Most organizations that adopt DevOps for conventional applications use automation tools and techniques, including Infrastructure-as-Code (IaC) and Configuration-as-Code (CaC), automated testing, release automation and application orchestration. Applying automation to operations isn’t always straightforward, especially with older systems that don’t easily fit into typical DevOps automation tools and strategies.
Yet legacy systems don’t have to sit on the sidelines of a DevOps automation strategy. It’s entirely possible to integrate legacy system requirements with today’s common automation techniques using the right tools and methodologies.
For example, IaC tools may not support legacy systems because they don’t support the required configuration languages or management tools. Current systems are configured using languages like YAML In contrast, legacy systems often depend on proprietary configuration languages and frameworks.
Similarly, test automation can be cumbersome to implement in the context of legacy applications. Most modern automation frameworks are designed for browser-based or mobile apps. However, legacy systems may run locally and they often use proprietary user interfaces. That makes automating testing more difficult.
Likewise, many release automation and application orchestration platforms are designed for applications deployed using containers. Because containers didn’t become popular until the release of Docker in 2013, most legacy systems have limited native support for application containerization.
Bring Automation to Legacy Systems, Step by Step
Fortunately, the obstacles to implementing DevOps automation for legacy systems are possible to overcome. Addressing these challenges requires adopting some innovative practices that enable the integration of automation with legacy systems:
- Migrate to the cloud: Legacy system vendors now offer cloud-based hosting platforms. While transferring legacy workloads from on-premises to the cloud doesn’t automatically enable all DevOps automation features, it does significantly facilitate the use of automatically scalable infrastructure and the ability to move workloads between cloud data centers to mitigate failures in one location.
- Containerize legacy workloads: In certain situations, legacy applications can now run in containers. Containerizing such apps allows businesses to manage them using orchestration solutions like Kubernetes, bringing much greater agility and scalability to legacy application management.
- Use machine learning : Incorporating machine learning into monitoring and management operations for legacy systems is a way to detect issues effectively in contexts where it’s not possible to leverage conventional automation. For example, if you can’t run automated tests for a legacy application because Selenium won’t support it, advanced machine learning techniques may help identify bugs based on how the application behaves.
- Change your mindset: A critical step toward taking advantage legacy applications’ automation is to change your organization’s mindset toward legacy systems. Instead of classifying them as outdated and inefficient environments, treat legacy applications with equal respect to all other software within your IT estate. It becomes much easier to refine a corporate culture toward collaboration and innovation that extends to those legacy systems.
Don’t Ignore Legacy Environments
There’s no denying that automating the management of legacy applications for DevOps teams can be more challenging than implementing automation for modern software. However, this doesn’t mean that it’s impossible. Many organizations successfully adopt automation as a strategy to improve their legacy software’s flexibility and quality, while reducing the cost of building and deploying them. But to achieve this, it’s necessary to think beyond the conventional approaches of DevOps.
Image source: Photo by Sebastián Santacruz on Unsplash
