ITOps and DevOps Trends and Predictions 2025 From Industry InsidersITOps and DevOps Trends and Predictions 2025 From Industry Insiders

We've published our IT operations predictions for 2025, providing six trends that should impact ITOps and IT service management (ITSM) in the new year — as well as predictions of what won't happen in the tech realm.

Do those in the IT trenches agree? Below, IT leaders and industry insiders share their 2025 ITOps and DevOps predictions:

What the Tech Industry Expects from IT Operations & Management in 2025

IT Teams Should Shift the Perception of IT to Be Margin Drivers

CIOs need to come to the table ready to partner and prosper, as opposed to presenting their teams as a legacy IT department focused exclusively on run costs, licenses, etc. IT is a profit optimizer, and it empowers a company's growth through making every part of the organization do their jobs more efficiently. — Bobby Cain, North American CIO, Schneider Electric

State of IT in 2025: Remigration to On-Premises

With rising IT costs driven by increased license fees from major vendors and soaring hyperscaler bills, many organizations are facing budget crises. In 2025, we predict a shift as companies begin moving workloads back from the cloud to on-premises or co-locations to reduce operational expenses. — Sascha Giese, Global Tech Evangelist, Observability, SolarWinds

Related:Cloud Trends to Watch in 2025: Sustainability, Supercloud, and a Shift Beyond Edge

Budget Pressures Intensify

IT cost concerns are growing louder, with forums like Reddit capturing frustrations from struggling organizations. CIOs face mounting challenges defending budgets and proving IT's value. Without solutions, many will scale back services, risking operational efficiency. — Sascha Giese, Global Tech Evangelist, Observability, SolarWinds

The 'Do More with Less' Mantra Demands Greater Collaboration

We still see individual IT units working in silos and only taking care of their direct responsibilities. This leads to communication problems and is the No. 1 reason projects get delayed, become too costly, or fail. We must remember that IT is about more than technology; humans are also involved. — Sascha Giese, Global Tech Evangelist, Observability, SolarWinds

Runtime Security Will Redefine Application Protection

As microservices and cloud-native apps become the standard, protecting applications during runtime will be crucial. Next-gen security solutions will monitor and defend live environments in real-time, detecting and blocking threats attempting to exploit vulnerabilities as they arise. This will include advanced protection against zero-day attacks, privilege escalation, and container escapes, all integrated into DevSecOps workflows to ensure proactive and seamless defense. — Jimmy Mesta, CTO and founder, RAD Security

Related:6 Software Development Trends to Watch in 2025

Organizations Will Retire Outdated Gear

Legacy technologies still dominate industries like finance and healthcare due to technical debt and inertia. However, as businesses seek agility and efficiency, more organizations will finally retire outdated gear and solutions, accelerating their digital transformation. — Sascha Giese, Global Tech Evangelist, Observability, SolarWinds

People Who Comprise the Workforce Are Most Important Assets

CIOs will lean on their staff for input, clarity, and ongoing assessment to build a high-performance culture. Offering employees digital training and development programs in cutting-edge areas like AI will allow team members to build their skillsets, strengthen the organization's technical talents and build the next generation of leaders. — Bobby Cain, North American CIO, Schneider Electric

Network Downtime Due to Misconfiguration Will Approach Zero

Over 40% of network outages are directly caused by misconfigurations, and can cost businesses 9% of their total annual revenue. As such, one of the most promising developments on the horizon is the potential for AI to virtually eliminate these manual misconfiguration mishaps. Intelligent, automated tools can execute automated workflows throughout the network lifecycle and provide traceability for every action. AI-driven tools are set to revolutionize network management and assurance, learning and benchmarking from each configuration to reduce errors and ensure uninterrupted operations. We will see misconfigurations decline rapidly as AI adoption grows, making automation accessible to more organizations, and we expect to see network downtime caused by human error rapidly approach zero. This is good news! Because as businesses increasingly rely on digital platforms, continuous network uptime becomes a critical resilience component directly tied to customer satisfaction and operational efficiency. — Liz Centoni, Executive Vice President and Chief Customer Experience Officer, Cisco

Related:ITOps in 2024: AI, Open Source, and the Challenges of Overstretched Teams

Profiles and Traces Converge

While traces and profiles have their unique benefits, 2025 will see their increasing convergence as organizations seek deeper insights into application performance. Traces excel at showing end-to-end request flows, while profiles reveal detailed system resource usage — by combining these tools, teams gain visibility into their applications that manually added spans never could. For example, when a trace shows a 400ms span, corresponding profile data can reveal exactly which code executed during that time period, down to the specific functions and their resource consumption. This allows teams to pinpoint performance bottlenecks with surgical precision, leading to more efficient optimization efforts and reduced operational costs. In the coming years, especially as profiling becomes stable in OpenTelemetry, forward-thinking organizations won't just be collecting traces and profiles — they'll be treating them as interconnected, contextual data streams that provide a holistic view of system performance and efficiency. — Ryan Perry, principal product manager, Grafana Labs

Transforming Enterprise Architecture with GenAI

In 2025, GenAI will transform enterprise architecture, driving organizations into a new era of software development, governance, and operational efficiency. Autonomous agents, new models like LAM (Large Action Models), and a recursive loop where GenAI is creating GenAI will drive the next iteration of products. In the past, emerging technologies have been difficult to procure, and significant investments are needed to make them a reality. Enterprise adoption will accelerate with GenAI tools available through SaaS models and affordable subscriptions. The subscription model enables even the smallest organizations to leverage AI capabilities that were once only available through hefty investments. In 2025, companies will harness GenAI to redefine processes, improve operational agility, and accelerate innovation cycles. GenAI will become a competitive advantage for enterprises across industries. — Jason Aitchison, senior director — transformational architecture practice lead, Launch by NTT DATA

IT Budgets to See Small Increases

I see organizations investing more in technology overall in 2025, but I don't think there will be a huge increase in IT budgets. Generative AI has fueled a lot of excitement in the last few years, but organizations have to be careful to not over index the technology in budgeting. Even internally, we're focusing on working with the tech stack we have now after a couple years of ambitious investments in new technology, and I anticipate others will follow a similar pattern. Organizations will be focused on tracking the value of their current tech stack instead of buying new add-ons or platform products, especially as the pressure to incorporate GenAI stretches organizations' budgets in other areas. At the end of the day, it's not possible to have all the latest and greatest technologies and I predict that organizations will focus on really assessing needs vs. wants. — Steve Watt, CIO, Hyland

2025 Will be the Year Observability Stacks Break Apart

Observability stacks are likely to become more disaggregated as companies move away from monolithic, all-in-one solutions to specialized, best-of-breed tools. As data volumes and complexity grow, teams will demand more flexibility in how they monitor and manage their infrastructure. This shift will result in observability stacks breaking into distinct layers —such as metrics, logs, traces, and events — each optimized with dedicated solutions. Disaggregation will enable more tailored observability strategies, greater scalability, and cost efficiency, as businesses can choose the most effective tools for specific parts of their systems rather than relying on a single, unified platform. — Kishore Gopalakrishna, co-founder and CEO, StarTree

FinOps Adoption to Face Uphill Battle  

FinOps talks a big game, but have FinOps practices really shifted left, or is it still centralized at most companies? While the idea of integrating FinOps early in the process sounds great, many organizations still need help to make this shift. Even FinOps practitioners admit to not having widespread buy-in yet, suggesting that it's more of an aspiration than a reality for many. — Bill Buckley, senior vice president of engineering, CloudZero

The FinOps Role Will Need Redefining

The expectations for FinOps professionals are growing unsustainably broad, which will prompt a need to redefine these roles. For instance, many job descriptions ask FinOps professionals to have DevOps, architecture, and accounting skills — essentially, wearing all hats simultaneously. This could spark debates within the community about whether the role needs more specialization or if companies are setting themselves up for failure by demanding too much from too few people. This could be one reason why the market doesn't seem to have caught up in terms of hiring for FinOps roles. In 2025, organizations must look closer at how they define these roles and reevaluate the talent they seek. — Bill Buckley, senior vice president of engineering, CloudZero

Increased Reliance on Cross-Region, Multi-Cloud Failover Clustering

To achieve stronger resilience against regional outages, enterprises will adopt cross-region and multi-cloud failover clustering strategies. These setups will allow critical applications to failover seamlessly across different cloud regions or cloud providers, ensuring continuity even in cases of large-scale disruptions. This trend will drive demand for clustering solutions capable of handling complex, geographically distributed infrastructures and automating failover processes across subnets and cloud regions with minimal manual intervention. — Cassius Rhue, vice president, customer experience, SIOS Technology

Always-On Monitoring: The Future of Automated High Availability Clustering for APM

High availability (HA) clustering with Application Performance Monitoring (APM) tools will become more streamlined and automated, making it easier to maintain continuous monitoring without disruptions. HA clustering solutions will feature improved integration with APM platforms, offering seamless failover, predictive analytics for proactive issue resolution, and reduced setup complexity. Users can expect more self-healing capabilities, where clusters can detect and address performance issues automatically, minimizing manual intervention and ensuring that critical monitoring remains active around the clock. — Cassius Rhue, vice president, customer experience, SIOS Technology

More Time and Resources Will Be Spent on IT Consolidation

Over the coming months, expect IT consolidation to become more urgent as more companies realize the productivity and data challenges of having too many disconnected tools. All the time lost shifting from app to app, verifying or correcting data, and navigating disparate processes and bespoke workflows, eats into productivity. Meanwhile, IT pros are under pressure to get that tech sprawl under control, even as they lose valuable time trying to manage all those apps, integrating them across teams and projects, and dealing with the hidden costs of upgrades, customization, and maintenance. Our own survey proved this out, with 68% of the 1,000 IT pros reporting they spend 10 hours a week, or more, managing and maintaining software applications. It's no wonder that 56% of those same IT pros said they expect to be spending more time and resources on IT consolidation over the next year. All that sprawl creates an unsustainable ecosystem of too much tech and too much time spent keeping it under control. It's time to tame that sprawl and use technology to get work done. — Dalan Winbush, CIO, Quickbase

 Re-evaluating Cloud vs. On-Prem Decisions

Enterprises, especially in regulated industries, will adopt a more structured and informed framework for deciding which applications will run in public clouds vs. in private cloud/virtualization infrastructure. This will be driven by performance, governance and cost considerations, as well as security. The automatic assumption that every new application needs to run in a public cloud has been losing its inertia as infrastructure and operations teams realize that, in some circumstances, they can do a better job with less effort and cost on-prem, and that not all applications need the on-demand elasticity enabled by public cloud providers. — Rani Osnat, SVP strategy, Aqua Security

Observability into the Toolchain Will Be More Important Than Ever

Observability, already a cornerstone of modern deployment processes, will increasingly extend to software builds and the broader developer toolchain. As distributed systems, microservices, and AI-driven code generation make development environments more complex, pinpointing issues like bottlenecks, test failures, and errors will become more challenging without robust observability tools. Greater visibility into these processes will be critical for maintaining efficiency and quality. — Brian Demers, developer advocate, Gradle

Achieving Balance Between Innovation and Security in 2025

Executives and leaders responsible for building systems sometimes confuse process control with security. Adding more checks, inspections, and audits can provide greater visibility, but often doesn't correlate with increased security and can increase costs as well as reduce capacity for innovation and creativity. "Secure by design," an emerging initiative in the IT industry, provides an alternative that calls for security to be integrated deeply into the design of products. In 2025, we can expect the increased use of modern tools with better designs that are not only more secure than legacy alternatives, but are more efficient, allowing teams to be more productive. — Michael Allen, CTO, Laserfiche

Demand for Robust Remote Remediation Solutions Will Intensify

2025 is set to be a pivotal year for IT support teams managing enterprise device fleets. As cyber threats become increasingly sophisticated, with a surge in Denial-of-Service (DoS) attacks and other disruptive tactics, IT departments are under mounting pressure to maintain seamless device uptime. Simultaneously, the ongoing shortage of skilled IT support staff is creating significant challenges, particularly in teams responsible for maintaining business-critical systems. With remote work expected to continue similar year-on-year growth seen from 2023 to 2024, demand for robust remote remediation solutions will only intensify in 2025. These will be essential when it comes to managing everything from basic troubleshooting to restoring unbootable laptops from afar. As organizations strive to minimize downtime and avoid costly device replacements, especially where it involves coordinating returns with distant employees, holistic solutions for remote management will become vital to ensuring business continuity. — Marcos Razon, SVP and Division President of Lifecycle Services & Customer Support, HP

The End of SLAs and New Pressure for Proactive IT Support

The way we measure the success of IT teams will change drastically in 2025. Service level agreements will become moot points as all eyes will be on preventing unforeseen disruption, not on how fast it can be fixed. The measure of IT services success will become less about productivity, and more about fulfilment. As computers become more capable of autonomously executing processes, monitoring outcomes, and ensuring reliability, IT teams will spend an increased amount of time focusing on how their work supports the employee experience, and less on issues management. — John Gordon, SVP and GM, HP Managed Solutions

Evolution of FinOps Practices

2025 will mark the end of operational FinOps, shifting from operational cost managers to strategic value enablers. This transformation will be driven by two factors: the increasing complexity of hybrid cloud environments and the C-suite's growing focus on technology ROI. Organizations that fail to make this transition risk being left behind as cloud costs continue to accelerate. This will create disruption for FinOps teams that are used to being operators and not strategists, and will challenge the notion of DIY/Native tooling usage. — Kyle Campos, chief technology & product officer, CloudBolt

Digital Workspaces Will Become Ubiquitous

In 2025 organizations will broadly adopt digital workspaces that provide the distributed workforce with consistent and secure access to resources. These environments will be more flexible and heterogenous than prior iterations offered as single-vendor stacks by industry giants. IT teams will realize that crafting a more vendor-independent digital workspace solution allows them to future-proof their infrastructure against unanticipated technology disruptions. There are many up-and-coming providers in this space, and they'll get increased attention. — Karen Gondoly, CEO, Leostream

Demand for Cost Efficiency and Resiliency in VDI and DaaS

Looking into 2025, we'll see an increase in demand for cost efficiency coupled with robust business continuity and resiliency in virtual desktop solutions. These themes are echoed consistently by our customers who are asking questions like, "How do I ensure my AVD desktops remain accessible at all times?" and "How can I meet stringent continuity requirements?" The shift to cloud VDI solutions has brought many benefits, yet with the growing focus on uninterrupted access, we expect to see an evolving approach to meet both budget and reliability needs. — Amol Dalvi, VP of product, Nerdio

Resurgence of On-Premises VDI Solutions

I anticipate a resurgence of on-premises VDI solutions in 2025. Azure Stack HCI could offer a VDI option for organizations that require specific data residency or regulatory control, face bandwidth challenges, or may not be fully comfortable relying solely on the public cloud. This trend would be especially significant for highly regulated sectors like healthcare, financial services, and federal government agencies, where tight control over data location and access can be critical. We're even seeing an uptick in interest for environments where a completely disconnected setup — think submarine-level isolation from the internet — is a real business requirement. — Amol Dalvi, VP of product, Nerdio

Balancing AVD's Versatility with Windows 365 Integration

As we look ahead, it will be fascinating to see how the market balances these options — whether enterprises lean more into the maturity and flexibility of AVD or focus on the pre-packaged option of Windows 365 for their evolving workforce needs. The decision will hinge on each organization's unique needs for both flexibility and operational continuity. — Amol Dalvi, VP of product, Nerdio

Visibility Into User Experience with Cloud-Based Apps Becomes More Important

As companies reverse many of the remote and hybrid work models of the last several years, visibility and observability among corporate offices and remote locations will be increasingly important in 2025. Similarly, as enterprises roll out new cloud-based AI applications and integrations, if "User Experience" is a focus going forward, as some suggest, then maintaining visibility into the performance and user experience (UX) of cloud-based applications needs to be a top priority. Unfortunately, too often, it is difficult for organizations to appreciate the level of visibility they need until after their employees or customers encounter UX issues with their mission-critical applications. — Eileen Haggerty, AVP, NETSCOUT

Enterprises Will Unlock AI Potential in 2025 Through Cost Optimization, Empowered by FinOps

I believe enterprises will transform AI project viability through more purposeful cost optimization, with FinOps teams becoming critical enablers. I expect we'll see many more organizations begin to pair AI initiatives with automated provisioning, real-time cost data, and sophisticated cost controls to reduce their AI investment risks. Getting this right will turn potentially unsustainable long-term AI initiatives into measurable, financially responsible innovation engines. — Tzvika Zaiffer, director, Solutions, Spot by NetApp

Enterprises Will Tackle Data Integration — the Blocker Between Truly Unlocking AI Today and the Path to the Autonomous Enterprise

In 2025, CIOs and IT leaders will need to prioritize data integration to truly unlock the potential of AI, now or down the line. The traditional approach of managing hundreds of disconnected applications is no longer sustainable. Enterprises that will excel in the AI era will be those that can effectively reason and act on data at scale through strong integration. Integration strategies must evolve beyond simple system connectivity to become intelligent orchestration layers that can reason on petabytes of unstructured data. To attain a solid foundation and agile integration system, organizations need to break down data silos and consolidate redundant point solutions — currently some of the biggest bottlenecks plaguing AI innovation. Success will be measured by how quickly organizations can adapt their integrated systems to changing business needs. Being able to create intelligent action (autonomous or not) relies upon a composable architecture, starting on the journey today will enable organizations to deploy cutting edge solutions much faster. — Rich Waldron, CEO and co-founder, Tray.ai

AI Will Introduce a Reorganization of Enterprise Engineering

As engineering teams rapidly adopt AI technologies, enterprises will face a growing risk of AI silos, with different departments implementing varied AI solutions and creating convoluted data architectures across organizations. However, this challenge is driving the emergence of unified AI platforms that will fundamentally reshape how engineering teams operate. Just as database management systems arose to address data silos, these new platforms will serve as abstraction layers across an organization's AI initiatives, providing a single interface for managing AI resources. The most profound change will be in how engineers interact with these systems. Natural language interfaces will increasingly replace specialized query languages, democratizing access to technical systems. Organizations that move quickly to establish unified AI architectures will gain significant advantages, but success will require viewing AI not as just another tool, but as a fundamental layer of the technical stack that requires enterprise-wide coordination and governance. — Gopi Duddi, SVP of engineering, Couchbase

Remaining Relevant in Increasingly Digital-First Landscape

Businesses in industries that are traditionally slower to adopt newer technologies — such as banking, government, and pharmaceuticals — will embrace comprehensive digital transformation in 2025 as an existential imperative. These organizations will systematically build data-driven cultures, complete cloud migrations, and implement AI/ML solutions — not merely to modernize, but to remain relevant in an increasingly digital-first competitive landscape. — Anil Inamdar, head of consulting services, NetApp Instaclustr

OpenTelemetry Opens New Paths to Value from Observability

The industry-wide move to OpenTelemetry's open source agents will make it significantly easier for organizations to switch between observability solutions and update their strategies. Previously, organizations were effectively locked into APM vendors because they'd have to replace proprietary agents across hundreds or thousands of servers — a massive barrier to change. Organizations will extract more value from their observability investments through OpenTelemetry's extensibility. Rather than being limited to basic application performance management, organizations can now layer new capabilities on top of their OpenTelemetry data, pulling extra value from their existing observability investments. This lets teams add new capabilities like architectural documentation and real-time architecture mapping. — Moti Rafalin, CEO and co-founder, vFunction

Architecture Insights Will Become Essential for Modern Observability

As applications grow more complex, traditional approaches to observability must expand to address architectural challenges that are often the root cause of many performance and scalability issues. While today's solutions excel at performance monitoring and outage detection, standard observability must evolve to help teams better understand how architectural decisions and patterns impact system reliability and performance. Architectural observability will emerge as the next value layer in the observability market, complementing existing strengths in APM observability tools. Providing teams with a way to visualize architecture, identify architectural drift and complexity will help them reduce mean time to resolution (MTTR) and better maintain application resilience and scale. Particularly with microservices, which are highly likely to experience sprawl as AI becomes more sophisticated in writing code, architectural observability will be essential for maintaining real-time application visibility, identifying issues, and supporting a strong foundation for development. — Moti Rafalin, CEO and co-founder, vFunction

Accelerated Shift to Outsourced IT Services Drives Innovation

The shift toward outsourced IT services will accelerate, with more companies recognizing the advantages of partnering with MSPs rather than maintaining purely internal IT teams. This approach eliminates concerns about staffing, ongoing training requirements, and technology currency while providing access to leading-edge expertise. Companies must keep up with technology to remain competitive and secure in the market, and partnering with MSPs that offer shared services will empower internal IT teams to be stronger and more innovative than they could otherwise be through traditional hiring and training methods. — Russ P. Reeder, CEO, ATSG

Companies Seek Streamlined, High-Impact Tech Solutions

Technology will be made simpler in 2025. The IT industry is full of great products with amazing claims, but many are complicated to use and don't live up to their assurances. In 2025, companies will tire of these products that promise a lot and deliver little, and turn to simple solutions that do one main thing, but do it well and without needing much oversight or maintenance. — David Bennett, CEO, Object First

Connected Sensors and AI Contributing to Plant Reliability Improvements

New sensors and analytics are providing predictive insights into equipment performance — particularly identifying conditions that could lead to unplanned downtime.  With the predictive insights maintenance can be performed proactively versus on a scheduled basis. — Jason Urso, VP and CTO of Industrial Automation, Honeywell

Exploding Costs Drive the Great Observability Shakeout

Incumbent vendors have built their offerings on a mish-mash of proprietary agents, proprietary databases and query languages. The result? As Data volumes have sky-rocketed so too have their bills and — worse — their customers are locked in. OpenTelemetry, Object Stores (such as AWS S3) and Apache Iceberg have provided a new breed of vendors with a standard, low cost, way to collect and store data. These products are based on a completely new architecture built on open standards and priced in a way that doesn't result in the usual overage bill each month. Legacy vendors will inevitably try to make it difficult for customers to switch, but those barriers will fall. Customers should plan now for the coming migration opportunities. — Jeremy Burton, CEO, Observe

Weaponized AI Will Be the Biggest Security Concern in 2025 — and IT teams Will Be Hit Hardest

The biggest security threat we're seeing is the continual evolution of AI. It's getting really good at content creation and creating false imagery (i.e. deepfakes) and as AI gets better at data attribution, it will become even more difficult for organizations to distinguish between real and malicious personas. Because of this, AI-based attacks will focus more on targeting individuals in 2025. Most of all, IT teams will be hit hardest, due to the keys they possess and the sensitive information they have access to. Most AI-based attacks will target individuals to solicit access and money, and IT organizations need to ensure they're prepared, educating staff, and shoring up defenses accordingly. 

The best way to reign in AI risks is with more employee training. People have to know what to be on the lookout for, especially as AI technology evolves. In general, you can't do enough cyber awareness training. It's very real — even beyond AI, there are a ton of ways to compromise an individual system or information, and I think the more that we can educate people, rather than try to curtail the technology, the better. — Mike Arrowsmith, chief trust officer, NinjaOne

Reliance on Third-Party APIs Will Continue to Accelerate

Already, millions of developers use APIs from LLM providers like OpenAI, Anthropic, and Google, exchanging vast amounts of data to power natural language interfaces and other innovations. Platform teams and SREs face the critical tasks of gaining visibility into these integrations and traffic patterns, maintaining reliability for their core applications, controlling costs and ensuring that sensitive data is not leaving the network. Despite the intense demand for AI, internal teams need to carefully scrutinize public LLM integrations to ensure secure, reliable and cost-effective applications in the AI-driven era. — Tyler Flint, CEO and co-founder, Qpoint

Enterprises Will Boost AI Viability Through Strategic Cost Optimization and FinOps Integration

I believe enterprises will transform AI project viability through more purposeful cost optimization, with FinOps teams becoming critical enablers. I expect we'll see many more organizations begin to pair AI initiatives with automated provisioning, real-time cost data, and sophisticated cost controls to reduce their AI investment risks. Getting this right will turn potentially unsustainable long-term AI initiatives into measurable, financially responsible innovation engines. — Tzvika Zaiffer, director, Solutions, Spot by NetApp

The Road to ZeroOps

Over the next year, enterprises will need to make heavy investments to reduce their levels of complexity. Besides the efforts, we won't overcome this in 2025 and not even in 2026. Some companies will focus on moving to SaaS and PaaS platforms, however there will need to maintain certain critical workloads running on legacy systems, until they figure out the best way to migrate. ZeroOps won't happen overnight; to make it possible we need to build our applications resilient by design, trying to apply ZeroOps to a complex existing environment requires an enormous amount of effort and it is not always justified. I believe that in 2025, the use of AI will be so common that we won't need to call it explicitly, the term "AIOps" will then become obsolete over the next 2 years. In 2025 we are going to experience the first wave of AI Agents, as early adopters will start deploying intelligent components in their landscape able to reason and take care of tasks with an elevated level of autonomy. — Efrain Ruh, Field CTO of Europe, Digitate

ITOps and AI: Navigating Liability and Accountability in the Push for Full Autonomy

I see similarities between the auto industry struggle to provide a full-autonomous driving experience, and ITOps trying to deploy a fully autonomous solution for Operations. It is not that the technology is not available, it has to do more with the liability, what happens when an AI Agent makes a mistake with catastrophic results? Who do we blame? The vendor of that software or the company that implemented the solution? Transparency and accountability will play a fundamental role in the deutilization of these new technologies in the future, this will not drastically change in 2025. — Efrain Ruh, Field CTO of Europe, Digitate

IT Will Start to Transition from Reactive to Proactive

In 2025, we can expect to see IT increasingly moving away from a reactive and "break-fix" mindset. Instead, IT professionals will increasingly focus more on proactive detection and preventive action, leveraging the tools and technologies to do so. Monitoring, telemetry, and predictive analytics will become key differentiators, especially in the unified endpoint management (UEM) space as it evolves into autonomous endpoint management (AEM). Furthermore, we will see an uptick in self-service functionalities, especially as new talent enters the workforce. Gen Z, accustomed to having solutions at their fingertips, prefer to handle tasks themselves and solve problems independently. To meet this expectation, more businesses will use conversational interfaces — powered by generative AI-powered agents—and starting to replace classic drag-and-drop and low-code paradigms of interaction. — Joseph George, SVP IT Solutions group, GoTo

The State of IT in 2025

In 2025, we will see an even greater push toward diversified IT infrastructure. It's no longer about being all on-prem, all-cloud, or all-SaaS—companies are finding a need to balance across these platforms to drive efficiency and better manage costs. We've had enough time with these technologies to know what works where, and we're getting smarter about budgeting for them. — Chrystal Taylor, evangelist, SolarWinds

Emerging AI Traction in IT

AI and machine learning are becoming essential tools in IT, helping teams connect the dots between systems and data. Whether it's automating correlation, supporting root cause analysis, or spotting seasonal anomalies, AI is taking on the heavy lifting that used to be manual. It's not perfect, but it's making a big difference in how quickly and effectively we can solve problems. We're also seeing AI integrate more deeply into tools like monitoring, observability, and incident response systems. For example, it can pull data from observability solutions and generate clear, concise summaries for technicians, saving them the time of sifting through raw data. Generative AI is also helping draft responses and even forecast capacity needs, like predicting when storage will run low, which keeps everything running smoothly. — Chrystal Taylor, evangelist, SolarWinds

Tools That May Fall Out of Favor

Traditional monitoring tools just don't cut it anymore. The shift to observability is well underway, and we're also seeing a big decline in homegrown apps. Open-source tooling is so robust and readily available now that spending the time and resources to build and maintain your own solution rarely makes sense. Add to that the growing expectation for IT pros to take on more roles, and it's clear that the tools we use need to help bridge those gaps and support us as we upskill. — Chrystal Taylor, evangelist, SolarWinds

Major Shifts in IT Practices

If they're not already on board, companies need to prepare for generative AI becoming a core part of everyday practices. Whether it's for marketing, coding, or something else entirely, everyone's looking for ways to use these tools to take some weight off their teams. It's not a question of "if" anymore — it's "how soon." — Chrystal Taylor, evangelist, SolarWinds

Weathering Industry Storms

IT implementations will increasingly be seen as a line of defense against external forces that can disrupt a market segment — another reason digital workspaces will prevail. Beyond cybersecurity needs, there will be efforts to improve business technologies to withstand the impact of climate threats and natural disasters, civil unrest, financial crises, supply chain disruptions, and other factors that can impact an industry. Those with modern, flexible, efficient IT environments will have an immense operational edge over those that do not. — Karen Gondoly, CEO, Leostream

Traditional Observability Tools Will Become Obsolete as AI Powers Self-Healing ITOps with Direct Data Access

As artificial intelligence advances, traditional observability tools are expected to become outdated in 2025, heralding a new era in IT. This will occur as AIOps platforms eventually receive raw data streams and symptoms, enabling them to automatically detect issues, determine root causes, and resolve them without human intervention. — Josh Kindiger, president and COO, Grokstream

Moving Beyond 'Hero' IT and Dev Teams to Control Costs and Scale Effectively

Stop building heroes: In the coming year, organizations are going to start paying even more attention to costs and work to control costs as they scale their environments. As they do this, organizations need to stop building heroes in IT and dev teams. Why? There's always one person in an organization who winds up solving all the problems — they are the developers who know the code so well that they get called in every time there's a problem. This is a huge risk for organizations as they scale. Organizations that don't have the appropriate observability practices in place are forces to continue to build these hero environments where they are depending on the same people all the time. — Bill Hineline, field CTO, Chronosphere

AI and Automation Will Take Over Operations

In 2025, AI will become central to data center management, optimizing resource allocation, predicting hardware failures, and managing capacity planning. Automation will extend to self-healing systems capable of resolving issues without human intervention, reducing downtime and operational costs. These advancements will allow IT teams to focus on innovation and strategy while maintaining unparalleled efficiency and reliability in operations. — George Crump, CMO, VergeIO

Organizations Will Risk Digital Chaos Without Full Visibility into 'Spaghetti Architecture' 

Many IT enterprise architectures can be likened to bowls of spaghetti made up of interconnected technologies making integration and visibility a major challenge. As organizations look to modernize their technology estates and focus on automating business processes in 2025, they'll realize that simply adding AI or other "quick fixes" won't magically boost efficiency, enhance customer experience, or help them to remain competitive. With growing technological and business process complexity it's vital that end-to-end process automation is built on solid foundations — otherwise a lack of control will result in digital chaos. To address these challenges in 2025, we'll see a growing focus on process orchestration to tame system landscape complexities and overcome the challenges of "spaghetti architecture." By enabling businesses to streamline and modernize their processes, process orchestration will provide IT and business teams with greater visibility and control. This improved oversight will help them manage increasing complexity and achieve better business outcomes while being able to adapt faster if needed. — Daniel Meyer, CTO, Camunda

Process Orchestration Will Become Higher Priority

AI or automation solutions are no longer the shiny new IT toys, they're becoming increasingly foundational to drive better business outcomes. As a result, they need to be orchestrated end-to-end within your overall business processes. In 2025, we'll see process orchestration rise up the corporate agenda as organizations strive to become more autonomous enterprises and realize greater value from their AI and automation investments. — Jakob Freund, CEO, Camunda

IT Complexity and Best of Breed Reign

Entering 2025, enterprise IT leaders might be facing their biggest conundrum in years if not decades. While there is money to spend — many analyst firms predict healthy IT and cloud budgets in 2025 — there are too many things to focus on and IT must proceed with caution. To compare, the years 2020 and 2021 revolved around two significant and universal mandates: supporting WFH and moving to digital-first or digital-only business models. Today, business leaders have been hearing the steady drumbeat of AI for at least two years now. Yet many organizations aren't prepared. AI requires significant investment across infrastructure, tools, processes, education and training. Meanwhile they must address rising ransomware threats, reduce technical debt, optimize hybrid cloud strategies and implement new platforms for data management, data security and AI. While large incumbent vendors will attempt to convince IT leaders that they can do it all, there are high risks in this approach. Leaders will lean on a best-of-breed approach for better cost economics and advanced capabilities —despite the greater IT management complexities this will bring. — Krishna Subramanian, co-founder and COO, Komprise

IT Leaders Will Get Creative to Deploy AI on a Budget

Many enterprise IT teams are not ready for AI. That's because it often requires new infrastructure, hard-to-find expertise on building and training learning models, unique governance and security solutions, employee training and more. In the 2024 Komprise State of Unstructured Data Management report, only 30% of IT leaders said they will increase the budget for AI. Organizations can go to the cloud for a more affordable approach by experimenting with AI services such as pre-trained AI models from AWS, Azure, Google, IBM and other cloud providers. Rather than developing and supporting a customized AI solution, an organization may get the benefits they need from upgrading to the latest version of their enterprise business applications which likely have AI built in—such as from Oracle, Salesforce or SAP. No-code or low-code AI platforms claim to allow non-technical staff to build AI models without extensive coding knowledge. Finally, being as efficient as possible with data storage by continually analyzing and right-placing unstructured data into the most cost-effective storage will free up funds for AI. — Krishna Subramanian, co-founder and COO, Komprise

What the Tech Industry Expects from DevOps in 2025

Continuous Everything Will Transform DevOps

The future of software development will be defined by Continuous Everything, fundamentally reshaping the CI/CD model. By integrating continuous testing, monitoring, security, and optimization across the entire software lifecycle, businesses will achieve unprecedented levels of automation and efficiency. This shift will streamline processes, enabling faster, more reliable, and secure releases. As a result, teams will be empowered to innovate while automating routine tasks, ensuring that software is not only delivered quickly but also with enhanced security and performance. Continuous Everything will become the cornerstone of DevOps practices, driving agility, resilience, and speed in an increasingly complex technology landscape. —Shankar Mishra, head of DevOps, Talentica Software

GitOps Adoption Will Grow

GitOps — which uses Git as a central source of truth for managing infrastructure and application configurations — offers a variety of benefits. It provides centralized visibility into IT resources, the ability to automate provisioning and simplified automated testing (because teams can run tests against the code stored in Git repositories). GitOps has been around since 2016, but it has only become a prominent DevOps practice recently. Heading into 2025, I see room for GitOps adoption to continue growing as more and more organizations seize upon this valuable DevOps technique. — Derek Ashmore, application transformation principal, Asperitas

Platform Engineering Will Accelerate Application Development

Platform engineering, which provides a company's developers with preconfigured tools and services that they can use to build applications, is another DevOps trend that's not entirely new, but has plenty of room to expand in the typical organization. In 2025 and beyond, I foresee platform engineering adoption continuing as more companies look for ways to accelerate application development by giving software engineering teams the car instead of a collection of car parts, so to speak. — Derek Ashmore, application transformation principal, Asperitas

AIOps Will Drive AI Implementation

AIOps — by which I mean the IT operations and services necessary to support the design, development, testing and deployment of AI tools and services — is another DevOps trend that I think will dominate 2025. The reason why is simple in this case: As companies move from talking about AI to implementing it, they'll need systematic operational practices in place to support mature AI products. — Derek Ashmore, application transformation principal, Asperitas

Policy-Based Governance Will Be a Key Practice for Security and Compliance

Policy-based governance is the practice of defining rules that IT resources must meet using code, then automatically assessing whether the resources align with the rules. Many organizations already have some form of policy-based governance in place, especially if they've been using the cloud for any length of time. As IT environments continue to grow in scale and complexity, policy-based governance will remain critical for meeting security and compliance mandates. — Derek Ashmore, application transformation principal, Asperitas

SaaS Will Be Preferred Model for Deploying COTS

Software-as-a-Service (SaaS) became popular because SaaS deployments reduce the burden placed on DevOps teams to maintain applications and their underlying infrastructure. In this respect, SaaS remains just as valuable today as it was when the SaaS concept became popular two decades ago. Expect SaaS to remain the preferred model for deploying commercial off-the-shelf software (COTS) in 2025 and beyond, and to see more organizations substituting SaaS for apps that they would otherwise have to deploy and manage themselves. — Derek Ashmore, application transformation principal, Asperitas

Cloud Allows DevOps Teams to Exit 'Property Management' Business

The cloud continues to provide enormous value by allowing DevOps teams to exit the "property management" business — by which I mean the business of having to deploy and maintain physical infrastructure. We'll continue to see migration of workloads to the cloud in the coming year as more and more organizations work toward an IT strategy in which virtually everything is cloud-based. — Derek Ashmore, application transformation principal, Asperitas

Serverless Computing Will Unlock Cloud Efficiency for DevOps

Serverless is an example of a type of cloud service that doubles down on the value of the cloud in general. The reason why is that with serverless, not only do DevOps engineers not have to manage a physical server, but they also don't have to provision or monitor any kind of operating system environment. They simply deploy applications as serverless functions. While not all apps are good candidates for a serverless approach, expect to see more and more organizations taking advantage of serverless for use cases where it's appropriate in 2025. — Derek Ashmore, application transformation principal, Asperitas

2025 Sees Rapid Shift to Post-Quantum Cryptography, Breakthroughs in Quantum Computing

In 2025, DevSecOps will continue evolving beyond the "shift-left" paradigm, embracing a more mature "shift everywhere" approach. This shift calls on organizations to apply the right tools at the right stages of the DevSecOps cycle, improving efficiency and effectiveness in security practices. Lightweight analysis in IDEs will help developers catch issues early, while automation integrated into pull requests and CI/CD pipelines will ensure a cohesive "integrate once" approach for core functions such as SAST, SCA, and increasingly DAST, particularly for API security testing. — Dylan Thomas, senior director of product engineering, OpenText Cybersecurity

The Emergence of xOps

As more and more "traditional applications" begin to adopt AI capabilities expect DevOps, DataOps, and ModelOps to converge into xOps. This new-found set of dependencies will dramatically accelerate "AI-aware" Release Orchestration while also challenging operations teams, support teams, QA teams, and more as the line between more traditional declarative applications blur with the new dependencies to LLMs and GenAI capabilities. — Derek Holt, CEO, Digital.ai

Rise of Decentralized Architectures

Architectures will be federated but decentralized. We see examples in things like the Mastodon protocol, a decentralized protocol which Bluesky has embraced and adopted and augmented. This is similar to what Slack did in the past with IRC, and we should expect more analogs in areas of AI training and inference, cryptocurrency, and event-driven architecture. — Robert Elwell, VP of engineering, MacStadium

AI-Driven Vulnerability Remediation in 2025

In 2025, DevSecOps will harness complementary AI models to analyze, generate, and test code against policy guidelines, driving more efficient vulnerability remediation. While GenAI accelerates development, it risks creating workflow bottlenecks as fixes lag. Advanced techniques like symbolic regression and insights from open-source release notes will enhance data flow understanding and vulnerability tracking. Leaders must implement processes and guardrails to seamlessly integrate AI capabilities into DevSecOps systems, ensuring efficiency without added pressure. — Danny Allan, CTO, Snyk

AI-Driven Threat Detection Will Integrate Seamlessly into DevOps Workflows

AI will become fully integrated into DevOps workflows, enabling security to be embedded directly into the development process. With cloud-native environments growing more complex, AI-powered threat detection will continuously monitor applications in real-time, catching vulnerabilities before they can escalate. Rather than interrupting development cycles, AI tools will seamlessly provide proactive alerts and insights, helping teams address security issues as they arise — without slowing down the pace of innovation or deployment. — Jimmy Mesta, CTO and founder, RAD Security

Platform Engineering's Next Frontier: eBPF

eBPF stands at the cusp of a major transformation — what started as a trendy technology will become the backbone of modern platform engineering, fundamentally reshaping how organizations handle observability and security. One significant shift will be the transition of instrumentation responsibility from application teams to platform teams. We're already seeing OpenTelemetry integrate with eBPF, with updates like the OpenTelemetry eBPF Profiling donation which is already helping drive adoption of eBPF. Moving forward we'll see more opportunities for eBPF to create a seamless bridge between system-level data and application telemetry while standardizing how platforms collect and process observability data. — Nikola Grcevski, principal software engineer, Grafana Labs

MLOps Evolution to AIOps

In 2025, we'll see the evolution from traditional MLOps to comprehensive AIOps platforms that manage the entire AI system lifecycle. These platforms will integrate sophisticated monitoring and automation capabilities for both models and infrastructure, enabling predictive maintenance and automatic optimization of AI systems. Teams will adopt practices that treat AI models as living systems rather than static deployments, with continuous learning and adaptation capabilities built into the deployment pipeline. This shift will require new tools and practices for version control, testing, and deployment that can handle the complexity of multi-modal models and distributed training environments. — Haoyuan Li, founder and CEO, Alluxio

AIOps Becomes a Necessity

As enterprises continue migrating to the cloud, AIOps will continue to evolve into an enterprise operational necessity. By unifying observability data with AI-driven insights, businesses can expect better end-to-end visibility, and proactive issue detection and resolution, fortifying security and compliance at scale. — Gab Menachem, VP ITOM, ServiceNow

Return of AI Realism

After two years of AI hype, we will see a return of realism. While we'll continue seeing rapid progress and breakthrough innovations, we will also see disappointment with inflated initial expectations. In fact, AI will not replace human work as fast as many had thought, it's turned out to be less reliable than we hoped, and very few of those startups that built a nice wrapper around OpenAI will be worth billions. Such disillusionment is a healthy and necessary stage in the evolution of generative AI. — David Brooks, SVP of evangelism, Copado

GenAI Will Becme a Core Component of AIOps Products

In 2025, the IT and AIOps landscape will increasingly incorporate GenAI as a foundational element in AIOps products, moving from an enhancement to a core capability. This shift is expected to spur new use cases, where GenAI acts as a bridge between human operators and autonomous systems, enabling more seamless, proactive IT operations. However, achieving a fully automated IT environment may remain challenging, particularly for industries still bound by legacy systems and traditional service models that prioritize full-time equivalent (FTE)-based contracts. Although this labor-intensive model limits the pace of AI-driven change, a heightened focus on cost reduction will drive greater automation adoption. The end-user interface with AIOps with improve, meaning prediction and prevention of issues will also improve. — Ugo Orsi, CCO, Digitate

GenAI Adoption Changes Low-Code Development and Tackles Technical Debt

Low-code teams will finally get serious about adopting functional testing best practices as they realize that low-code + GenAI can produce sophisticated applications that rival pure code solutions. In addition, as GenAI increases the velocity of code development, companies will begin to tackle more complex projects that were impractical in the past. They will finally address mountains of technical debt and spend more time on user experience improvements that require significant coding to realize. — David Brooks, SVP of evangelism, Copado

Consumption-Based Pricing Models Gain Traction

he shift towards consumption-based pricing will likely become more prevalent in the DevOps tool market. This pricing model, particularly for AI-driven products, will allow companies to scale their usage as AI technologies become less expensive. This trend will drive more revenue from existing products and increase usage among larger customers. Companies that can successfully implement this pricing model while delivering clear value through AI-powered features will likely see increased adoption and revenue growth. This shift will also lead to consolidation in the market, with larger players acquiring smaller, innovative companies to enhance their AI capabilities and expand their customer base. — David Brooks, SVP of evangelism, Copado

Code-to-Cloud Security Set to Redefine Protection from Development to Deployment

The convergence of cloud security and application security will drive code-to-cloud approaches to become standard in cloud security solutions. As cloud environments grow more complex, identifying and fixing security issues at the code level before production becomes essential. This approach integrates security throughout the software lifecycle — from development through runtime. With DevSecOps, CI/CD integration, and automated threat response, code-to-cloud strategies streamline security practices, making it easier to trace vulnerabilities back to their source and resolve them quickly. — Gilad Elyashar, chief product officer, Aqua Security

Organizations Will Embrace a Product-Led Approach/Self-service Nirvana

Every enterprise is progressing toward a true self-service platform experience where infrastructure becomes invisible to end users. The journey follows a clear evolution: from basic infrastructure or Terraform, to automated workflows, standardized deployments and ultimately, centralized platform operations delivering true self-service capabilities. The goal is to get to a point where developers and data scientists can simply click a button to get a result, and that is self-service. That is nirvana. Currently, most organizations are still in early stages, focused on basic automation rather than comprehensive self-service delivery. Many companies have fragmented their platform efforts by creating distributed DevOps teams, but this approach needs to be consolidated into centralized platform engineering teams delivering standardized self-service capabilities. Success requires organizations to adopt a product-led approach to platform engineering to efficiently build and deliver internal platforms as a service for developers and data scientists that accelerate application deployment across diverse cloud-native and AI/ML infrastructures. Many organizations start their respective automation journey, but look at each step in the process as an individual action to automate, vs holistically thinking about automation. This nuance results in teams having many distinct steps, each of which is automated, but no uber layer to execute end-to-end workflows. Organizations need to step back and think about the end-to-end workflows that developers and data scientists need; this is the only way to deliver "products" vs "technical features." — Mohan Atreya, CPO, Rafay Systems

Expect a Shift-Left Evolution in DevSecOps

Reinforcing a shift-left approach, 2025 will see a more integrated DevSecOps pipeline, breaking down silos between development, quality, and security teams. This convergence will enable faster releases and reduce vulnerabilities by embedding testing and security checks early and often throughout the pipeline, aided by AI-driven insights. Additionally taking an integrated approach will also provide greater visibility to stakeholders, allowing the ability to track the overall status of an application including development progress, quality and security in order to make more informed decisions and prioritize accordingly. — Udi Weinberg, director of product management, OpenText

ModelOps Will Become a Critical Component of Software Development Lifecycle

While many data scientists and data engineers operate outside the traditional DevSecOps workflow, this disconnect will increasingly hinder their effectiveness. As AI becomes more deeply integrated into software development, ModelOps will emerge as a critical component of the SDLC. By combining DataOps, which focuses on preparing and managing data, with MLOps, which handles the development, training, deployment, and versioning of AI models, ModelOps will provide a comprehensive framework for ensuring the successful integration of AI into the SDLC. — David DeSanto, chief product officer, GitLab

AIOps Teams Will Rise, but Fully Autonomous AI Is Still Years Away

In 2025, we'll see the rise of dedicated AIOps teams to manage AI operations, while the appeal of "agentic AI" (AI acting independently) won't pan out as fast as some people are predicting. As companies adopt more AI, there's going to be a need for specialized AIOps teams. These teams will handle everything from model deployment to managing quotas and security for AI-driven workflows, sort of like how infrastructure teams manage data pipelines. However, the idea of fully autonomous "agentic AI"—AI that runs without human oversight—will remain a distant reality. Real-world complexity will likely prevent us from going fully autonomous in the near future. So many situations require a human in the loop, especially when there's potential for errors. We've seen the most success when AI works with humans, each complementing the other. Autonomous AI without human checks has led to more problems than solutions. So, for now, a balanced approach where humans and AI work together is where we're going to see value. — Eoin Hinchy, CEO/co-founder, Tines

Platform Engineering Will Unburden Developers

Soon, we will see a significant shift: Everything beyond application development will be abstracted to the portfolio level through centralized platforms. This marks the decoupling of "Dev" from "Everything else." Integrating Dev, Ops, and Sec was necessary to reduce the siloed teams, but doing so at the application development level has introduced significant complexity. The "shift left" movement correctly identified the need for earlier involvement in critical processes but also unnecessarily burdened engineers. Developers are now overextended, taking on invisible tasks that consume significant time but remain unseen by the broader organization. These include orchestrating and maintaining tools, processes, and fast-changing requirements. To overcome this challenge, we must shift towards platforms that handle these operational and security responsibilities at the portfolio level, allowing developers to focus solely on building high-quality applications. This will improve efficiency, enhance quality, and restore the velocity lost in the current approach. — Brian Wald, head of global, field CTO, GitLab