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Creating Agility with DevOps and AI-Driven ITSM

Akhil Sahai

There are some IT organizations that are using DevOps methodology but are wary of getting bogged down in ITSM procedures. But without at least some ITSM controls in place, organizations lose their focus on systematic customer engagement, making it harder for them to scale.

Other IT organizations believe that they're too large, complex and/or process-driven to adopt DevOps. Perhaps team members would like to give it a try but fear that their culture is too old-school and would not allow the disruption that DevOps usually brings. However, process is made for users, not the other way around, and an over-focus on process can keep customers from receiving the experience they need.

So then, DevOps and IT service management must not be mutually exclusive anymore. In fact, combining the two offers organizations ways to scale the enterprise and create agility while maintaining control of IT. They gain both speed and process controls. IT Service Management has to be re-imagined for that to happen successfully. By using technologies like AI/ML, ITSM has been re-imagined so much so that DevOps and ITSM are synergistic now. For instance, organizations can track and resolve incidents and create service requests and have them fulfilled in DevOps environments with AI-driven service management in minutes.

AI-Driven ITSM and DevOps Are Colleagues, Not Enemies

With the advent of AI, many such scenarios are made possible. Organizations for example can deploy an AI-driven digital agent available 24/7 to developers to use across multiple channels. Developers can create service requests for sandboxed environments and have them stood up or taken away and add additional capacity to existing development environments, in minutes. The digital agent would understand and classify the intent of requests using AI and resolve these requests automatically without human intervention. If there are approvals involved, such a digital agent will be able to seek approvals and still automate these deployments thus taking significant load off operations teams.

Similarly, incidents may be tracked in the operations environment, service tickets created and may be resolved by using AI-driven automation in matter of minutes. This would help bring much-needed agility in DevOps environments while following the best of IT Service Management practices.

DevOps doesn't eliminate the need for controls and data. Controls still need to be maintained and risks still need to be managed. AI-driven ITSM for DevOps brings new ways to achieve speed and control while driving value through the IT channel and supporting existing ITSM and DevOps initiatives within a company.

A More Perfect Union

DevOps and ITSM are not an either/or proposition. Instead, they need to be integrated so that the best aspects of each yield a result that is greater than the sum of their parts. Organizations will be able to scale quickly while maintaining process controls. Integration tools make this easier, as do AI-based digital agents. Essentially, there's never been a better time to bring AI-driven ITSM and DevOps together. Doing so will yield greater agility, speed, control and growth potential.

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Creating Agility with DevOps and AI-Driven ITSM

Akhil Sahai

There are some IT organizations that are using DevOps methodology but are wary of getting bogged down in ITSM procedures. But without at least some ITSM controls in place, organizations lose their focus on systematic customer engagement, making it harder for them to scale.

Other IT organizations believe that they're too large, complex and/or process-driven to adopt DevOps. Perhaps team members would like to give it a try but fear that their culture is too old-school and would not allow the disruption that DevOps usually brings. However, process is made for users, not the other way around, and an over-focus on process can keep customers from receiving the experience they need.

So then, DevOps and IT service management must not be mutually exclusive anymore. In fact, combining the two offers organizations ways to scale the enterprise and create agility while maintaining control of IT. They gain both speed and process controls. IT Service Management has to be re-imagined for that to happen successfully. By using technologies like AI/ML, ITSM has been re-imagined so much so that DevOps and ITSM are synergistic now. For instance, organizations can track and resolve incidents and create service requests and have them fulfilled in DevOps environments with AI-driven service management in minutes.

AI-Driven ITSM and DevOps Are Colleagues, Not Enemies

With the advent of AI, many such scenarios are made possible. Organizations for example can deploy an AI-driven digital agent available 24/7 to developers to use across multiple channels. Developers can create service requests for sandboxed environments and have them stood up or taken away and add additional capacity to existing development environments, in minutes. The digital agent would understand and classify the intent of requests using AI and resolve these requests automatically without human intervention. If there are approvals involved, such a digital agent will be able to seek approvals and still automate these deployments thus taking significant load off operations teams.

Similarly, incidents may be tracked in the operations environment, service tickets created and may be resolved by using AI-driven automation in matter of minutes. This would help bring much-needed agility in DevOps environments while following the best of IT Service Management practices.

DevOps doesn't eliminate the need for controls and data. Controls still need to be maintained and risks still need to be managed. AI-driven ITSM for DevOps brings new ways to achieve speed and control while driving value through the IT channel and supporting existing ITSM and DevOps initiatives within a company.

A More Perfect Union

DevOps and ITSM are not an either/or proposition. Instead, they need to be integrated so that the best aspects of each yield a result that is greater than the sum of their parts. Organizations will be able to scale quickly while maintaining process controls. Integration tools make this easier, as do AI-based digital agents. Essentially, there's never been a better time to bring AI-driven ITSM and DevOps together. Doing so will yield greater agility, speed, control and growth potential.

Hot Topics

The Latest

Developers building AI applications are not just looking for fault patterns after deployment; they must detect issues quickly during development and have the ability to prevent issues after going live. Unfortunately, traditional observability tools can no longer meet the needs of AI-driven enterprise application development. AI-powered detection and auto-remediation tools designed to keep pace with rapid development are now emerging to proactively manage performance and prevent downtime ...

Every few years, the cybersecurity industry adopts a new buzzword. "Zero Trust" has endured longer than most — and for good reason. Its promise is simple: trust nothing by default, verify everything continuously. Yet many organizations still hesitate to implement Zero Trust Network Access (ZTNA). The problem isn't that ZTNA doesn't work. It's that it's often misunderstood ...

For many retail brands, peak season is the annual stress test of their digital infrastructure. It's also when often technical dashboards glow green, yet customer feedback, digital experience frustration, and conversion trends tell a different story entirely. Over the past several years, we've seen the same pattern across retail, financial services, travel, and media: internal application performance metrics fail to capture the true experience of users connecting over local broadband, mobile carriers, and congested networks using multiple devices across geographies ...

PostgreSQL promises greater flexibility, performance, and cost savings compared to proprietary alternatives. But successfully deploying it isn't always straightforward, and there are some hidden traps along the way that even seasoned IT leaders can stumble into. In this blog, I'll highlight five of the most common pitfalls with PostgreSQL deployment and offer guidance on how to avoid them, along with the best path forward ...

The rise of hybrid cloud environments, the explosion of IoT devices, the proliferation of remote work, and advanced cyber threats have created a monitoring challenge that traditional approaches simply cannot meet. IT teams find themselves drowning in a sea of data, struggling to identify critical threats amidst a deluge of alerts, and often reacting to incidents long after they've begun. This is where AI and ML are leveraged ...

Three practices, chaos testing, incident retrospectives, and AIOps-driven monitoring, are transforming platform teams from reactive responders into proactive builders of resilient, self-healing systems. The evolution is not just technical; it's cultural. The modern platform engineer isn't just maintaining infrastructure. They're product owners designing for reliability, observability, and continuous improvement ...

Getting applications into the hands of those who need them quickly and securely has long been the goal of a branch of IT often referred to as End User Computing (EUC). Over recent years, the way applications (and data) have been delivered to these "users" has changed noticeably. Organizations have many more choices available to them now, and there will be more to come ... But how did we get here? Where are we going? Is this all too complicated? ...

On November 18, a single database permission change inside Cloudflare set off a chain of failures that rippled across the Internet. Traffic stalled. Authentication broke. Workers KV returned waves of 5xx errors as systems fell in and out of sync. For nearly three hours, one of the most resilient networks on the planet struggled under the weight of a change no one expected to matter ... Cloudflare recovered quickly, but the deeper lesson reaches far beyond this incident ...

Chris Steffen and Ken Buckler from EMA discuss the Cloudflare outage and what availability means in the technology space ...

Every modern industry is confronting the same challenge: human reaction time is no longer fast enough for real-time decision environments. Across sectors, from financial services to manufacturing to cybersecurity and beyond, the stakes mirror those of autonomous vehicles — systems operating in complex, high-risk environments where milliseconds matter ...