AWS Global Growth Challenges

Over the past year, I’ve been vocal about the rapid changes in cloud adoption strategies and how the dominance of traditional hyperscalers like Amazon Web Services (AWS) is being increasingly challenged. The latest AWS revenue report, showing slower-than-expected growth in what was once Amazon’s flagship cloud business, is yet another clear indication: the cloud market is evolving—and quickly. While I don’t take pleasure in pointing out the shortcomings of others, I have emphasized this shift for quite some time. Organizations are no longer defaulting to a few massive cloud providers for every solution. Instead, they’re diversifying their approach, strategically adopting tactical, value-based solutions that offer more flexibility, specific capabilities, and a better return on investment. Businesses are pursuing multi-cloud and hybrid-cloud architectures, integrating niche providers, and investing in tech that better aligns with their specific needs—whether it’s specialized AI workloads, edge computing, or localized data centers. The era of ‘just put everything on one hyperscaler’ is fading, as enterprises look for smarter, more bespoke options. Hyperscalers like AWS, Microsoft Azure, and Google Cloud must reevaluate their role in this shifting market. No longer can they rely on being the default or simply scaling compute and storage to win. The expectation now is to provide real business value, deeper integrations, and solutions that empower enterprise innovation at scale. To lead in this new era of cloud, the hyperscalers need to prioritize adaptability, invest in capabilities that align with multi-cloud ecosystems, and focus on their customers’ growth—not just their own. For the providers, it’s time to get a clue. The cloud game is evolving—and the players who adapt quickly will be the ones who thrive. Let’s see who’s ready to meet the challenge. #CloudComputing #AWS #Hyperscalers #MultiCloud #DigitalTransformation #CloudStrategy

The Redundancy Evangelism - Is Multi-Cloud and Multi-Region the Answer? When AWS goes down, the internet feels it. So naturally, everyone says, “You see? Every company should go multi-cloud or multi-region!” But did these organisations really lack redundancy? Most companies running on AWS have engineers who understand best practices, disaster recovery, and multi-region setups. Yet many were still affected in the recent outage. It’s easy to assume they didn’t “design for resilience,” but the real issue is over-reliance on a single region or one provider’s global backbone. According to Reuters, the latest outage centred in US-East-1 - the third time in five years that this region has caused major disruption. The cause? A DNS failure affecting AWS’s internal load balancers and services like DynamoDB. Outages don’t happen every day, but when they do, the losses can reach billions. Forbes estimates this one may have cost businesses billions globally. Now, building true multi-region or multi-cloud systems adds huge cost and complexity. For many, the trade-off is real: Does the cost of full redundancy outweigh the benefit of reduced risk? AWS hosts many “global” services in US-East-1 partly due to cheap electricity, proximity to Washington DC, access to undersea cables, and historical growth. Because of this, even multi-region setups still suffered. So the problem isn’t just that customers weren’t resilient enough. It’s also that AWS’s own architectural dependency on one region magnifies the impact when it fails. Maybe AWS should rethink its global service architecture and reduce that overreliance on a single region. What should businesses do? This isn’t a call to go fully multi-cloud. It’s a call to be smarter about resilience. - Pilot-light architectures: Keep minimal standby infrastructure in another region or on-premises. - Infrastructure as Code (IaC): Rebuild environments quickly when a failover is needed. - Hybrid continuity: Maintain small local setups for critical workloads. Fail smart, not big: Balance cost and resilience. The truth? Organisations weren’t careless. Failure modes have simply evolved. It’s no longer just about data centres - it can be a regional issue, a DNS or control plane failure, or an unexpected cascading event. It means being intentional about trade-offs, architecture, and dependency management. So before jumping on the “multi-cloud” bandwagon, ask: Are you chasing resilience, or just reacting to fear?

"Data Nationalization" is increasingly impacting the strategy & operations of many enterprise organizations, with localized data storage, processing/handling requirements, and Sovereign Data requirements changing the way data, platforms & core infrastructure are designed and operated. 5 categories of themes we are observing: 1️⃣ Enterprise organization of all types are dealing with this change: 👨💻 Software vendors: software delivery is now challenged to have dedicated instances, localized infrastructure while still delivering in a sustainable model mostly aligned to global shared services for commercial and public sector clients. ☁ Cloud Service Providers: are now rethinking their regional deployments and new market entry, and creating bespoke offerings (e.g. Amazon Web Services (AWS) Digital Sovereignty). 💻 SI's and MSPs: are considering the impact to their workforce, delivery locations and how they serve markets with specific localization needs . 🏭 Enterprise customers: with multi-market and global reach are now rethinking their strategies that include hybrid and multi-cloud, global platforms, and the new need for market based granularity, configuration and localization. 2️⃣ Three broader trends in the market: ✅ Stricter compliance laws, even exceeded by customers: significant regional/country variation exists despite standard data regulation principles; customers are even exceeding these standards for attempted future proofing 👨💻 Multi-strategy approach leveraged by platforms: market regulations & commercial nuances require platform players to deploy multiple strategies. 🔑 Thinking beyond compliance: a desire to be the ‘easy choice’ for customers with compliance across all solutions and ease of integration in the customer's landscape. 3️⃣ Competing priorities requiring "Commercial vs. Compliance" decisions: 💵 Commercial: Run vs Change budgets are constantly competing, and organizations seek to maximize product and feature deployment while remaining compliant. ✅ Compliance: the growing localization backlog, and anticipation of more markets to come, has all players thinking longer term for adaptability to unknown and yet to be enforced mandates. 4️⃣ Two forms of regulation we are observing: 📦 Regulations that enforce local storage and processing of data. 🌎 Regulations that permit data transfer outside of their own country only if certain rules are met. 5️⃣ A dynamic cross-functional approach can address complex, global data residency strategies: 🌎 Residency strategies should be market-based, not customer-specific: must be proactive with regulatory and customer engagement, and market segmentation and tech / data strategy. ⚙ Data residency strategy extends beyond data infrastructure & tech requirements: integrate compliance and reqs. early in the product development cycle. ♻ Constant re-evaluation: crucial in dynamic regulatory environment #data #sovereigndata #cloud #infrastructure #software #aws #azure #gcp

The detailed incident report from AWS is now public, and it’s well worth a read (link in comments). Here’s a distilled summary of what went wrong, and what tech leaders should take away. What happened: 1️⃣ A race condition in the DNS management system serving DynamoDB in US-EAST-1 led to endpoint resolution failures. 2️⃣ That dominant database service failure cascaded: new EC2 launches failed due to lease-management issues (on which EC2 depends) and network components suffered health-check failures that rippled across load balancers. 3️⃣ The impact was global. Apps and critical services relying on AWS saw outages, degraded performance, or intermittent failures. Why this matters: 1️⃣ Concentration risk: Even for a hyperscale provider like AWS, a failure in one region and one service (DynamoDB DNS) can cascade globally, turning a “cloud issue” into a business continuity event. 2️⃣ Complex interdependencies: The issue wasn’t just database DNS; it propagated into compute, networking, automation, and customer-facing systems. We often design for failure at one layer but underestimate coupling across layers. 3️⃣ Recovery complexity = resilience risk: Recovery isn’t just restarting services; it’s clearing backlogs, restoring state, and ensuring downstream systems don’t remain impaired. My perspective/takeaways: 1️⃣ Design for worst-case provider failure. Not just “an AZ down,” but “core service in region down” and the ripple effects. 2️⃣ Visibility and dependency mapping matter, so know what services your stack depends on, and how managed service failures might cascade. 3️⃣ Recovery orchestration is as vital as fault tolerance, so plan for backlog recovery, state cleanup, and cross-team communication. 4️⃣ Cloud-vendor resilience is not infinite, and shared failure domains persist even in hyperscale clouds. Plan for multi-region or cross-provider fallback and clear internal recovery roles. 5️⃣ Executive mindset and risk alignment. For C-suites, this is a reminder: infrastructure risk is business risk. Discuss cloud-failure modes at the board table, not just application risk. What this isn't about: This isn’t about blaming AWS. The lesson is that even the largest provider can experience a systemic failure, and we can all learn from these experiences. And... it's always DNS 😉