Blog

Five Keys to Rebuilding Apps with Microservices

The cloud offers IT organizations an opportunity to break down applications into reusable pieces of functionality called microservices that can be combined and recombined in almost endless variations. This rapid build-and-deploy approach, however, does not “play well” with monolithic existing applications that are wrapped into a single executable file. Making even the smallest tweak to those kinds of applications requires a whole new version of the application be built, tested and deployed – a counter to the improved productivity and efficiency that are hallmarks of microservices-based applications. To move existing applications to the cloud mandates a full rewrite with functionality being broken down into a cloud-native form, such as microservices, event-driven architectures and serverless technologies (such as AWS’s Lambda).

During this rebuild effort, IT organizations need to follow four key principles to leverage the cloud’s benefits:

  1. Use domain-driven design
  2. Create guidelines for code libraries
  3. Resist the urge to share databases between microservices
  4. Measure performance when scaling

Additionally, IT organizations just starting their cloud migration efforts can learn much from those who have gone before them. A quick Google search reveals comprehensive migration white papers and use cases that can jump-start the effort, such as a step-by-step guide from AWS.

Yellow light’ microservices’ first steps

When IT organizations elect to adopt this new microservices architecture, it is wise to proceed with caution. This advice is particularly relevant when selecting the first microservice container to build from scratch. Even experienced IT professionals will find it challenging to learn how to develop and deploy in the microservices environment as they build new containers. Our advice is to decide whether to build either the microservices environment OR the container as a first step – trying to do both will make the task more challenging than it needs to be. It is also recommended that IT leaders work with their teams to select a low-value application as the place to start the microservices-based effort. Customer-facing or business-critical applications contain too much visibility and too much risk to be a first effort.

IT leaders should be confident that their DevOps teams have mastered the basics before assigning them to a complex project that can be overwhelming in its scope and depth. Remember that proficiency with the automated tools that are part of microservices is a table-stakes requirement. Finally, constantly measure the applications’ performances and keep a vigilant eye out if microservices seem to be “thickening” over time.

Taking a deliberate approach in moving to microservices helps ensure that IT professionals can grow into their digital roles with confidence. In addition, a phased approach can help to lessen unrealistic expectations coming from the company’s executive team who may be pressuring this critically important, yet brand new, digital effort to move at a faster-than-normal pace.

Related Blogs
See All Blogs
Blog
Apr 29, 2025

The Hidden Powerhouse for Industry Disruption

Mid-market companies are quietly outpacing larger competitors, not with massive budgets, but with speed, focus, and real-world results. In our latest article by Senior Director of Solutions Consulting, Josh Scott, he breaks down how mid-market companies are using AI and cloud tools to solve real problems, move faster than the competition, and rewrite the rules of their industries. Forget tech for tech’s sake — it’s about execution that actually delivers.

Read More
Abstract tech image
Blog
Apr 15, 2025

Analysis Paralysis in AI Adoption

Learn why endless discussions and the relentless pursuit of flawless data are actually costing you valuable time, insights, and competitive advantage – just like it did for giants like Kodak and Blockbuster.

Read More
Product team at a meeting
Blog
Apr 4, 2025

Don’t Take Product Out of the Equation: How to Nail Your AI Implementation

AI isn't just about the technology, it's about solving real problems and delivering real value. One way to do that is to keep product at the forefront during your AI implementation. Learn more about why having a product-first mindset is so important in this article by Principal Product Strategist Heather Harris.

Read More
Female financial analyst at a computer
Blog
Apr 3, 2025

Navigating AI in Banking and Financial Services: A Risk-Based Rebellion for Leaders

Every shiny AI use case in regulated industries has a shadow: governance, compliance, model risk, ethics, bias, explainability, cyberattack vectors and more. It's not that organizations and leaders don’t want AI, it’s that they’re paralyzed by the political, regulatory, and operational realities of deploying it. Sparq's Chief Technology Officer Derek Perry and VP, BFSI Industry Leader Rob Murray argue we need to change that. Check out this article to learn how to actually ship production AI use cases in regulated environments.

Read More
See All Blogs
noun-arrow-2025160 copy 2
noun-arrow-2025160 copy 2
See All Blogs