Dockerizing Healthcare Project: React & Node
Overview
The Mayo medical Clinic wanted to create a web app that allowed healthcare to run multiple applications on the same infrastructure, in an isolated manner, avoiding the issues of dependency and compatibility. They decided to use- GCP Google Cloud Run
- GCP Google Container Registry
- GKE Google Kubernetes Engine
Challenges
Interoperability: Healthcare systems often involve a wide range of different technologies, applications and protocols, making it difficult to share data and ensure consistency across different systems.
Data Security and Compliance: With the increasing amount of personal and sensitive data in healthcare, ensuring the security and compliance of that data becomes more crucial.
Scalability and Flexibility: Healthcare systems are often subject to rapid changes and fluctuations in demand.
Workflow Automation: Healthcare organizations are generating and managing large volumes of data from various sources, including electronic health records (EHRs), medical devices, and telehealth.
Solution
Portability: The Docker image can be run on any platform that supports Docker, making it easy to move your application between development, staging, and production environments.
Isolation: Each container runs in its own isolated environment, which helps to reduce conflicts between different applications running on the same host.
Scalability: Because your application is running in a container, it can be easily scaled up or down to meet changing demand.
Consistency: By using a Docker image to deploy your application, you can ensure that the environment is always the same, regardless of where it is deployed, which can help to reduce issues caused by differences in configuration.
Docker containers are a lightweight and portable way of packaging and deploying software applications. They allow developers to build an application, its dependencies, and its runtime environment into a single package that can be run anywhere.
Containers are an efficient and cost-effective way of deploying and scaling applications, as they allow for greater resource utilization and faster provisioning of new instances. They also provide a consistent environment for development, testing, and production, which reduces the risk of compatibility issues and improves the overall development workflow.
One of the most notable benefits of using containers is the ability to run multiple applications on the same infrastructure, in an isolated manner, avoiding the issues of dependency and compatibility. This is possible because containers bundle all the dependencies and runtime environments needed to run the application inside the container, making the application self-contained and portable.
Containers also provide an efficient way to deploy and scale applications. In a containerized environment, new instances of an application can be spun up quickly, and resources can be utilized more effectively than with virtual machines. In addition, container orchestration platforms such as Kubernetes can automate the scaling and deployment of containers, making it easy to manage a large number of instances.
Another important benefit of using containers is the ability to create repeatable, consistent environments for development, testing and production. By containerizing an application, developers can ensure that the same environment is used across all stages of development, which reduces the risk of compatibility issues and makes it easier to find and reproduce bugs.
CODE SAMPLE
Here's an example of how you might use Docker to create an image for a ReactJS project and deploy it to a GCP environment:
Create a Dockerfile in the root directory of your ReactJS project. This file contains instructions for building the Docker image. Here's an example of a Dockerfile that could be used for a ReactJS project:
Build the image using the command docker build -t my-react-app:latest .
Once built, you can use the command docker run -p 3000:3000 my-react-app to run the container locally.
To deploy the image to a GCP environment, you can use Google Container Registry to store the image, and then use Google Kubernetes Engine to deploy it to a cluster.
Also used cloud run for some images which were short running codes
Google Cloud Run is a fully managed compute platform that enables you to run stateless containers in the cloud, it allows you to deploy and run containerized applications quickly, without the need to manage infrastructure. Here's an example of how you can deploy a Docker image to Cloud Run:
Build your Docker image locally and give it a tag, for example: docker build -t gcr.io/[YOUR_PROJECT_ID]/my-react-app:latest .
Push the image to the Google Container Registry:
Go to the Cloud Run Dashboard in the GCP console, click on the "Create Service" button and select the container image you want to deploy.
Configure the service settings, such as the number of instances, memory, and CPU. You can also configure the service's environment variables, networking, and security settings.
Once the service is deployed, you can access it via a URL provided by Cloud Run, and you can monitor and update the service as needed.
Cloud Run also supports traffic splitting and automatic scaling, which allows your application to handle a variable amount of traffic, reducing the risk of downtime and improving the overall user experience.
Industry - : Healthcare
Technology Leveraged
- ReactJS
- NodeJS
- Docker
- GCP Google Cloud Run
- GCP Google Container Registry
- GKE Google Kubernetes Engine