The research firm Forrester has put a number on a worry that infrastructure teams have carried since last year's big cloud failures: in its Predictions 2026: Cloud Computing report, principal analyst Lee Sustar forecasts at least two major multi-day outages across the large hyperscalers in 2026. The stated reason is not just bad luck but investment trade-offs — the argument that AWS, Microsoft Azure and Google Cloud are pouring money into GPU-centric AI data centres while older, general-purpose x86 and ARM infrastructure gets less attention. It is worth being clear from the start that this is a forecast, not a reported fact. But it rests on a real pattern, and the practical response to it does not depend on whether the exact number turns out right.

What the prediction actually says

Forrester's core claim is mechanical. Hyperscalers are in a capital race to build GPU-centric, AI-native data centres, and to fund it they are diverting investment away from the aging x86 and ARM environments that run most existing workloads. As that legacy infrastructure is deprioritised while overall system complexity keeps rising, Forrester argues the result is fragility — and it expects that fragility to surface as at least two major multi-day outages during 2026. The firm pairs this with a prediction about how customers respond: the complexity and tangled dependencies that made recovery slow during 2025's failures will push large enterprises to pressure providers to renovate their infrastructure, and to rethink how much they concentrate on a single cloud.

Two related forecasts sit alongside the outage call. Forrester expects at least 15% of enterprises to pursue private AI running on private clouds in 2026, driven by AI costs, fears of data lock-in, and the operational risk of depending on infrastructure optimised for someone else's priorities. And it expects AI-focused "neoclouds" — specialist GPU-cloud providers — to gain revenue alongside the hyperscalers. The throughline is that the AI build-out is reshaping not just what cloud can do but how reliable and how concentrated it is.

Why the warning has weight

The 2025 and early-2026 incidents do not prove Forrester's multi-day forecast — the examples are multi-hour, not multi-day — but they show why the warning has traction: failures in shared foundations can create broad, slow-to-recover disruption. In October 2025, AWS traced a major US-EAST-1 incident to DNS resolution problems for its regional DynamoDB endpoints. By AWS's own account the DNS fault was mitigated within hours (by around 2:24 AM PDT on 20 October), but residual impairment and throttling of operations such as EC2 instance launches continued until AWS said all services had returned to normal at 3:01 PM PDT — roughly fifteen hours after the event began at 11:49 PM PDT the night before. The disruption hit thousands of companies, including consumer names such as Netflix and Snapchat.

Microsoft Azure had its own high-profile disruptions. Its February 2026 outage was triggered by a policy change unintentionally applied to a subset of Microsoft-managed storage accounts that host virtual-machine extension packages; that blocked public read access and caused VM provisioning and scaling failures across regions, and the recovery step then triggered a follow-on failure of the Managed Identities for Azure Resources service in the East US and West US regions. These were failures in shared foundations, not obscure edge services. A separate reminder came in June 2026, when a fire at a third-party data-centre facility in Delhi forced an emergency power shutdown that isolated a non-compute Google Cloud network node and degraded traffic across Delhi, Mumbai and Chennai — a different failure mode from Forrester's software-complexity thesis, and a reminder that hyperscaler availability also rests on physical dependency chains.

Where the forecast could be overstated

A prediction deserves scrutiny, not just amplification. There are reasons to treat the specific "two major outages" figure cautiously. First, it is a forecast from a research firm, and big, attention-getting numbers are easier to publish than to verify after the fact; the resilience and alternative-infrastructure vendors that amplify such warnings also have a commercial interest in the anxiety they create. Second, large outages are partly a function of scale: as more of the world's workloads concentrate on three providers, any single failure looks more dramatic, which is not the same as the underlying failure rate getting worse. It is genuinely hard to distinguish "infrastructure is becoming more fragile" from "we have put more eggs in fewer baskets, so each dropped basket hurts more." Both can produce the same headlines.

That caveat does not make the prediction wrong — other analyst guidance has also pushed enterprises to revisit resilience and concentration risk, so Forrester is not alone in the broader theme — but it argues for treating the forecast as a prompt to examine your own exposure rather than as a calendar entry. The useful question is not whether Forrester's count is exactly right; it is whether your systems would survive one of the outages it describes.

What infrastructure teams should do regardless

The value of the prediction is that the response to it is the same whether or not the number lands. The first step is honest dependency mapping: knowing which of your critical services sit on a single region, a single provider, or a single shared component such as DNS or an identity service, because the 2025 and 2026 incidents all turned on shared foundations rather than exotic features. The second is deciding, service by service, where multi-region or multi-cloud redundancy is worth its real cost — full cross-cloud failover is expensive and complex, poorly designed multi-cloud can add failure modes of its own, and not every workload justifies it, so the work is prioritisation rather than blanket duplication. The third is rehearsal: failover that has never been tested tends not to work when it is finally needed. Forrester's own framing is that resilience has to be an architectural principle rather than a checkbox, and that is the durable takeaway whatever 2026's outage count turns out to be.

What it means for the region

For enterprises and governments across Southeast Asia, the structural point matters more than the specific forecast. The region's digital economy increasingly runs on the same three hyperscalers, often through a small number of local regions and connectivity hubs, which concentrates risk: a single provider or regional failure can take out a wide range of dependent services at once. For Singapore-based teams, where many regional services centralise operations and cloud connectivity, that concentration deserves explicit design attention. None of this argues against using hyperscale cloud — the economics are compelling and the alternatives have their own costs — but it does argue for regional businesses to know their concentration, to decide deliberately which services need cross-region or cross-provider resilience, and to test that resilience before an outage tests it for them.

Key Takeaways

  • Forrester's Predictions 2026 report (principal analyst Lee Sustar) forecasts at least two major multi-day hyperscaler outages in 2026, blaming investment shifting from aging legacy infrastructure toward GPU-centric AI data centres. It is a forecast, not a fact.

  • These are multi-hour examples, not proof of the multi-day forecast: an October 2025 AWS US-EAST-1 incident (DynamoDB DNS) whose residual impact ran ~15 hours and hit Netflix and Snapchat; a February 2026 Azure outage from a storage-account policy change that broke VM provisioning and then Managed Identities; and a June 2026 Google Cloud disruption in India caused by a third-party data-centre fire — physical, not software, risk.

  • Forrester also predicts ≥15% of enterprises will move to private AI on private clouds, and that AI "neoclouds" will gain revenue alongside the hyperscalers.

  • The forecast deserves caution: it is a research-firm prediction amplified partly by resilience vendors, and bigger outages may reflect concentration on three providers rather than a rising failure rate.

  • The response is the same regardless: map single points of dependency (region, provider, DNS, identity), decide service-by-service where multi-region or multi-cloud redundancy is worth its cost, and test failover before it is needed. For Southeast Asia, reliance on the same few hyperscalers and hubs like Singapore concentrates that risk.