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Microservices Deployment at the Edge and its Best Practices

Gursimran Singh | 12 August 2024

Microservices Deployment at the Edge

What is Monolith?

A monolith application is a deployment setup where a single deployment unit handles various business activities. Such applications are good to start with and develop features with, but they need to be more specific and easier to manage as it scales and handle complex real-time business requirements.

A monolithic can be helpful with some of the following features:

  • Easy to Deploy: Since the application and all its components are deployed as a single unit, it becomes easy to deploy the application and eradicate the need to manage complex architecture and component coordination.
  • No Overhead of Latency: Since the backend and the frontend are working end to end in a single server, the communication between both components becomes easy, thus leveraging low latency.
  • Lower Costs: Single unit of deployment can effectively reduce architecture complexity and thus reduce the cost for resources to be used.
  • Easy Testing: Integration testing can be skipped as all the components are in the same unit/server.

However, the monolith approach for application deployment is not feasible when it comes to business-grade deployments and planning. This strategy can be a blocker for application scalability and reliability and can be unuseful for complex applications.

An approach for developing small services each running in its process. It enables the continuous delivery/deployment of large, complex applications. Taken From Article, Microservices Architecture and Design Patterns

What is Microservices?

Microservices is a grade-up deployment strategy that focuses on the independent working of the application components. This makes the applications more scalable, reliable, and independently deployable applications.  

Some of its features are as follows:

  • Scalability: Microservices can be scaled independently based on demand, allowing the system to accommodate increasing or changing loads.
  • Resilience: As each microservice is isolated, the failure of one microservice will not affect the overall system, making the application more resilient.
  • Flexibility: Microservices can be developed using different programming languages, technologies, and tools, providing greater flexibility to the development team.
  • Agile Development: With small and independent components, microservices enable more frequent and faster releases, reducing the time to market for new features and functionality.
  • Easier to Manage: As each microservice has its own data store, it can be easier to manage and update each component independently, reducing the risk of affecting other parts of the system.

Microservices to Edge

With the increasing demand for more available and reliable applications, it became necessary to develop a more flexible, feasible, and efficient deployment model. This was when edge computing came up as a possible solution. 
The Edge deployment strategy focuses on deploying application components in computing resources and resources that are close to the end users or devices. This strategy would improve the performance of applications, lower latency, and increase reliability. Some of the strategies for this emerging deployment strategy include:

  • Micro Data Centers: Network-edge data centers that process and store data. 
    Edge computing devices: Edge computing devices include gateways, routers, and fog nodes.
  • Hybrid Cloud: A cloud platform combining public and private clouds to enable edge deployment of applications and services.
  • Multi-access Edge Computing (MEC): A way of deploying cloud computing services and resources at the network edge.
  • Containerization and Orchestration: Deploy applications and services at the Edge using containers and orchestration tools.

Edge Deployment Strategy Use Cases

Since edge computing and edge networking are much more efficient in handling complex applications and data, it can be feasible in the following use cases:

  • Internet of Things (IoT) Devices: IoT is marking its presence in many modern applications. Edge can help process large amounts of data generated by IoT devices at the Edge.
  • Augmented Reality/Virtual Reality (AR/VR) Applications: To provide real-time processing and reduce latency.
  • Autonomous Vehicles: To process sensory data and make real-time decisions.
  • Industrial Automation: To improve operational efficiency and reduce downtime by processing data locally.
  • Intelligent Cities: To analyze data generated by connected devices and make real-time decisions to improve city services.
  • Remote Healthcare: To provide real-time medical analysis and treatment.
  • Robotics: To perform real-time control and decision-making for robots.
  • Retail: To provide personalized experiences and improve operational efficiency.

How to design Applications for Edge Microservices Deployment?

Writing Edge microservices deployment applications: Keys to getting started with

  1. Planning: Determine whether your application has specific requirements and the problem you want edge computing to solve.
  2. Decide on Architecture: Considering scalability, reliability, and security, choose the appropriate architecture for your application.
  3. Technology Stack: Choose cloud-native platforms or edge-specific frameworks to build your edge microservices.
  4. Design Microservices: Separate the application into smaller, independent components.
  5. Test Locally: Test Each Microservice locally before deploying it to the Edge, ensuring it works as intended.
  6. Deploy to the Edge: Ensure that the microservices are configured correctly and have access to the necessary resources.
  7. Monitor and Optimize: Make sure the microservices are running optimally by monitoring their performance.
  8. Maintain and Update: Ensure that microservices remain up-to-date to meet the application's needs.
The main difference between DevOps and DevSecOps is information security. Taken From Article, DevSecOps with Microservices Solution

Best Practices for writing Edge Microservices-based Applications

Due to their high centralization, it takes a long time for data produced at the Edge to be processed on traditional cloud computing networks. Edge can be a breakthrough for such situations, where it uses a hierarchical architecture where devices report into an edge node close to the data source, which in turn transmits a much smaller subset of data to a cloud node. This:

  1. It greatly reduces response latency
  2. Lowers network bandwidth needs
  3. Helps preserve data privacy

Use Reverse Proxy/API gateway

Access control is significant for edge microservices. Reverse proxies/API gateways are a good choice for most real-world applications. Your application's entry point is set up before any edge microservice.

Use a Registry Service

Regarding microservices, it is essential to have control over the component's configurations. Primarily, the units/services in a microservices architecture run in a container environment which could have dynamic values input. A registry service can help keep track of all such changes.

Introduce Unique Request IDs

Having unique request IDs each time a request is made to any microservice can help compute various actions' latency and throughput.

Plan for Intermittent Connectivity

The IoT solutions can face connectivity issues when requesting a cloud endpoint—a solution to store data until the subsequent transmission can be helpful in such conditions.

Limit Vulnerability

Edge service is more vulnerable to access than the microservices hosted in a cloud environment. It becomes more critical to ensure security while setting up edge services.

Encrypt Data at Rest and in Transit

Data encrypted at rest is a must in edge services, as the storage devices might get stolen. 

cloud-managed-services-card-icon
An architectural style that structures applications as the collection of loosely coupled services, which implement business capabilities. Managed Microservices and Integration Solutions

Conclusion

 In a microservices deployment strategy, the large and complex application is divided into small, operable, and independent components that communicate via well-defined APIs. The smaller unit can be developed, managed, and deployed separately without affecting the whole application and its working.