The primary objective of a Microservices hosting platform is to simplify the tasks around developing, deploying, and maintaining Microservices while optimizing the infrastructure resource consumption. Together, these tasks can be called Microservice lifecycle management tasks.
The journey starts with the hosting platform supporting development of the Microservices by providing means for integrating with platform features and application framework. This is critical to enable the hosting platform to manage the lifecycle of a service hosted on it. Integration is usually achieved by the hosting platform exposing APIs (application programming interfaces) which can be consumed by the development team. These APIs are generally compatible with popular programming languages.
Co-locating code and state is desirable for improving the efficiency of a Microservice. While this is true, storing state locally introduces challenges around maintaining the integrity of data across multiple instances of a service. Hosting platforms such as Service Fabric come with rich features for maintaining consistency of state across multiple instances of a Microservice there by abstracting the complexity of synchronizing state from the developer.
The hosting platform is also responsible for abstracting the complexity around physical deployment of Microservices from the development team. One way this is achieved is by containerizing the deployment. Containers are operating system-level virtualized environments. This means that the kernel of the operating system is shared across multiple isolated virtual environments. Container-based deployment makes possible an order-of-magnitude increase in density of the Microservice deployed. This is aligned with the recommended cloud design pattern called compute resource consolidation. A good example to discuss in this context, as mentioned by Mark Fussell from Microsoft, is the deployment model for Azure SQL Databases hosted on Azure Service Fabric. A SQL Azure Database cluster comprises hundreds of machines running tens of thousands of containers hosting a total of hundreds of thousands of databases.
Each of these containers hosts code and state associated with multiple Microservices. This is an inspiring example of how a good hosting platform can handle hyperscale deployment of Microservices.
A good hosting platform will also support deployment of services across heterogeneous hardware configurations and operating systems. This is significant for meeting demands of services which have specific requirements around high-performance hardware. An example would be a service which performs GPU (graphics processing unit) intensive tasks.
Once the Microservices are deployed, management overhead should be delegated to the hosting platform. This includes reliability management, health monitoring, managing updates, and so on. The hosting platform is responsible for the placement of a Microservice on a cluster of virtual machines. The placement is driven by a highly optimized algorithm which considers multiple constraints at runtime to efficiently pick the right host virtual machine for a Microservice.
The following diagram illustrates a sample placement strategy of Microservices in a cluster:
As the number of Microservices grows, so does the demand for automating monitoring, and diagnostics systems which takes care of the health of these services. The hosting platform is responsible for capturing the monitoring information from every Microservice and then aggregating it and storing it in a centralized health store. The health information is then exposed to the consumers and also ingested by the hosting platform itself, to take corrective measures. Modern hosting platforms support features such as preventive healing, which uses machine learning to predict future failures of a virtual machine and take preventive actions to avoid service outages. This information is also used by the failover manager subsystem of the hosting platform to identify failure of a virtual machine and to automatically reconfigure the service replicas to maintain availability. The failover manager also ensures that when nodes are added or removed from the cluster, the load is automatically redistributed across the available nodes. This is a critical feature of a hosting platform considering the nature of the cloud resources to fail, as they are running on commodity hardware.
Considering the fact that migrating to a Microservices architecture can be a significant change in terms of the programming paradigm, deployment model, and operational strategy, a question which usually rises is why adopt a Microservice architecture?