#itoperations

Software sprawl is becoming a silent budget killer for many organizations. Teams often subscribe to tools quickly, but very few companies maintain a clear picture of what they own, what is being used, and what is draining money in the background. Unused licenses, duplicate subscriptions, and missed renewals create hidden costs that scale faster than most businesses realize. Research and industry discussions increasingly point to software visibility and lifecycle control as major priorities for modern IT teams. 

That is where Software Asset Management (SAM) moves from a “nice-to-have” process to a business strategy. Effective SAM is not only tracking licenses, it helps organizations optimize spending, improve compliance, strengthen security and make better purchasing decisions across the technology ecosystem. Mature asset practices can also significantly reduce unnecessary software expenses. 

The modern enterprise runs on digital infrastructure. From cloud applications and hybrid networks to cybersecurity systems and customer-facing platforms, organizations today depend heavily on uninterrupted IT performance. However, as IT ecosystems become more distributed and complex, traditional monitoring tools are no longer sufficient to manage the growing volume of data, alerts, and operational risks. This is where the AIOps Solutions Market is emerging as a transformative force for businesses worldwide.

According to QKS Group, the market is expected to grow at a compound annual growth rate (CAGR) of 22.31% through 2032, reflecting the increasing importance of intelligent automation in IT operations. Enterprises across industries are investing in AIOps platforms to improve operational efficiency, reduce downtime, strengthen security, and gain actionable insights from massive streams of operational data.

AIOps, or Artificial Intelligence for IT Operations, combines artificial intelligence, machine learning, automation, and big data analytics to optimize and automate IT management processes. These platforms collect and analyze data from multiple IT environments, including metrics, logs, traces, and events, to provide real-time visibility into infrastructure health and performance.

One of the major reasons behind the rapid growth of the market is the rising complexity of IT environments. Organizations are rapidly adopting cloud computing, microservices, containerized applications, and remote work infrastructure. While these technologies offer scalability and flexibility, they also generate enormous amounts of operational data that human teams alone cannot effectively manage. AIOps solutions simplify this complexity by correlating data across systems and identifying patterns that indicate potential issues before they impact business operations.

Another key driver accelerating the adoption of AIOps is the increasing demand for proactive IT management. Businesses today cannot afford unexpected outages or performance degradation, especially in sectors such as banking, healthcare, retail, manufacturing, and telecommunications where digital services are mission-critical. AIOps platforms enable organizations to shift from reactive troubleshooting to predictive and preventive IT management. By detecting anomalies in real time, these solutions help IT teams address problems before they escalate into costly disruptions.

Automation is also reshaping enterprise IT strategies. Modern AIOps platforms reduce the burden on IT teams by automating repetitive tasks such as incident detection, root cause analysis, alert prioritization, and remediation workflows. This allows IT professionals to focus on strategic initiatives rather than spending countless hours managing operational noise. As organizations continue to face skill shortages and increasing operational pressure, automation-driven AIOps capabilities are becoming essential for improving productivity and reducing operational costs.

The AIOps Solutions Market is also benefiting from the growing focus on cybersecurity and digital resilience. Cyber threats are evolving rapidly, and organizations require advanced monitoring solutions capable of identifying suspicious patterns and security anomalies in real time. AIOps tools enhance security operations by correlating IT and security data to provide a unified view of threats and vulnerabilities. This integration helps organizations respond faster to incidents while improving overall resilience.

Industries such as banking and financial services are expected to witness significant adoption during the forecast period due to their dependence on real-time digital services and strict compliance requirements. Similarly, healthcare organizations are increasingly leveraging AIOps to maintain uptime for critical systems, protect patient data, and ensure operational continuity. Retail and e-commerce sectors are also investing heavily in intelligent IT operations to deliver seamless customer experiences and manage fluctuating digital demand efficiently.

From a regional perspective, North America is expected to remain a dominant market due to early technology adoption, advanced IT infrastructure, and strong presence of leading vendors. However, Asia-Pacific is projected to witness the fastest growth as enterprises across countries such as India, China, Japan, and Singapore accelerate digital transformation initiatives. Increasing cloud adoption, expanding data center investments, and growing awareness of AI-powered IT management are fueling regional market expansion.

Cloud-based deployment models are anticipated to gain stronger traction over the coming years due to their scalability, flexibility, and lower upfront investment requirements. Organizations are increasingly preferring cloud-native AIOps platforms that can support hybrid and multi-cloud environments efficiently. Meanwhile, large enterprises continue to dominate adoption due to their complex infrastructure needs, although small and medium-sized businesses are also gradually recognizing the benefits of intelligent IT automation.

The competitive landscape of the market includes several prominent technology providers focused on innovation and platform enhancement. Vendors such as Aisera, Amelia, BigPanda, BMC, Broadcom, Cisco, CloudFabrix, Datadog, Devo, Digitate, Dynatrace, Elastic, IBM, LogicMonitor, ManageEngine, New Relic, PagerDuty, ServiceNow, Splunk, Sumo Logic, and ScienceLogic are continuously expanding their AI and automation capabilities to strengthen their market positions.

Integration capabilities are becoming a major differentiator among vendors. Organizations increasingly demand platforms that seamlessly integrate with existing IT service management, observability, security, and cloud management tools. As a result, vendors are focusing on open ecosystems, advanced analytics, and intelligent automation to deliver more comprehensive operational visibility.

The future of the AIOps Solutions Market will likely be shaped by advancements in generative AI, predictive analytics, and autonomous IT operations. Emerging innovations are expected to enhance decision-making, automate complex workflows, and further improve incident resolution times. Over time, organizations may increasingly move toward self-healing IT systems capable of automatically detecting and resolving operational issues with minimal human intervention.

As businesses continue to rely on digital infrastructure for growth and customer engagement, the importance of intelligent IT operations will only increase. AIOps is no longer viewed as an optional technology investment but as a strategic necessity for maintaining operational efficiency, resilience, and competitiveness in a rapidly evolving digital economy.

Organizations that embrace AI-driven IT operations today will be better positioned to manage future complexity, improve service reliability, and accelerate innovation. With strong market momentum and continuous technological advancements, the AIOps industry is poised to become a cornerstone of modern enterprise IT strategy through 2032.

Related Reports

Market Forecast: AIOps Solutions, 2026-2030, Western Europe : https://qksgroup.com/market-research/market-forecast-aiops-solutions-2026-2030-western-europe-6258

Market Forecast: AIOps Solutions, 2026-2030, USA :

Market Forecast: AIOps Solutions, 2026-2030, Middle East and Africa : https://qksgroup.com/market-research/market-forecast-aiops-solutions-2026-2030-middle-east-and-africa-6256

Market Forecast: AIOps Solutions, 2026-2030, Latin America :

Market Forecast: AIOps Solutions, 2026-2030, Japan :

Market Forecast: AIOps Solutions, 2026-2030, China :

Market Forecast: AIOps Solutions, 2026-2030, Central and Eastern Europe :

Market Forecast: AIOps Solutions, 2026-2030, Canada :

Market Forecast: AIOps Solutions, 2026-2030, Asia (Excluding Japan and China) :

Introduction

The modern corporate software landscape runs on massive cloud networks that process transactions and handle user data every single second. As a result, the backend infrastructure powering these applications has become incredibly complicated. Every single piece of hardware, virtual machine, and microservice generates a continuous stream of operational data points. Trying to watch over all this information by hand has become an impossible job. When software breaks, engineering teams often spend hours or even days digging through cluttered dashboards just to find the root cause. This manual way of working causes costly business downtime, system instability, and immense stress for operational teams. To solve this major issue, companies are pivoting toward intelligent automation that combines big data processing with smart machine learning algorithms.

If you are looking to position yourself at the forefront of this modern tech movement, validating your skills is an absolute must. The premier global training standard for this field is the Certified AIOps Professional credential. You can read all about the curriculum and start your learning journey by visiting the official Certified AIOps Professional URL, which is proudly developed and offered by the primary provider AIOpsSchool.

What it is

The Certified AIOps Professional credential is an industry-recognized validation track built to prove your hands-on ability to mix artificial intelligence with daily IT management. It verifies that you know how to build smart monitoring systems that automatically catch application anomalies, clean up noisy alarm dashboards, and fix system errors before they affect customers.

Who should take it

This advanced program is tailor-made for tech professionals who want to make their infrastructure highly autonomous and resilient. It is ideal for:

DevOps Practitioners who want to build smart, predictive deployment gates into their software delivery channels.

Site Reliability Engineers (SREs) who want to replace manual log troubleshooting with instant, automated machine learning analysis.

Systems Administrators looking to upgrade their technical profiles from standard automation scripting to AI-driven operations.

Cloud Engineers and Enterprise Architects responsible for maintaining system uptime across massive multi-cloud setups.

Certified AIOps Professional Certification Overview

The entire training journey and technical coursework are delivered directly via the main online learning program hosted on the official AIOpsSchool platform. The entire curriculum framework, exam standards, and lab environments are owned and updated by the central site team to make sure the training stays in perfect lockstep with real enterprise requirements.

Understanding how the program is structured helps candidates prepare effectively:

Certification Levels: This program focuses heavily on professional-level implementation skills, ensuring you can deploy actual machine learning models into live corporate environments rather than just memorizing definitions.

Assessment Approach: You will earn your designation by passing an online evaluation that tests you on complex, scenario-based architecture questions alongside real-world lab challenges where you must troubleshoot a broken data pipeline.

Practical Framework: The course structure walks you seamlessly from the basics of telemetry data collection all the way up to configuring self-healing infrastructure triggers that remediate system errors automatically.

Skills you'll gain

Intelligent Anomaly Detection: Discover how to train algorithms to monitor massive streams of infrastructure metrics and flag strange patterns long before traditional fixed alerts go off.

Alert Noise Suppression: Master the technical art of grouping thousands of repetitive system notifications into a single, clean, and actionable corporate incident report.

Automated Root-Cause Discovery: Gain the skills to automatically trace complex application crashes back to their exact line of code or faulty server node.

Predictive Capacity Forecasting: Use historic storage and computing logs to accurately forecast exactly when your cloud environments will need resource upgrades.

Big Data Tooling Mastery: Establish deep, hands-on comfort with modern big data clusters, real-time log collection managers, and pattern-matching software tools.

Real-world projects you should be able to do after it

Build a Self-Healing Cloud Ecosystem: Set up an automated monitoring loop that flags when a database drops connections, safely isolates that failing node, and spins up a healthy clone without manual human intervention.

Design a Central Intelligence Log Engine: Build a unified pipeline that gathers system logs from thousands of distributed application instances and uses algorithms to highlight seasonal red flags.

Deploy an Algorithmic Scaling Script: Write an intelligent cloud script that studies daily user traffic trends and pre-emptively adds computing power right before predictable high-load surges hit your platform.

Common mistakes

Treating AI as an Instant Cure-All: Many corporate teams think buying an AIOps software platform fixes messy internal workflows immediately, but unorganized infrastructure data will always produce unorganized automated results.

Skipping the Data Cleaning Phase: Throwing messy, unformatted system logs directly into a machine learning model, which causes a high rate of frustrating false alarms for your engineering teams.

Failing to Define Clear Baselines: Attempting to spot weird anomalies across your cloud networks without taking the time to study and chart what a normal, healthy business day looks like first.

Automating Destructive Commands Too Quickly: Giving automated scripts the absolute power to delete primary server instances or wipe storage directories without putting strict human safety gates in place first.

Best next certification after this

After successfully learning how to introduce data intelligence and predictive analytics into your operations, the absolute best step forward is to pursue the Certified SRE Professional designation. Moving into advanced Site Reliability Engineering allows you to take your machine learning models and apply them directly to corporate reliability policies, error budgets, and long-term application uptime strategies.

Choose your path

Picking a clear professional focus helps you dedicate your study time to the exact technical problems your company needs to solve. Select from these 6 primary operational pathways:

DevOps: Center your daily work around continuous software delivery, automated testing, and building a smooth, rapid bridge between development teams and live servers.

DevSecOps: Put digital safety first by embedding automated compliance checks, container vulnerability scanning, and secret management tools directly inside your release tracks.

SRE: Keep your entire focus locked on platform uptime, structural resilience testing, incident post-mortems, and keeping customer experiences stable.

AIOps/MLOps: Focus your career on pattern analytics, algorithmic alerting filters, autonomous system healing, and managing the lifecycles of operational models.

DataOps: Build and optimize the flow of large-scale corporate data pipelines, ensuring maximum data quality, validation, and velocity for your analytics teams.

FinOps: Take command of cloud infrastructure finance by tracking resource waste, rightsizing virtual hardware, and ensuring maximum business value for every dollar spent.

List of Top Training Institutions

Partnering with an accredited academy is key to mastering the complex labs required for this examination. The international cloud community features brilliant schools that provide deep-dive, practical bootcamps. Top-rated platforms like DevOpsSchool, Cotocus, and Scmgalaxy offer immersive learning setups built around expert-led classes and extensive sandbox project environments.

In addition, highly focused learning centers such as BestDevOps, Devsecopsschool, Sreschool, Aiopsschool, Dataopsschool, and Finopsschool specialize deeply in their respective technical niches, offering targeted practice exams and specific operational modules. Training with these recognized institutions ensures you get genuine hands-on practice with modern machine learning toolsets rather than just memorizing theoretical terms from a slide deck.

Next certifications to take

Once you have firmly established your core AIOps engineering foundation, keep your professional momentum going by selecting one of these three clear business tracks:

Same Track (Deep Specialization): Climb into higher machine learning infrastructure tiers by pursuing expert MLOps engineering programs focused on model retraining loops and automated drift tracking.

Cross-Track (Horizontal Growth): Expand your infrastructure portfolio by diving into a Certified DevSecOps Professional course to learn how to mesh automated security scanners with your smart analytics platforms.

Leadership (Strategic Scale): Prepare yourself for technology management roles by acquiring advanced site reliability leadership credentials that teach you how to build and organize global engineering operations.

FAQs on Certified AIOps Professional

How does an AIOps certification help corporate leaders lower overall infrastructure spending?

From a strategic decision-maker's viewpoint, this program equips engineers with the skills to find and eliminate hidden cloud resource waste. Instead of waiting for a manual billing review, trained professionals configure predictive algorithms that analyze usage trends and downscale idle cloud infrastructure during slow operational windows, directly lowering overhead while protecting performance.

What is the return on investment for migrating traditional operations teams over to an AI-driven framework?

The business return on investment is visible across two critical corporate performance indicators: a severe reduction in Mean Time to Repair (MTTR) and fewer high-priority customer outages. Catching small anomalies early allows organizations to fix system bugs before they grow into full service blackouts, safely protecting client contracts and platform revenue.

Does this professional certification demand a deep background in advanced academic mathematics?

No, the curriculum is designed strategically for practical infrastructure engineers rather than data science researchers. The course focuses purely on how to deploy, set up, and manage pre-existing machine learning toolsets and open-source analytics engines within an enterprise cloud environment, making it highly accessible.

How does the Certified AIOps Professional curriculum address corporate data security and compliance laws?

The training covers the secure handling of system logs, teaching your technical staff how to automatically strip away sensitive customer details or private data before information enters central analytics databases, keeping your operations fully aligned with global compliance laws.

Can these automated AI operational methods be used effectively with older, legacy on-premises data centers?

Yes, the architectural concepts taught throughout the program are completely environment-agnostic. The base principles of pattern discovery, alert grouping, and log aggregation work just as effectively on older bare-metal enterprise servers as they do inside modern public cloud infrastructures.

How can a technology director accurately measure the success of an engineer holding this credential?

Success is measured through clear, observable team metrics: a sharp decline in the volume of raw notifications hitting your on-call teams, a higher percentage of system bugs solved by automated remediation scripts, and fewer performance hiccups reaching your active user base.

What makes an AIOps setup different from standard automated DevOps infrastructure scripting?

Classic DevOps scripting relies entirely on rigid, human-written rules that must be manually updated whenever systems change. AIOps introduces dynamic adaptability, meaning the analytics platform studies your infrastructure habits over time and shifts its alert filters automatically without requiring manual changes to configuration code.

How does this certification prepare a technology executive for long-term infrastructure scaling challenges?

It changes management style from reactive crisis response to proactive resource planning. Certified professionals gain the skills to build long-term capacity forecasting models, giving business stakeholders months of advance warning regarding infrastructure demands for smooth corporate budget planning.

Why Choose AIOpsSchool?

Selecting the right training partner to upgrade your technical profile is the most important decision you can make for your career trajectory. AIOpsSchool stands out globally because its entire course catalog is built around real-world production challenges instead of abstract, purely theoretical lectures. Their educational platform provides every student with continuous access to live cloud environments and actual enterprise monitoring setups, allowing you to safely practice configuring machine learning models on real operational data.

Furthermore, the study paths are continuously updated by active, working industry experts to keep pace with the latest shifts in big data tools and open-source automation frameworks. When you choose to train with them, you are doing far more than just passing a multiple-choice test; you are constructing a verified portfolio of production-ready automation systems that prove your immediate value to elite technical employers worldwide.

Conclusion

Data center operations are the backbone of modern businesses. From keeping websites live to ensuring smooth business communication, they help everything run without interruption.

In today’s fast-paced digital landscape, enterprises can no longer afford to treat IT management as an afterthought. As organisations scale, their IT infrastructure becomes increasingly complex - and managing a powerful platform like ServiceNow in-house demands deep expertise, constant attention, and significant resources. This is exactly where ServiceNow Managed Support Services steps in.

Whether you’re a growing mid-market business or a global enterprise, understanding where and how managed support services add real value can transform how you operate, innovate, and compete.

What Are ServiceNow Managed Support Services?

ServiceNow Managed Support Services refer to the ongoing management, optimisation, and support of the ServiceNow platform by a dedicated team of certified experts - often a third-party Managed Service Provider (MSP). Rather than relying solely on in-house IT staff, organisations partner with specialists who handle everything from day-to-day platform administration to complex upgrades, integrations, and proactive health monitoring.

Think of it as having an elite ServiceNow team on call - one that already knows the platform inside out, keeps your instance running optimally, and helps you extract maximum ROI from your investment.

Where Are ServiceNow Managed Support Services Used?

One of the most common questions organisations ask is: “Do we really need managed support, and where does it apply?” The answer depends on your operational maturity, business complexity, and growth goals. To get a full picture, this detailed breakdown of where ServiceNow Managed Support Services are used by Aelum Consulting is a must-read for IT leaders evaluating their options.

That said, here are the most impactful areas where managed support makes a measurable difference:

1. IT Service Management (ITSM)

The most widely adopted use case, ServiceNow’s ITSM module, enables MSPs to manage and resolve incidents, problems, and requests while delivering a seamless user experience. From ticket routing to SLA enforcement, managed support ensures your service desk runs efficiently around the clock - without burning out your internal team.

2. Post-Go-Live Stabilisation

Many organisations underestimate what happens after a ServiceNow go-live. Go-live is a milestone, not a finish line. The weeks and months that follow are often where the real work begins - workflows need tuning, users need hand-holding, and edge cases that never appeared in testing start showing up in production. Without a structured post-go-live support model, most organisations end up in reactive mode.

A managed services partner provides the structured continuity needed to stabilise and optimise the platform during those critical early months.

3. Platform Upgrades & Version Management

ServiceNow releases two major platform upgrades every year. Each brings new features, AI capabilities, and security patches — but also the very real risk of breaking custom workflows if organisations aren’t prepared. Many fall behind by one, two, sometimes three versions. The further they fall, the bigger the technical lift to catch up, and the more security and compliance exposure they accumulate.

A managed services team owns the upgrade lifecycle end to end, keeping you current without disrupting operations.

4. IT Operations Management (ITOM)

ServiceNow’s ITOM module helps MSPs monitor and manage IT infrastructure and applications, automate workflows, and ensure compliance with policies and regulations. For enterprises running hybrid or multi-cloud environments, this visibility is critical to preventing downtime and maintaining performance benchmarks.

5. Security Operations (SecOps)

Cybersecurity threats are evolving faster than most in-house teams can track. The Cost of a Data Breach Report 2024 by IBM revealed that the global average cost of a data breach in 2024 surged to USD 4.88 million — a 10% increase from the previous year, making it the highest recorded figure to date. With escalating cybersecurity concerns, many organisations are shifting to managed service providers for specialised risk management and compliance expertise.

ServiceNow’s SecOps module allows MSPs to proactively detect, prioritise, and respond to security threats while maintaining compliance with industry standards and regulations.

6. Customer Service Management (CSM)

ServiceNow’s CSM module enables MSPs to provide a personalised and consistent customer experience, manage customer interactions and feedback, and track customer satisfaction. Industries like banking, healthcare, and telecom rely heavily on this capability to retain customers and reduce churn.

7. Technical Debt Remediation

Over time, undocumented customisations and quick fixes pile up. Every quick fix that was never properly documented and every workaround that became permanent, Aelum Consulting adds to technical debt that slows your platform down. Managed services teams systematically audit, clean, and modernise your instance to restore performance and agility.

Key Benefits of ServiceNow Managed Support Services

Beyond specific use cases, the business case for managed support is compelling across the board:

Cost Efficiency — MSPs offer a pay-as-you-go model with no long-term commitments. This flexibility reduces the cost of infrastructure, maintenance, and hiring specialised talent to manage ServiceNow internally.

Proactive Monitoring — ServiceNow experts use advanced monitoring tools to detect trends and resolve issues before they escalate - ensuring smoother operations and less downtime.

Business Continuity — With the MSP handling backend operations and technical maintenance, your team can focus on core business goals - more time for strategic thinking and better customer service, while IT tasks are efficiently managed behind the scenes.

Access to Latest Technology — MSPs help organisations fully leverage ServiceNow’s functionalities without the significant investment of a full-scale implementation. They deliver software upgrades and ensure organisations always have access to the latest technology.

Who Should Consider ServiceNow Managed Support?

Managed support is not just for large enterprises. It’s an ideal fit for:

Organisations post-implementation that need stability and continuous optimisation

Lean IT teams that lack the bandwidth or specialised knowledge to manage ServiceNow effectively

Rapidly scaling businesses that need their platform to grow with them without re-hiring

Compliance-heavy industries (healthcare, BFSI, government) that require rigorous audit trails and security controls

Final Thoughts

ServiceNow is a powerful platform - but its value is only realised when it’s managed, maintained, and continuously optimised. Whether you’re struggling with post-go-live chaos, falling behind on upgrades, or simply not getting the ROI you expected, ServiceNow Managed Support Services offer a proven path forward.

Running IT operations without a Cloud Console feels like… honestly, guessing half the time 😅 You’re jumping between tools, chasing alerts, trying to figure out what’s wrong before users even notice. It’s exhausting.

With a Cloud Console, everything is in one place—performance, uptime, logs, alerts. It gives IT and NOC teams a clearer view of what’s actually happening, especially in hybrid setups where things can get messy fast.

And the thing is, it’s not just about monitoring 👀 It’s about reacting faster, preventing issues, and making smarter decisions before problems grow. That’s where real efficiency starts to show.

Infrastructure Managed Services are essential for businesses that depend on reliable and secure IT systems to support daily operations and long-term growth. Goognu provides professional Infrastructure Managed Services that help organizations efficiently manage, monitor, and optimize their IT infrastructure while reducing operational complexity and minimizing downtime. With proactive monitoring and expert infrastructure management, Goognu ensures that business-critical systems remain stable, secure, and high performing.

Goognu’s Infrastructure Managed Services include complete IT infrastructure support such as 24/7 monitoring, server and network management, cloud infrastructure administration, storage management, virtualization services, endpoint security, and compliance monitoring. Using modern monitoring platforms and automation tools, Goognu quickly detects infrastructure issues and resolves them before they impact business operations. Regular patch management, system updates, and performance optimization keep IT environments secure and running efficiently.

These Infrastructure Managed Services are designed to support a wide range of IT environments including on-premise infrastructure, hybrid cloud platforms, and multi-cloud architectures. Goognu also helps organizations modernize legacy infrastructure, implement disaster recovery solutions, manage secure data backups, and optimize workloads for improved performance and cost efficiency.