Why you need the cloud to maintain your traditional LMS
The global EdTech market is expected to exceed $349 billion by 2030, with learning management systems (LMS) being one of the fastest growing segments. As AI becomes integral to modern learning, these platforms are expected to provide predictive insights, automated workflows, and highly personalized learning experiences. However, many providers still operate legacy LMS systems that are unable to support modern workloads and data-intensive features. These platforms are rigid, expensive to maintain, and slow to update. Release cycles often span quarterly or annual updates, widening the gap between user expectations and platform capabilities.
To break this pattern, organizations need to make architectural changes. LMS cloud deployment provides that foundation. Moving from a legacy environment to a cloud-based LMS can dramatically reduce TCO while accelerating the deployment of new learning capabilities. This article explains how migrating legacy LMss to the cloud can help EdTech providers modernize their LMS, reduce operational complexity, and deliver meaningful improvements faster.
The state of EdTech and LMS: growth, pressure, and expectations
Let’s take a look at where the existing LMS market is.
market trends
The broader EdTech sector is in the midst of rapid expansion. According to Grand View Research, the global market is expected to grow at a compound annual growth rate (CAGR) of 13.3% over the next five years.
growth pressure
This pressure is caused by multiple factors, including:
Increased demand for personalized and flexible learning Increased adoption of digital classrooms Emergence of data-driven pedagogy supported by AI, analytics, and adaptive learning
As a result, institutions and organizations are under pressure to modernize their LMS and the technology stack that supports it. At the same time, the market for AI-enabled educational tools, especially those that support adaptive learning, is growing even faster. The global AI in education market was valued at approximately $6.7 billion in 2024 and is projected to grow to nearly $39.8 billion by 2030 [1].
LMS segment snapshot
As the demand for EdTech and AI in education surges, the LMS market is also growing. According to recent data, the global LMS market was valued at approximately $24.05 billion in 2024 and is projected to grow to $70.83 billion by 2030. Despite this rapid growth, the bar for agility and better experiences remains higher than ever.
Current bottleneck: Why traditional LMS systems have high TCO and slow releases
Traditional LMS platforms used to work. This is because the previous workloads were not as dynamic and robust but still met expectations for quick releases. However, it is not the same today. Traditional LMS systems currently face several challenges. [2]:
Cost and maintenance burden
Traditional LMS systems rely on expensive on-premises infrastructure, database licenses, and hardware refresh cycles. They also require a dedicated IT team to maintain them, increasing operational overhead. Deploying features that are slow and risky
The monolithic codebase found in traditional LMS systems is error-prone to updates and requires extensive regression testing to ensure success. Hidden risks and opportunity costs
Outages during feature rollouts or minor updates can disrupt the learner experience and damage your reputation. Additionally, when teams spend too much time maintaining a legacy LMS, they incur an opportunity cost to innovate.
LMS cloud deployment
Organizations are increasingly moving from traditional LMS systems to modern cloud-based LMS. LMS cloud deployments provide a direct response to traditional limitations by eliminating infrastructure overhead, improving reliability, and empowering teams to innovate instead of troubleshooting.
What does cloud adoption actually mean for an LMS?
A cloud-based LMS deployment looks like this:
1. SaaS LMS (fully managed, multi-tenant)
Organizations subscribe to an LMS through a turnkey agreement where the vendor manages hosting, updates, security, and scaling. Ideal for organizations looking to minimize operational overhead.
2. LMS hosted or managed on a public cloud
Often accomplished through lift-and-shift or replatforming, this approach preserves an institution’s LMS while moving to a cloud platform such as AWS, Azure, or Google Cloud.
3. Hybrid cloud LMS model
The core LMS is hosted on-premises or in the cloud, and advanced functionality (analytics, AI/machine learning) runs as cloud-native modules, giving you greater flexibility.
How does LMS cloud deployment reduce total cost of ownership?
Before moving legacy applications to the cloud, it makes sense to find out whether an on-premises setup or a cloud-based learning management system will actually cost more.
TCO breakdown for on-premises legacy LMS solutions
To run a legacy LMS platform on your own server, you need:
infrastructure and equipment
Servers, storage, networking, backup hardware, DR sites, power, cooling, physical security. Software and license
OS, database, middleware, licenses, support contracts, third-party plugins. people and business
Time spent by LMS administrators, DBAs, infrastructure engineers, security teams, plus patching, upgrades, monitoring, and incident response.
TCO breakdown after moving to a cloud-based learning management system
Moving to a cloud-based LMS or managed model changes your TCO profile. Pay the following fees:
Cloud services and subscription fees
There are predictable cloud service costs for LMS licenses, compute, and managed databases, typically on a per-user or usage basis. However, there are also upfront costs for cloud migration for initial evaluation, configuration, and optimization. Infrastructure and storage
There are no on-premises hardware, physical data centers, or facilities. You only pay for what you use, including cloud data storage costs, backups, and content delivery.
Your cloud service provider handles all platform updates, security patching, and basic security, allowing your in-house resources to focus on innovation and future roadmaps instead of normal operations. The net effect is that more spending shifts from surviving traditional LMS platforms to funding product improvements and new learning experiences.
How can cloud deployment speed up LMS feature delivery?
Moving from a traditional LMS to a modern cloud LMS solution fundamentally changes the delivery model for new features. Benefits include:
CI/CD pipeline for faster releases
A cloud-native LMS simplifies development, future updates, and feature rollouts via CI/CD pipelines. As a result, all code changes are automatically tested and deployed to staging and production environments with little manual intervention.
Shorter release cycles Reduced rollback incidents
Modular, microservices-friendly architecture
Modernizing a cloud-based legacy LMS allows you to separate assessments, lectures, notifications, and analytics into smaller services. Each of these services can be updated, extended, and deployed independently without impacting the entire platform.
Reduce downtime Easier experimentation
Enabling AI and data-intensive features
Moving legacy applications to the cloud frees up flexible compute and storage for AI models, recommendation engines, and real-time analytics. As a result, your LMS can handle much larger amounts of event data (clicks, completions, rating submissions, etc.).
With flexible computing and data processing, cloud-based LMSs are also ideal for AI integration. Cloud platforms provide easy access to managed AI services, scalable APIs, and real-time data pipelines so you can embed features like adaptive learning, automated scoring, semantic search, recommendations, and predictive risk scoring directly into your LMS workflows. Instead of adding another tool, you can place your AI models close to your training data, process large numbers of events locally, and continually improve your models as usage increases.
Adaptive and personalized learning experiences Future-proof EdTech solutions
What do you expect from the future of legacy LMS modernization?
In essence, LMS cloud adoption is less about “moving servers” and more about repositioning the LMS as a product that can evolve quickly to match learner expectations. As legacy LMS modernization efforts gain momentum, the next wave of platforms will be cloud-native, AI-enabled, and modular in design in nature. We also expect integration between cloud-based LMSs and AI agents, opening the door to greater decision-making autonomy. A cloud-based LMS with agent AI capabilities makes digital coaching more realistic, allowing you to adjust learning paths based on streaming data rather than waiting for instructors to override decisions. For LMS owners, the decision now is not whether to migrate, but how quickly they can align their roadmap to this future.
References:
[1] Section 1: Introduction and strategic background
[2] From obsolete to optimal: Solving the challenges of legacy systems
