Modernizing legacy systems to embrace a loosely-coupled microservices architecture is the biggest predictor of success for continuous delivery, according to Google Cloud’s 2021 Accelerate State of DevOps report. Studies continue to show that the most elite DevOps performers enjoy more frequent code deployments, faster lead times to deploy, low change failure rates and faster time-to-recovery.
Leading enterprises like Netflix, Tesla and Starbucks proved that a microservices architecture minimizes fine-grained dependencies between services, which can then be independently tested, deployed and scaled. Combined with DevOps best practices, this reduces technical debt and allows for modernization based on a factory model approach that incorporates automated analysis and deep observability.
That said, application modernization to date has been a manual process requiring multi-year projects that suffer a high failure rate. How can we apply modern tools, known DevOps best practices and desired business benefits to improve and accelerate a company’s modernization efforts? In other words, how do we make modernization more modern?
By using automation, AI and data science, building repeatable pipelines and shifting architecture left, architects can get in front of technical debt before it becomes unmanageable. In this article, we’ll explore these practices in more detail.
Intelligently Automate Everything Possible
DevOps methodologies have taken manual steps and applied automation to create repeatable processes that scale. Modernization teams today are in dire need of these methodologies, as they are stuck with manual approaches that don’t scale across an entire application estate. Thus, applying intelligent automation, AI and data science to modernization—and creating a repeatable pipeline for refactoring—is a natural extension of DevOps successes over the last decade.
Continuous Integration, Continuous Deployment, and Continuous Modernization
CI/CD methodologies are a core best practice for DevOps teams and are already familiar patterns that development organizations are using for their application life cycles. But, there is no continuous delivery without continuous modernization. Elite teams continuously monitor technical debt accumulation and address it at every application release cycle, thereby implementing continuous modernization in their application life cycles.
Deep Application Observability
Observability, defined as monitoring, logging and tracing, is a foundation for cloud-native architectures. Modernizing an existing monolith requires deep observability beyond simple static code analysis to include deeper domain-driven behavior analysis and dynamically tracking dependency interactions. This is also the secret to uncovering dead code that is no longer used.
Ensure Architectural Parity
You must understand your infrastructure architecture to inform your application architecture and your modernization options. Lift-and-shift causes headaches for many organizations because the traditional three-tier architectures of monolithic applications have a completely different topology than cloud-native applications, which are designed from scratch to leverage the efficiencies of the cloud.
Whether it’s a hybrid approach (part on-premises, part cloud), public or private cloud, it’s important to ensure that your modernization strategy ensures architectural parity between the target application and its ultimate destination in the cloud. Also, it’s important to understand your modernization options: Rehost, replatform, refactor, rewrite, etc. What can you lift-and-shift and what needs more attention?
To find the answer, incorporating data science-driven analysis, automated service extraction and, more importantly, people, to help you understand the possibilities is critical.
Get Executive Support for Your Modernization Project
This isn’t about simply churning through your backlog; your executive sponsors for a project of this scope need to understand, in business terms, why this is crucial for the organization. There are plenty of metrics showing the financial and opportunity costs of maintaining mission-critical applications that are aging and problematic.
To get executive buy-in for your modernization initiatives, you need to formulate a business case that communicates the cost of maintaining the legacy apps, both in time and resources to maintain, but also the negative impact on innovation, customer acquisition and retention and speed to market.
DevOps practices emerged to improve how IT organizations reliably and efficiently deliver software from development to operations and out to customers. Applying these emerging technologies of automation, pipelines and deep observability to application modernization initiatives will enable teams to accelerate how they deliver application transformation projects. By investing in training application teams in these methods and providing modern tooling to support that training, organizations more reliably and more efficiently move both people and projects forward into the next generation of cloud applications.
