As we approach 2026, DevOps stands at the forefront of digital transformation, reshaping how organizations build, deploy, and manage software at unprecedented scale. Once a niche engineering practice, DevOps is now mainstream: over 80% of organizations have implemented DevOps workflows, with adoption expected to continue climbing as demand for rapid delivery and automation intensifies.
The global DevOps market reflects this momentum. It is projected to grow from a multi-billion-dollar industry to a market valued in the tens of billions by the end of the decade. All fueled by cloud adoption, AI integration, and the need for resilient, secure pipelines. In 2026, the intersection of AI-driven automation, integrated security practices, and next-generation cloud-native architectures will define the next chapter in DevOps evolution. Read on and discover what experts feel this chapter has in store.
A Shift Towards Autonomous Pipelines
DevOps will shift toward autonomous pipelines powered by AI-driven observability and self-healing infrastructure. Instead of engineers reacting to incidents, systems will anticipate and correct performance issues in real time. The biggest leap will be in trusting intelligent systems to make production-level decisions safely
Roman Milyushkevich, CEO and CTO, HasData
Architecture-as-code Implementation
The number of DevOps teams will increase their focus from pipeline automation to architecture-as-code implementation. The use of Pulumi and Terraform has proven successful for applying application code discipline to cloud infrastructure through versioned and peer-reviewed and testable management. The actual development of DevOps maturity starts at this point.
Igor Golovko, Developer, Founder, TwinCore
A Mindset Centered on Autonomy With Accountability
In 2026, DevOps will evolve from a process to a mindset centered on autonomy with accountability. AI-driven tooling will handle more of the repetitive work, allowing teams to focus on resilience, experimentation, and faster learning cycles, the true heart of DevOps
Ali Yilmaz, Co-founder&CEO, Aitherapy
Smarter And More Predictive
DevOps will evolve beyond automation by 2026, becoming smarter and more predictive. Teams will use AI and real-time data to spot issues and optimise systems before they affect users. Collaboration will improve as engineering and business work from shared insights, focusing on stability and continuous learning.
Nirmal Gyanwali, Website Designer, Nirmal Web Studio
Internal Developer Platforms
One trend that I really see taking off in 2026 is IDPs or internal developer platforms. Companies are realizing that building a central platform for their engineers, like self-service pipelines, reusable templates, and standard tooling lets teams ship faster without chaos. So, the ones who get this right won’t just deploy more but they’ll actually scale their DevOps in a way that sticks. It’s practical, and it’s going to reshape how DevOps works in most organizations in the next year or so.
Pratik Mistry, EVP – Technology Consulting, Radixweb
A Culture of Clarity
It will shift from a culture of speed to a culture of clarity. The conversation will move beyond pipelines and automation toward visibility, trust, and smarter decision-making across the entire delivery cycle. As a CEO, I’m seeing teams demand platforms that don’t just ship faster, but help them understand what’s happening in real time and why. That clarity will become the new competitive edge. AI will play a big part in this, surfacing insights before issues arise and simplifying complex workflows. But the real transformation will come from leaders who make DevOps less about tools and more about how people connect through technology to deliver consistent value.
Tashlien Nunn, CEO, Apps Plus
Teams Taking a Closer Look at The Operations Side of DevOps
The integration of AI/ML and automated security have been big advances in DevOps of late, and I’m sure those trends will continue into 2026. But I think the big story of the year ahead will be teams taking a closer look at the ‘operations’ side of DevOps. For instance, it’s hard to successfully automate critical development steps with AI unless you’ve thought carefully about governance and training or re-skilling needs. People and processes matter more, not less, when tech is changing rapidly.
At Huntress, our growth has hinged on maturing DevOps, and our continued growth will be accelerated thanks to a foundation of DevOps maturity. We talk about building things in “the Huntress way”, and it’s not just a meaningless phrase. It’s underpinned by a whole host of cultural and technical practices that have been refined over the years and are unique to our hyper-scaling business. That includes a genuine clarity about where product ideas come from, how we decide when they’re ‘ready’ to go into production, and how we treat each other, and how we develop our capabilities — which feeds into the collaboration approaches, skills, and tools we apply to streamline coding and release processes. Many of these practices are well-documented, others are understood but less tangible, with some still in flux.
Aimee Simpson, Director, Product Marketing, Huntress
Platform Engineering Will Evolve
In 2026, platform engineering will evolve. It won’t focus on tool integration. It will track how many developers stick to your ideal path. This way, they won’t just find their own solutions without help.
Pratik Singh, Team Leader Digital Experience at Cisin, CIS
A Broader Adoption of Self-correcting AI Models
In 2026, we’ll see financial institutions—from community banks to global players—deploying AI-native fraud detection systems that learn in real time. These platforms don’t just flag suspicious activity; they understand what “normal” looks like for each account or transaction and spot deviations instantly. Expect broader adoption of self-correcting AI models that continuously retrain on new fraud patterns and synthetic data, catching subtle scams that static rules often miss.
Ratan Saha, VP of Sales, Infinite Computer Solutions
Culture of Collaboration Will Mature Into Co-Creation
The DevOps culture of collaboration will mature into one of co-creation. Developers, IT, and business teams will share real-time feedback loops powered by AI insights—turning operations into a continuous improvement engine instead of a bottleneck.
Yaniv Masjedi, Chief Marketing Officer, Nextiva
Observability Becomes Lightweight; ITSM Shifts to a System of Record
Full-stack observability will evolve into lightweight aggregation and normalization layers, while ITSM will increasingly serve as the system of record for auditability, change, and compliance. Intelligence and orchestration will shift to adaptive AI layers, minimizing tool lock-in and enabling modernization without disruptive re-platforming. This architecture will favor flexibility, interoperability, and faster time to value
Casey Kindiger, CEO, Grokstream
SDD Will Continue Gaining Traction
Spec-Driven Development (SDD) is expected to continue gaining traction in 2026, largely due to the growing need for effective governance and guidance of AI Agents across both ends of the DevOps spectrum. New standards such as Spec Kit will serve as authoritative references for design, task management, and workflow execution, enabling teams of AI Agents and humans to speed up product release cycles. DevOps tools will adapt in support of this transformation, enabling Agentic workflows via standards such as the Model Context Protocol (MCP). With machine-readable artifacts (specs) as the ground truth, code & infrastructure generation becomes more deterministic and consistent. SDD offers a shared language usable by developers, operations, security, and AI tooling to align across concerns.
Steve Tranchida, Vice President, Architecture and Strategy, Verinext
Disillusionment of AI Hype in DevOp
As far as DevOps is concerned, I predict that in 2026 we will witness the trough of disillusionment from the promises that the AI hype has been promising. While AI has proven itself in other fields, for the accuracy and repeatability that engineering practices such as DevOps require, new models will need to deliver on rather than the LLMs and Generative models. We will also realize that, in general, engineering jobs are still highly sought after, as AI agents have not replaced, but rather raised the stakes for skilled engineers needed to govern and deliver production-grade code, rather than smaller proof-of-concept ones.
Ian Amit, CEO and Co-Founder, Gomboc AI
On Project Post-mortems And The Need For Boardroom Visibility
Leaders are under pressure to implement AI, and IT wants to say “yes” as much as they can, but organizations that move too far and too fast with AI risk getting in over their head and drowning. When that happens, it’s not pretty for the organization. We’re going to see more signs of fallout from such events throughout 2026, including where blame will be placed, whether that is on the technology itself or on individuals tasked with building or leading it. This is a breaking point for AI strategy to become a boardroom conversation and the focus needs to be “Are we ready to do this right now and do we have checks and balances to determine if we are ready?” Organizations that are more mature will be better positioned to weather these challenges than younger businesses and startups that aren’t yet firmly established but still are still trying to harness AI.
To some degree, leaders will need to have something akin to a postmortem to identify problems that they should have discovered sooner, before the situation got out of hand. By establishing stronger foundations, readiness assessments, and shifting away from L&D consumption metrics, organizations can better determine how ready or not ready they are to effectively implement AI tools into their processes.
Drew Firment, Vice President of Global Partnerships, Pluralsight
Coders Will Be Optional
In 2026, the IT bottleneck breaks as no-code tools put integration power into everyone’s hands. Employees will automate workflows and build solutions without relying on developers or complex code. Complexity will no longer be a strength; it will be a liability.
Steven Pappadakes, Founder & CEO, NE2NE
Incident Management is Changing
Balanced Vibe Coding
Vibe coding is not a fad, but it’s also not a silver bullet that will replace disciplined software engineering. Companies will embrace vibe coding as a powerful accelerator for the user-facing layers of your application, but for the mission-critical core of the stack, companies will empower their developers by augmenting their skills with context-aware tools and rely on a trusted, well-architected, and unified platform.
Mohith Shrivastava, Principal Developer Advocate, Salesforce
DevOps Will Include Security & Compliance From The Start
Grounding AppSec in Reality
The Continued Scaling of AI Agents by DevOps
A Shift Toward Real-time, Parallel Validation
Build-and-release Pipelines
DevOps Will Fully Absorb the Data Layer
The Credential is The New Compute
For the last decade, the competitive edge in AI was defined by compute: whoever had the biggest GPU clusters won. That era is ending. In the next phase, the constraint isn’t model capacity; it’s access. The most capable agents will be the ones that can act on behalf of users and systems, not just predict text. Every meaningful AI capability, from automation to decision-making, depends on credentials: API keys, OAuth tokens, service accounts. That’s what turns intelligence into action. And that’s why the companies that master secure credential brokering: verifying who an agent is, what it can access, and how it uses that access, will define the next generation of AI infrastructure. The future of AI scale won’t be measured in FLOPs; it’ll be measured in permissions.
Nancy Wang, SVP, Head of Engineering, 1Password
Innovative Approaches to Measuring Developer Experience
In 2026, organizations will adopt innovative approaches to measuring Developer Experience, linking it directly to business outcomes. For example, organizations might aggregate several metrics and/or build customized metrics tailored to their unique operational needs.
Rebecca Dilthey, Director, Solution & Customer Marketing, Rocket Software
Kubernetes Will Lose Its Shine
Kubernetes will lose its shine as an auto-include for application stacks in 2026. As cloud costs spiral, enterprise architects are starting to ask why an app serving 100 internal users need its own clusters of high-margin VMs around the clock and a $400,000/year specialist to keep them running. Hyperscale CSP-managed services now handle exotic workloads just as well — and everything else will migrate to simpler, cheaper hosting approaches.
Ryan McElroy, Vice President of Technology, Hylaine
A Shift From Direct Execution to System Design
In 2026, engineers will act as orchestrators of virtual AI agent teams, defining each agent’s role, rules, tools, and collaboration patterns next year. Their job will shift from direct execution to designing systems of intelligence that align with business outcomes. Success will depend on setting checkpoints and KPIs that guide autonomous workflows and adjusting them when they drift, and they will also design new testing methods to validate non-deterministic, agentic systems.
Tal Levi Joseph, VP of Product & Engineering, OpenText
Resilient Internal Platforms That Act as Unified Ecosystems
In 2026, we will continue witnessing the shift in DevOps from building pipelines towards creating resilient internal platforms that act as unified ecosystems. In turn, team members will no longer be seen as manual pipeline operators: their role as platform providers will give them more power when it comes to decision making and risk management. Plus, AI further speeds up this shift by automating processes and preventing failures.
Every year, the DevOps community asks whether DevOps is dying. Our team, however, is convinced that while the label may eventually lose its relevance, the skills and principles that define DevOps will remain. Automation, shared ownership, and constant monitoring are not going anywhere! They are getting absorbed into new roles such as platform engineering and site reliability engineering. DevOps definitely isn’t dying; instead, it’s becoming the default way to build and maintain software.
Bruce Mason, Delivery Director at QArea
Smarter Collaboration
The next evolution of DevOps isn’t about more tools, it’s about smarter collaboration. Teams that combine automation with ownership will define reliability in the AI-driven era. In 2026 and beyond, DevOps will move from continuous delivery to continuous intelligence, where systems not only deploy faster but also learn, adapt, and heal themselves.
Afaq Ahmed, Senior DevOps Engineer, Vodworks
AI Maturity: From Experimentation to Understanding
The early excitement around AI led to a kind of experimental chaos. But 2026 will likely mark a new phase of restraint and rational assessment.
Teams are beginning to understand where AI genuinely excels: pattern detection, test generation and repetitive code scaffolding. They’re also clearer about its limits. AI is less effective where human context and creative problem-solving still drive value. This growing maturity will see AI deployed with intention.
As organizations gain familiarity, they’re aligning AI strategies with measurable business outcomes. Leadership teams are re-evaluating ROI and focusing on results that can be sustained. The use of AI is evolving from “everywhere, all at once” to targeted implementation backed by experience.
Tim te Beek, Solutions Engineering Manager, Moderne
Increased Integration of High Availability Clustering Into Application Planning
Clustering tools with robust APIs, automation hooks, and real-time observability will allow rapid updates without interrupting production services. DevOps engineers will use clusters to test patches against active workloads, reducing the risk and degree of change. HA becomes a built-in feature of the delivery process—not an afterthought.
Dave Bermingham, Senior Technical Evangelist, SIOS Technology
AI-Driven Security Becomes the Core of DevSecOps
In 2026, security won’t just be a checkpoint—it will be an intelligent partner in how we build and deliver software. AI will transform DevSecOps from reactive to predictive, spotting vulnerabilities before they become risks and automating compliance, so it happens in real time, not after the fact. This means our systems will self-heal and adapt as threats evolve, giving businesses confidence that innovation doesn’t come at the cost of security. Companies that embrace this shift will move faster and safer; those that don’t will find security becoming their biggest bottleneck.
Brady Lamb, Sr. Manager DevOps, Security, and IT, Recast Software
Greater Traction For Security and Privacy
I expect security and privacy to gain even greater traction across the component ecosystem in 2026. As editors, SDKs, and plugins become deeply embedded in critical business workflows, teams are taking a closer look at what data flows through them and where it’s stored. Single-purpose, unconfigurable tools will likely fall behind. In an environment where technology evolves weekly, software that can’t integrate or adapt simply can’t keep up. The trend is shifting toward flexible, extensible components that evolve with the stack rather than isolated features frozen in time. By 2026, we’ll start to see “Track Origin” features appear in editors. More and more content already includes notes that it was created or assisted by AI, and users will expect that transparency to be built into their tools. Each edit will clearly show who or what created it, the source, and any policy details, all in a single history view. As trust and compliance grow in importance, this level of openness will shift from a nice-to-have to an expectation.
Ondřej Chrastina, Developer Advocate, CKEditor
A Blind Spot For Agentic AI Systems In DevOps Environments
One of the biggest blind spots from agentic AI systems we will see in 2026, particularly in DevOps environments, is how they inherit and act on the existing access rights of users. An agentic AI doesn’t just answer questions – it takes actions on behalf of people. If you don’t have a framework to ensure the AI is constrained by the same permissions and context as the human, it can accidentally overstep, exposing sensitive systems or data.
Steve Touw, co-founder and CTO, Immuta
Continuous Validation Loops Replace Traditional Deployment Gates
AI Continues To Set Blazes In The DevOps Space
In 2026, we stop trying to beat the old thing into some new AI solution and start using AI to augment and improve what we already have. We finally stop chasing the “I can solve this with AI” hype and start focusing on “How can AI help me solve this better, faster, cheaper.” The AI overhype bubble bursts as we discover sane ways to integrate.
Brett Smith, Distinguished Software Developer, SAS
Wield AI or get wiped out
AI will deepen the arms race and the need for ‘proactive security’. Attackers are already using LLMs like DeepSeek to weaponise known vulnerabilities. What used to take state-level capability is now accessible to a teenager with a jailbroken model. Defensive teams will need to “fight fire with fire,” embedding AI into triage, discovery and response just as aggressively. The momentum is real, but speed is survival. Hesitation is the new vulnerability. By the end of 2026, over 70% of enterprise security teams will deploy AI-based tools for triage, detection or response.
Laurie Mercer, Senior Director of Solutions Engineering, HackerOne
Self Securing AI
In 2026, we will see the emergence of ‘Self-Securing AI.’ As AI becomes a core dependency in modern software, reactive tools like attack analysis and detection will no longer suffice. The entire lifecycle — from data ingestion to model training to deployment — must be treated as part of the software supply chain and ‘self-secured’ accordingly. In the race to embed ‘good’ large language models (LLMs) into AI software, organizations will realize that choosing the right model is just the beginning, as the differentiator will be AI that is secure by design and continuously self-securing.
Javed Hasan, CEO and Co-founder, Lineaje
Quality at Scale
