MuleSoft Deployment Strategies
In Mulesoft, the deployment model is pivotal as it decides how to manage and run mule applications in different environments. For every organization, a key goal is providing great customer service. We can do this by cutting costs and giving customers personalized views.
The deployment model is pivotal for any customer and key when onboarding an organization for its business needs. The architect at Mulesoft makes strategic decisions based on customer needs, setups, and assets. These decisions enable the selection of a model. The model helps customers optimize scalability, process, and cost.
To understand the deployment model, we must grasp the control and runtime planes.
Control Plane
The control plane is part of the Mulesoft platform. We use it to design, deploy, share, and manage APIs and applications.
Control Plane can be of two types:
- Mulesoft hosted: These are hosted in the cloud offered by Mulesoft and ready to use.
- Customer hosted: These are hosted by customers using private cloud like AWS, Azure or VM.
Runtime Plane
Runtime plane is part of Mulesoft. It’s where the API and Mule apps are deployed and made available to users.
The Runtime plane can be of two types:
- Mulesoft Hosted:
-Public Cloud: Runtime is shared by the public (other clients) by shared load balancer
-Virtual Public Cloud(VPC): Runtime is dedicated to a client by using a dedicated load balancer. - Customer Hosted:
-On-Premise: Runtime can be hosted on Virtual Machines/blades and Legacy systems.
-RTF: Runtime fabric can be hosted on the cloud.
Deployment Models
CloudHub Model
In this deployment model, Mulesoft hosts both the control and runtime planes. This deployment model resides in AWS. CloudHub is a fully managed and highly available integration service. To manage it there is no requirement to monitor any server, it is hosted and managed by MuleSoft Cloud. CloudHub has built-in integration with Anypoint Studio for easy and fast API deployment.
Strengths:
- High Availability and Disaster recovery capabilities.Efficient Application monitoring and Automatic restart features.
- Impaired working monitoring functionality.
- Seamless scalability.
- This model offers a shared or dedicated load balancer. It meets the unique needs of each customer.
Limitations:
- Domain project not supported.
- The high price point to deploy new workers.
Hybrid Model
Mulesoft hosts the Control Plane. The customer hosts the runtime plane. They do so either On-Premise or in a Private Cloud. The hybrid model deployment needs to host infrastructure for Mule servers. The application is deployed to the Mule servers through the runtime manager cloud console. Using this option, we can add servers to server groups or clusters for high availability. We do it from the runtime manager.
Strengths:
- Allows to leverage the benefits of both on-premise and cloud environments.
- Maintain sensitive data on premises.
- Secure connection between control and runtime plane.
Limitations:
- There could be data latency issues based on the location of the on-premise data centre.
- Customer must have their firewall and implement their non-functional requirement.
Runtime Fabric
This applies when Mulesoft hosts the control plane. The customer hosts the runtime plane. The deployments of the fabric run at runtime are container-based. They run on a Kubernetes cluster. The Docker containers are optimized to work efficiently with Mule runtimes. The fabric runs on infrastructure managed by customers. They use AWS, Azure, virtual machines (VM), and bare metal servers. It keeps runtime in full control of the user. It also provides horizontal scaling and zero redeployment.
Strengths:
- Scalability and performance capabilities.
- It enables organizations to maintain control over security measures.
Limitations:
- The customer is responsible for managing and maintaining their infrastructure.
- Initial setup complexities.
Private Cloud Edition
Customer-managed infrastructure includes both the Control plane and runtime plane.
Run and manage mule applications on local servers using required security policies. PCE used Docker and Kubernetes to provide built-in high availability and scalability.
Strengths:
- PCE provides high security, catering to the individual customer needs.
- PCE enables customers to keep sensitive data within the premises.
- PCE enables customisations of infrastructure as per customer needs.
Limitations:
- PCE has both control and runtime planes. It needs lots of infrastructure, which raises its costs.
- PCE needs maintenance, updates, and patches. These can take time, resources, and expertise.
Conclusion
In conclusion, the user can choose the deployment model from the above. They should select it based on their organization’s assets and customer needs.
