How to Migrate to Microservices

Migrating to Microservices may be risky, costly, and time-consuming unless the strategy is very well-defined in the beginning. Migrating to Microservices has been beneficial to many Fortune 1000 companies, which confirms its transformation potential to a variety of industries.

Our developers at Charter Global have expertise in Microservices, DevOps & QA Automation. We have successfully implemented in several Fortune 1000 companies, including Financial, Healthcare, and Retail & Media.

Charter Global recommends a practical three-step Microservices approach to focus on the business functionality allowing self-contained units to represent a module’s end-to-end functionality.

Learn More about How to Implement Microservices Framework Developed by Charter Global


Migration Approach

In order to migrate to microservices, you must first make a decision on a microservices architecture. Before trying to optimize its implementation, it is necessary to evaluate how the services will interact. Next, continually optimize those speed gains that microservices architecture provides. This requires flexibility in the tools used in deploying the architecture.

To migrate to microservices, a practical three-step approach is suitable:

Componentize: From your already existing applications, select a component and create a microservices implementation on a pilot basis.

Collaborate:  All stakeholders, programmers, and developers on the team should know about the techniques and lessons learned from the Pilot in Stage One. This keeps them updated with new processes and initiatives.

Connect: Complete the application and connect to users in a real-world scenario.



Microservices Benefits

Microservices Architecture comes with a lot of benefits. Some of which include:

Agility: Banking and Fintech applications are designed to be complex, constantly evolving and scaling, integrating with multiple systems (internal/external) as well as demand high security at various levels. Microservices support greater agility in building and managing these systems making them highly suitable.

Scalability:  Unlike a monolithic application that has a lot of resources wasted for scaling services that are not required since they are all packed together in a single deployable unit, each microservices can scale independently without affecting the other microservices.

Availability: Failure of one microservices does not affect other microservices, as the failed one can be uninstalled and rectified quickly with minimal downtime. It does not require the entire application to be brought down for maintenance, unlike the monolith application.

Maintenance: A separate microservices is created for each business service. This means that the amount of codebase is reduced and functional changes can be faster and more efficient due to the decomposed architecture.

Separation of Business Concerns: Microservices offer a clear separation of business concerns as each Microservices caters to particular business functionality.

Faster Deployment: by catering to single business functionality, the code-based required for microservices are reduced, creating a rapid deployment.


Charter Global

While migrating to microservices might be risky, costly and tasking, the inclusive quality of the application is undeniably bound to increase in the long run, provided that the strategy is rightly planned. Migrating to microservices has been beneficial to Fortune 1000 companies, ultimately confirming its potential for transformation for all varieties of businesses.

Our developers at Charter Global are experts in QA automation, DevOps, and Microservices, providing skilled resources, tools, and guidance in implementing DevOps processes and Microservices architecture.


Wrapping Up

This plan for migrating existing applications to microservices is intended to enable organizations to realize the benefits of microservices architectures, such as resilience, scalability, improved time to market, and easier maintenance, with maximum efficiency and minimal disruption to existing applications and services.

What are the 5 phases in the Software Development Life Cycle (SDLC)?

SDLC methodologies are used to create complex applications of varying sizes and scales, such as Agile, Waterfall, and Spiral. Each model follows a particular life cycle in order to ensure success in the software development process.

1. Planning and analysis

This phase is the most fundamental in the SDLC process. Business requirements are compiled and analyzed by a business analyst, domain expert, and project manager. The business analyst interacts with stakeholders to develop the business requirements document. They also write use cases and share this information with the project team. The aim of the requirements analysis is for quality assurance, technical feasibility, and to identify potential risks to address in order for the software to succeed.

2. Designing the product architecture

During the design phase, lead developers and technical architects create the initial high-level design plan for the software and system. This includes the delivery of requirements used to create the Design Document Specification (DDS). This document details database tables to be added, new transactions to be defined, security processes, as well as hardware and system requirements.

3. Developing and coding

In this phase, the database admin creates and imports the necessary data into the database. Programming languages are defined by requirements. Developers create the interface as per the coding guidelines and conduct unit testing. This is an important phase for developers. They need to be open-minded and flexible if any changes are introduced by the business analyst.

4. Testing

Testers test the software against the requirements to make sure that the software is solving the needs addressed and outlined during the planning phase. All tests are conducted as functional testing, including unit testing, integration testing, system testing, acceptance testing, and non-functional testing.

5. Maintenance

In a post-production, live software environment, the system is in maintenance mode. No matter the number of users, the sophistication of the software, and rigorous QA automation testing services, issues will occur. That’s the nature of software with managing data, integration, and security, and real-world usage. Access to knowledgeable, reliable support resources is essential, as is routine maintenance and staying up to date on upgrades.

Read More: https://www.charterglobal.com/what-are-the-5-phases-in-the-software-development-life-cycle-sdlc/

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Accelerate Your Application Delivery with QA Automated Testing - Charter Global

2019 will be remembered as an important year for software testing services – with a record 97% of Agile adoption according to Forrester. Upon entering 2020, it’s time to identify several new software testing trends in hopes of achieving new, strategic heights.

As advancements in testing approaches and techniques continue to surge, QA Automation Testing Services teams strive to improve their skill sets. This is crucial in maintaining synchronicity with rapid technological advances that effectively make of break software delivery strategy.

What trends have shown promise in 2019?

Creating a unique, refined, and savory customer experience has taken center stage in 2019 software delivery trends. Growing organizations rely on high-quality software to systematically produce succinct deliverable.

Moving forward, development teams must consider the following trends to maintain a competitive advantage in a fiercely expanding market.

AI Finds its Footing in Business and QA

The rise of automation and Artificial intelligence was predicted in last year’s trends. Nevertheless, it has been included this year as companies will analyze how artificial intelligence applies to their business. According to The World Quality report, 55% of respondents said that this was their main problem with setting up AI projects.

With regards to QA, more companies are expected to adopt machine learning techniques in areas such as predictive analytics (predicting future outcomes of the testing process based on historical data), defect analytics (highlighting at-risk areas of an application) and test suite optimization (identifying redundant test cases).

The use of AI in testing might require newer skills which will eventually lead to organizations creating new roles for AI QA strategists, data scientists, as well as AI test experts in QA and testing teams.

Instant Apps Take the Spotlight

Instant apps are native mobile apps that are smaller in size. Thus, more convenient for the user who is no longer required to download a standalone app.

The demand for better user experiences and shorter load times are constantly increasing.

Google’s introduction of Android App Bundles allows developers to modularize their apps and deliver features on demand; this will make more organizations adopt the Instant Apps approach.

QA Decentralization

The QA and testing department has been fragmented as a result of the transition to agile and DevOps. QA is now embedded into cross-functional teams. So, quality is dependent on the team members’ skills and their responsibility to integrate testing into their product life-cycle.

Continuous Improvement

The trends mentioned above have contributed to the rise in the adoption of Agile & DevOps over the past few years. Testing is an early part of the development process. More companies will adopt more agile/DevOps models to help them release faster and receive quick feedback. Other companies will take it a step further by adopting approaches such as continuous testing and continuous monitoring.

An attitude of “continuous improvement” will enhance the overall performance and quality of products by teams.

Quality Engineering over Quality Assurance  

QA professionals will enhance their technical skills and include some automation-related work organized by quality engineers. The role of Quality Assurance will deviate to implementing the latest technologies to boost the speed of quality checks. This is a trend that will come into play in the coming years.

Big Data Testing

With big data testing, testers have to verify that terabytes of data are successfully processed. Additionally, the aggressive increase in quantity is making it more tasking for companies. More likely, QA will have to deal with validating the quality, accuracy, and consistency of huge datasets.

These trends above demonstrate the crucial transformation both companies and QA Automation Testing Services is undergoing. The expectations of consumers will continue to shoot up. Organizations must adapt and deliver if they must remain in the front line and grow beyond 2019.

If you are interested in learning more about Benefits of QA Automated Testing Services, check out other blogs here.

Get in touch with our team to discuss IT staffing and software development solutions that can supersede your existing solutions on mobile and web applications.