Even before the onset of a global pandemic, IT professionals were coming to the conclusion that their legacy tools were no longer fit for the demands of today’s modern organizations. Their tools have likely met the needs they were originally purchased for, but chances are they’re insufficient to help organizations grow, innovate and move their IT teams from a cost-center to an engine for digital transformation and business success for one simple reason: those tools weren’t built for it.
If you look at typical legacy IT monitoring and management tools, you’ll find point solutions that were built in-house are more likely purchased from smaller, point-tool companies. They’ve been augmented, updated and patched as far as they can stretch. Any integration is most likely of the swivel-chair variety, relying on your IT team to jump back and forth among different tools and screens in an attempt to piece together the bigger picture. Bolting afterthought add-ons onto an outdated system is not an effective way to deliver a unified, predictive, automated, machine learning-driven IT management system that can meet the challenges and demands of today’s increasingly digital enterprises.
So, with that being said, let’s take a look at five reasons why your legacy tools are holding your IT team back.
Legacy Tools Weren’t Built for the Cloud
Legacy tools were built for a physical or virtual IT infrastructure that resided within the walls of your data center and under the control of your IT team. They were designed to manage monolithic applications — a single system that scales or changes very slowly and is disconnected from other services and systems. Plus, they were built to deliver data the IT department cared about, not the key performance indicators (KPIs) that drive your organization’s success. The tools you use today that provide domain-specific capabilities already struggle to track and manage complex systems. This difficulty increases when those tools need to manage an infrastructure that comprises multiple hosted cloud solutions or loosely coupled microservices.
Whether your IT operations are completely or partially on-prem, you know your future investments will be in the cloud, and senior leaders are keeping a keen eye on that investment. You’re committed to the cloud journey, but your current tools don’t map your new application destinations. You need to make appropriate investments in tools built to monitor and manage more than physical and virtual IT infrastructure. The tools you invest in today must be able to keep you and your business informed regardless of where your key applications reside and operate, and be future-proofed for whatever technological disruptions come next.
Legacy Tools Have Stretched as Far as They Can
Have the demands on your IT department and your network changed since your current tools were planned and implemented? Legacy tools weren’t designed to handle the demands you face every day. The tools themselves are likely operating at the limit of their capabilities, and they certainly weren’t built to take advantage of the new world of data. Today’s environments produce data from increasingly diverse sources — including containerized workloads, microservices and unique SaaS provider APIs. Applications themselves are now highly distributed, making it even more difficult to collect and use incoming data to gain actionable insights in the environment.
Inflexibility in tools often becomes a key limitation in your organization’s ability to rapidly adopt and operationalize new technologies. And if they’re already struggling today, what does that mean for next year, or three years from now? What happens when your tools prevent you from capitalizing on your business’s most critical services? They become barriers to success. The tools you use will often dictate your outcomes. Modern tools need to be as agile and flexible as the demands you put on them. They can bend, but they should not break.
Legacy Tools Were Not Built for Empowering Digital Transformation
If we’re honest, many of the legacy tools still in use today aren’t very different in design or function than the first IT monitoring and incident management tools that defined the market. In fairness, the demands on those tools did not change much once they adapted to virtualized workloads. Back then the demands on IT were simpler and mirrored the organization’s mission: keep everything up and running.
Management tools gave you numerous dashboards to identify specific issues in limited context. You would seldom be able to get an end-to-end perspective on your applications and infrastructure. If the environment was large or complex, you typically had to choose between moving between numerous instances or having significant gaps in coverage.
These days you may find your IT organization judged by very different criteria, including cost metrics and revenue goals, in a much more complex and diverse landscape. That’s because the mission has changed. You’re expected to be a primary driver of digital transformation, including the adoption of new technology distributed across multiple environments. You won’t be able to do that effectively with tools designed before broad cloud adoption and mobile customer engagement. Modern tools must empower both the IT organization and the business, because technology has become a critical component of every organization and a direct line to the customer.
Legacy Tools Are Domain-Centric
Systems built over time often include a variety of tools, most of which were designed to only handle specific tasks. Combine this with the tooling sprawl that occurred with the adoption of agile development and DevOps and you have a kaleidoscope of complexity, making it very difficult to collect, aggregate, correlate and analyze all the data necessary to view and manage overall business service health and performance. IT departments need a single tool that can handle diverse use cases and provide the right information for the right context. True AIOps platforms were built specifically to address that need.
Legacy Tools Lack Intelligence
Legacy tools are still mostly reactive rather than proactive, let alone predictive. The “AI�? in AIOps stands for “artificial intelligence�? (even if the functionality is actually machine learning-based). The value of machine learning for IT is pretty well established. The machine learning at the core of AIOps solutions allows them to automate repetitive monitoring and incident management activities and, as they learn, predict an incident before it happens.
While some vendors will tell you they can graft AI-like features onto their legacy systems, at best they’re trying to fill gaps and plug leaks. Only a system built from the ground up with machine learning at its core is able to offer true AIOps functionality and quickly adapt to meet future needs. Learning systems must not be an afterthought, but core to your tooling strategy with intelligence present at every stage of the operational life cycle.
Now Is the Best Time to Investigate AIOps
This is a difficult and challenging time for everyone that raises unique challenges for IT professionals. Recent events have highlighted both successful technology implementations and lingering legacy challenges. I would suggest it’s never been more important for IT teams to ensure alignment with the overall business and show their value beyond the basics.
An AIOps approach can help you succeed in today’s complex technology landscape and reduce cost by consolidating outdated tools that have been holding you back from your true potential. AIOps is the best option to make your IT department more efficient and cost effective while improving your overall customer experience. I’d argue that these are the KPIs that matter most to your organization during these uncertain times. Most of us have a new perspective on the impact unexpected conditions can have on our technology systems. If you think you’ll be asked to reconsider your IT priorities and goals in the next few months, now is the time to build an informed plan.
