Kubernetes Is No Longer Number One — The REAL 2025 Cloud Native Report (CNCF x SlashData)
By Tatiana Mikhaleva · Developer Advocate · Docker Captain · IBM Champion
Hey my cloud-native queens, kings, and everyone shipping to production in between.
So I read the whole thing so you don’t have to. We’re walking through the key facts from the 2025 “State of Cloud Native” report by CNCF and SlashData, and there’s a lot here.
The big spoiler first: Kubernetes is NO LONGER the most interesting number.
Everyone’s chasing K8s. Meanwhile the real action is happening somewhere else entirely.
Where do these numbers come from? Over 12,000 developers from 128 countries, surveyed between June and July 2025, sliced by role: backend, DevOps, ML/AI, IoT, and games. Solid sample, darling.
Okay. Facts time.
Finding Number One: Backend won
56% of backend developers are now cloud native.
Put that in raw headcount and you get 15.6 million cloud-native developers, of which 9.3 million of them are backend. Backend is the engine room, sis.
Why care? Because backend teams are the ones carrying the weight. APIs, observability, microservices, CI/CD, who actually owns a service at 3am. All of it.
So if you’re building a platform, build it for backend and DevOps. Not for “everyone in general,” because “everyone in general” never ships.
Backend + DevOps is the new core of the cloud-native community.
Finding Number Two: AI is not that cloud native
You’d assume AI/ML lives in the cloud, GPUs blazing, all-in. Nope. Only 41% of ML/AI professionals are cloud native.
The report points to one big culprit: heavy reliance on MLaaS, those managed services that hide the infrastructure from you completely.
Here’s the gap. AI models keep scaling like crazy. But the boring DevOps discipline — logs, versioning, deployments — tends to limp along behind.
And that gap? That’s the opportunity, queen. If you’re in DevOps, SRE, or Platform Engineering, this is your moment to bring real engineering hygiene into MLOps. Actual pipelines. Versioned environments. Logs that exist. Managed clusters that someone owns.
Finding Number Three: What’s really being used
The most-used cloud-native tech is not exotic. Not even a little. It’s deeply, refreshingly boring:
- API gateways — 50%
- Microservices — 46%
- Kubernetes — 28%
- Observability — 28%
Notice anything? Observability (28%) just caught up to Kubernetes (28%). People finally clocked that “just running it” isn’t the finish line. You have to see what’s happening too.
Then there’s service mesh. 8%. Eight percent, code cuties. The hype made it sound like 80.
So no, the world is not living in “service mesh everywhere.” The world is living in:
just give me a solid gateway, logs, and orchestration.
Building a product for DevOps? Aim at this reality. Not at some super-exotic architecture almost nobody actually runs in prod.
What to do with this data
If you’re an architect, a DevOps lead, or the person building the platform, here’s what the report is really telling you.
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Go backend- and DevOps-first. These two groups are the most cloud-native in the whole report. This is where IDPs, artifact repositories, and policy-as-code earn their keep.
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Support hybrid. 30% of all developers are on hybrid cloud, and 23% are multi-cloud. Your networking, secrets, and observability have to span everything. One provider is not the whole picture anymore.
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Bring ML teams up to code. Got ML folks in-house? Give them the exact engineering hygiene your production teams already have. Versioned environments, pipelines, logs, clusters, proper deployments. The works.
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Don’t over-engineer. The mainstream stack is this: API gateways, microservices, Kubernetes, plus observability. It is not a universal service mesh draped over everything. It’s mature, it’s understandable, and you can actually ship on it and make money.
Final verdict
Cloud native is now mainstream for backend and DevOps. AI is the one still playing catch-up.
So how does this map to your world? Do these numbers match what you’re seeing day to day, or is your stack heading somewhere totally different?
Tell me in the comments, darling. I’m genuinely curious how this data lands against real life.
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