Organizations can be under huge pressure to make changes to their IT estates. In particular, there are two drivers of this change.
Firstly, there’s the pressure to innovate. The rapid advancement of technology and AI coupled with shifting business priorities can put organizations under pressure to adopt the latest tools, with vendor messaging advocating for the speed of adoption. Simultaneously, ongoing inflation and slower economic growth can mean there is a need to find more cost-effective solutions.
Secondly, there’s the change that is forced. Operating systems might be reaching their end of life and need upgrading, or there are outages and cyber threats to defend against. There have also been several recent examples of software vendor prices rising significantly due to ownership changes, like with VMware, and companies therefore needing to find new solutions for their budget and reduce vendor dependency.
However, in dealing with these pressures, the trap companies can fall into is trying to deliver all of this change at once and within a small timeframe. Yet in doing so, this change becomes harder to manage and the risk of outages and system failures increases. So, how can they deliver any change that is needed safely?
The dangers of too much change at once
The main challenge in changing too much too quickly is visibility. Companies have to oversee complex IT estates – on-prem systems, the cloud, servers, end-user computing, networks – where change is constant and security updates are largely automated. As this change happens, there are more interactions between older and newer systems, different operating systems, different products, and this means the risk of failure can increase.
Configuration drift, for example, occurs when changes, which haven’t been recorded or authorized, cause a system to drift away from its intended baseline (of how it should perform). Without the right monitoring software, this drift can remain invisible, creating added risk to every subsequent change – and that’s when an outage or cyber incident happens.
In May, for example, Google Cloud suspended Railway’s production account without warning because Railway couldn’t see that the platform had a technical dependency on GCP that caused it to fail, leading to an eight hour outage.
What’s more, as we’ve seen with the adoption of AI tools, change can happen faster than training and processes can keep up with, further increasing the risk of disjointed workflows, security vulnerabilities and data breaches. But even when teams can see the changes that need to take place, they can also be faced with the challenge of deciding how to modernize their existing applications.
Finding alternatives to the buy-or-rebuild dilemma
Of course, trying to slow down change isn’t always possible. A company might have been priced out of its VM software or needs to upgrade its applications for security purposes. In this position, traditionally, IT teams have had to either buy new software or rebuild existing apps, which can both be expensive and time-consuming.
This can lead to vendor lock-in, as IT doesn’t see a viable alternative and doesn’t have the engineering capacity to rewrite applications tied to their original operating systems.
To overcome this dependency, as agentic coding matures, organizations may increasingly opt for a third option: using AI agents to build their own replacements for SaaS tools. But while this can appear to remove vendor lock-in and license costs, it also transfers responsibility for maintenance, security, configuration and ongoing support in-house, making it even harder to oversee change without additional resources or capacity.
However, there is another route. Packaging and migrating existing applications can allow teams to modernize without taking on the burden of building from scratch. By packaging an app’s or virtual machine’s existing operating system dependencies, teams can move them into containers and modern desktop infrastructure without needing to rewrite the app.
The app maintains its existing behavior, but can now work on the latest operating systems and in workspaces like AWS.
Delivering change at scale
With a modernization strategy formed, how do teams gain ongoing visibility across their entire estate and know when apps need to be packaged?
With so much change taking place, manual monitoring and reconciliation processes will struggle to keep up with the demands of infrastructure modernization. Instead, teams should consider using configuration monitoring software to gain continuous visibility into change across their entire estate.
Drift detection tools, for example, can automatically measure change across an estate against established configuration baselines and alert IT teams whenever a change triggers a system to move away from its baseline. This means that an automated patch by an external provider or a manual intervention by a user gets detected and flagged to IT, changes that might otherwise go unnoticed and trigger an outage further down the line.
Imperatively, this estate-wide visibility means teams can see and understand the impact of any unauthorized changes taking place and intervene before they lead to failure.
It also gives them the information they need to understand how a transformation project might interact with the systems currently running in their estate, helping to inform the feasibility and implementation of the proposed changes and deliver more targeted, impactful and safer change.
Alongside configuration visibility, it’s also possible for teams to automate the packaging and delivery of apps, saving them a large amount of time and cost in manually performing a typically laborious task. This subsequently creates a repeatable and scalable process that enables apps to be regularly deployed and made available to users.
Escaping the trap
With so much pressure to change, above all, escaping the transformation trap requires a mindset shift. It involves, one, seeing change as an ongoing problem to manage, and two, not attempting to carry out too many innovation projects at once.
Small, incremental changes can deliver more meaningful impact and ensure systems are properly deployed or integrated, while this targeted approach also provides more capacity for IT teams to deal with any forced change that might surface.
Yet by prioritizing change visibility, IT teams can mitigate forced change by addressing risks earlier and seeing when upgrades are needed in good time. And by automating processes like packaging apps, they gain more capacity to prioritize innovation projects as routine changes take place faster and more securely.
When these processes are joined together, instead of grappling with an overwhelming and uncontrolled level of change that increases risk, teams can ensure change remains a driver of security, resilience and innovation.
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