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April 19.2025
3 Minutes Read

How AI is Transforming Data Center Power and Cooling Solutions

Presenter discussing AI Data Center Power and Cooling Solutions.

Transforming Data Centers: The AI Revolution

The landscape of data centers is undergoing a radical transformation thanks to artificial intelligence, impacting how power and cooling are managed. At the forefront of these discussions was Vlad Galabov, Omdia's Research Director for Digital Infrastructure, who spoke at Data Center World 2025. He predicts that by 2030, AI will account for over 50% of global data center capacity and dominate more than 70% of revenue opportunities.

The Burgeoning Demand for Power

As industries across the globe increasingly adopt AI technologies, the demand for power within data centers is soaring. Galabov emphasized this surge, noting that since late 2023, the installed capacity for power in data centers worldwide has gone from under 150 GW to nearly 400 GW expected by 2030.

At the center of this growing capacity is a paradigm shift towards higher rack densities. The next generation of design, targeting 120 kW per rack with aspirations for 600 kW racks, reflects the aggressive trajectory that data centers are navigating. Each year, approximately 50 GW of new data center capacity is projected to be added, suggesting that half a terawatt will soon become standard.

The Financial Surge in CAPEX Investments

Accompanying the increase in power demands are monumental shifts in capital expenditures (CAPEX) related to the physical infrastructure of data centers. By 2030, global CAPEX for data centers is projected to skyrocket to $1 trillion, contrasting sharply with figures around $500 billion at the end of 2024. The most substantial gains will occur within infrastructure investments, particularly in power and cooling systems, slated to grow at an impressive rate of 18% per annum.

According to Galabov, these investments are crucial as compute and rack densities escalate. The future of data centers may veer away from a scalable server approach towards fewer systems with heightened capabilities, making it essential for operators to stay innovative amidst the ongoing advancements in AI technologies.

Cooling Innovations: A New Frontier

As power demands rise, conventional methods of cooling are nearing their absolute limits. Omdia's Principal Analyst Shen Wang spoke about the cooling implications of this AI-driven power surge. Air cooling, which has been a staple for data center operations, can only support up to 80 Watts per cm². Beyond this threshold, innovations like single-phase direct-to-chip (DtC) cooling are emerging as the best solutions.

This method involves employing water or cooling fluids directly on chips to efficiently dissipate heat, potentially allowing heat management of up to 140 W/cm². Wang anticipates that by 2026, the latest rack designs will surpass the capabilities of existing air cooling methods, further challenging data center operators to adapt and innovate.

Challenges on the Horizon

Despite the optimistic projections, the rise of AI in the data center industry is not without challenges. Galabov cautioned that while many new developments thrive, not all will succeed. Some startups and data center campuses may struggle to establish sustainable business models, especially if they lack technical expertise and strategic acumen.

Galabov's insights serve as a warning for investors: diversification among providers is crucial, as the fast-paced evolution of technology may lead to failures among less prepared competitors.

Looking Ahead: What Does This Mean for Future Developments?

As we gaze into the future of data centers enhanced by AI, one can’t help but ponder the broader implications of these changes. With self-generated data center power set to exceed 35 GW by 2030, dependency on local grids will lessen. Off-grid and behind-the-meter solutions will likely become indispensable for the upcoming generation of data centers.

The integration of AI into operations can foster agility within DevOps teams, enhancing responsiveness and efficiency across all facets of data management. Providing actionable insights to monitor and optimize energy consumption aligns closely with Agile DevOps methodologies, ensuring that energy strategies evolve as quickly as the technologies that require them.

Conclusion: Making Sense of the AI Surge in Data Centers

The sweeping changes in data center management driven by AI offer a clear path toward enhanced efficiency, but they also introduce a host of complexities. For anyone invested in the future of technology infrastructure—whether as an operator, developer, investor, or technologist—the message is clear: engage deeply with the emerging trends, and prepare to adapt to an environment where innovations in power and cooling are no longer options but necessities.

Agile-DevOps Synergy

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01.23.2026

AI-Driven Quality Assurance: Why It’s Essential for Modern Software Testing

Update AI-Driven Quality Assurance: The Future of Software Testing As artificial intelligence (AI) continues to evolve, it is reshaping the landscape of software testing and quality assurance (QA) like never before. In a recent discussion with Fitz Nowlan, the vice president of AI and architecture at SmartBear, he highlighted the rising importance of stronger QA practices in managing the burgeoning complexities of AI-generated code. Understanding the Shifting Terrain of Software Development The speed and scale at which AI-driven development operates introduce significant risks; more code is produced faster, leading to greater susceptibility to defects and failures. Traditional QA methods simply can't keep pace with the exponential rate of change that AI brings to the software lifecycle. This scenario necessitates a renaissance in how organizations approach testing and quality assurance. The Rise of AI-Powered QA: Efficiency Meets Reliability Fitz Nowlan advocates for a decisive shift toward AI-powered QA processes. This approach uses automation to enhance testing effectiveness, covering gaps that traditional manual processes cannot address. As organizations adopt this modernized QA landscape, they will find that AI can improve test case generation through techniques like natural language processing (NLP) and predictive analytics. Tools equipped with these capabilities allow for seamless transitions from requirement gathering to automated test execution. The Advantages of Integrating AI in QA Processes One of the key advantages of AI-driven quality assurance is the reduction of human error. Manual testing can be labor-intensive, time-consuming, and prone to inconsistencies. In contrast, AI systems can standardize processes, ensuring consistency across multiple testing scenarios. This leads to more accurate outcomes and significantly reduces the time needed to deliver software to market. Beyond Code: The Scope of QA Validation The essence of AI-powered QA transcends mere defect detection. It aims to validate the operational signals of software, including system behavior and performance metrics like latency. Nowlan emphasizes the necessity of separating the frameworks used for coding from those used in testing. This is crucial not only for maintaining code quality but also for ensuring that the performance aligns with user expectations. Future Insights: Vibe Coding and Citizen Development Looking ahead, we must prepare for a world of 'vibe coding' where testers and developers work in closer synergy. In this new environment, non-technical users—referred to as citizen developers—will play an essential role in generating prompts and specifications that enhance software quality. This collaborative effort is prime for refining the standards by which we measure software integrity. Practical Tips To Thrive in the AI-Enhanced QA Landscape Organizations looking to capitalize on AI in their QA processes should start by embracing autonomous testing methods. Here are a few actionable steps they can take: Invest in AI Training: Equip QA teams with the skills needed to leverage AI effectively. Integrate AI Tools: Adopt platforms that facilitate automated test case generation and defect detection. Emphasize Continuous Learning: Use machine learning to adapt testing strategies and processes over time. Conclusion: Building a Resilient Future in Software Testing The necessity of robust QA practices in an AI-driven era cannot be overstated. The imperative is clear: organizations must double down on testing to mitigate the inherent risks associated with AI-generated code. By doing so, they not only improve product reliability but also position themselves for success in a competitive market. As industries continue transforming, organizations must gear up for the exciting possibilities that AI presents. Call to Action: Start investing in AI-powered QA tools and strategies today to ensure your organization stays ahead of the curve in the ever-evolving software landscape!

01.23.2026

Setapp Mobile's Shutdown Signals Trouble for Alternative App Stores

Update The Abrupt Shutdown of Setapp Mobile: A Deep Dive In an unexpected turn of events, Setapp Mobile, one of the European Union's most significant alternative app stores, will close its operations next month. The Ukrainian developer, known for its innovative approach to mobile applications, cited Apple's "complex business terms" as a key reason behind this tough decision. Developers are now faced with a landscape of skyrocketing fees and burdensome regulations that make operating within the creative realm uncertain and increasingly risky. The Implications of Apple’s Monopoly Setapp Mobile’s closure is emblematic of a much larger issue surrounding Apple's dominance in the app market. Following a fresh European Union investigation into Apple's practices, many developers are left questioning the viability of alternative app distribution channels. Apple is a key player in a market that generated a staggering $1.3 trillion in sales and billings in 2024. This market concentration has conditioned developers to be overly dependent on an ecosystem that operates on strict rules and high commissions, sometimes reaching up to 30%. This scenario stifles innovation and discourages new app development, leaving many to wonder whether alternative marketplaces can ever truly flourish under such conditions. Concerns About Fees and Compliance According to industry insiders, the shift in fee structures from a flat rate of €0.50 per installation to a complex tiered system contributes to rising uncertainty among developers. Setapp Mobile's experience is not isolated; it reflects a wave of apprehension among developers who fear that the alternatives to the App Store may offer little financial advantage. With fewer users and functions that require additional developmental effort, the appeal of operating through these alternative apps continues to diminish. The EU's Digital Markets Act: A Beacon of Hope or a Pipe Dream? The European Union's Digital Markets Act is designed to promote fair competition and ensure that technology giants like Apple allow third parties access to their ecosystems. However, while the intentions behind the Act are noble, the practical implications for developers remain uncertain. Even Epic Games, known for its parallel app store initiatives, has faced resistance from Apple. Their attempts to break the monopolistic grip are ironically hampered by the very platforms they’re attempting to rival. The complexity of navigating these markets raises critical questions about whether the Digital Markets Act will deliver tangible change or remain a theoretical safeguard. Fighting Back: The Rise of Alternative App Stores While the challenges are daunting, some competitors are emerging amid the chaos. Epic Games, for instance, continues to push its app store, attempting to capitalize on drawbacks of the current system. With significantly lower commission rates—12% compared to Apple’s 30%—Epic is trying to create a more developer-friendly environment. However, as the complexity of installing third-party apps remains high, their success may be stymied by user hesitance and the convoluted operational processes that come with downloading alternative stores. Looking Ahead: What Lies Beyond Setapp Mobile? As the curtain falls on Setapp Mobile, there’s a palpable sense of urgency among developers to reassess their strategies. While the broader mobile app ecosystem appears deeply entrenched in the status quo, the potential for evolution exists. Developers must now weigh their options ruthlessly—from opting for smaller stores that might better serve their needs to actively engaging in advocacy for more liberating regulations. Conclusion: A Call for Action and Change The situation facing alternative app stores, encapsulated by Setapp Mobile’s impending closure, is a wake-up call for both developers and policy-makers. If they want to truly level the playing field, efforts must be concentrated not only in advocacy but in exploring innovative distribution strategies and technologies. In light of these developments, it’s crucial for developers to pivot strategically and embrace the rapidly shifting landscape of the mobile app economy. Staying informed and agile in this evolving environment is no longer optional—it’s essential.

01.22.2026

How AI Change Resilience Agents Transform DevOps and Agile Practices

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