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You can use this pattern when gradually migrating from a back-end application to a new architecture. The strangler fig pattern may not be suitable if the requests to the back-end system cannot be intercepted. When dealing with smaller systems without much complexity, it’s better to go for a wholesale replacement rather than choosing this pattern.

Here’s how you can implement the strangler fig pattern:

Transform

Given below is an example of legacy code and architecture, where all the modules are tightly coupled, and it is hard to maintain them in the same condition with upcoming modern technology.
Here, the loan service contains three services: personal, partner, and business loans.

Code Snippet:

We choose the personal loan method as the first to refactor. It could be unreliable, inefficient, outdated, or even hard to get skilled developers to maintain the same legacy code.

Let’s make a new implementation for the personal loan service and divide it into separate classes or even a microservice. After correcting or refactoring our code snippet, we can create a Proxy class for handling both new and old approaches.

We have developed a new API with a separate database. Initially, all services used a shared database, but as part of code refactoring, the personal loan module had to be decoupled from the existing database. The same applies to the API endpoint.

Coexist: where two implementations coexist together.

Here we have extracted another layer abstraction from the loan service and made it coexist with the original service. Both services provide the same functionality, and the signature of the services is also the same. The proxy will decide whether the call goes to a new API or an existing service.

Run new service with a fallback of old service: In such a scenario, we always have a safety buffer if the new one fails.

Run both services and compare the output to confirm whether the new one works fine. In such a scenario, to avoid duplicate loans or transactions, we should turn off all external references and assume that we accept loan data only from one source.

Use a feature flag to decide whether to use the new API or the old one. Here in the configuration, we can set a flag, and it will choose how the call will work — whether with legacy API or with Newly developed service.

Most companies understand that successfully competing in a digital age demands flexible and scalable IT systems. Experimenting with data sharing and the applications or cloud platforms that work best for your business is expected and allows for quick changes that won’t derail projects and workflows.

As a result of this experimentation, businesses on a global scale began to launch programs that focus on modernizing their technology and legacy systems, concentrating on rethinking the modernization process and how they should go about it. A vital component to digitally transforming a business is realizing the potential impact of sharing data in real-time. Real-time sharing of data and analytics is crucial to the modern approach to utilizing data insights.

Relying only on internal data is no longer sufficient. However, if companies can make the correct data information available to the right people, collaborations begin to form, and valuable insights and knowledgeable input can improve business decision-making.

Modernizing company technology can have an incredible impact on many industries where data in real-time is crucial to quality assurance, including food sourcing, customer experience, aviation safety, and efficient global supply chains. There isn’t an industry on Earth that won’t see improvements from sharing data in real-time because it enhances the ability to make educated decisions faster.

There’s no question that the open-source version of Terraform Enterprise is the most popular. A massive reason for that is that companies typically begin using this version, utilizing a POC to work on growing an infrastructure. However, it’s common for many businesses to start using Enterprise over open-source as time passes and company needs evolve.

Launching your Terraform journey with a small team and a mutual understanding among that team regarding how to manage resources and files from a Terraform open-source perspective is advised. Companies use Terraform to configure the information they have stored in their cloud platform.

There’s no need to reconfigure and establish provisions all at once, so don’t be afraid to start slow, allowing Terraform to map out real-world (and real-time) resources that will assist in your application configuration and inevitably improve company performance.

Kicking off your company’s journey with Terraform means choosing the version that will keep you moving forward. Smaller teams will likely not need additional assistance other than the open-source version of Terraform to keep company-wide infrastructure in the right state.

However, as teams grow, or teams that are large from the start, will likely find a need to employ Terraform Enterprise. In a more substantial company, managing and maintaining the resources related to Terraform can become challenging. It’s common for administrative teams to develop a process using tools to help align Terraform’s integration.

While these new processes may help, there is often too much time spent creating a workflow that works around Terraform, which can defeat the original purpose of the software. Companies that work with remote teams need access to cloud service and better, more efficient access to cloud controls, and Terraform Enterprise can help safely manage that infrastructure. Still, companies need to determine the best way to implement a new way of doing without creating dependency on a specific team or team member.