Tightly coupled microservices are a cardinal sin. In particular when those connected services are owned by different development teams, the coordination costs in the organization tend to soar as new features and fixes require work by multiple teams.
Use the concept of Change Coupling to uncover logical service dependencies in the context of the development teams.
Visualize microservices dependencies in a team context
Tightly coupled microservices are a cardinal sin. In particular when those connected services are owned by different development teams, the coordination costs in the organization tend to soar as new features and fixes require work by multiple teams.
Use the concept of Change Coupling to uncover logical service dependencies in the context of the development teams.
Visualize microservices dependencies in a team context
Conway’s Law tell us that an organization’s communication structure should be reflected in the software architecture. In a microservice context, that means loosely coupled services with a clear team ownership.
Conway’s Law is an important principle that drives both organizational and technical decisions. At the same time, the organizational and social side of code is largely left to subjective judgments. What if we could guide those decisions with objective data instead?
Detect coordination bottlenecks in a microservice system
Conway’s Law tell us that an organization’s communication structure should be reflected in the software architecture. In a microservice context, that means loosely coupled services with a clear team ownership.
Conway’s Law is an important principle that drives both organizational and technical decisions. At the same time, the organizational and social side of code is largely left to subjective judgments. What if we could guide those decisions with objective data instead?
It’s challenging to know where to start. Fortunately, a hotspot analysis can help. Hotspots identify the most volatile parts of your monolith; the parts that are worked on the most by the development teams.
By guiding the migration from hotspots, you pull risk forward and improve the parts of the codebase that bring the largest and fastest benefits.
It’s challenging to know where to start. Fortunately, a hotspot analysis can help. Hotspots identify the most volatile parts of your monolith; the parts that are worked on the most by the development teams.
By guiding the migration from hotspots, you pull risk forward and improve the parts of the codebase that bring the largest and fastest benefits.
Code quality issues cost time, money, and missed deadlines. Microservices are no different. CodeScene’s code health measure points gives you a straightforward overview that lets your team drill down to the code with actionable recommendations. It also comes with an automated pull request code review that ensures your code will remain maintainable.
It’s a game changer – understanding the code quality of a large-scale codebase has never been this easy!
Code quality issues cost time, money, and missed deadlines. Microservices are no different. CodeScene’s code health measure points gives you a straightforward overview that lets your team drill down to the code with actionable recommendations. It also comes with an automated pull request code review that ensures your code will remain maintainable.
It’s a game changer – understanding the code quality of a large-scale codebase has never been this easy!
Contact us if you have any questions about CodeScene. We also provide custom quotes for larger accounts.
