5 Strategies to Deploy MicroservicesMohnish Jain
Strategies to Deploy Microservices
As an IT solutions provider, while discussing the diverse IT needs of various companies (from SMEs to multinationals), one of the most common concerns we come across is microservices deployment.
The decision-makers of companies are more concerned about the deployment of microservices. That is due to the various benefits such as increased application speed, agility, scalability, etc., that building apps with microservices results in.
But microservices deployment isn’t as straightforward. Deploying microservices successfully and effectively is a strategic task as much as it is a tactical one. Accordingly, here’s an overview of a few strategies through which you can deploy microservices successfully within the context of your company’s IT environment.
5 Strategies to Deploy Microservices
The strategies we are about to discuss leverage routing techniques to introduce new features, services, enable iterative enhancements, test functionalities, etc. These approaches or strategies can help reduce the risk involved during the development and deployment of applications based on microservices.
Practically, choosing the best one can prove a bit challenging for you, especially if you are a layperson. But as the decision-maker of the company, you must consult a microservices expert and select the approach, based on a rational consideration of your business needs, feasibility, results, and the value you expect.
A/B testing focuses on assessing user acceptance of a particular feature. It can help developers gather user feedback and determine the extent to which users have accepted a specific feature. Furthermore, developers can know how users have received a particular service and their feedback.
A/B testing involves software routing to activate and test a particular feature across various target user segments. It also comprises introducing the features to a limited number of users or a specific percentage of them. The A and B routing segments may transmit traffic to the software’s various builds. Or, the service instance may be using the same software, – however, with varying configuration attributes.
The method is pretty similar to canary deployments, which is precisely the next microservices deployment approach of strategy that we will discuss.
Canary deployment involves catching a specific percentage of incoming requests to try out new builds or features. The testers and developers can review the results and then graduate to a complete deployment to all servers or nodes if everything is in order. If not, they can redirect the traffic from canary deployments and review and debug the offending code.
Now, how do you implement canary deployment? It is done through integrations with edge routing components that process incoming user traffic. One example is where the deployment taps the ingress controller configuration to allocate a particular percentage of traffic requests to stable canary deployments. It enables new services an opportunity to prove their efficiency before a full rollout receipt. If they are not in order, the system sends them back to go through another canary deployment when they are ready to undergo it.
Multiple Service Instances per Host
Traditionally used for deploying an application in the Multiple Service Instances per Host pattern, in this type of approach, developers provide single or multiple physical or virtual hosts and run multiple instances on each. The approach proves beneficial, as it enables efficient storage use, which is, in turn, on account of the different service instances using the same server operating system.
The deployment process is relatively quick, as the deployers will only have to copy the service to a host and run it. Additionally, the absence of overheads results in hassle-free initiation of service in this pattern.
Serverless deployment involves packaging services as a zip file and uploading them to the Lambda function. The function runs microservices instances to deal with instances automatically. It is more cost-effective as you pay based on the number of requests. However, you cannot adopt server-less deployment for long-running services. Hence, you will undoubtedly require an expert to know if the strategy suits your goals.
Blue-green is a straightforward minimal downtime strategy. It refers to placing an identical service of equivalent capacity (while the target service is running) and switching the traffic at the load balancer to the new service.
In addition to minimal downtime, there exist a few other benefits. For instance, you do not have to design your service to handle multiple versions running beside each other. Besides, it enables immediate response through shifting traffic back to the previous deployment. Nevertheless, a failure affects all users until the traffic is shifted back. Additionally, having to run two identical sets of services running is a cost to be borne by you.
Choose the Right Microservices Deployment Strategy with Datafortune
Experts at Datafortune review your needs and IT environment to help you select the right microservices deployment strategy in your context. We possess extensive consulting and execution expertise to implement the best-suited microservices deployment strategy. To know more or talk to our experts, connect with us through our Contact Us section or write to us at Info@datafortune.com.