise reality. Looking ahead, we'll likely see a shift from 'cloud-first' to 'cloud-smart' strategies, with companies taking a more selective approach to cloud adoption.