devopsy.kinsta.cloud

Tag: ITSM

Bringing Trust and Governance to AI-Driven DevOps

At swampUP 2025 in Napa Valley, Alan Shimel sat down with three industry leaders whose companies sit at the heart of today’s AI-driven DevOps transformation: Rahul Tripathi, general vice president and GM of ITSM at ServiceNow; Justin Boitano, vice president of enterprise AI at NVIDIA; and Shlomi Ben Haim, co-founder and CEO of JFrog.

Tripathi, only months into his role at ServiceNow, stressed the importance of grounding product strategy in lived practitioner experience. Having led DevOps teams himself, he emphasized that ITSM remains the “bread and butter” of ServiceNow, but AI integration is reshaping expectations for productivity and security across IT operations.

Boitano reflected on NVIDIA’s long journey from pushing CUDA adoption in 2008—when many thought GPU computing was a stretch—to today, where GPUs and AI frameworks have become central to enterprise computing. He noted that partnerships with companies like ServiceNow and JFrog are critical to building out the ecosystem, particularly as organizations look to infuse AI into every layer of their development lifecycle.

Ben Haim underscored the urgency behind what he called “AI FOMO.” With board-level pressure driving 40% of CIOs to expand AI budgets, enterprises are rapidly embedding AI into software supply chains. For JFrog, that means positioning itself as the “system of record” for DevOps, launching new platforms like JFrog Fly to simplify AI agent adoption while strengthening governance, traceability and security.

Together, the panel painted a picture of an industry balancing excitement with pragmatism. AI agents may not replace developers anytime soon, but they are already changing workflows, tooling expectations, and the economics of software delivery. As the panelists made clear, success will depend less on hype and more on how well organizations align AI adoption with trust, verification, and long-term resilience.

September 12, 2025
Survey Surfaces Incident Management Gap Between DevOps and ITSM

A survey of 505 software developers, IT professionals and IT decision makers (ITDMs) in the U.S. finds that 70% of respondents work for organizations that hold developers responsible for deployments, with only 22% practicing conducting blameless post-mortems.

Conducted by Atlassian, the survey also finds only 60% of respondents work for organizations where developers are part of the team managing IT incidents, with 57% reporting developers are on call when needed. A total of 70%, however, report it is easy to bring in the right teammates when needed.

Most respondents (86%) are also running postmortem or post-incident reviews (PIR) after an incident. A full 97% also report having procedures, processes, or runbooks in place for managing incidents, with 78% using wargames or some other form of incident management training.

Overall, the survey finds IT incidents are nearly all managed by an IT operations team (95%). Besides developers, other teams involved include engineering (53%), executives (43%) and site reliability engineers (37%).

However, the survey also finds only 15% of respondents have cross-functional teams that include developers, operations staff and other IT professionals and only 35% said their organization emphasizes DevOps as a cultural shift that merges development and operations teams. Only 30% highlighted the use of automation and continuous integration/continuous delivery (CI/CD) practices to streamline workflows, reduce manual operations, and ensure faster and more reliable software delivery.

Additionally, only a quarter (25%) associate DevOps with improving the speed and efficiency of software development, and even less (20%) are focused on the role DevOps plays in improving software quality and reliability through automated testing, continuous monitoring and real-time performance tracking. Only 15% said security and compliance is a top priority within their DevOps practices.

Nevertheless, 96% said they feel development and operations teams have the visibility needed to do their jobs effectively in a way that minimizes disruption. A full 70% said their organization can access incident history, recent deployments or recent changes for context during incident response but only 55% have access to live service health information.

More than two-thirds of respondents (68%) work for organizations that proactively manage IT incidents, the survey finds. Nearly all (99%) are using monitoring tools, with 86% relying on them to discover incidents. Nearly three-quarters (73%) said they are using those tools to proactively discover incidents before they are reported by end users or customers.

Capacity planning (80%), artificial intelligence (AI) for incident trending (74%) and user transaction monitoring (73%) are the most widely used incident tools employed, the survey finds.

Kate Clavet, product marketing manager for IT service management (ITSM) at Atlassian, noted that as artificial intelligence (AI) continues to evolve it will only become easier to incorporate simulations into incident response training.

In terms of metrics tracked, most respondents track meantime to resolve (80%), while 71% track meantime to acknowledge and 55% track meantime to respond. A total of 61% use the tickets created by ITSM platforms as the single source of truth for managing incidents, while 39% rely on some type of chat tool. A full 60% said they are not using a configuration management database (CMBD) to help manage their IT environments. A full 97% said they do, however, have change management practices in place to minimize potential disruptions

Despite some recent notorious outages, incident management appears to have reached a level of advanced maturity but in the absence of tighter integrations between DevOps and ITSM teams, there is also still plenty of room for improvement.

September 17, 2024
AIOps Success Requires Synthetic Internet Telemetry Data

Any form of artificial intelligence (AI) is only as good as the data used to train it. If organizations expect to effectively apply AI to IT operations (ITOps) they need to collect as much telemetry data as possible.

IT teams frequently discover that their AIOps platform was been trained on a narrow base of telemetry data. It might have been collected from, for example, a DevOps platform that lacks complete visibility into the distributed computing environment where their application runs. In the absence of the synthetic telemetry data collected from an Internet performance monitoring (IPM) platform to collect that telemetry data, it’s simply not likely the machine learning algorithms that are at the core of any AIOps platform are going to surface the best recommendations for optimizing application experiences.

The challenge is the probabilistic nature of AI. The relevancy of the recommendations that surface is determined by the quality of the data that has been exposed to the AI model. Real user data, for example, may be sparse or non-existent. Of course, if telemetry data was never shared with the AI model in the first place, it’s extremely unlikely that the AI’s recommendations will to better application experiences.

Gaining Visibility Using Synthetic Data

IT teams need to be certain the data used to train the AI model reflects the production environments where applications are deployed. Otherwise, no matter how advanced an AI model may be, garbage in still equals garbage out. Before any IT team adopts an AIOps platform, it needs to know the data provenance of the underlying AI model. If the pool of AI training data is limited, the recommendations generated will be, too. IT teams are not going to put their faith in AIOps platforms that are advising them to take specific actions based on partial or incomplete data. Nor should they.

Instead, the teams will assume that every output needs to be verified before the next step in a process is allowed to proceed. After all, the only thing worse than being wrong when it comes to IT and AI is to be wrong at catastrophic scale. Of course, continuing to manage IT sequentially arguably defeats the purpose of investing in an AIOps platform that is supposed to manage tasks in parallel.

Given the dependency modern applications have on Internet services, any effort to apply AI to IT management that doesn’t include synthetic Internet telemetry data will lead to a suboptimal outcome. By including this type of telemetry, the insights being surfaced to DevOps teams will enable them to ensure key performance indicators (KPIs) are attained and maintained.

Multiple AI Models

There’s not likely to be one AI model to rule them all. In many cases, networking, security, and other IT service management (ITSM) platforms will have already applied AI to the telemetry data they collect in real time. The output from those AI models will then be shared with AIOps platforms to automate a series of tasks on an end-to-end basis that previously would require IT teams to orchestrate workflows across multiple islands of automation.

DevOps teams, as a result, need to evaluate the efficacy of what will soon be a network of AI models. There are so many, each of which is or will be designed to automate specific tasks, such as analyzing Internet traffic to identify the source of bottlenecks that might only intermittently impact an application. Armed with insights, it then becomes possible for the AIOps platform to consistently generate useful recommendations that DevOps teams can trust. Then they can let the tools automatically apply the suggestion to how, for example, Internet traffic should be rerouted to maintain service level objectives (SLOs).

Realizing the Promise of AI

As AIOps platforms improve, they can substantially reduce much of the toil that DevOps teams regularly encounter. Teams can spend weeks trying to determine the root cause of an issue that, once discovered, might take a few minutes to fix. The challenge is that the source of the issue often has little to do with anything the DevOps team has immediate control over, as is the case when, for example, latency created by an Internet service adversely impacts application performance. However, those insights should enable DevOps teams to send support requests that better pinpoint the exact source of an Internet service issue that their provider should be able to resolve faster. Just as importantly, the DevOps team can move onto issues that they have more direct control over.

Much of the stress that any DevOps team experiences stems from not knowing the real cause of issue that despite their best efforts continues to generate a series of ongoing alerts. AIOps promises to reduce that stress by making it simpler to first correlate causation and, secondly, automate remediation. That promise, however, will never be fully realized if the data being relied on to train the AI model doesn’t provide enough of the picture required to make a truly informed decision.

April 22, 2024
Techstrong Group Launches Techstrong ITSM Community Platform to Bridge the Gap Between Agile, DevOps and ITSM
Techstrong Group launches new ITSM site to empower organizations to navigate the complete IT life cycle with greater efficiency, quality and agility.

Boca Raton, FL, February 28, 2024 — Techstrong Group, the power source for people and technology, today announced the launch of its latest community site, Techstrong ITSM. This new venture seamlessly integrates Agile, DevOps and IT service management (ITSM) methodologies into a unified resource for IT professionals, offering a holistic approach to managing the complete IT life cycle.

“We recognized a critical gap in the current IT landscape: The need for a cohesive strategy that encompasses Agile’s adaptability, DevOps’ efficiency and ITSM’s reliability,” said Techstrong Group CEO Alan Shimel. “The mission of Techstrong ITSM is to offer a comprehensive resource that facilitates understanding, adoption and integration of these methodologies across the entire IT life cycle.”

Techstrong ITSM offers a wealth of resources designed to empower IT professionals, managers and organizational leaders:
- Educational Content: Articles, tutorials and case studies provide insights into best practices, challenges and solutions for integrating Agile, DevOps and ITSM.
- Tools and Resources: Access to tools, templates and frameworks facilitate the practical application of these methodologies across the IT life cycle.
- Community Engagement: Forums and discussion groups foster a community of continuous learning and improvement, allowing professionals to share experiences, advice and support.
Techstrong ITSM offers a platform for organizations to enhance their IT capabilities and drive innovation in the digital era.

For more information, read Alan Shimel’s blog or visit the Techstrong ITSM website.

About Techstrong Group
Techstrong Group is the power source for people and technology. Techstrong Group accelerates understanding of technologies that drive business. With a broad set of IT-related communities and offerings, Techstrong Group is the only media company serving the needs of IT leaders and practitioners with news, research, analysis, events, education, certifications and professional development. Our focus is DevOps, cybersecurity, AI, digital transformation, cloud and cloud native. Techstrong Group business units include: Techstrong Media (devopsy.kinsta.cloud, Security Boulevard, Cloud Native Now, Techstrong.ai, DigitalCxO, Techstrong ITSM, Techstrong TV and Techstrong Group Podcasts), Techstrong Research and Techstrong Learning. For technology providers, Techstrong business units offer many ways to share their stories, expand their audience and grow their business.

Techstrong Group is based in Boca Raton, Florida. For more information, visit us on the web and follow us on LinkedIn.

Contact
Veronica Haggar
veronica@techstronggroup.com
February 28, 2024
DevOps 2024: DevOps Isn’t Dead; Long Live DevOps

Well, it has been quite the year in general and quite the year as it relates to DevOps. As I sit here on the cusp of the 10th year of publishing devopsy.kinsta.cloud, I look back and recognize how much DevOps has grown, evolved, matured and shifted over time. As was the case 10 years ago, there are those who say DevOps does not work or insist that DevOps is dead. My response:

“They stab it with their steely knives
But they just can’t kill the beast.”
~ Eagles, Hotel California

No, it seems you can’t kill DevOps. Much like Obi-Wan Kenobi being struck down by Darth Vader, DevOps, it seems, is more powerful than ever. It has seeped into the very fabric of IT.

While cloud native has become the dominant form of computing, the fact is you really would not have cloud-native stacks without DevOps fundamentals enabling them. As cloud-native continues to grow, so does DevOps.

One of the interesting things about DevOps is the fact that it really has become an enterprise toolset. While initially scaling DevOps across an organization was challenging (and still is for many), it has become much more common to see large enterprises—or ‘horses,’ as Gene Kim would call them—adopting DevOps methodologies across significant parts of their IT teams.

Speaking of Gene Kim, some have pointed to his recent announcement that he’s changing the name of his DevOps Enterprise Summit (DOES) to Enterprise Technology Leadership Summit as evidence of DevOps’ demise. We will be interviewing Gene on Techstrong.TV the first week in January 2024 and will address this with him, so stay tuned. But without giving out too many spoilers, Gene felt that DOES had expanded beyond just DevOps to encompass a general technology discussion (hey, AI will be in there for sure) aimed at technology leaders (C-suite). But rest assured that Gene Kim does not think DevOps is dead.

Looking ahead to 2024, I see DevOps making broad inroads into the SMB and mid-enterprise market. The DevOps toolset and methodology have matured to the point where it can be adopted and used successfully in IT environments not as resource-rich or process-driven as large enterprises generally are.

Another continuing story in DevOps is DevSecOps. Security and/or quality continues to be a key driver for DevOps pipelines, with the software supply chain and SBOM security still driving lots of adoption and adaptation.

Did I mention AI? You can’t discuss much today without mentioning it, or so it seems. AI is a catalyst for automation. Generally, in software development and deployment, where there is automation, you guessed it—there is DevOps.

But here is one out of left field for you: ITSM. It seems like IT service management is making a big comeback (some say it never left). Today’s ITSM incorporates many DevOps fundamentals to increase scale and agility. On this front, stay tuned; in partnership with PeopleCert, the folks behind ITIL, Prince 2 and the DevOps Institute, we will roll out a series of virtual events in 2024, tying all three of these key technologies together.

So, there’s lots going on in the DevOps world for 2024. You can count on us here at Techstrong Group to keep you in the know.
On that note, this will close out our coverage for 2023. To all of our readers, watchers, listeners, friends, sponsors and contributors, a Merry Christmas, Happy New Year, and here is to a healthy and prosperous 2024.

December 26, 2023
All Your IT Team Wants This Holiday Season is a Break!

The holiday season is all about giving. As organizations increasingly look to IT as they move toward new digital tools and processes, now is the perfect time to give back to IT teams tirelessly working to keep the modern enterprise online. Whether your system performance has been naughty or nice this year, there’s no denying that tech professionals have earned our appreciation, respect—and the tools to set them up for success in 2024.

For IT teams limited in both time and resources, simply maintaining systems can feel as impossible as squeezing themselves down a chimney or delivering gifts to millions of homes in a single night. On top of that, instead of being greeted with milk and cookies, they’re inundated with endless performance issues, support requests and alerts—leaving little time left over for the important work of innovating.

They say the best gifts are the ones you can’t wrap. That holds true for IT teams, too. This year, bring your organization the gift of a simpler, speedier, more rewarding workload. If your team is dreaming of a tech-savvy future, here are some enterprise software solutions to make their lives easier that they won’t want to re-gift:

Enjoy the View With Observability

Everyone loves to cozy up at home during a winter snowstorm, but with the widespread migration to combined remote, on-premises and distributed hybrid environments, the daily monitoring journey for today’s IT teams is more akin to trekking blindly through a blizzard.

Observability tools are metaphorical snowshoes and goggles that can help them not only weather the storm but see clearly from the mountaintop. Observability is the answer to the modern enterprise’s struggle to gain full visibility into their organization’s apps, networks, databases and infrastructure—something nearly half of IT professionals lack, according to SolarWinds research. IT teams will be able to rest easier at night with visions of sugarplums, rather than outages or anomalies, dancing in their heads.

Even better, integrating artificial intelligence (AI) capabilities into observability solutions to collect and provide data on what’s not performing as expected and why will help your teams take a proactive approach to solving issues.

Lend a Helping Hand With AIOps

AI isn’t just the shiny new toy of the tech world. Organizations using AI for IT operations (AIOps) can give the gift of support to their overworked IT teams by automating some of the time-consuming and mundane tasks that stand between them and a focus on innovation.

Adding AIOps to observability can provide IT teams with maximum visibility into the state of their digital ecosystems through automated discovery and dependency mapping. Additionally, your teams can gain the ability to easily track inbound connections linked across the organization’s application stack and storage volumes with auto-instrumented views.

Today, it simply isn’t feasible for humans alone to manage modern IT environments without intelligent automation. Think of AIOps as a workshop of elves operating in the background to ensure workloads and processes are streamlined and moving as efficiently as possible. With AIOps in place to analyze data and streamline workloads and processes, IT teams are relieved of some pressure—and can focus on accelerating your digital transformation rather than just maintaining it.

Give the Gift of Time

Finally, although you can’t outright give the gift of time to your IT team, you can still arm them with tools that save time year-round. In 2024, more organizations will embrace IT service management (ITSM) to improve their IT outcomes, service delivery and employee satisfaction.

SolarWinds research found that enterprises using AI-powered ITSM tools were able to reduce system downtime by 21% and decrease time spent resolving incident and service requests by 23%. In fact, the average SolarWinds customer reported savings of 23 hours weekly due to reduced ticket volume—nearly the equivalent of adding an employee to the team.

This holiday season, the best gifts you can give your IT teams are the actionable, predictive intelligence and tools they need to optimize performance, cut down on complications and quickly resolve issues. (As a bonus, it will certainly make you more popular than the guy from The 12 Days of Christmas who thought it was a good idea to gift his partner geese, milkmaids and leaping lords.)

December 22, 2023
PagerDuty Previews Generative AI Copilot for ITSM

Under an early access program, PagerDuty, Inc. is making available a tool that brings generative artificial intelligence (AI) capabilities to its IT service management (ITSM) platform.

Jonathan Rende, senior vice president of products for PagerDuty, said PagerDuty Copilot for the PagerDuty Operations Cloud extends previous investments in machine learning algorithms the company has made as part of an ongoing effort to apply AI to ITSM.

Designed to be invoked via Slack, PagerDuty Copilot makes use of multiple large language models (LLMs) to automate tasks ranging from providing summarization of IT incidents to creating code to automate workflows. PagerDuty plans to transparently swap LLMs in and out of its platforms as AI advances continue to be rapidly made, noted Rende.

PagerDuty Copilot provides a level of abstraction for invoking AI models along with appropriate guardrails that make it simpler to manage IT operations without IT teams needing to have AI expertise, said Rende.

The overall goal is to boost the productivity of IT operations teams by eliminating much of the drudgery and toil that conspires to make working in IT tedious, noted Rende. AI technologies are not likely to replace the need for IT personnel as much as they will enable IT teams to focus on tasks that add more value to the business, he added.

It’s now only a matter of time before generative AI capabilities are pervasively applied across both ITSM and DevOps workflows. Less clear is the impact those capabilities will have on the best practices currently relied on to manage those workflows as more tasks are automated. Ultimately, however, AI should make it easier for more organizations to embrace those best practices as the level of skill and expertise required to manage IT at scale is reduced.

In addition, the whole concept of issuing tickets to manage tasks tracked by a central system of record may need to evolve simply because AI has automated requests for service. There will naturally need to be some system of record for tracking requests. Still, ultimately that process will be managed via copilots rather than by a ticket created by an end user that is then tracked via an ITSM platform.

Savvy IT teams, in the meantime, are already moving to determine which tasks and workflows will be automated in anticipation of AI becoming more widely embedded in ITSM and DevOps platforms. Roles and responsibilities within IT teams will inevitably evolve as AI increasingly automates mainly mundane tasks, such as creating reports that many IT professionals would rather not spend time writing.

The biggest IT management platform challenge in the future might not necessarily be adjusting to AI as much as it will be orchestrating requests that are likely to be generated by multiple types of copilots that have been embedded into almost every application.

One way or another, AI is about to transform how IT operations are managed. As disruptive as those advances will be, AI, more importantly, will also enable organizations to manage IT at levels of scale that were previously unimaginable.

December 7, 2023
IT Service Incidents Are Becoming More Frequent, Survey Says

A survey of 1,000 IT operations, DevOps, site reliability engineering (SRE) and platform engineering professionals in the U.S. conducted by Transposit, a provider of an incident management platform, found more than two-thirds (67%) have seen an increase in the frequency of service incidents that have affected their customers over the past 12 months.

Announced at the Kubecon + CloudNative conference today, the survey found 62% of respondents have also seen an increase in the amount of time it takes to resolve incidents over the course of the last year, with 80% reporting it takes up to six hours on average to resolve incidents from the first alert to mitigating the issue.

Paradoxically, however, 71% of respondents also claim to have automated incident management to their satisfaction, with 59% having a defined incident management process in place. One-third (33%) said only 11-25% of their incident management tasks or workflows are automated.

Transposit CEO Divanny Lamas said despite that level of comfort it’s clear the number of incidents that need to be addressed are continuing to increase as IT environments become more complex. In fact, in the next 12 months, 72% expected their organization to expand its IT stack.

At the same time, costs per incident are rising, with organizations at risk of losing up to $499,999 per hour on average, according to 63% of respondents. Nearly half (47%) said downtime can cost anywhere from $100,000 to $2 million.

A full 85% of respondents are hopeful that generative artificial intelligence (AI) will help further streamline incident management processes, with 80% having already embraced AI to varying degrees. More than half (51%) feel AI is making their job better, with 65% using it to improve the accuracy and quality of data. Just over half (51%) reported faster time to incident resolution, with 50% using it to more quickly and easily identify the root cause of issues, potential threats and vulnerabilities. Just under half (48%) use it to automate repetitive tasks or processes, streamlining their operations effectively.

A full 90% of respondents said integrating generative AI capabilities into incident management tools or platforms decreased the time it takes to create new automations.

Overall, 43% reported current incident management processes are not effective or are only being used by some team members due to confusing documentation (41%), limited access to tools (40%) and reliance on institutional knowledge (40%). Well over a third (37%) reported that only select team members have a comprehensive understanding of the defined incident management process and that they are adhered to consistently.

A full 96% said they believed it would be beneficial if all the tools their organization used to manage incidents were integrated through one tool or platform, the survey finds.

Top challenges cited included not enough buy-in from leadership or management (57%), not enough sharing of knowledge (54%), inadequate documentation of institutional knowledge and existing processes (54%) and a lack of clarity about what to automate (52%).

Respondents reported they expected to embrace technologies including AI or tools that employ machine learning algorithms (60%), automation tools or applications (53%) and communication/collaboration tools or applications (48%).

In addition, over the past year, 62% of respondents have increased their focus on SRE practices, with 58% planning to increase adoption of platform engineering as a methodology for centralizing the management of DevOps workflows.

Ultimately, automation should reduce incident management stress for all concerned, said Lamas. The challenge, as always, is making it simpler to achieve that goal in a way that doesn’t rely on a complex mix of custom scripts that don’t scale, she added.
One way or another, it’s clear that when it comes to incident management, there is still plenty of room for improvement.

November 7, 2023
Atlassian Brings Generative AI to ITSM

Atlassian today added generative artificial intelligence (AI) capabilities to Jira Service Management, an IT service management (ITSM) platform built on top of Jira project management software already used widely by DevOps teams.

Generative AI is at the core of a virtual agent that analyzes and understands intent, sentiment, context and profile information to personalize interactions. Based on the same natural language processing (NLP) engine that Atlassian is embedding across its portfolio, the virtual agent dynamically generates answers from sources such as knowledge base articles, onboarding guides and frequently asked questions (FAQs) documents.

In addition, it can facilitate conversations with human experts any time additional expertise is required to respond to more complex inquiries.

Atlassian is also extending the reach of Atlassian Intelligence, a generative AI solution launched earlier this year, to provide concise summaries of all conversations, knowledge base articles and other resolution paths recommended by previous agents that have handled similar issues. It will also help IT staff craft better responses and adjust their tone to be more professional or empathetic if needed.

During setup, support teams can easily configure the virtual agent experiences to match how they deliver service without writing a single line of code.

Edwin Wong, head of product for IT solutions at Atlassian, said these additions are part of a larger commitment Atlassian is making to unify the helpdesk experience. The company plans to leverage Atlassian Intelligence to coordinate routing of all employee requests to the right tools as it aggregates requests from multiple communications channels such as web portals, email, chat and from within third-party applications, he noted.

The overall goal is to reduce the number of tickets generated by leveraging AI as much as possible to handle service requests in a way that costs less to implement and maintain, Wong said.

In the longer term, Atlassian will also apply generative AI to enable organizations to automate IT asset management further, he added.

There is little doubt at this juncture that AI will be pervasively applied across both ITSM and DevOps workflows. As those advances are made, it should also become easier to address issues that arrive either programmatically or by generating a ticket for a service request that is then processed by an ITSM platform such as Jira Service Management.

Each organization will need to decide how quickly to incorporate AI into ITSM, but hopefully, the level of burnout experienced by IT personnel will be sharply reduced as more tasks are automated. Less clear is the impact AI will have on the size of IT teams required to provide those services, but for the foreseeable future, there will always be a need for some level of human supervision.

In the meantime, IT teams should take an inventory of the processes that are likely to be automated by AI today with an eye toward restructuring teams as more tasks are automated. Ultimately, the goal should be to let machines handle the tasks they do best so humans can provide higher levels of service that deliver more value to the business.

October 31, 2023
DevOps and ITIL Integration: Driving Collaborative Agility in ITSM

Businesses face continuous pressure to deliver high-quality IT services efficiently. One emerging integration to meet these goals is between DevOps and IT service management (ITSM), more commonly known as DevOps+.

DevOps+ is becoming more than a trend and has emerged as a powerful collaborative approach to meet these challenges. By combining the strengths of DevOps’ agile software development practices and ITSM’s structured service management approach, organizations can foster better collaboration, enhance agility and improve overall service delivery efficiency.

DevOps and ITSM Symbiosis

DevOps and ITSM traditionally operated as separate frameworks with distinct focuses. DevOps emphasizes rapid software delivery and collaboration between development and operations teams. On the other hand, ITSM-based ITIL (information technology infrastructure library) provides best practices for ensuring service stability, reliability and adherence to governance and compliance.

Integrating DevOps and ITIL creates a symbiotic relationship, allowing organizations to leverage the best of both worlds. DevOps+ encourages a cultural shift, breaking down silos and promoting cross-functional communication. This collaboration enhances the entire software development lifecycle, leading to faster feedback loops, accelerated innovation, and increased responsiveness to business needs.

Enhancing Agility and Speed

DevOps+ integration brings greater agility and speed to IT service management. Organizations can streamline the release process by automating deployment pipelines and implementing continuous integration and continuous delivery (CI/CD) practices, reducing time-to-market for new features and updates. Agile development methodologies enhance the adaptability of ITSM processes to meet evolving business requirements effectively.

Ensuring Stability and Reliability

While agility is crucial, it must not compromise service stability and reliability. ITIL’s best practices provide a strong foundation for maintaining service quality. By incorporating ITIL processes such as incident management, change management and problem management, organizations can effectively manage risks, reduce service disruptions and ensure the stability of critical IT services.

Leveraging Automation and Orchestration

Automation is central to both DevOps and ITIL. Through integration, organizations can leverage automation and orchestration tools effectively. Automated testing, infrastructure provisioning and configuration management improve efficiency and consistency across the ITSM lifecycle. This enables teams to focus on higher-value tasks, reducing manual errors and operational overhead.

Emphasizing Customer-Centricity

DevOps+ puts the end-user experience at the forefront of service delivery. By continuously seeking customer feedback and measuring service performance, organizations can better align their offerings with user expectations. A customer-centric approach fosters higher satisfaction, loyalty, and competitive advantage.

Breaking Down Barriers to Change

Change management is vital in ITIL, ensuring that modifications are planned and controlled. In the context of DevOps+, change management becomes more adaptive and responsive, facilitating a culture that embraces change as an integral part of the development process. This promotes experimentation, reduces resistance to change, and accelerates innovation.

Challenges of DevOps and ITIL Integration

Despite the numerous benefits of DevOps+ integration, organizations may encounter challenges during implementation:

Cultural Shift: Merging DevOps and ITIL requires a cultural shift. Overcoming resistance to change and fostering collaboration between traditionally separate teams can be challenging but is crucial for success.

Process Alignment: DevOps and ITIL have different processes and terminologies. Aligning these methodologies while preserving their individual strengths can be complex.

Skill Sets: Integrating DevOps and ITIL necessitates upskilling teams in both domains to operate effectively in the integrated environment.

Tooling and Automation: Adopting suitable tools and technologies that support DevOps+ practices and integration is vital but may require significant investments.

Metrics and Performance Measurement

Measuring the success of DevOps+ integration is essential to understand its impact and effectiveness. Key performance indicators (KPIs) can help monitor progress and identify areas for improvement.

Deployment Frequency: The frequency of software deployments indicates the efficiency of the integrated approach. Higher deployment frequency implies faster and more reliable releases.

Mean Time to Resolve Incidents (MTTR): MTTR measures how quickly teams can resolve incidents and restore services after disruptions occur. A reduced MTTR demonstrates improved service reliability and faster incident resolution.

Customer Satisfaction Scores: Measuring customer satisfaction provides insights into how well the integrated approach meets end-users’ needs and expectations.

Continuous Improvement and Feedback Loops

Continuous improvement is at the core of DevOps+. Establishing feedback loops and conducting regular retrospectives empowers teams to identify areas for improvement and implement iterative enhancements to processes and practices.

Implementing DevOps+ integration requires a well-structured roadmap. For example, assessment and planning help leaders evaluate the organization’s current ITSM practices to understand how DevOps and ITIL principles align and define integration vision and goals.

Additionally, your continuous optimization efforts allow you to continuously monitor performance metrics, gather feedback, and conduct retrospectives to identify improvement areas, leading to better team collaboration and communication. Fostering cross-functional collaboration between development, operations and other relevant teams is easily accomplished. To meet these goals, encourage regular meetings, schedule joint planning sessions and enable shared documentation to ensure everyone is aligned on goals and progress.

When this happens, leverage automation tools to streamline manual processes and increase efficiency. Implement continuous integration and continuous delivery pipelines to automate software deployment and testing. Automation enhances consistency, reduces the risk of human errors and adds a new layer for measuring and evaluating to continuously measure the performance of the integrated approach using defined KPIs. In this vein, you can regularly review progress against the initial vision and goals to ensure the integration aligns with organizational objectives.

Next, as the DevOps+ integration proves successful in pilot projects, gradually scale and expand it to other teams and departments. Share the success stories and best practices to encourage broader organizational adoption.

Conclusion

In conclusion, the integration of DevOps and ITIL, known as DevOps+, marks a transformative approach to IT service management. By combining the agility and rapid deployment of DevOps with the stability and reliability of ITIL, organizations can drive collaborative agility and achieve efficient service delivery.

DevOps+ integration requires overcoming cultural barriers, aligning processes and upskilling teams, but the rewards are immense. With clear metrics to measure success, organizations can continually optimize their DevOps+ approach to meet customer needs and adapt to evolving market demands.

As technology evolves, DevOps+ integration will remain at the forefront of cutting-edge IT service management, empowering organizations to embark on a journey of innovation, efficiency and excellence.

By embracing DevOps+ as a guiding philosophy, organizations can cultivate a culture of collaboration, continuous improvement and customer-centricity, laying the groundwork for a prosperous future in the dynamic world of IT service management.

October 20, 2023