Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Harshit Omar, CTO and Co-Founder, FluidCloud
DevOps teams spent most of 2025 playing defense. Every time an outage hit one of the major cloud platforms, it didn’t matter how clean your pipelines were or how perfect your monitoring setup looked. If the provider was down, you were down. And no amount of dashboards, alerts, or incident war rooms could change that.
This was the year the industry finally had to acknowledge something engineering teams have whispered for a long time: the cloud is powerful, but it is not invincible. And when it fails, it takes everything built on top of it with no warning.
The outage problem is no longer hypothetical
We saw outages hit some of the biggest platforms on the planet. OpenAI. Snapchat. Canva. Venmo. Fortnite. Starbucks. Atlassian. Palo Alto Networks. Cloudflare. Some were caused by DNS issues. Others came from automation systems doing exactly what they were configured to do, only at the worst possible time. A few were tied to networking failures that started small and cascaded quickly.
Different causes. Same result. Widespread disruption.
If you are responsible for uptime, you already know that an outage happening “somewhere out there” becomes your problem within minutes. And this past year, there were a lot of minutes.
DevOps has become the catch-all for fragility it doesn’t control
Every outage turns into an incident ticket that DevOps has to triage. It doesn’t matter that the root cause is a provider issue. From the outside, customers only see one thing: the service is down.
This is the uncomfortable truth. DevOps inherited the operational risk of cloud dependence but not the control. When a hyperscaler goes down, you cannot fix it. You can only wait. And that is no longer an acceptable strategy for teams that have strict SLAs, global user bases, or nonstop pipelines.
We talk a lot about resilience, but if your entire stack lives inside a single provider’s boundary, resilience is mostly theoretical.
Multi-cloud has been marketed badly and implemented even worse
Most companies that say they are multi-cloud mean they have workloads in more than one place. That is not portability. It is two separate systems with two separate operational models and two separate headaches.
True multi-cloud means the application, the data, the identity layer, the networking, and the security controls all remain portable without a six-month migration project. Kubernetes helped with compute portability, but anyone who has ever tried to replicate networking rules or IAM policies across providers knows the rest of the stack is where the friction lives.
If the parts around your workloads are tightly coupled to a single cloud, then you are not multi-cloud. You just have a backup home you cannot actually move to in time.
2026 will force resilience into the design phase
DevOps leaders are starting to accept that cloud reliability is not improving at the rate the industry needs. Outages are coming from deeper parts of provider stacks. They propagate faster. They affect more services at once. And AI is increasing dependency on central compute resources that are themselves becoming pressure points.
The only sustainable response is to design infrastructure for movement. Not manual failover. Not incident-by-incident triage. Actual, intentional workload mobility.
That means a few practical shifts.
� Systems need the ability to shift workloads automatically.
� Data needs replication models that do not assume a single provider.
� Identity must be detached from the cloud it was born in.
� Networking must become a compatibility layer, not a constraint.
� Automation must understand more than one environment.
This is the kind of work organizations usually postpone because it feels like a “nice to have.” After 2025, it is clearly not optional.
AI will put even more stress on brittle architectures
AI pipelines are unforgiving. Training workloads are massive and expensive. Inference systems are latency-sensitive. If your AI stack stalls even briefly during an outage, the cost is not just downtime. It is also lost data, lost iteration cycles, and in some cases lost performance windows.
AI wants elasticity across providers. It wants compute wherever it is available. It wants the ability to shift tasks when capacity dries up or services fail. This is going to push DevOps teams toward architectures that behave more like distributed systems and less like traditional cloud deployments.
The companies that figure out how to make AI workloads portable will have an enormous advantage. Everyone else will be stuck pausing pipelines every time something upstream breaks.
What DevOps leaders should expect next
The cloud providers are not disappearing. They are still the most capable infrastructure engines we have ever had access to. But the assumption that a single cloud can keep an entire enterprise online without interruption is now outdated.
In 2026, the high-performing DevOps teams will be the ones who treat portability and resilience as core engineering functions. They will design for failure instead of hoping it does not happen. They will collapse the gap between “an outage somewhere in the cloud” and “our systems are still running.” And they will automate continuity in ways that were previously left to last-minute incident response.
The cloud isn’t unreliable. It is just fallible. And DevOps needs infrastructure that keeps running when the provider doesn’t.
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