Topic: Monolith Transformation

Simplify Refactoring Monoliths to Microservices with AWS and vFunction

Posted on April 20, 2022 by - Uncategorized

refactoring effort

The Challenge to Modernize Complex Legacy Applications

With estimates that 80% of the world’s business systems still not cloud ready, executives have begun to mandate initiatives to modernize their legacy applications for the cloud. These legacy applications are usually large monolithic systems with years or decades of accumulated technical debt, making them difficult to change, expensive and risky to scale, and weighing down an organization’s capability to innovate.

For simple use cases, some teams begin modernizing their legacy stack by re-hosting some applications on a cloud platform like AWS. Though rehosting an application on AWS can bring immediate cost reductions, customers still have to manage and maintain these applications, which are often composed of tightly-coupled services which are difficult to change and face risks of downstream effects.

For very complex and large legacy monoliths however, enterprises quickly run into a wall with re-hosting alone. Put simply, the more lines of code, classes, and interdependencies, the less value we’ll get from lifting and shifting. To gain agility, these applications must be modularized, and that means refactoring, rearchitecting, or even rewriting critical legacy applications to be cloud native. 

Solution Overview: Analyze, Select, and Decompose Services

AWS Migration Hub Refactor Spaces is a modernization platform for developers working with applications that are not cloud native, or that are in the midst of their journeys to be cloud-native.. 

AWS Refactor Spaces provides the base architecture for incremental application refactoring to microservices in AWS, reducing the undifferentiated heavy lifting of building and operating AWS infrastructure for incremental or iterative refactoring. You can use Refactor Spaces to help reduce risk when evolving applications into microservices or extending existing applications with new features written in microservices.

vFunction, an AWS Partner, provides an AI-driven platform for developers and architects that intelligently and automatically transforms complex monolithic Java applications into microservices, restoring engineering velocity and optimizing the benefits of the cloud. Designed to eliminate the time, risk, and cost constraints of manually modernizing business applications, vFunction delivers a scalable, repeatable factory model purpose-built for cloud native modernization.

Using vFunction Platform and AWS Refactor Spaces together can solve the dual challenges of decomposing monolithic apps into microservices and then iteratively and safely stage, migrate, and deploy those microservice applications onto AWS environments. This lets enterprises breathe new life into their legacy applications, and refactor old code for new cloud environments.

Legacy system architects and developers start off with vFunction, which analyzes the complexity of monolithic apps using automation, artificial intelligence (AI), and patented analysis methods, allowing architects to automate and accelerate the re-architecting and rewriting of their legacy Java applications into microservices.

The Base Report – Static Analysis to Calculate Technical Debt

base report
The Base Report from vFunction Assessment Hub

Within minutes of installing vFunction, we see the vFunction Base Report (image above). Using static analysis data, vFunction uses machine learning algorithms to calculate technical debt and quantify it. vFunction then enables architects and developers to begin building a business case for modernization. The primary goal of the Base Report is to help stakeholders make an informed decision about which apps and services to prioritize for modernization.

In the vFunction Platform, technical debt is calculated by looking at the complexity, calculated based on the number of entangled interdependencies that reflect tight-coupling between business domains, and the risk, calculated by the length of class-dependency chains that increase the impact of downstream changes to any part of the system.

As a result, vFunction is able to determine the “Cost of Innovation”, which is a metric that reveals how much per $1.00 invested is needed simply to manage your system’s technical debt, rather than innovating and building new functionality. In this case, the company will have to spend $2.80 (x2.8) to achieve $1.00 towards innovation. The Post-Refactor metric shows that by tackling the top 10 High Debt Classes alone, this can be reduced to $2.20 (x2.2). 

The Refactoring Effort – Dynamic Analysis to Determine Priorities

refactoring effort
The Refactoring Effort Radar in vFunction Modernization Hub

We can now look at Refactoring Effort analysis in the image above. Adding to the static analysis performed earlier, vFunction now performs patented dynamic analysis that leverages AI to build a representation of the effort it would take to refactor the application. 

These parameters are based on vFunction analysis utilizing clustering algorithms and graph theory to measure complexity scores based on: 

  • Class Exclusivity
  • Resource Exclusivity
  • Service Topology 
  • Infra Percentage
  • Extracted Percentage

Class Exclusivity 

Class Exclusivity refers to the percentage of classes exclusive to specific services. A high class exclusivity score means that most services contain whole domains, indicating more bounded contexts and fewer interdependencies.

Resource Exclusivity

Resource Exclusivity refers to the percentage of application resources–like Java beans, DB tables, sockets, and files–that are exclusive to the services. Similar to class exclusivity, a high resource exclusivity score hints that the domain is encapsulated within the service, and that there are limited constraints for extracting the service.

Service Topology

Service Topology refers to the complexity of service-to-service calls required for the application to run. In this case, we want a lower service topology score, which indicates less chatter and communication overhead between services. In some applications, it is required to add more complexity to the communication between services in order to increase class and resource exclusivity. This is a decision that architects will be required to make in many complex applications. 

Infra Percentage Score

Infra Percentage refers to the number of overall classes that vFunction recommends be put in a common library. A high infra percentage score indicates a low amount of infra classes found in common libraries, which helps us avoid tight coupling between services and limits technical debt.  

Extracted Percentage

The Extracted Percentage refers to the percentage of classes that can be safely removed from the monolith based on the target refactoring plan. A high percentage here indicates that it will be possible to eliminate any remainder of the original monolithic application.

Using these scored metrics above, we can then enter the Analysis pane (aka vFunction Studio) of the vFunction Platform dashboard to view the exact services identified, with drill down capabilities to better review the analysis. 

service creation
The Analysis pane in vFunction Modernization Hub lets your merge, split, and analysis different services

In the image above, we are looking at a sample application called Order Management System (OMS). This image shows a visual representation of the services and classes in this application. The size of the circle is determined by the number of classes called in each service. Green circles represent services with high class exclusivity (over 67%), and blue circles represent services with lower class exclusivity (between 33%-67%). The higher the class exclusivity, the easier it will be to extract it into a microservice architecture–it is less tightly-coupled and the number of interdependencies is lower.

Further interaction with the platform reveals interdependencies between beans, synchronization objects, database tables, database transactions, and more. You can drill down into a specific service to see entry points and call trees, classes that were found by the dynamic analysis or by the static analysis, tracked resources, and dead code classes. The platform allows you to refine the boundaries of the services and determine the architecture, while automatically recalculating the metrics of the designed architecture. Next, you can iteratively extract any service.

service extraction
Create and extract a newly configured service in JSON with vFunction Modernization Hub

The image above shows vFunction extraction configuration of your updated single microservice to a target platform and source repository. The platform then generates human readable JSON files that includes all the information to create the service with the extracted code from the original monolith using vFunction’s Code-Copy utility, which we can then run in our terminal or IDE.

In the next section we’ll look at how to take your extracted services and use AWS Refactor Spaces to set up and manage the infrastructure to test, stage, deploy the new version of your service.

Solution Overview: Deployment to AWS

Now that we’ve looked at the vFunction Platform experience, let’s look more at the sample application architecture after service extraction and the beginning of modernization. 

The OMS example referenced above is a legacy Spring Framework application running on Apache Tomcat 9 and deployed on an AWS EC2 instance. In the image below, we see a system architecture in which the original monolithic OMS application is running on Tomcat 9 (bottom right).

aws refactoring

Using AWS Refactor Spaces, we employed the familiar Strangler Fig Pattern on the OMS application, decomposing it into microservices with vFunction and deployed to AWS (top right). From a previously monolithic architecture, we’ve split the OMS into multiple services deployed with Kubernetes on AWS Elastic Kubernetes Service (EKS) using NGINX for exposing the REST API. 

We created a proxy for the OMS app, services, and routes. In this case, there are two services: one for the original monolith, and the other representing the microservice extracted by vFunction and now running on EKS with NGINX Ingress. This produces default routes to the service that represents the monolith, along with the URI path that routes API calls to the other controller service.

aws ec2

In the end, we’ve produced an API gateway that routes the API calls to a network load balancer and transit gateway. Some traffic continues to go to the monolith running on EC2, where we have the product and inventory data. Other traffic goes through NGINX–with the same URL, but with a different route–to the other controller in EKS. 

Conclusion – Start Decomposing Your Monolith

To conclude, enterprises that have been challenged by having to modernize highly complex legacy applications within their business landscape can now jump-start their journey to cloud native architecture, in a de-risked, methodical, and iterative way. 

With the vFunction Platform to assess, analyze and extract services from the monolith, and with AWS Refactor Spaces to route and manage traffic, architects and developers are now enabled to employ the Strangler Fig pattern to decompose a traditional application into services, and route requests to two different destinations: the original monolith, and the newly decomposed microservices.

Does this seem like a good fit for your modernization initiative? Contact vFunction to learn more about our products in a personal demo session with one of our engineers. 

“Java Monoliths” – Modernizing an Oxymoron

Posted on March 1, 2022 by - Uncategorized

Use AI and Cloud-Native Principles for Selective Modernization

In the late 1990s, Java quickly proved invaluable for building applications that depended on n-tier architectures to deliver web sites at scale. The web wouldn’t be what it is today if it weren’t for the power of Java Enterprise Edition (Java EE).

Today, those massive object-oriented applications of the 1990s and 2000s are themselves legacy – and all those Java EE monstrosities have become today’s monoliths.

The irony in this situation should not be lost, especially for those of us who lived through the Web 1.0 days. 

Object orientation promised all the benefits of modularity at scale – but now, complex interdependencies and questionable architectural decisions counteract any advantages that modular code might have promised.

Despite Java EE’s modularity and encapsulated business logic, its package-based deployment model remained monolithic. Today, Java EE apps have become an oxymoron – the antithesis of their original vision of modularity.

Are we stuck, then, with these creaking Java monoliths, nothing more than impenetrable spaghetti?

The good news: the answer is no. It’s possible to modernize legacy Java code in such a way that preserves what value remains while moving to a new paradigm of modularity based on microservices: cloud-native computing.

If it Ain’t Broke, Don’t Fix it

The first principle of legacy modernization, Java monolith or not: if it ain’t broke, don’t fix it.

Just because some code is old, runs on older infrastructure, or was written in an out-of-date language, doesn’t automatically mean that you should replace it.

Instead, the modernization team should take a close look at legacy assets in order to sort them into four categories: reuse, refactor, rewrite, or replace.

Business priorities should drive the decisions on how to sort various software objects. What value does the code provide today? What value does the business expect from its modernization? What is the cost of the modernization, and is a particular approach cost-effective?

Sometimes it makes the most sense to leave code in place (reuse). In other cases, transitioning from legacy to modern code without changing its functionality meets the business need (refactor).

In other cases, fixing existing code simply isn’t practical, in which case rewrite or replace is the best choice.

Resolving Dependencies

Well-written Java code was certainly modular, but its complicated inheritance and instantiation principles easily led to a proliferation of interdependent objects and classes.

Mix in the multiple tiers that Java EE supported, and the interdependencies soon became intractable “spaghetti code” messes. Any successful Java modernization project must untangle these messes in order to come up with a plan for cleaning them up.

Dynamic and static analysis techniques that identify the appropriate groupings of functionality that will reduce interdependencies is essential for understanding the complex interconnections within legacy Java applications.

vFunction uses graph theory and machine learning-driven clustering algorithms to automatically identify such groupings. The goal is to identify target microservices that fall into optimized business domains.

Business domains, in fact, are central to cloud-native architecture, as they provide the boundaries between groups of interconnected microservices.

In other words, cloud-native architectures introduce modularity at a level that is more coarse-grained and thus more business-focused than the modularity at the object level that Java and other object-oriented languages support.

Note, however, that these two types of modularity work hand in hand. Modern microservices might be written in Java, .NET or other object-oriented languages, and thus a single microservice might contain multiple such objects. 

Iterating the Architecture

vFunction also discovers interdependencies among database tables and the various objects and services that access them. The platform further optimizes service decomposition accordingly.

Once a platform like vFunction exposes interdependencies and recommends groupings of target microservices, it’s up to the architects to iteratively fine-tune the architecture. 

This human touch further minimizes dependencies and optimizes the exclusivity and cohesion of target microservices – in other words, ensuring that each microservice does one thing and one thing well.

Architects are also able to refine the modernization plan following the first rule of modernization above – deciding which parts of the code the team should reuse, refactor, replace, or rewrite.

Architects can handle these tasks entirely within the vFunction platform UI, taking advantage of the insights that the platform’s machine learning have provided into the optimal organization of microservices into business domains.

Building the Target Microservices

When the modernization effort calls for new or refactored microservices, the vFunction platform specifies those services in JSON format, essentially providing a recipe for developers to follow as they create modern Java microservices (typically using Spring Boot) that refactor or replace existing functionality as necessary.

This microservice specification also aids in testing, as it represents the functionality that the modernization analysis has identified. In other words, the specification feeds the test plans that ensure that modernized functionality behaves as required.

Just as architects will continue to iterate on the architecture, developers should continue to iterate on creating and updating microservices. 

Modernizing a monolith is itself not a monolithic task. It’s essential for the entire team to look at modernization as an ongoing process that continues to discover previously unknown interdependencies that lead to selective refactoring and rewriting as the overall cloud-native microservices architecture continues to mature.

The Bottom Line     

Modernizing legacy Java monoliths by creating modern microservices as part of a cloud-native architecture deployment may represent the entire modernization effort for some organizations – but more often than not, this effort is only one facet of a more complex modernization strategy.

A typical large enterprise, for example, may have many different instances of legacy technology, including mainframe and client/server applications that may consist of many different languages.

A successful enterprise modernization strategy, therefore, must invariably focus on the business benefits of modernization, where the team carefully balances benefits with the significant costs and risk of such initiatives. 

Adding to this challenge is the fact that modernization is always a moving target as business requirements change and available technologies and best practices continue to evolve. 

Calculating a firm return on investment for modernization, therefore, can be a difficult task – but don’t allow the challenges with measuring its business benefits get in the way of getting started.

Copyright © Intellyx LLC. vFunction is an Intellyx customer. Intellyx retains final editorial control of this article.

Migration Strategies Basics: Lift and Shift, Refactor, or Replace?

Posted on February 4, 2022 by - Uncategorized

As the pace of technology innovation increases by the minute, companies of all sizes are racing to become more data-driven and efficient. The recent pandemic has only accelerated this process–industry analyst IDG reports that “Application/legacy system modernization” has risen in importance to become a top priority for CIOs in 2022 . Forward-thinking businesses will continue to innovate and compete for decades to come if they use the right mix of modern solutions, techniques, and strategies, becoming more agile and responsive as a result.

Migrating applications to different JVMs, frameworks, operating systems, and infrastructure is often one of the first opportunities identified as part of an overall application modernization strategy. Application modernization begins with a comprehensive assessment of an organization’s application estate, which includes, among other decisions, which applications should migrate to the cloud and how migration fits into your overall modernization initiatives. Although this process can be challenging, new technology makes the process easier and more reliable. 

Gartner specifies application modernization services as those that “address the migration of legacy to new applications or platforms, including integrating new functionality to provide the latest functions to the business. Modernization options include re-platforming, re-hosting, recoding, rearchitecting, re-engineering, interoperability, replacement and retirement, as well as changes to the application architecture to clarify which option should be selected.”

You can measure the success of a company’s application modernization strategy–including its efforts to migrate to the cloud by re-hosting or replatforming–by evaluating how it has changed its products and services to digital environments, along with the acquisition of skills tied to these changes. Companies that have become digitally mature utilize information and communication technologies in a significant part of their activities and have the capability and willingness to modernize their processes, functions, and organization.

Why Do Companies Decide to Modernize Monolithic Applications for the Cloud?

To level set terminology, a monolithic application is defined as “an app that has all or most of its functionality within a single process or container, and it’s componentized in internal layers or libraries.” 

It is this type of mature application that often represents core application functionality and is responsible for a significant percentage of product or service revenue. Making small changes on the outside of this application can bring some limited benefits, but unless the primary business system is targeted for modernization, the most significant benefits of the cloud are rarely achieved: 

  • Improving application performance and scalability
  • Increasing development team velocity, morale, and innovation
  • Eliminating technical debt: “Technical debt is a concept in programming that reflects the extra development work that arises when code that is easy to implement in the short run is used instead of applying the best overall solution.”
  • Improving compliance and security

In general, companies want to enhance the user experience, keep employees productive and motivated, and ensure sensitive data is protected. Their applications would benefit from being in the cloud to scale, secure, and comply with these goals. 

However, when decision-makers run into limitations for new initiatives and processes due to old and outdated applications, they reach a breaking point: They either stay the same and lose competitiveness, or determine that modernizing business-critical applications and development processes must become a priority.

Related: Monolith to microservices: all you need to know

Assessing Legacy Applications

If the previous sections sound familiar to you, perhaps you want to take the next step in modernizing monolithic applications for the cloud. In this case, Gartner recommends considering the following factors when assessing the value of modernizing legacy applications.

Business fit

Competitors are modernizing their apps and moving them to the cloud or using SaaS for their solutions. This lets them innovate faster, provide a better customer experience, and recruit the best employees. The longer you wait, the more market share they gain.

Business value

Modern applications benefit from modular architectures or microservices, which allow for easy changes with less risk. Customers can benefit from faster value delivery.

Agility

Developers are able to add new features faster with modern applications because the development process is accelerated. Automated building, testing, and releasing builds streamline time-to-market processes.

Cost

In modern applications, operating costs are significantly lower because they typically operate on a pay-as-you-go model. Using this method avoids both wasting resources and paying to keep infrastructure running during downtime. In addition, the price and overhead of infrastructure management decrease.

Complexity

In monolithic systems, adding new features is difficult because of tight coupling and dependencies. This sort of complexity is also responsible for the difficulty in decoupling monolithic services and moving from on-premise servers or data centers to the cloud. You have to weigh these pros and cons.

Risk

Making changes to complex monolithic systems can have unpredictable downstream effects on unrelated parts of the monolith, which carries a significant risk. Businesses should assess the costs, vulnerability, competitiveness impact, and operational consequences before making a decision.

With these concepts, you will be able to evaluate your applications more efficiently and choose the best approach to modernization. This will allow you to make the right decision for your company.

Lift and Shift, Refactor, Replace, or Another Option?

If you’ve heard only about lift and shift, refactor, and replace, know there are other ways to begin your application modernization journey. Here are some ways Gartner explains.

Encapsulation

This approach makes the application’s features accessible as services through APIs by encapsulating or separating their data and functions.

In other words, the process creates a more modern interface or API for the existing application and its components making it easier to access by other, newer cloud-native applications but doing nothing to modernize the system or improve the architecture for the future.

You may benefit from encapsulation in the short term because it allows you to move your application to a modern API-driven interface without spending time rewriting it. While it’s a gradual transformation, it is also a stop-gap approach that continues to accrue technical debt and slow down innovation. Thus, in turn, this method comes with some risks, too. Monolithic applications are complicated because of their complexity and size. Without decoupling the logic into microservices, you cannot take advantage of the full benefits of the cloud.

Lift and Shift Strategies (Migration)

Simply put, the “lift and shift” method can also be described as another way of saying that an app will move to the cloud. It is a common mistake for companies to categorize their legacy application modernizations under this heading, as it genuinely does not modernize anything. The “rehost” and “replatform” categories above fall under the “lift and shift” label.

The first step in making lift and shift really work is to make sure that the application, which previously operated in the on-premises data center, still has access to the same data and documents once it is in the cloud. You can successfully lift and shift workloads from the data center to the cloud if the access to shared folders remains the same.

Suppose a company did not thoroughly examine its apps before making the “lift and shift” decision, but it still adopted this approach. In that case, it will oversimplify modernization’s goals and merely move technical debt to the cloud without achieving any substantial business benefits.

It’s good to know that you don’t have to make the migration strategy decision alone. Companies can modernize their applications with the most efficient migration strategy thanks to technology. Check out the following section to learn how.

Replatform

This migration style means making as few changes as possible to the code for it to run on a new platform, such as the most current operating system. Replatforming does not require you to  manipulate the app’s architecture or functionality.

There is no need to undertake a significant development initiative with replatforming, which makes it cheaper. Taking small steps can be beneficial at first, then you can scale up as needed. The approach also allows you to migrate some workloads to the cloud, run tests on a cloud platform, analyze the results, and then move on to other workloads without committing to a lengthy migration process.

You can leverage the cloud effectively using cloud capabilities such as auto-scaling, managed storage and data processing, infrastructure as code, and more.

This method is not without its risks. One of them is the scope of your work can increase the possibility of turning a replatforming project into a much greater refactoring effort. Limit scope and avoid unnecessary changes to reduce this possibility.

Automation is further necessary since you can’t manage cloud workloads manually after replatforming. As a result, it is essential to invest in automation tools to allow for some flexibility when using the application in the cloud.

Rehost (Migration)

Rehosting refers to migrating the application without modifying its code, data, or functionality to another infrastructure, on-premises or in the cloud. 

With rehosting, you can often migrate relatively quickly and test in the cloud in case there is anything wrong. There’s a risk of disruption to business services unless your organization understands this and is ready with enough contingency plans. Additionally, rehosting may lead to poor user experiences early on, which could hurt user retention. 

Replatform (Migration)

This migration style means making as few changes as possible to the code for it to run on a new platform, such as the most current operating system. Replatforming does not require you to manipulate the app’s architecture or functionality.

There is no need to undertake a significant development initiative with replatforming, which makes it cheaper. Taking small steps can be beneficial at first, then you can scale up as needed. The approach also allows you to migrate some workloads to the cloud, run tests on a cloud platform, analyze the results, and then move on to other workloads without committing to a lengthy migration process.

Refactor (Modernization)

As opposed to migration tactics like rehosting or replatforming, refactoring is the application modernization process of reorganizing and optimizing existing code. It lets you get rid of outdated code, reduce significant technical debt, and improve non-functional attributes such as performance, security, and usability. 

This modernization strategy matches cloud infrastructure to actual resource requirements, which results in long-term cost savings. Refactoring provides long-lasting ROI by enabling you to scale when required and reducing resource consumption.

Furthermore, by refactoring, you can also adapt to changing requirements since cloud-native, and microservice architectures make it possible for applications to add new features or modify existing ones right away. 

There are a few downsides to consider. First, without automation, this strategy requires a large number of manual resources. It is much more complex than lifting and shifting, so it traditionally has taken much longer for projects to become profitable. You can’t rely on just anyone to refactor because you need a team with advanced coding, automation, and DevOps skills. The code, infrastructure, and configuration are also at high risk of errors. Last, the smallest mistakes in refactoring cause delays, many cost overruns, and service disruptions. Automation can address these issues.

Rearchitect (Modernization)

The design of some outdated applications prevents them from working in the cloud because they are just not compatible. When this occurs, it is prudent to modernize the application in its entirety by rearchitecting it. It takes a lot of coding to move to a new application architecture in order to make the most of the apps’ features. 

With this modernization method, you break up applications into smaller, more manageable pieces for subsequent individual adaptations and development. You can transfer each component, or microservice, to the cloud separately.

In addition to requiring significant adjustments, without intelligent automation and analysis tools to support the architect, this effort will take a great deal longer and cost more than other alternatives. Nevertheless, the benefits include more flexibility, scaling, and control over the architecture.

Rewrite (Modernization)

Using this approach is a good idea when you need to upgrade a business application and  need to alter some of the previous specifications or functionality while retaining others. This is a good approach for companies that have invested significant amounts of time and money in developing their own applications. A business that rebuilds and innovates, can retain its intellectual property and unique selling propositions, making it a good option for them.

During the rewriting process, you will be able to engage with customers once again and make your customized applications even better. Unfortunately, this approach requires substantial time and expense investment, as well as considerable expertise. 

Replace

This solution offers to replace the application with a brand new version of the software or SaaS service that will take into account any further requirements, user requests and perhaps even use a different technology stack.

In replacement, you can compare different apps and get the ones that work best for your business. If you find something that works better, you can switch apps relatively easily. With the replace approach, the app’s developer is responsible for updating, improving, and securing your application with the replace approach. This can also help relieve you of other migration concerns.

On the other hand, replacing old systems can be problematic for employee engagement due to users becoming attached to the old systems since they are accustomed to using them. Managing change and collaborating with your user base is vital, or you might have a hard time while they adapt. Without custom apps, you might lose future ROI, and you’ll have little say on future features or updates.

Partnering Strategically to Make Application Modernization Happen

Both migration and modernization strategies can be complex and diverse, as you may have noticed. Determining which one is the best, implementing it, and preventing risks is not a simple process. However, you can choose a strategic partner to achieve the best results.

vFunction is at the forefront of cloud and application modernization. Its goal is to assist leading companies globally in accelerating their journey toward cloud-native architecture and gaining a competitive edge. With a factory model purpose-built for cloud-native modernization, the solution removes the time, risk, and cost constraints associated with manually updating business applications.

The vFunction AI-driven platform enables software architects to rapidly and incrementally modernize their legacy application portfolios and technology leaders to unlock the power of the cloud, innovate, and scale. The vFunction Platform consists of two products:

  • vFunction Assessment Hub: vFunction Assessment Hub analyzes the technical debt of a company’s monolithic applications, accurately identifies the source of that debt, and measures its negative impact on innovation. The AI-powered solution measures app complexity based on code modularity and dependency entanglements, measures the risk of changes impacting stability based on the depth and length of the dependency chains, and then aggregates these to assess the overall technical debt level. It then benchmarks debt, risk, and complexity against the organization’s own estate, while identifying aging frameworks that could pose future security and licensing risks. vFunction Assessment Hub integrates seamlessly with the vFunction Modernization Hub which can directly lead to refactoring, re-architecting, and rewriting applications with the full vFunction Modernization Platform.
  • vFunction Modernization Hub: vFunction Modernization Hub is an AI-driven modernization solution that automatically transforms complex monolithic applications into microservices, restoring engineering velocity, increasing application scalability, and unlocking the value of the cloud. Utilizing both deep domain-driven observability via a passive JVM agent and sophisticated static analysis, vFunction Modernization Hub analyzes architectural flows, classes, usage, memory, and resources to detect and unearth critical business domain functions buried within a monolith. Whether your application is on-premise or you have already lifted and shifted to the cloud, the world’s most innovative organizations are applying vFunction on their complex “megaliths” (large monoliths) to untangle complex, hidden, and dense dependencies for business critical applications that often total over 10 million lines of code and consist of 1000’s of classes.

Through our solutions, software companies can become faster, more productive, and truly digitally transformed. Contact us if you want to see how we can convert your legacy application to a modern, high-performance, scalable, and authentic cloud-native architecture. Request a demo today.

Intesa Sanpaolo transforms monoliths into microservices

Posted on February 2, 2022 by - Uncategorized

Executive summary

Three years ago, the management of Intesa Sanpaolo adopted a modern IT vision to evolve both infrastructure and applications. Although microservices were still a cutting-edge technology they would form the basis for building the applications we now label as cloud native. This decision was designed to initiate the modernization of applications and services to address modern IT challenges, achieving three objectives: cost control, better stability and scalability, and greater customer satisfaction.

In this case study we will describe the challenges, how Intesa Sanpaolo decided to convert one of its main business-critical applications from a monolithic application to microservices, and how a platform called vFunction helped to turn this challenge into a success.

The challenge

Microservice & PaaS transformation to modernize legacy applications

Three years ago, the management of Intesa Sanpaolo adopted an IT modernization vision that evolved both infrastructure and applications. Although microservices were still a cutting-edge technology at that point, they would form the basis for building the applications we now label as cloud native. This decision initiated the modernization of applications and services to address their modern IT challenges, achieving three objectives: cost control, better stability and scalability, and greater customer satisfaction.

The Solution

vFunction accelerates microservice transformation

Using vFunction, Intesa transformed FVCB0, one of the FVCB monoliths, into a microservices application, delivering the three essential business functions provided by the application monolith: import, download and flow management. It was a collaborative effort between Intesa Sanpaolo and vFunction with Intesa Sanpaolo teams to accelerate microservice transformation, providing extensive feedback and feature requests to vFunction. Before refactoring, FVCB0 was based on Java, and WebLogic. Following the refactoring, the application is now based on JBoss and OpenShift and compatibility tests are underway for portability to the public cloud.

Scaling modernization across the organization: factory model

After deploying vFunction on a dozen applications, the Intesa Sanpaolo team needed a way to manage the entire modernization process at scale.  They wanted to understand the modernization stage for each application and manage vFunction across multiple applications at the same time.  This included starting and stopping the learning phase, reviewing the potential extracted services from each application from a central location, prioritizing which applications to refactor first, and enabling all of these actions with minimal involvement from the development and testing teams. vFunction responded to the challenge by releasing its production agent which could be deployed automatically on hundreds or thousands of applications in production, as well as its factory dashboard and management console. These latter capabilities allow vFunction to support the modernization journey of hundreds of applications while providing visibility and control to the project team.

The results

3x Increase in Deployment Frequency, Lower Costs

vFunction has enabled Intesa Sanpaolo to accelerate their modernization journey. The major improvements that refactoring brought them can be classified into three categories: cost, application management, and customer satisfaction. From the point of view of costs, the reduction of WebLogic licenses and over four months of savings per application – which translates to both time and manpower savings. This significantly reduced development/test cycles and manual deployment activities, translating to substantial cost improvements. A 3x increase in release frequency, combined with the principles of automated deployment to Intesa Sanpaolo’s Platform-as-a-Service (PaaS) platform, has made infrastructure management a much leaner experience. Finally, from the customer’s point of view, refactoring has allowed for increased stability, better scalability and reduced downtime for updates, increasing customer satisfaction.

Fortune 100 bank uses vFunction’s AI and automation to decompose massive legacy Java monolith

Posted on February 1, 2022 by - Uncategorized

Executive summary

With over $2 trillion in assets, this Fortune 100 bank is one of the largest asset holders in the world. As a publicly-traded, government-sponsored bank, they were created 50 years ago to expand and finance the secondary mortgage market in the United States.

Fast-forward several decades. They are now faced with a catalog of aging monolithic Java EE applications and increasing technical debt. After years of attempting to modernize with internal teams and external resources, they turned to the vFunction Platform, which provides AI for Application Modernization. 

Within 3 weeks, vFunction provided never-before-seen insights and observability into their scariest legacy Java EE application (over 10,000 classes and 8 million LoC), enabling them to accelerate their AWS cloud adoption initiatives by 25x and cut the cost of modernization by 3x.

The challenges

Internal mandate for cloud readiness

  • As a traditional brick-and-mortar company, the company has been tracking the development of cloud computing trends for over a decade. 
  • With the benefits of the cloud becoming proven in the field, they began investing tens of millions of dollars into developing a secure cloud platform onto which would be migrated their hundreds of traditional applications. 
  • After several years of hard work, research, and analysis, only a small percentage of their legacy applications were now running on their cloud infrastructure. 
  • Due to the size and complexity of their legacy Java EE applications, something else was needed to achieve their goals.

Massive legacy footprint

  • The company processes around $1 billion per day, mainly through legacy systems built with Java EE 6 and Oracle’s WebLogic web server. 
  • Their largest and most complex application is a 20-year-old monolith with over 10,000 classes and 8 million lines of code (LoC). 
  • After spending nearly 2 years internally trying to wrap their arms around this enormous and business-critical application, the team was frustrated with the lack of progress. 
  • Outside help was needed so that their development organization could focus more on their core capabilities and accelerate innovation.

Lack of success clouding the future

  • Several years of intensive project strategy sessions with both internal and external teams achieved limited results and refactoring was still not within scope.  Without a solution to automatically and intelligently extrapolate and organize the application into something understandable and actionable, the company was in a tough position.
  • They needed to ensure their future application architecture was architected to work in a complementary way to take advantage of cloud native services. 
  • This meant refactoring, which is extremely difficult and time-consuming for humans, but made much easier with automation, AI and data science: enter vFunction.

The solution with vFunction

Automated complexity analysis

  • vFunction provided a multi-phase approach to automate the analysis of the company’s legacy Java applications, assessing the complexity of selected apps to determine readiness for modernization.
  • First, the vFunction agent was installed to observe and learn the business domain-driven application flows, in the pre-production environment. 
  • This included deep tracking of call stacks, memory, and object behaviors from actual user activity, events and tests. 
  • This analysis, which synthesized dynamic learning with directed static code inspection of the binaries, ensured complete coverage of all app flows and enabled to prioritize & plan modernization in the most comprehensive manner.

AI and data science

  • Using patented methods of static analysis, dynamic analysis, and dead code detection, plus data science and AI, vFunction helped them prioritize which applications to modernize first.
  • Dynamic and static analysis applied graph theory and clustering algorithms to automatically identify optimal business-domain microservices and untangled deep dependencies across databases, classes, and resources. 
  • This enabled them to better preview refactorability, stack rank applications, estimate schedules, and manage the modernization process to accelerate cloud native migrations.

Actionable recommendations with automated execution

  • vFunction enabled architects to design services using the platform’s interactive UI design studio, providing the ability to refine service boundaries, automatically refactor classes, assign code to common libraries, and conduct impact analysis of design decisions based on the architect’s input.
  • This included methods for optimizing service decomposition based on database dependency discovery & analysis, which discovers, detects, and reports on which database tables are used by which services when decomposing a monolith.
  • In the final stages, they was able to extract services using vFunction’s human-readable JSON format specification files, then build and test new microservices based on the newly refactored code that runs natively on their existing application stack.

The results

25x reduction in time-to-market

  • After years of intense but ultimately unsatisfactory efforts, the company was able to unlock and take action on never-before-seen insights about their largest Java monolith within just a few weeks of installing the vFunction agent–a time-to-market reduction of over 25x.

3x reduction in cost of modernization

  • Powered by vFunction’s AI-driven insights and actionable recommendations, the company’s massive cut in time-to-market directly reduced the cost of modernization by more than 3x compared to manually decomposing the application without vFunction.

ROI on the horizon for internal cloud platform 

  • The combination of vFunction and the company’s cloud ecosystem built on AWS has enabled them to move forward with their strategy of refactoring and migrating hundreds of legacy Java applications to the AWS cloud, faster and less expensively than ever imagined.

The Best Java Monolith Migration Tools

Posted on January 17, 2022 by - Uncategorized

As organizations scale to meet the growing tsunami of data and the sudden rise of unexpected business challenges, companies are struggling to manage and maintain the applications that run their business. When unprepared, exponential data growth can tax a company’s legacy monolith Java systems and their IT departments. 

To solve that challenge, massive data-driven companies such as Amazon, Uber and Netflix have moved their data from a single unit monolith architecture to microservice cloud architecture. In this article, we will examine the Java migration tools needed to decouple bulky and unscalable monoliths.

What are Java migration tools?

Java migration tools help organizations upgrade from a monolithic to a microservices system. They assist in the re-architecture and migration of Java applications and the databases, files, operating systems, code, websites, networks, data centers and virtual servers that make up the application.

What is a monolithic architecture?

Monolithic architecture is a single-tiered software application that integrates several components into a single program and onto a single platform, using the same backend codebase.

In many cases, the monolithic structure is built on a Java Enterprise Edition (JEE) platform such as WebLogic, WebSphere, or JBoss or often a Spring Framework. Usually, a Java monolith application has a layered design. There are separate units for data access, application logic and the user interface.

A monolith architecture starts small but as the business and its data grows, it stops suiting the business’s needs.

●  Because the applications are tightly coupled, the individual parts can’t be independently scaled

●  The tight coupling and hidden dependencies make the code difficult to maintain

●  Testing becomes complicated

In a recent survey in TechRepublic Premium, they asked 477 professionals about their plans to transform their monolith systems into more manageable microservice architectures. According to the study, the vast majority (96 percent) of respondents knew at least something about microservices. A still sizable majority (73 percent) have already started integrating microservices into their application development processes. Of those who hadn’t started, 63 percent are toying with the idea.

Further, respondents reported that the top benefits to cloud microservice architecture are:

●  Faster deployment of services (69 percent of respondents)

●  Flexibility to respond to changing conditions (61 percent of respondents)

●  The ability to quickie scale up new features into large applications (56 percent of respondents)

●  Increased standardization of services (42 percent of respondents)

●  Reduced technical debt (33 percent of respondents)

Among those who had begun the transformation, the best-ranked application development tools were REST, Agile, Web APIs, DevOps, or a combination. Containers and cloud services were also popular among respondents. However, only 1 percent used COBRA.

Related: Migrating Monolithic Applications to Microservices Architecture

The advantages to monolithic architecture

Despite the fact that so many companies are moving away from monolithic architectures, there are advantages to a single application. It is easy to develop, easy to test and easy to deploy. In addition, horizontal scaling is relatively simple. Operators simply run multiple copies behind a load balancer.

The disadvantages of monolithic architecture

Monolith architecture presents a number of challenges, including difficulty in scaling, difficulty in maintaining, performance issues, lack of reliability, less reusability, cost, and unnecessary complexity. Since everything is in a single application, there is a tight coupling between components. 

A large code base makes it difficult for developers and quality assurance teams to understand the code and business knowledge. It does not follow Single Responsibility Principle (SRP) and there are more restart and deployment times.

What are microservices?

Before you lift the hood of a car, you see a single unit. Underneath the hood of a car, however, is a complex set of parts that propels it forward or backward, stops it on command and monitors how each part of the car is functioning.

A microservices architecture is similar to a car in that while to front-end users, it may seem like a single unit, underneath the metaphorical hood is a suite of modular services. Each of them uses a simple to use and well-defined interface to support a single business goal while communicating with other services.

Each service in a microservice system has its own database that is best suited to its needs and ensures loose coupling. For example, an ecommerce microservice system might have separate databases for tracking online browsing, taking and processing orders, checking inventory, managing the user cart, authorizing payments and shipping.

The advantages of microservice architecture

Going back to the car analogy, imagine if, instead of separate parts, everything under the hood wasn’t just interconnected. Imagine that each part was permanently affixed to each adjacent part. In that scenario, if a single belt breaks a mechanic has to change out the engine, transmission and entire drive train.

While that analogy might be overly simplistic, it does illustrate some of the benefits of microservice architecture. As with a car, separate yet interconnected services gives organizations the flexibility to individually test, deploy, maintain and scale services without affecting the rest of the application or disrupting functionality as a whole.

Java migration tools offer a convenient pluggable architectural style for cost-effective and fast upgrades.

The disadvantages of microservice architecture

Microservice architectures contain several user interfaces, each potentially programmed with its own language and each with its own set of logs. As such, communication can be a challenge, as can finding the sources of bugs and coding errors. 

Testing a single unit in a microservice system is much easier than testing a huge monolithic system, but integration testing is not. Each of the components of a microservice system is distributed, which means that developers can’t test their system from individual components.

Because an architecture contains multiple microservices, each with its own API, interface control becomes critical.

How to assess your current infrastructure for a microservices cloud migration

Before committing to migrating from a monolithic Java application to microservices cloud applications, it’s imperative that a company conducts a thorough assessment of their current situation, which includes:

●  Determining future needs and goals

●  Mapping transaction flow through the current infrastructure

●  Assessing response time impact risks

●  Assessing security and infrastructure requirements

●  Evaluating current resources

●  Classifying data

●  Determining compliance and migration requirements

●  Assessing operational readiness

●  Determining timeline and budget

Related: How to Conduct an Application Assessment for Cloud Migration

Cloud migration challenges

According to a recent report, nearly two out of three companies say that they’re still managing security via manual processes despite the fact that about one in every three companies admit that most misconfigurations and errors were caused by humans.

Lack of automation isn’t just a security risk. Cloud transformations are resource-heavy. One of the reasons companies wish to migrate to the cloud is to free-up resources, so further charging in-house resources with conducting a cloud assessment and managing and enacting a cloud migration is not only counterintuitive, it’s costly and resource-prohibitive.

Single pane of glass platforms conduct assessments and manage and track the entire cloud migration across an enterprise estate as well as integrate information from numerous sources. The single pane of glass appears as a single display, such as a dashboard.

The Seven “R”s of cloud migration

In 2010, Gartner wrote about the five ways to migrate to the cloud. At the time, those included: rehost, refactor, revise, rebuild and retire. In the years since, most experts add replatform and rewrite to the list.

●  Rehost (lift and shift)  – Rehosting is fairly intuitive and relatively simple. During a migration, applications and servers are “lifted” from their current hosting environment and shifted to the cloud or rehosting infrastructure.

●  Replatform – Replatforming is a modified lift and shift. During a replatform, some modifications are made to the application during the migration. Replatforming does require some programming.

●  Repurchase – Repurchasing, or “drop and shop” means to drop all or part of the existing architecture and moving to new systems altogether.

●  Refactor – Manual refactoring is resource intensive in that it requires re-architecting one or more services or applications by hand, unless more modern automated refactoring tools are used.

●  Retain – If a company chooses to implement a hybrid approach to cloud migration, they may retain the parts of their current architecture that works for them.

●  Rewrite – Some companies rewrite, rebuild or re-architect a monolithic application or system to be cloud-ready. Rewriting takes a considerable programming team.

●  Retire – Some companies choose a retire strategy, which means identifying the services and assets that no longer benefit the organization. Retiring can be complicated and labor-intensive since teams will need to supervise to ensure nothing goes wrong before shutting those applications down.

Java migration tools

AWS Migration Services

For companies that find investing in entire new hardware and software infrastructure cost-prohibitive, AWS (Amazon Web Services) offers a cloud computing platform that mixes infrastructure as a service (IaaS), software as a service (SaaS) and platform as a service (PaaS),

Azure Migration Tools

Azure Migration Tools, a Microsoft product, offers a centralized hub where companies can track and execute a cloud migration to ensure that the migration is as seamless as possible and that there are no interruptions. One downside is that the hub is only available to companies that choose on-premises migrations.

Carbonite Migrate

Carbonite Migrate has a repeatable and structured process that lets users innovate. The tool reduces downtime and prevents data loss. Users have remote access and can migrate across environments, between physical, virtual and cloud-based applications.

Corent SurPaas

Corent SurPass promises to balance workloads by optimizing the migration process. It allows for quick transformation into SaaS applications.

Google Migration Services

Google Migration Services promises to eliminate data loss and improve agility during the migration. Its features include built-in validation testing, rollbacks to secure the data and live streaming during the migration and while running workloads.

Micro Focus PlateSpin Migration Factory

Micro Focus PlateSpin Migration Factory performs fast server migrations as it reduces data loss and errors. There is a built-in testing tool for each migration cycle. It is an excellent all-around tool in that it includes automated testing, executing, planning and assessment.

Turbonomic

Using artificial intelligence, Turbonomic optimizes and monitors workloads. Because it uses AI, it excels at complex hybrid cloud migrations. In addition, there are visual components that enable users to see what’s happening with their data.

CloudHealth Technologies

CloudHealth Technologies aligns business operations with infrastructure by using specialized reporting and analysis tools. Migration teams can set new policies for proper configuration. 

vFunction

vFunction accelerates Java migration projects by automating the refactoring of the Java monolith into microservices, saving years of rewriting and manual re-architecting time and money.

Cloudscape

Cloudscape uses infrastructure lifecycle reporting to simplify manual modeling. The tools demonstrate how data is scattered throughout the company architecture so migration teams can choose the best application and strategy,

ScienceLogic

Science Logic allows remote access where they can manage every aspect of the database migration. It lets users analyze even large databases.

Oracle Cloud

Oracle Cloud delivers IaaS, PaaS and SaaS services. It leverages built-in security and improved automation to mitigate threats.

Red Hat Openshift

Red Hat Openshift is a cloud-based PaaP that allows teams to build, test, deploy and run their own applications. Users can customize the functionality with any language and they can choose whether to manually scale or allow the system to autoscale.

Kubernetes

Kubernetes is an Open Source platform that, used on a cloud-based server, offers speed, simplicity and portability. It lets users deploy, scale and manage containerized applications. It’s also the fastest-growing project in the history of Open Source software. 

Transformations Can Be Easier

vFunction is the first and only platform for developers and architects that intelligently and automatically transforms complex monolithic Java applications into microservices. Designed to eliminate the time, risk, and cost constraints of manually modernizing business applications, vFunction delivers a scalable, repeatable factory model purpose-built for cloud-native modernization.

vFunction can help speed up software companies in their journey to become faster, more productive, and truly digitally transformed. If you want to see exactly how vFunction can speed up your application’s journey to being a modern, high-performant, scalable, true cloud-native, request a demo.

vFunction is headquartered in Palo Alto, CA. Leading companies around the world are using vFunction to accelerate the journey to cloud-native architecture thereby gaining a competitive edge.

Go-to Guide to Refactoring a Monolith to Microservices

Posted on January 12, 2022 by - Uncategorized

The transition from a monolith to microservices has become popular in the digital world because of its multiple benefits, including business agility, flexibility, and elimination of barriers associated with monolithic applications. You can enjoy these benefits by refactoring a monolith application to microservices.

And here, we explore the benefits of refactoring a monolith to microservices and the best practices of doing so.

Refactoring a Monolith to Microservices: Understanding the terms

With more and more companies moving to a cloud-first architecture, it is essential to understand the difference between monolithic applications and microservices. The two are styles of program architecture. 

An enterprise application has three parts: the database, a client application, and a server application. On the server application, there is a web interface, data layer, and business logic layer. This can be designed as a single monolithic block or as small independent pieces known as microservices.

A monolith application has all its components located in one program. It means that the web interface, data layer, and business logic layer are built in a single unit of application such as WAR or JAR. Most legacy applications are established as monoliths, and converting them to microservices is beneficial.

Related: Succeed with an Application Modernization Roadmap

Microservices architecture consists of small, autonomous programs that run independently and communicate via API (Application Programming Interface). One of the core benefits of microservices is that the individual components work differently and achieve their goals faster. The application can combine web analytics with e-commerce or AI services from different providers to work together and support different business procedures.

Benefits of Microservices in Detail

Microservices architecture has multiple other perks, including agility, scalability, upgradability, velocity, cost, and more. Let us discuss the advantages in detail.

Agility

The design of a microservice allows it to be disconnected from the rest of the system or program. As such, any adjustments made to it will not affect the functionality of the system. 

As a developer, you need not worry about complex integrations, which means making changes is easier, and there’s no need for a long testing time. So, migrating monolithic applications to microservice architecture is most often the best option as it enhances agility.

Great Focus on Value and Capabilities

Microservices users are not required to understand how it functions, the programming language it employs, or its internal logic. They just need to learn how to access and call its API method and know the data it returns. In essence, microservices can be reused across applications when they are well-designed.

Flexibility

Microservices architecture is self-contained. Designers are free to use frameworks, programming languages, databases, and other tools of their choice. If they wish, users can update to newer versions or switch between different languages or tools. As long as the exposed APIs aren’t modified, no one else is affected.

Automation

When comparing monolithic to microservices apps, the importance of automation cannot be understated. Microservices design allows for the automation of various essential operations that would otherwise be manual and tedious, such as building, integration, testing, and continuous deployment. As a result, employee productivity and satisfaction increase.

Cost-Effective

A nicely designed microservice is small enough to be developed, tested, and released by a single team. With the codebase being smaller, understanding it is easier, which maximizes team productivity. Additionally, since the business logic and data storage isn’t used to connect microservices, dependencies are reduced to a minimum. All of this contributes to improved team communication and lower management costs.

Easy Upgrading

One of the most significant differences between monolithic apps and microservices is upgradability. It’s crucial in today’s fast-paced market. Since it is possible to deploy a microservice independently, it’s easier to repair errors and add new features. 

A single service can be deployed without having to reinstall the entire program. It is possible to roll back the erring service if problems are discovered during deployment. This is more convenient than deleting the entire application.

Increased Velocity

All of the advantages above lead to teams concentrating on rapidly producing and delivering value, resulting in a velocity increase. Organizations can therefore adapt quickly to shifting business and technological demands. 

Related: Advantages of Microservices in Java

Why Refactoring A Monolith To Microservices Is The Best Migration Approach

In recent years, the popularity of cloud applications has led to a critical question: Which is the best approach to ensure long-term success? Refactoring has historically been rated as the most intensive migration approach, but new automated tools are changing that calculus. It is a disciplined process where developers review, rearchitect and re-code components of applications before migrating to the cloud.

This approach is adopted to fully take advantage of native cloud features and the flexibility they offer. Despite the resource commitment and the upfront cost, refactoring serves as the ideal way of producing the best return on investment in the long run. In addition, it offers a continuous cloud innovation model, with improvements in operations, functionality, resilience, security, and responsiveness. 

While refactoring a monolith to microservices, instead of the traditional time-consuming manual approach, we advocate that you use modern automation tools and also avoid refactoring all of your code at once while modernizing your application. Instead, we recommend refactoring the monolithic program in stages.

Why Not Just Use The Lift-And-Shift Approach To Get To Cloud?

Over the last decade, cloud experts and analysts have developed a conventional wisdom that it is desirable to move applications to cloud computing infrastructure. Besides, this is very handy in the modernization effort. 

Think of successful companies like Uber and Netflix, which were established in the cloud. Emulating them will lead to fast-growing and more productive companies. Moving to the cloud means re-platforming applications. This involves lifting databases and VMs from conventional servers to pay-as-you-go models with an IaaS provider.

The lift-and-shift approach is also in the cloud, and it provides excellent capabilities like maintenance of parallel instances or reserving excess capacity for recovery or failover purposes. However, because of the hefty nature of monolith applications, you might rack up shockingly large storage and compute costs while still having difficulty adding new functionality. 

This approach is not able to achieve efficient scaling or modern cloud-native agility. Therefore, refactoring a monolith to microservices remains the best method for a company aiming at achieving long-term success. 

Migrating Monolithic Apps to Microservices: Best Practices

When refactoring a monolith to microservices, you can do it manually or automatically. Below are guidelines to help you modernize your app, whether you go the manual way or use automated tools.

Find a Decoupled, Basic Functionality

Begin with functionality already separated from the monolith which doesn’t need changes to client-facing apps or the use of a data store. This should be converted into a microservice. It assists the team in upskilling and establishing the minimalistic DevOps architecture required in building and deploying the microservice.

Eliminate the Microservices Dependency on Monoliths

The dependence of freshly formed microservices on monoliths should be decreased or eliminated. New dependencies between the monolith and the microservices are established during the decomposition process. This is great because it does not affect the speed with which new microservices are built. The most challenging element of refactoring is generally identifying and eliminating dependencies.

We also recommend extracting modules with requirements that differ from the rest of the monolith. For instance, a module containing an in-memory database can be converted into a service and deployed on servers with better memory. Making the application considerably easier to scale by turning modules with specific resource requirements into services is possible.

Check out and Split the Sticky Functionality

Identify any form of sticky functionality in the monolith that too many monolith functions rely on unnecessarily. This will make removing additional independent microservices from the monolithic app difficult. To move ahead, flip the script on lift-and-shift modernization with refactoring. It can be a time-consuming and frustrating task, but the results are satisfying.

Use Vertical Decoupling

Usually, many decoupling attempts begin by separating user-facing functions to permit independent UI updates. Because of this technique, monolithic data storage becomes a velocity limiting issue. 

Instead, the functionality should be split into vertical “pieces,” with each piece containing business logic, UI, and data storage capabilities. The most difficult thing to unravel is knowing what business logic is dependent on which database tables. You must carefully separate the logic, capability data, and user-facing elements and direct them directly to the new service to successfully decouple capabilities from a monolithic app.

Prioritize Decoupling the Most Used and Changed Functionality

The main purpose of migrating microservices to the cloud is to speed up updates to monolithic features. To do so, the developers must first determine the most often modified functionality. The quickest and most cost-effective solution is to move this functionality to microservices. Focus on refactoring the business domain with the best business value.

Start with Macro, then go Micro

The new microservices should not be too small, at least at first, since this generates a complex and difficult-to-debug system. The recommended strategy is to start with fewer services, each with more capability, and then break them up afterward.

Use Evolutionary Steps to Migrate

Refactoring a monolith to microservices should be done in small, atomic stages. The atomic steps involve the creation of new services, routing of clients to the new services. It also involves retiring the code within the monolith that was previously delivering this functionality. This ensures that the developing team gets closer to the ideal design with each atomic step.

Note that the migrating app should work with all monolithic applications. The scale, agility, velocity upgradability, and affordability are some of the advantages the process should provide. These factors should not be negatively impacted at any point, and the migration should be completed quickly, intelligently, and automatically.

Simplifying the Migration Process

When examining refactoring a monolith to microservices, it’s evident that manual transformation is time-consuming, error-prone, labor-intensive, and requires significant architecture knowledge. These skills are lacking in the majority of companies. 

How about migrating automatically? Would it not be great if you could just drop a monolith application into a software modernization platform? This would have all of the time-consuming and complicated stages above accelerated and simplified. All the above best practices should be followed but in an intelligent, automated, and repeatable way.

Is there an Ideal Platform for Refactoring a Monolith to Microservices?

Refactoring an operational app into microservices has multiple benefits, as explored above. However, refactoring a monolithic to microservice isn’t a walk in the park. The developers must look for the best platform that can help in performing the task smoothly.

Are you wondering whether there is an ideal platform for this migration? Many platforms exist in the market, and you may get confused about the best product to use. If you’re in this situation, vFunction can help. It’s the first and only platform that allows developers to effectively and automatically refactor a monolith to microservices. It also restores the engineering velocity and optimizes the benefits of the cloud.

Some of the benefits include the elimination of cost constraints, risks, and time associated with manually modernizing your applications. Headquartered in Palo Alto, CA, with offices in Israel, vFunction is led by a team experienced who have been in the IT industry for a long time.

Do you want to learn more about vFunction? If yes, please request a demo to explore how vFunction helps your application become a modern and truly cloud-native application while improving its performance, scalability.