Over the years, DevOps has been called many things: A culture, a practice, a mindset. Today, it’s increasingly framed as a platform, coalescing with platform engineering, cloud native maturity and next‑generation AI. But what do DevOps engineers themselves think about where we stand in 2025? Having spoken to dozens of professionals, combed through the latest surveys and observed trends closely, here’s a look at what the trenches are telling us.

Platform Engineering’s Domination: A Double‑Edged Sword

Platform engineering has moved from buzzword to battleground. According to a Red Hat survey conducted in September‑October 2024, nearly half of organizations say generative AI is a core component of their platform engineering strategy. And platform engineering maturity strongly correlates with success, particularly when organizations treat their internal platforms as products with measurable KPIs. (Red Hat)

DevOps engineers commonly report relief in daily toil — IDPs and golden paths reduce friction and enable faster delivery. But complaints persist: building and maintaining a platform can be costly, inflexible, and siloed unless it’s scoped carefully. One recent report emphasized that challenges like workflow integration (37%), security risks (37%), and skills gaps (34%) remain barriers even for advanced organizations. (Red Hat)

In short: Engineers appreciate platform engineering — so long as it’s well built, developer‑centric and not a one‑size‑fits‑all. Otherwise, it risks becoming another source of friction instead of productivity.

AI’s Two Faces: Agentic and Generative in the Trenches

Generative AI is no longer a novelty — it’s everywhere in DevOps workflows. Surveys show 83% of organizations plan to increase spending on AI code generation, and 76% on agentic AI in the next 12–18 months. (Red Hat, DevOps.com) Tooling that automates documentation (76%), generates code (74%) and provides intelligent code suggestions (59%) is already standard fare in many shops. (Red Hat)

But Ai’s influence goes deeper. TechRadar recently identified three generations of AI coding tools: From Copilot‑style completions, to in‑IDE agents, to full SDLC‑integrated agentic systems. As of mid‑2025, tools like GitHub Copilot, DevOps agents and Zencoder Zen are automating entire pipelines — almost like AI co‑engineers. (TechRadar)

DevOps engineers I speak with are cautiously optimistic. They see agentic AI relieving routine toil: Spinning up IaC, reviewing compliance, optimizing cloud costs. Platforms like CloudBees Unify now connect toolchains under AI‑enhanced control planes. (Wikipedia) At the same time, many practitioners note that AI is still brittle — it works, but only when supervised, prompted carefully and monitored.

The rise of “vibe coding” — a nearly free‑flow, conversational style where engineers guide LLMs rather than write every line — is increasingly common in startups, and sneaking into enterprise prototypes. (Wikipedia)

DevOps Tools Maturing into Platforms

The toolchain is consolidating. CI/CD, monitoring, compliance, security and cloud provisioning tools are increasingly bundled or bridged in platform layers. DevOps.com’s coverage tracks this trend: It’s no longer about separate pipelines, it’s about unified DevOps platforms.

CloudBees Unify is a prime example: Launched in mid‑2025, it unifies governance across toolchains without forcing migration — an AI‑powered operating layer over existing tools. (Wikipedia) Other providers are doing similar strategic shifts, responding to DevOps teams tired of fragmented tooling.

Engineers say platform‑style tools work — when they’re flexible, extensible and don’t lock them out. Simplicity and integration win; fragmentation and vendor lock‑in frustrate.

Cloud Native: From Cutting‑Edge to Default

Cloud Native is no longer optional — it’s the de facto standard. According to surveys, 61% of organizations run some (41%) or most (19%) production workloads on Kubernetes, with AI/ML and analytics topping the list at 56% each. (TechRadar, DevOps.com) Engineers affirm that masteries like ArgoCD, Flux, service meshes, eBPF and GitOps practices are now standard radiation of skills. (Reddit)

The link between Cloud Native and AI is especially tight; data workloads, model serving and feature rollout are deeply intertwined with container orchestration and microservices. DevOps engineers increasingly identify as “platform engineers” working at scale in that space.

Education and Certification: Catching Up Slowly

DevOps education and certification remain fragmented. Traditional certs — Kubernetes (CKA, CKAD), AWS/Azure/GCP and DevOps Foundation — remain staples. (Reddit) But DevOps engineers express frustration: Formal learning often lags behind real‑world tooling, AI integration, or platform engineering practices.

Many engineers now augment certs with hands‑on labs, bootcamps and informal community learning. Organizations are piloting internal platform engineer training programs to bridge skills gaps. Still, a mismatch persists between the modern tech stack and classroom syllabi.

Macro‑Economics: Jobs, Layoffs and Demand Shifts

In 2025’s turbulent economic climate, DevOps engineers feel mixed pressure. Layoffs in tech surged 35% in Q1‑Q2 2025 versus the same period in 2024. AI is partly blamed, especially in coding jobs.(Business Insider) But experienced practitioners remain in demand. Firms are automating low‑level roles while doubling down on strategic DevOps and platform roles. (Business Insider)

Waze co-founder Uri Levine recently argued that AI will actually increase demand for software engineers — especially those who can adapt, lead, and architect AI‑infused systems. (Business Insider) Meanwhile, others warn that entry‑level roles are shrinking—some startups now operate as “100× engineer” shops, using AI to super‑charge top performers. (Business Insider)

Most DevOps engineers I speak with say: keep growing skills, especially in AI orchestration, security‑by‑design, cloud cost optimization, platform engineering discipline. Senior and strategic roles are safe; apprentice roles are under pressure.

What DevOps Engineers Think of the Road Ahead

Looking forward, DevOps engineers express hope infused with realism:

• AI will accelerate productivity, but not replace engineers. They expect to supervise agents, shape workflows and solve complex problems—not type boilerplate. (Business Insider)
• Platform engineering is here to stay, but success depends on impact, metrics and a product mindset. Engineers expect more rigor in design, developer‑centric UX, service‑like governance and clear business alignment. (adaptavist.com)
• Cloud Native is standard, but emphasis is shifting to stability, cost control, observability and AI‑ready infrastructure. Knowledge of service mesh, eBPF and GitOps is now table stakes.
• Certs matter, but only to a point. Real‑world experience, continuous hands‑on exposure to AI‑augmented tooling and platform building are where skills live.
• Economic uncertainty looms, but so do opportunities — for architects, platform builders, security‑minded DevOps leaders and AI‑savvy engineers.

Final Thought

DevOps engineers today stand at a crossroads: Platform engineering and cloud tooling have matured into the ecosystem, AI is no longer experimentation but embedded flow. Job markets are shifting, but real demand remains strong — for creative, strategic and adaptable engineers who can shepherd tools, teams and AI together into scalable delivery platforms.

From my vantage, DevOps is no longer about “doing DevOps” — it’s about owning DevOps Platforms, empowering developers and leveraging AI as a force multiplier. That’s what the field’s elite expect, and that’s what you should be building toward.

Alan Shimel is Editor‑in‑Chief and Founder of TechStrong. He has been covering DevOps and digital transformation for over two decades, exploring the intersection of culture, tooling and emerging technologies.