Junior Developer Pipeline AI Crisis: The Narrowing Pyramid

Back in February, I wrote about how AI is reshaping software development at a cost we’re only beginning to understand. I looked at three threads: skill erosion, open-source sustainability, and Agile methodology. Together they pointed at the same underlying tension: AI is accelerating what we can measure while quietly degrading what we can’t. Two months later, the evidence has hardened, and a new dimension has come into focus. It’s not just about individual developers losing depth. It’s about the junior developer pipeline itself.

How AI is collapsing the junior developer pipeline

For my April piece on InfoQ, I covered a peer-reviewed opinion paper by Microsoft Azure CTO Mark Russinovich and VP Scott Hanselman, published in the April 2026 issue of Communications of the ACM. Their argument is precise and uncomfortable: agentic AI coding tools are creating a structural crisis in software engineering. AI boosts senior engineers while imposing what they call “AI drag” on early-in-career developers who haven’t yet built the judgment to steer, verify, and fix AI output. The incentive consequence is predictable: organizations hire seniors, automate juniors, and the pipeline that produces the next generation of seniors quietly collapses.

They call this the “narrowing pyramid hypothesis.” Traditionally, junior developers grow through the bottom rungs: bug fixes, straightforward implementation, exposure to real architecture, and build systems. Over time, the best rise to the tech lead role. When AI eliminates that entry-level work, the apprenticeship disappears with it.

Two pyramid diagrams comparing the traditional junior developer pipeline versus the AI-era pipeline, showing how AI eliminates entry-level roles and collapses career progression from the bottom up.
The junior developer pipeline AI is eroding from the bottom: entry-level roles are disappearing faster than organizations are replacing them.

Payroll records, not projections

A Harvard study cited in the paper found that after GPT-4’s release, employment of 22- to 25-year-olds in AI-exposed jobs fell by roughly 13%, even as senior roles grew. The Stanford AI Index 2026 adds a harder data point: employment for software developers aged 22 to 25 has dropped nearly 20% from its 2022 peak, based on ADP payroll data matched against AI exposure. These aren’t speculative projections; they’re payroll records.

The structural picture at the job posting level is equally stark. Developer roles such as Android, Java, .NET, iOS, and web development are down 60% or more from 2020, while postings for machine learning engineers are up 59%. Forrester’s 2026 Predictions project a 20% decline in CS enrolments. Prospective students are responding to deteriorating signals in the job market. Fewer graduates entering today means a potential shortage of senior engineers in five to ten years.

The vacancy chain is breaking. In a healthy market, a senior leaves, a mid-level moves up, and a junior gets hired. AI disrupts this chain by automating the bottom link, severing the pathway for new entrants. This is the mechanism behind the junior developer pipeline crisis: the bottom rung disappears, and the whole ladder stops working.

What the productivity data doesn’t show

I spend a lot of time on the productivity narrative because it dominates the boardroom conversation. McKinsey analyzed nearly 300 publicly traded companies and found that top-quintile performers are achieving 16-30% improvements in productivity and 31-45% gains in software quality. That’s real. I don’t dispute it.

But productivity gains at the team level and investment in the junior developer pipeline are not mutually exclusive; in practice, they apparently are. A Harvard study tracked 62 million workers across 285,000 US firms. It found junior employment at AI-adopting companies declined 9-10% within six quarters of implementation. Senior employment remained virtually unchanged. Organizations are taking the productivity gains and banking them rather than reinvesting them in the junior developer pipeline.

The problem with this trade-off is temporal. The people who become your senior engineers in 2031 need to be junior engineers today. A Harvard/Berkeley study captures the downstream effect for the seniors who remain: instead of mentoring juniors, senior engineers now spend hours reviewing and fixing AI-generated code. One engineer described the experience as being “a judge at an assembly line that is never-ending.” The time cost of AI output review hasn’t disappeared; it’s just shifted upward.

Why the junior developer pipeline AI problem runs deeper than hiring

This connects directly to what I wrote in February, drawing on the Anthropic study showing that developers using AI assistance scored 17% lower on comprehension tests. The dividing line sat around a 65% threshold: above it were developers using AI as a thinking partner; below it were those who had delegated the thinking entirely.

Russinovich and Hanselman illustrate what that delegation looks like in production. An AI agent responding to a race condition inserted a sleep call, a classic masking fix that hides the underlying synchronization bug. An experienced engineer catches this immediately. A developer who has never debugged a real race condition, because they’ve always had an AI to write the code, does not. The term they use for what’s being lost is “systems taste,” the intuition developed through years of production exposure. You can’t prompt-engineer your way to systems taste.

The US Bureau of Labor Statistics reports that overall employment for programmers fell 27.5% between 2023 and 2025, while more design-oriented software developer roles held roughly flat. The market is bifurcating: roles that require judgment are surviving, roles that are primarily about code production are being automated. If junior developers are no longer doing the production work that builds the judgment, we’re investing in neither.

A possible path forward

Rebuilding the junior developer pipeline requires treating it as infrastructure, not overhead. Russinovich and Hanselman propose a preceptor model borrowed from medical education: pair early-career developers with experienced mentors in real product teams, with learning measured and compensated as an explicit organizational goal rather than a side effect of shipping.

The preceptor model

The senior’s role shifts from “person who answers questions” to “person who teaches judgment.” The pair uses AI tools together, with the senior observing what the junior accepts, rejects, and misses. Hanselman explained the thinking behind this in a LeadDev interview: just as a nurse needs to prove clinical readiness, engineers need to do the same to earn the title.

Honeycomb CTO Charity Majors noted on X in response to the paper that at every organization she has seen successfully hire junior engineers in recent years, the charge was led and lobbied for by senior engineers. That’s the critical variable. This isn’t something HR can mandate. It requires senior engineers who recognize that their own long-term relevance depends on a healthy profession.

Community reaction has been sharp on the question of whether good intentions survive corporate incentive structures. One Reddit thread puts it bluntly: the math doesn’t work. Hiring a junior who takes two years to become productive loses out against an AI assistant that makes a mid-level engineer 30% more productive today. Unless you’re training juniors specifically to oversee AI output, which is not what CS programs teach.

That reframe is actually the right one. The goal isn’t to protect junior roles from AI. It’s to deliberately design a new apprenticeship path in which AI is part of what juniors learn to manage, not a substitute for the learning process.

More code is not better architecture

From my vantage point as both an enterprise architect and a technology editor, I see this playing out in real organizations. The teams moving fast on AI tooling are producing more code. But “more code” and “better architecture” are different things, and the gap only becomes visible under pressure: during incidents, migrations, and the inevitable moment when someone has to explain why a system behaves the way it does. That explanation requires comprehension, not generation.

I wrote in February that the choices made in the next year or two would shape the industry for a decade. The narrowing junior developer pipeline makes that window feel shorter than it did then.

AI Is Reshaping Software Development — At What Cost?

February has been a busy month for me at InfoQ. I wrote three articles that, on the surface, cover different topics: skill formation, open-source sustainability, and Agile methodology. But when I stepped back and looked at them together, a pattern jumped out at me. Each one tells a piece of the same story: AI is transforming how we build software at a pace that exceeds our ability to think about the consequences.

I want to use this post to connect the dots.

AI Software Development Is Eroding Developer Skills

The first piece I wrote covered an Anthropic study on how AI coding assistance affects skill development. The research was a randomized controlled trial with 52 junior engineers learning a Python library called Trio, which none of them had used before. The findings were stark. Developers who used AI assistance scored 17 percent lower on comprehension tests compared to those who coded by hand. That gap is roughly equivalent to two letter grades.

What struck me most wasn’t the headline number, though. It was the nuance underneath. Participants who used AI as a thinking partner, asking conceptual questions, requesting explanations, and working through problems alongside the tool, retained far more knowledge than those who asked the AI to generate code for them. The dividing line sat around a 65 percent score threshold. Above it, you found the curious developers. Below it are the ones who had delegated the thinking.

I’ve been working in IT for a long time. I’ve seen junior engineers grow into senior architects, and the path always involved struggle. Debugging code you don’t understand at 11 PM on a Tuesday. Reading documentation that makes your eyes glaze over. Writing something that breaks, then figuring out why. That struggle is where the learning happens. What concerns me is not that AI exists; I use it daily and find it genuinely helpful, but that we might be removing the friction that develops competence in the first place.

The full article is here: Anthropic Study: AI Coding Assistance Reduces Developer Skill Mastery by 17%

AI Coding Tools Are Overwhelming Open Source Maintainers

My second article examined a problem I’ve been watching develop for months. Daniel Stenberg shut down cURL’s bug bounty after AI-generated submissions reached 20 percent of the total. Mitchell Hashimoto banned AI-generated code from Ghostty entirely. Steve Ruiz took it even further with tldraw, auto-closing all external pull requests. These aren’t fringe projects. cURL runs on billions of devices. These are maintainers reaching a breaking point.

RedMonk analyst Kate Holterhoff coined the term “AI Slopageddon” to capture what’s happening, and it does so well. The flood of AI-generated contributions looks plausible at first glance but falls apart on inspection. The problem isn’t just quality, it’s volume. Maintainers are human beings with limited time, and they’re now spending that time sifting through submissions that an AI produced in seconds without any real understanding of the project.

A research paper from the Central European University and the Kiel Institute for the World Economy modeled the bigger structural risk here. Open-source projects depend on user engagement, documentation views, bug reports, and community recognition as a return on the maintainer’s investment. When AI agents assemble packages without developers ever reading the docs or filing bugs, that feedback loop breaks. The researchers tried to model a “Spotify-style” revenue redistribution. Still, the numbers didn’t work: vibe-coded users would need to generate 84 percent of the engagement that direct users currently provide. That’s not realistic.

I keep thinking about this one. My entire career has been built on open source, from the tools I integrate at work to the libraries I rely on for InfoQ articles. If the ecosystem that produces and maintains these tools becomes unsustainable because AI-generated noise overwhelms the people doing the actual work, we all lose. Not eventually. Soon.

More details here: AI “Vibe Coding” Threatens Open Source as Maintainers Face Crisis.

AI Software Development Puts Agile Under Pressure

The third article I wrote covered a debate sparked by Steve Jones, an executive VP at Capgemini, who declared that AI has killed the Agile Manifesto. His argument: when agentic SDLC systems can build applications in hours, the Manifesto’s human-centric principles no longer apply. If the tooling matters as much as or more than the people using it, then the Manifesto’s preference for “individuals and interactions over processes and tools” breaks down.

It’s a provocative claim that generated a lot of discussion. Casey West proposed an “Agentic Manifesto” that shifts the focus from verification to validation. AWS’s 2026 prescriptive guidance suggests “Intent Design” should replace sprint planning. Kent Beck, one of the original Manifesto signatories, has been talking about “augmented coding” as a new paradigm.

But here’s the counterpoint that keeps sticking with me. Forrester’s 2025 State of Agile Development report found that 95 percent of professionals still consider Agile critically relevant to their work. That’s not a methodology on its deathbed. And as one commenter noted in the discussion thread, bureaucracy killed Agile long before AI agents came along.

I think the question isn’t whether the Agile Manifesto is obsolete. It’s whether we’ve ever fully lived by its principles in the first place. The Manifesto says “responding to change over following a plan.” If there’s ever been a moment that demands responsiveness and adaptation, it’s right now. The irony of declaring Agile dead precisely when we need its core philosophy the most isn’t lost on me.

Full article: Does AI Make the Agile Manifesto Obsolete?

What AI’s Impact on Software Development Really Tells Us

When I look at these three stories together, I see a common tension. AI is accelerating what we can measure, lines of code produced, pull requests submitted, and applications prototyped, while eroding what is harder to quantify. Deep understanding of a codebase. Thoughtful engagement with an open-source community. The human judgment that sits at the heart of iterative development.

The Anthropic study shows that speed and learning pull in opposite directions, at least for developers acquiring new skills. The open-source crisis tells us that volume and quality are diverging at an alarming rate. The Agile debate tells us that our existing frameworks for organizing human work are straining under the weight of AI-driven change.

None of this means we should reject AI tools. I certainly won’t. But I think we need to be far more intentional about how we deploy them. That means designing AI assistants that support learning rather than replace it. It means building platforms that protect maintainers from low-quality noise. It means evolving our methodologies rather than abandoning them.

As someone who has spent years exploring new technologies, it’s one of the things I enjoy most about working in this field. I remain optimistic about where AI can take us. But optimism without caution is just naivety. The choices we make in the next year or two about how AI integrates into our development practices will shape the industry for a decade.

We should probably pay attention.

AWS European Sovereign Cloud Launches—But Does It Solve the Real Problem?

Earlier, AWS officially launched its European Sovereign Cloud, backed by a €7.8 billion investment in Brandenburg, Germany. The infrastructure is physically and logically separated from AWS global regions, managed by a new German parent company (AWS European Sovereign Cloud GmbH), and staffed exclusively by EU residents. On paper, it checks every compliance box for data residency and operational sovereignty. AWS CEO Matt Garman called it “a big bet” for the company, and it is. The question is whether it’s the right bet for Europe.

European Sovereign Cloud: Real Isolation, Real Trade-offs

The technical separation is genuine. An AWS engineer who deployed services to the European Sovereign Cloud confirmed on Hacker News that proper boundaries exist—U.S.-based engineers can’t see anything happening in the sovereign cloud. To fix issues there, they play “telephone” with EU-based engineers. The infrastructure uses the partition name *aws-eusc* and the region name *eusc-de-east-1*, which are completely separate from AWS’s global regions. All components, IAM, billing systems, and Route 53 name servers using European Top-Level Domains—remain within EU borders.

But this isolation comes with costs. As that same engineer warned, “it really slows down debugging issues. Problems that would be fixed in a day or two can take a month.” This is the sovereignty trade-off in practice: more control, less velocity. The service launches with approximately 90 AWS services, not the full catalog. Plans exist to expand into sovereign Local Zones in Belgium, the Netherlands, and Portugal, but this remains a subset of AWS’s offerings globally.

For some workloads, this trade-off makes sense. For others, it’s a deal-breaker.

Why the European Sovereign Cloud Can’t Escape U.S. Jurisdiction

Here’s the uncomfortable truth that AWS’s marketing carefully sidesteps: technical isolation doesn’t create legal isolation. AWS, headquartered in America, remains subject to U.S. jurisdiction. The CLOUD Act allows U.S. authorities to compel U.S.-based technology companies to provide data, regardless of where it is stored globally. Courts can require parent companies to produce data held by subsidiaries.

This isn’t theoretical hand-wraving. Microsoft had to admit in a French court that it cannot guarantee data sovereignty for EU customers. When Airbus executive Catherine Jestin discussed AWS’s sovereignty claims with lawyers late last year, she said: “I still don’t understand how it is possible” for AWS to be immune to extraterritorial laws.

Cristina Caffarra, founder of the Eurostack Foundation and competition economist, puts it bluntly:

A company subject to the extraterritorial laws of the United States cannot be considered sovereign for Europe. That simply doesn’t work.

The AWS response focuses on technical controls—encryption, the Nitro System preventing employee access, and hardware security modules. These are important safeguards, but they don’t address the core legal issue. If a U.S. court orders Amazon.com Inc. to produce data, technical barriers become legal obstacles the parent company must overcome, not protections.

Europe’s European Sovereign Cloud Strategy: The Cloud and AI Development Act

AWS’s launch comes as Europe finalizes its own legislative response. The EU Cloud and AI Development Act, expected in Q1 2026, aims to strengthen Europe’s autonomy over cloud infrastructure and data. As Christoph Strnadl, CTO of Gaia-X, explains:

For critical data, you will never, ever use a US company. Sovereignty means having strategic options — not doing everything yourself.

The Act is part of the EU’s Competitiveness Compass and addresses a fundamental problem: Europe’s 90% dependency on non-EU cloud infrastructure, predominantly American companies. This dependency isn’t just about data residency—it’s about strategic autonomy. When essential services depend on infrastructure governed by foreign law, questions arise about jurisdiction, resilience, and what happens during geopolitical disruption.

Current estimates indicate that AWS, Microsoft Azure, and Google Cloud collectively control over 60% of the European cloud market. European providers account for only a small share of revenues. The Cloud and AI Development Act aims to establish minimum criteria for cloud services in Europe, mobilize public and private initiatives for AI infrastructure, and create a single EU-wide cloud policy for public administrations and procurement.

Importantly, Brussels isn’t seeking to ban non-EU providers. As Strnadl notes:

Sovereignty does not mean you have to do everything yourself. Sovereignty means that for critical things, you have strategic options.

Gaia-X and the European Sovereign Cloud: A Lesson in Sovereignty Washing

Europe has been down this path before. Gaia-X, launched in 2019, intended to create a trustworthy European data infrastructure. Then American companies lobbied to be included. Once Microsoft, Google, and AWS were inside, critics argue, Gaia-X lost its purpose. The fear now is that AWS’s European Sovereign Cloud represents sophisticated “sovereignty washing”—placing datacenters on European soil without resolving the fundamental legal issue.

Recent European actions suggest growing awareness of this problem. Austria, Germany, France, and the International Criminal Court in The Hague are taking concrete steps toward genuine digital independence. These aren’t just policy statements—they’re actual migrations away from U.S. hyperscalers toward European alternatives.

European Sovereign Cloud Adoption: No Full Migration in 2026

Forrester predicts that no European enterprise will fully shift away from U.S. hyperscalers in 2026, citing geopolitical tensions, volatility, and new legislation, such as the EU AI Act, as barriers. The scale of dependency is too deep, the feature gap too wide, and the migration costs too high for rapid change.

Gartner forecasts European IT spending will grow 11% in 2026 to $1.4 trillion, with 61% of European CIOs and tech leaders wanting to increase their use of local cloud providers. Around half (53%) said geopolitical factors would limit their use of global providers in the future. The direction is clear, even if the pace remains uncertain.

This creates a transitional period where organizations must make pragmatic choices. For non-critical workloads, AWS’s European Sovereign Cloud may be sufficient. For truly sensitive data—government communications, defense systems, critical infrastructure—organizations need genuinely European alternatives: Hetzner, Scaleway, OVHCloud, StackIT by Schwarz Digits.

What AWS’s European Sovereign Cloud Actually Delivers

Let’s be precise about what AWS European Sovereign Cloud achieves. It provides:

  • Data residency within the EU
  • Operational control by EU residents  
  • Governance through EU-based legal entities
  • Technical isolation from the global AWS infrastructure
  • An advisory board of EU citizens with independent oversight

What it doesn’t provide is independence from U.S. legal jurisdiction. For compliance requirements focused purely on data residency and operational transparency, this may be sufficient. For organizations requiring protection from U.S. government data requests, it fundamentally isn’t.

As Eric Swanson from CarMax noted in a LinkedIn post:

Sovereign cloud offerings do not override the Patriot Act. They mainly reduce overlap across other contexts: data location, operational control, employee access, and customer jurisdiction.

European Sovereign Cloud and Strategic Autonomy: Not Autarky

Europe’s path forward isn’t about digital isolationism. As Strnadl emphasizes, technology adoption that involves a paradigm shift doesn’t happen in two years. The challenge is adoption, not frameworks. “Cooperation needs trust,” he says, “and trust needs a trust framework.”

The Cloud and AI Development Act, expected this quarter, will provide that framework. It will set minimum criteria, promote interoperability, and establish procurement rules that favor sovereignty for critical workloads. The question for organizations is: what constitutes critical?

For email, public administration, political communication, and defense systems, the answer should be obvious. These require European alternatives. For other workloads, AWS’s European Sovereign Cloud may strike an acceptable balance between capability and control.

The Bottom Line

AWS’s €7.8 billion investment is real. The technical isolation is real. The economic contribution to Germany’s GDP (€17.2 billion over 20 years) is real. What’s also real is that Amazon.com Inc., a U.S. company, ultimately controls this infrastructure and remains subject to U.S. law.

For organizations seeking compliance checkboxes and data residency guarantees, AWS European Sovereign Cloud delivers. For organizations requiring genuine independence from U.S. legal jurisdiction, it remains fundamentally insufficient. That’s not a criticism of AWS’s engineering—it’s a statement of legal reality.

The sovereignty question Europe faces isn’t technical. It’s strategic: do we accept managed dependency or build genuine autonomy? AWS offers the former. Only European alternatives can provide the latter.

The market will decide which answer matters more.

Europe’s Sovereignty Challenge: A Framework for Cloud Control

Europe’s sovereignty challenge has moved from political debate to concrete policy. With the EU’s new Cloud Sovereignty Framework now in place, the continent is redefining how it procures and governs cloud infrastructure, shifting from dependency on foreign providers to measurable, auditable control over its digital destiny.

Today, Europe and the Netherlands find themselves at a crucial junction, navigating the complex landscape of digital autonomy. The recent introduction of the EU’s new Cloud Sovereignty Framework is the clearest signal yet that the continent is ready to take back control of its digital destiny.

This isn’t just about setting principles; it’s about introducing a standardized, measurable scorecard that will fundamentally redefine cloud procurement.

Europe’s Sovereignty Challenge: Why Digital Independence Is Non-Negotiable

The digital revolution has brought immense benefits, yet it has also positioned Europe in a state of significant dependency. Approximately 80% of our digital infrastructure relies on foreign companies, primarily American cloud providers. This dependence is not merely a matter of convenience; it’s a profound strategic vulnerability.

The core threat stems from U.S. legislation such as the CLOUD Act, which grants American law enforcement the power to request data from U.S. cloud service providers, even if that data is stored abroad. Moreover, this directly clashes with Europe’s stringent privacy regulations (GDPR) and exposes critical European data to external legal and geopolitical risk.

As we’ve seen with incidents like the Microsoft-ICC blockade, foreign political pressures can impact essential digital services. The possibility of geopolitical shifts, such as a “Trump II” presidency, only amplifies this collective awareness: we cannot afford to depend on foreign legislation for our critical infrastructure. The risk is present, and we must build resilience against it.

The Sovereignty Scorecard: From Principles to SEAL Rankings

The new Cloud Sovereignty Framework is the EU’s proactive response. It shifts the discussion from abstract aspirations to concrete, auditable metrics by evaluating cloud services against eight Sovereignty Objectives (SOVs) that cover legal, strategic, supply chain, and technological aspects.

The result is a rigorous “scorecard.” A provider’s weighted score determines its SEAL ranking (from SEAL-0 to SEAL-4, with SEAL-4 indicating full digital sovereignty). Crucially, this ranking is intended to serve as the definitive minimum assurance factor in government and public sector cloud procurement tenders. The Commission wants to create a level playing field where providers must tangibly demonstrate their sovereignty strengths.

Hyperscalers vs. European Providers: The Cloud Sovereignty Challenge

The framework has accelerated a critical duality in the market: massive, centralized investments by US hyperscalers versus strategic, federated growth by European alternatives.

Hyperscalers Adapt: Deepening European Ties

Global providers are making sovereignty a mandatory architectural and legal prerequisite by localizing their operations and governance.

  • AWS explicitly responded by announcing its EU Sovereign Cloud unit. This service is structured to ensure data residency and operational autonomy within Europe, explicitly targeting the SOV-3 (Data & AI Sovereignty: The degree of control customers have over their data and AI models, including where data is processed) criteria through physically and logically separated infrastructure and governance.
  • Google Cloud has also made significant moves, approaching digital sovereignty across three distinct pillars:
    • Data Sovereignty (focusing on control over data storage, processing, and access with features like the Data Boundary and External Key Management, EKM, where keys can be held outside Google Cloud’s infrastructure);
    • Operational Sovereignty (ensuring local partner oversight, such as the partnership with T-Systems in Germany); and
    • Software Sovereignty (providing tools to reduce lock-in and enable workload portability).To help organizations navigate these complex choices, Google introduced the Digital Sovereignty Explorer, an interactive online tool that clarifies terms, explains trade-offs, and guides European organizations in developing a tailored cloud strategy across these three domains. Furthermore, Google has developed highly specialized options, including Air-Gapped solutions for the defense and intelligence sectors, demonstrating a commitment to the highest levels of security and residency.
  • Microsoft has demonstrated a profound deepening of its commitment, outlining five comprehensive digital commitments designed to address sovereignty concerns:
    • Massive Infrastructure Investment: Pledging a 40% increase in European datacenter capacity, doubling its footprint by 2027.
    • Governance and Resilience: Instituting a “European cloud for Europe” overseen by a dedicated European board of directors (composed exclusively of European nationals) and backed by a “Digital Resilience Commitment” to contest any government order to suspend European operations legally.
    • Data Control: Completing the EU Data Boundary project to ensure European customers can store and process core cloud service data within the EU/EFTA.

European Contenders Scale Up

Strategic, open-source European initiatives powerfully mirror this regulatory push:

  • Virt8ra Expands: The Virt8ra sovereign cloud, which positions itself as a significant European alternative, recently announced a substantial expansion of its federated infrastructure. The platform, coordinated by OpenNebula Systems, added six new cloud service providers, including OVHcloud and Scaleway, significantly broadening its reach and capacity across the continent.
  • IPCEI Funding: This initiative, leveraging the open-source OpenNebula technology, is part of the Important Project of Common European Interest (IPCEI) on Next Generation Cloud Infrastructure and Services, backed by over €3 billion in public and private funding. This is a clear indicator that the vision for a robust, distributed European cloud ecosystem is gaining significant traction.

Redefining European Cloud Sovereignty: Resilience Over Isolation

Industry experts emphasize that the framework embodies a more mature understanding of digital sovereignty. It’s not about isolation (autarky), but about resilience and governance.

Sovereignty is about how an organization is “resilient against specific scenarios.” True sovereignty, in this view, lies in the proven, auditable ability to govern your own digital estate. For developers, this means separating cloud-specific infrastructure code from core business logic to maximize portability, allowing the use of necessary hyper-scale features while preserving architectural flexibility.

The Challenge: Balancing Features with Control

Despite the massive investments and public commitments from all major players, the framework faces two key hurdles:

  • The Feature Gap: European providers often lack the “huge software suite” and “deep feature integration” of US hyperscalers, which can slow down rapid development. Advanced analytics platforms, serverless computing, and tightly integrated security services often lack direct equivalents at smaller providers. This creates a complex chicken-and-egg problem: large enterprises won’t migrate to European providers because they lack features, but local providers struggle to develop those capabilities without enterprise revenue.
  • Skepticism and Compliance Complexity: Some analysts fear the framework’s complexity will inadvertently favor the global giants with larger compliance teams. Furthermore, deep-seated apprehension in the community remains, with some expressing the fundamental desire for purely European technological solutions: “I don’t want a Microsoft cloud or AI solutions in Europe. I want European ones.” Some experts suggest that European providers should focus on building something different by innovating with European privacy and control values baked in, rather than trying to catch up with US providers’ feature sets.

My perspective on this situation is that achieving true digital sovereignty for Europe is a complex and multifaceted endeavor. While the commitments from global hyperscalers are significant, the underlying desire for independent, European-led solutions remains strong. It’s about strategic autonomy, ensuring that we, as Europeans, maintain ultimate control over our digital destiny and critical data, irrespective of where the technology originates.

The race is now on. The challenge for the cloud industry is to translate the high-level, technical criteria of the SOVs into auditable, real-world reality to achieve that elusive top SEAL-4 ranking. The battle for the future of Europe’s cloud is officially underway.

Figma AWS Costs Explained: Beyond the Hype and Panic

Figma’s recent IPO filing revealed that its Figma AWS costs amount to roughly $300,000 per day, approximately $109 million annually, or 12% of its reported revenue of $821 million. The company is also committed to a minimum spend of $545 million with AWS over the next five years. Cue the online meltdown. “Figma is doomed!” “Fire the CTO!” The internet, in its infinite wisdom, declared. I wrote a news item on it for InfoQ and thought, let’s put things into perspective.

(Source: Figma.com)

But let’s inject a dose of reality, shall we? As Corey Quinn from The Duckbill Group, who probably sees more AWS invoices than you’ve seen Marvel movies, rightly points out, this kind of spending for a company like Figma is boringly normal.

As Quinn extensively details in his blog post, Figma isn’t running a simple blog. It’s a compute-intensive, real-time collaborative platform serving 13 million monthly active users and 450,000 paying customers. It renders complex designs with sub-100ms latency. This isn’t just about spinning up a few virtual machines; it’s about providing a seamless, high-performance experience on a global scale.

The Numbers Game: What the Armchair Experts Missed About Figma AWS Costs

The initial panic conveniently ignored a few crucial realities, according to Quinn:

  • Ramping Spend: Most large AWS contracts increase year-over-year. A $109 million annual average over five years likely starts lower (e.g., $80 million) and gradually increases to a higher figure (e.g., $150 million in year five) as the company expands.
  • Post-Discount Figures: These spend targets are post-discount. At Figma’s scale, they’re likely getting a significant discount (think 30% effective discount) on their cloud spend. So, their “retail” spend would be closer to $785 million over five years, not $545 million.

When you factor these in, Figma AWS costs fall squarely within industry benchmarks for its type of business:

  • Compute-lite SaaS: around 5% of revenue
  • Compute-heavy platforms (like Figma): 10–15% of revenue
  • AI/ML-intensive companies: often exceeding 15%

At 12% of revenue, Figma’s AWS costs are exactly where you’d expect them to be for a platform delivering real-time collaborative experiences at a global scale.

Furthermore, the increasing adoption of AI and Machine Learning in application development is introducing a new dimension to cloud costs. AI workloads, particularly for training and continuous inference, are incredibly resource-intensive, pushing the boundaries of compute, storage, and specialized hardware (like GPUs), which naturally translates to higher cloud bills. This makes effective FinOps and cost optimization strategies even more crucial for companies that leverage AI at scale.

So, while the internet was busy getting its math wrong and forecasting doom, Figma was operating within a completely reasonable range for its business model and scale.

The “Risky Dependency” Non-Story

Another popular narrative was the “risky dependency” on AWS. Figma’s S-1 filing includes standard boilerplate language about vendor dependencies, a common feature found in virtually every cloud-dependent company’s SEC filings. It’s the legal equivalent of saying, “If the sky falls, our business might be affected.”

Breaking news: a SaaS company that uses a cloud provider might be affected by outages. In related news, restaurants depend on food suppliers. This isn’t groundbreaking insight; it’s just common business risk disclosure. Figma’s “deep entanglement” with AWS, as described by Hacker News commenter nevon, illustrates the complexity of modern cloud architectures. Every aspect, from permissions to disaster recovery, is seamlessly integrated. That makes a quick migration akin to open-heart surgery. Not something you do on a whim.

Cloud Repatriation: A Valid Strategy, But Not a Universal Panacea

Figma’s costs reignited the cloud repatriation debate. The most vocal advocate is 37signals CTO David Heinemeier Hansson, who famously exited the cloud to save millions. And he’s not wrong for some companies; repatriating workloads delivers significant savings. But it’s not a one-size-fits-all solution.

Every company’s needs are different. Scrimba, for example, runs on dedicated servers and spends less than 1% of revenue on infrastructure. For them, repatriation is a perfect fit. Figma is a different story. Its real-time collaborative demands and massive user base require agility, scalability, and managed services at a global scale. A hyperscale provider like AWS isn’t optional; it’s central to the business model.

This brings us to a broader conversation, especially relevant in Europe: digital sovereignty. As I’ve discussed in my blog post, “Digital Destiny: Navigating Europe’s Sovereignty Challenge,” deep integration with a single hyperscaler isn’t just a cost question. It also affects the control an organization retains over its data and operations. Vendor lock-in carries real strategic implications. Data governance, regulatory compliance, and negotiating power can all be compromised. The extraterritorial reach of foreign laws adds another layer of concern. Many organizations are responding by exploring multi-cloud strategies or hybrid models. The goal: mitigate risk and assert greater control over their digital destiny.

My Cloud Anecdote: Costs vs. Value

This whole debate reminds me of a scenario I encountered back in 2017. I was working on a proof of concept for a customer, building a future-proof knowledge base using Cosmos DB, the Graph Model, and Search. The operating cost, primarily driven by Cosmos DB, was approximately 1,000 euros per month. Some developers immediately flagged it as “too expensive,” as I can recall, or even thought I was selling Cosmos DB. The reception, however, wasn’t universally positive. In fact, one attendee later wrote in their blog:

The most uninteresting talk of the day came from Steef-Jan Wiggers, who, in my opinion, delivered an hour-long marketing pitch for CosmosDB. I think it’s expensive for what it currently offers, and many developers could architect something with just as much performance without needing CosmosDB.

However, the proposed solution was for a knowledge base that customers could leverage via a subscription model. The crucial point was that the costs were negligible compared to the potential revenue the subscription model would net for the customer. It was an investment in a revenue-generating asset, not just a pure expense.

The Bottom Line: Putting Figma AWS Costs in Perspective

Thanks to Quinn, I understand that Figma is actively optimizing its infrastructure, transitioning from Ruby to C++ pipelines, migrating workloads, and implementing dynamic cluster scaling. He concluded:

They’re doing the work. More importantly, they’re growing at 46% year-over-year with a 91% gross margin. If you’re losing sleep over their AWS bill while they’re printing money like this, you might need to reconsider your priorities.

The “innovation <-> optimization continuum” is always at play. Companies often prioritize rapid innovation and speed to market, leveraging the cloud for its agility and flexibility. As they scale, they can then focus on optimizing those costs, and Figma AWS costs are no exception to that pattern.

This increasing complexity underscores the growing importance of FinOps (Cloud Financial Operations), a cultural practice that brings financial accountability to the variable-spend model of cloud computing, empowering teams to make data-driven decisions about cloud usage and optimize costs without sacrificing innovation.

Figma’s transparency in disclosing its cloud costs is actually a good thing. It forces a much-needed conversation about the true cost of running enterprise-scale infrastructure in 2025. The hyperbolic reactions, however, expose a fundamental misunderstanding of these realities. Which I also encountered with my Cosmos DB project in 2017.

So, the next time someone tells you that a company spending 12% of its revenue on infrastructure that literally runs its entire business is “doomed,” perhaps ask them how much they think it should cost to serve real-time collaborative experiences to 13 million users across the globe. When you understand what drives Figma AWS costs, the answer might surprise you.

Lastly, as the cloud landscape continues to evolve, with new services, AI integration, and shifting geopolitical considerations, the core lesson remains: smart cloud investment isn’t about avoiding the bill, but understanding its true value in driving business outcomes and strategic advantage. The dialogue about cloud costs is far from over, but it’s time we grounded it in reality.

Digital Destiny: Navigating Europe’s Sovereignty Challenge

During my extensive career in IT, I’ve often seen how technology can both empower and entangle us. Today, Europe and the Netherlands find themselves at a crucial junction, navigating the complex landscape of digital sovereignty. Recent geopolitical shifts and the looming possibility of a “Trump II” presidency have only amplified our collective awareness: we cannot afford to be dependent on foreign legislation when it comes to our critical infrastructure.

In this post, I will delve into the threats and strategic risks that underpin this challenge. We’ll explore the initiatives underway at both the European and Dutch levels, and, crucially, what the major U.S. Hyperscalers are now bringing to the table in response.

The Digital Predicament: Threats to Our Autonomy

The digital revolution has certainly brought unprecedented benefits, not least through innovative Cloud Services that are transforming our economy and society. However, this advancement has also positioned Europe in a state of significant dependency. Approximately 80% of our digital infrastructure relies on foreign companies, primarily American cloud providers, including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud. This reliance isn’t just a matter of convenience; it’s a strategic vulnerability.

The Legal Undercurrent: U.S. Legislation

One of the most persistent threats to European digital sovereignty stems from American legislation. The CLOUD Act (2018), an addition to the Freedom Act (2015) that replaced the Patriot Act (2001), grants American law enforcement and security services the power to request data from American cloud service providers, even if that data is stored abroad.

Think about it: if U.S. intelligence agencies can request data from powerhouses like AWS, Microsoft, or Google without your knowledge, what does this mean for European organizations that have placed their crown jewels there? This directly clashes with Europe’s stringent privacy regulations, the General Data Protection Regulation (GDPR), which sets strict requirements for the protection of personal data of individuals in the EU.

While the Dutch National Cyber Security Centre (NCSC) has stated that, in practice, the chance of the U.S. government requesting European data via the CLOUD Act has historically been minimal, they also acknowledge that this could change with recent geopolitical developments. The risk is present, even though it has rarely materialized thus far.

Geopolitics: The Digital Chessboard

Beyond legal frameworks, geopolitical developments pose a very real threat to our digital autonomy. Foreign governments may impose trade barriers and sanctions on Cloud Services. Imagine scenarios where tensions between major powers lead to access restrictions for essential Cloud Services. The European Union or even my country cannot afford to be a digital pawn in such a high-stakes game.

We’ve already seen these dynamics play out. In negotiations for a minerals deal with Ukraine, the White House reportedly made a phone call to stop the delivery of satellite images from Maxar Technologies, an American space company. These images were crucial for monitoring Russian troop movements and documenting war crimes.

Another stark example is the Microsoft-ICC incident, where Microsoft blocked access to email and Office 365 services for the chief prosecutor of the International Criminal Court in The Hague due to American sanctions. These incidents serve as powerful reminders of how critical external political pressures can be in impacting digital services.

Europe’s Response: A Collaborative Push for Sovereignty

Recognizing these challenges, both Europe and the Netherlands are actively pursuing initiatives to bolster digital autonomy. It’s also worth noting how major cloud providers are responding to these evolving demands.

European Ambitions:

The European Union has been a driving force behind initiatives to reinforce its digital independence:

  • Gaia-X: This ambitious European project aims to create a trustworthy and secure data infrastructure, fostering a federated system that connects existing European cloud providers and ensures compliance with European regulations, such as the General Data Protection Regulation (GDPR). It’s about creating a transparent and controlled framework.
  • Digital Markets Act (DMA) & Digital Services Act (DSA): These legislative acts aim to regulate the digital economy, fostering fairer competition and greater accountability from large online platforms.
  • Cloud and AI Development Act (proposed): This upcoming legislation seeks to ensure that strategic EU use cases can rely on sovereign cloud solutions, with the public sector acting as a crucial “anchor client.”
  • EuroStack: This broader initiative envisions Europe as a leader in digital sovereignty, building a comprehensive digital ecosystem from semiconductors to AI systems.

Crucially, we’re seeing tangible progress here. Virt8ra, a significant European initiative positioning itself as a major alternative to US-based cloud vendors, recently announced a substantial expansion of its federated infrastructure. The platform, which initially included Arsys, BIT, Gdańsk University of Technology, Infobip, IONOS, Kontron, MONDRAGON Corporation, and Oktawave, all coordinated by OpenNebula Systems, has now been joined by six new cloud service providers: ADI Data Center Euskadi, Clever Cloud, CloudFerro, OVHcloud, Scaleway, and Stackscale. This expansion is a clear indicator that the vision for a robust, distributed European cloud ecosystem is gaining significant traction.

Dutch Determination:

The Netherlands is equally committed to this journey:

  • Strategic Digital Autonomy and Government-Wide Cloud Policy: A coalition of Dutch organizations has developed a roadmap, proposing a three-layer model for government cloud policy that advocates for local storage of state secret data and autonomy requirements for sensitive government data.
  • Cloud Kootwijk: This initiative brings together local providers to develop viable alternatives to hyperscaler clouds, fostering homegrown digital infrastructure.
  • “Reprogram the Government” Initiative: This initiative advocates for a more robust and self-reliant digital government, pushing for IT procurement reforms and in-house expertise.
  • GPT-NL: A project to develop a Dutch language model, strengthening national strategic autonomy in AI and ensuring alignment with Dutch values.

Hyperscalers and the Sovereignty Landscape:

The growing demand for digital sovereignty has prompted significant responses from major cloud providers, demonstrating a recognition of European concerns:

  • AWS European Sovereign Cloud: AWS has announced key components of its independent European governance for the AWS European Sovereign Cloud.
  • Microsoft’s Five Digital Commitments: Microsoft recently outlined five significant digital commitments to deepen its investment and support for Europe’s technological landscape.

These efforts from hyperscalers highlight a critical balance. As industry analyst David Linthicum noted, while Europe’s drive for homegrown solutions is vital for data control, it also prompts questions about access to cutting-edge innovations. He stresses the importance of “striking the right balance” to ensure sovereignty efforts don’t inadvertently limit access to crucial capabilities that drive innovation.

However, despite these significant investments, skepticism persists. There is an ongoing debate within Europe regarding digital sovereignty and reliance on technology providers headquartered outside the European Union. Some in the community express doubts about how such companies can truly operate independently and prioritize European interests, with comments like, “Microsoft is going to do exactly what the US government tells them to do. Their proclamations are meaningless.” Others echo the sentiment that “European money should not flow to American pockets in such a way. Europe needs to become independent from American tech giants as a way forward.” This collective feedback highlights Europe’s ongoing effort to develop its own technological capabilities and reduce its reliance on non-European entities for critical digital infrastructure.

My perspective on this situation is that achieving true digital sovereignty for Europe is a complex and multifaceted endeavor, marked by both opportunities and challenges. While the commitments from global hyperscalers are significant and demonstrate a clear response to European demands, the underlying desire for independent, European-led solutions remains strong. It’s not about outright rejection of external providers, but about strategic autonomy – ensuring that we, as Europeans, maintain ultimate control over our digital destiny and critical data, irrespective of where the technology originates.

Some Cloud IT Trends in 2022

We are a few weeks into 2022, and you might have seen or read articles and reports on trends for this year. I also like to outline the few significant IT trends in this blog post from my point of view based upon my work as Cloud Editor for InfoQ and experiences in the consulting field.

First of all, the importance of Artificial Intelligence (AI). You can see that Microsoft, for example, is structurally building these kinds of capabilities into their entire platform. Its intelligence is increasing rapidly, and you can already see with enterprises that they can quickly make valuable business applications with it.

Microsoft Azure AI Platform

Microsoft is already implementing it in their Azure environment. For example, monitoring users’ login behavior is a straightforward example: they continuously keep track of which user logs in when and from which location. They also immediately pass all the data they collect through an AI robot, which will make connections. Furthermore, other examples are that the company enhanced its Translator service and launched the Azure OpenAI service. And it’s not just Microsoft as other public cloud vendors AWS and Google are on board too.

The second trend I see is that more and more companies are looking at options for customizing applications without really having to program, with no code or low code. This has been in the spotlight for some time now, especially among larger companies that would like to facilitate their so-called citizen developers to develop software for use in their own work.

To this end, Microsoft has developed the Power Platform over the past two to three years into a mature low-code platform, which is also interesting for larger organizations. However, you do have to look closely at governance; you can’t just release that completely to users, and you have to build in-game rules, frameworks, and guidelines.

Microsoft Power Platform

We also see increasing adoption of that platform among enterprises, especially with Dynamics 365. The combination of Dynamics 365, Office 365, and Power Platform is becoming a compelling low-code platform for building business applications. Microsoft has an excellent starting position in the low-code market space with competitors like OutSystems, Mendix, and offerings by AWS (HoneyCode, Amplify) and Google (AppSheets). Also, I recommend reading the InfoQ article: Low-Code Platforms and the Rise of the Community Developer: Lots of Solutions, or Lots of Problems?

The third major trend is cloud integration. In recent years, many organizations have moved to the cloud with their applications and data or will move in the wake of COVID-19. Moreover, organizations that have moved to the cloud are now discovering that as you adopt more cloud technology, the need for integration between those systems increases.

Assume you have a CRM from Microsoft, an ERP from SAP, and a data warehouse on Azure. Your business processes run across all those systems. So you must therefore ensure that these systems can exchange data with each other. And you have to make sure that if you have a CRM in the cloud and a customer portal based on customization, you can also see your customer data in that portal. Or some data needs to enter a system on-premise. So, in the end, you need to integrate that!

Therefore, the need for cloud integration is increasing, especially among organizations increasingly investing in the cloud. Microsoft has an answer to that, too, with a perfect and very complete integration platform on Azure named Azure Integration Services (AIS). As a result, even the most demanding enterprises can meet their needs with this.

Azure Integration Services

Recent analyst reports from Gartner and Forrester showed the services are leading. For example, Microsoft was among the leaders in the latest Forrester Wave for Enterprise Integration-Platform-as-a-Service (iPaaS) 2021. In addition, it has been in the leader quadrant of iPaaS reports from Gartner consistently over the last couple of years and that also accounts for API Management.

Lastly, with the last trend, the need for integration increases, and so will the demand for supporting and monitoring them.