Generative AI Solutions
November 22, 2023
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Microservices architecture has become popular for its superior software scalability. The architecture pattern has been adopted by many organizations. Yet, when it comes to deploying it to the microservices-based application, most firms struggle to develop a solid strategy.
A microservices application comprises tens or hundreds of services that have been written in multiple frameworks and languages. For successful deployment, one needs to have a clear understanding of those frameworks and languages. Since each service has its own specifications for resource demands, scaling, deployment, and monitoring, obtaining this understanding can be a massive challenge.
In this guide, we’ve explained some effective microservices deployment strategies for organizations.
1. Traffic Shadowing
In this approach, routing technology duplicates the incoming production traffic and copies it to a separate test deployment that hasn’t become public yet. Based on genuine traffic, it helps understand the results of deploying a new version. This also means that the actual product isn’t affected by these tests. Developers have the option to replicate a certain proportion of requests to a test service, where they can conduct performance benchmarking and integration testing.
One might question the need for this testing as developers already use various testing methods to ensure that the requirements for the new application code are met. No doubt the code must clear the unit and functional tests, but the nature of microservices architecture makes end-to-end integration testing extremely important.
Microservices architectures involve the risk of long-term interface drift and a high volume of interdependencies. Synthetic tests are certainly useful but ultimately fail to precisely represent all interactions between services in production environments.
2. A/B Testing
A/B testing utilizes software routing to activate and test features for different traffic segments. This could mean that the A and B routing segments send traffic to different software builds for testing or different configuration attributes of a single software build are tested. Hence, the A/B testing strategy focuses on determining user acceptance for new application features. For instance, to find out whether a set of new features are easy to discover, are popular among users, or the UI is functioning properly, A/B testing should prove extremely valuable for developers.
3. Server-Less Deployment
This microservices deployment strategy supports Node.js, Java, and Python services. The popular technology, AWS Lambda, is used by developers around the globe. The strategy involves packing the service as a ZIP file and uploading it to the lambda function.
When handling a request, you may also provide metadata that carries the name of the function to be invoked. To handle requests, the lambda function should automatically run enough microservices instances, while you’re billed for each request based on the memory consumed and the time taken by the process.
The most sought-after benefit of this deployment strategy is that you’re only charged for the work performed by your server. On top of that, you need not worry about the IT infrastructure, such as containers, VMs, etc., allowing you to focus on application development.
However, the biggest drawback of this method is that the requests shouldn’t take more than 300 seconds to complete. This means that the strategy can’t be used for long-running services.
Another limitation of serve-less deployment is that the services need to launch quickly and be in one of the supported languages. Otherwise, it will time out and terminate.
4. Multiple Service Instances Per Host
This is the most traditional technique to deploy an application, where developers provision one or more virtual or physical hosts and run multiple service instances on each one. The variants of this pattern include one for every service instance to be a process or multiple service instances running in the same process.
This strategy allows for relatively efficient resource usage because the same server and operating system is used by multiple service instances. Since you’re copying the service to a host and running it, the approach enables fast deployment of a service instance.
Moreover, no overheads are involved, so starting service on this pattern should be quick. If the service is among the many instances running in the same process group or container process, you can restart it.
The drawback of this strategy is that unless each instance is a separate process, you lack control over service instances. It’s simply not possible to limit the resources each instance can utilize. The memory consumption of the host can thus be pretty high.
In addition, the approach requires the operations team to be aware of every single detail of the services, so the chances of errors during deployment are quite high.
To eliminate the complexities, efficient information sharing between the operations and the development teams is a must when using this approach.
5. Service Instance Per Host
Service Instance Per Host is a microservices deployment strategy in which each service instance can separately run on its respective host. The strategies can be divided into two categories:
Service Instance Per Virtual Machine
This approach enables you to package every service in the form of a virtual machine image. The instances act as virtual machines that run using a VM image. Not only does this method allow for limited memory consumption but it also makes it is impossible to steal resources from multiple resources while running in isolation. Besides, the strategy allows systems to utilize sophisticated cloud infrastructure like AWS and benefit from auto-scaling and load balancing.
Service Instance Per Container
On the other hand, each service instance in the Service Instance Per Container model operates within its corresponding container, which is a mechanism or a virtualization device at the operating system level. Solaris Zones and Docker are among conventional container technologies.
The services are packaged in what’s referred to as a container image, a file image containing the libraries and applications required to execute the service. After being packaged, one or more containers are launched, which can then be managed on a virtual or physical host. Cluster managers such as Marathon or Kubernetes can be used for container management.
Final Word
Now that you’re familiar with various microservices deployment strategies, it’s time to find the right service provider and get started. For reliable and efficient cloud microservices, contact Enterprise Cloud Services today.
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