Fast, Efficient Development of Kubernetes Microservices
Adopting Kubernetes was supposed to enable your team to ship features faster, so why is it slowing you down? To develop quickly you and your teammates need to be able to run your application, no matter its size, in environments that give you fast feedback and the freedom to use your favorite tools.
Infinite-Scale Development Environments
Maintain productivity even as your application grows to hundreds or thousands of services
Eliminate the tedious task of deploying and maintaining your development environment and its dependencies
Interact with dependencies free of complex configuration
Instant Feedback Loops
- Make code changes to your service and see the results instantly, without waiting for a container build, push to registry, and deploy
- Share your development environment with teammates and collaborate on fixes without wasting time reproducing bugs
- Query cluster resources and experiment rapidly with additional services in real time
Extend Your Existing Development Toolkit to Kubernetes
- Maximize your productivity with your favorite tools: work with any IDE, debugger, or other tools that run locally
- Keep your existing local development, build, and debugging workflows
- No need to maintain remote environment configuration
Is Developing Locally Melting Your Laptop?
When organizations first begin adopting Kubernetes, they typically start with a fairly simple architecture. When Kubernetes services are few, loosely coupled, and don’t have many dependencies, it is easy for developers to run the entire application locally on their laptop.
As the Kubernetes application becomes more sophisticated and the architecture evolves --services become bigger, dependencies become more numerous and complicated-- running the entire application on a local machine gets slower and slower as your laptop begins to run out of memory..
Eventually, the addition of a new dependency could mean that developers can’t run the application locally at all.learn more
The Warning Signs
Developers can’t run their application locally, so your cloud bill rises as each engineer spins up their own cluster to deploy remotely.
Feedback is slow, so it takes longer to get new features in front of your customers
Developers can’t use their favorite tools to run realistic tests, so more breaking changes are being pushed to production