Deployment Strategies In Kubernetes

Quick Overview of Kubernetes

Kubernetes is an orchestration tool that is responsible of deployment and provisioning resources, resource allocation load balancing, discovery of services and high availability as well as other crucial elements in any application. Utilizing this platform, we're able to break down our apps in smaller units (called microservices) when developing them; and later we can put (or orchestrate) the systems in conjunction as we deploy.

The cloud-native approach has led to the development of software based on microservices. In these applications, one of the most difficult issues that companies face is the deployment. A proper plan regarding deployment is crucial. In Kubernetes it is possible to choose different methods to deploy applications; it's essential to select the best method to ensure that your infrastructure is stable during a release or upgrade. In production environments it is necessary to ensure that users don't be impacted by any downtime. When it comes to Kubernetes orchestration, a well-planned strategy is essential to ensure the proper management of various versions of containers. To summarize the article will focus on the various deployment methods in Kubernetes. Kubernetes offers a variety of monitoring options, including the capability to record events and load the CPU instance. There's a growing number of open-source and open-standard tools that can be utilized to extend Kubernetes already-built-in capabilities. Some of the most well-known tools for observing include Promtail Fluentbit, Promtail, and Fluentd, which logs data; Prometheus to measure and OpenTelemetry for trace data , among other. If you're looking to learn more about Kubernetes you should consider taking Kubernetes Course.

Prerequisites

To understand this post, we'll require prior experience with Kubernetes. If you are new in this platform take a look at the Step-by-Step Introduction to the Basic Kubernetes concepts tutorial. In this, you will be able to discover everything you need to know to follow these instructions. We also suggest reading through Kubernetes documentation. Kubernetes documents whenever you require.

In addition, we'll require kubectl which is an Command-Line Interface (CLI) tool that allows you to control the cluster from an terminal. If you don't have this tool, check the instructions on the Installing Kube Control (kubectl).We will also require a basic knowledge about Linux as well as YAML.

What is a deployment in Kubernetes?

A deployment is an object of resource within Kubernetes that specifies the desired state of our program. Deployments are declarative. That means that we do not dictate the method of achieving the desired state. Instead, we declare the desired state and allow the Deployment-controller to automatically reach that end goal in the most efficient way. A deployment lets us explain the entire life cycle of an application for instance, what images are required to run the application and the amount of pods that should be used and the method by how they will be modified.

Benefits Of Using Kubernetes Deployment

Manually updating containers is time-consuming and exhausting. The Kubernetes deployment allows this process to be automated and repeatable. All deployments are managed via the Kubernetes backend and the entire updating process takes place by the server with no interaction from the client.

Furthermore there is furthermore, the Kubernetes deployment manager is constantly checking the state of pods and the nodes. It can replace a failing pod or nodes that are down, to ensure the continuity of critical applications.

Strategies for deploying

Rolling Update Deployment

Rolling deployments are the standard deployment technique in Kubernetes. It replaces the pods, one at a time, from the earlier version of our application by pods from the latest version, without causing any downtime to the cluster. The rolling deployment replaces instances from the previous version of the application with instances of the latest versions of our application.

If we are you are using the RollingUpdate strategy There are two additional options to tweak the update process:

maxSurge Maximum number of pods that are generated above the desired number of pods in an update. This could be either an absolute number, or a percentage of the replica count. It is usually 25%.

maxUnavailable Maximum Unavailable: The amount of pods that are inaccessible during the process of updating. It can either be an exact number, or as a proportion of replicas count. The normal value is 25%%.

Lue-Green Deployment

A blue-green deployment technique (sometimes sometimes referred to as black/red) The blue is the version of the application currently in use while the green is the latest version. In this scenario, only one version can be live at any given time. Traffic is directed through the blue installation as the deployment in green is being created and test. When we've finished testing, we move traffic to the latest version.

When the deployment has succeeded it is possible to keep the blue deployment for possibility of rollback, or remove it. Additionally, it is possible to install a newer version of the application in these occasions. In this case this present (blue) environment is used as a staging zone to test the new version.

This method can reduce the downtime that we experienced with the strategy to recreate deployment. Additionally, deploying blue and green lowers the risk: in the event that something unexpected occurs with the new version of Green it is possible to immediately return to the previous version, switching into Blue. The rollback and rollout are instantaneous. It is also possible to prevent issues with versioning; the entire state of the application is updated in one single deployment.

Canary Deployment

The canary update approach is a part-time update procedure which allows us to try out our new program version with a real client base, without the need to commit to the full deployment. Similar to blue and green deployments, but they're more controlled and employ a more gradual delivery method that is the form of a gradual approach. There are several methods that fall under that umbrella called canary such as dark launches and A/B testing.

In canary deployments this is where the latest version is slowly being deployed to the Kubernetes cluster, while receiving only a small portion of real-time traffic (i.e. only a small portion of active users have migrated to the new version of the application while the majority of users are using the older version).In this way there are two nearly identical servers. One is available to all current active users and another that has the latest features that are distributed to a smaller number of users before being is compared. If no errors are detected and confidence is increased then the updated version will gradually be released to the remainder of the infrastructure. At the end of the day all live traffic flows to canaries, which makes it the current versions in production.

The image below is the most simple and easy method of performing an canary deployment. The new version is then deployed to a limited number of servers.

We must be aware of a myriad of things when planning a deployment of a canary:

Stages: how many people will we add to the canary in the beginning and in what number of stages.

Duration What is the length of time we be running the canary? Canary releases differ since we need to wait for the right clients updated so that we are able to evaluate the outcomes. It could take several hours or perhaps weeks.

Metrics What are the most important metrics to track to track progress, such as the performance of the application and reports on errors? The right parameters are crucial to an effective deployment of canaries. For instance, a simple method to evaluate the success of the deployment is using HTTP code status. It is possible to create a simple Ping service that will return 200 when the deployment has been successful. It will give a server-end error (5xx) in the event of an issue during the deployment.

Evaluation What criteria will be used to decide if the canary is successful?

Canaries are used in situations where we need to test new features usually on an application's front end. Canary deployment is advised when we're not 100% sure about the latest version, and we think we could have a small chance of failing. This is usually done for significant update, such as adding an entirely new feature or feature.

Summary K8s Strategies for Deployment

In short it is possible to find different methods of deploying an application in staging and development environments, a recreated of a ramped or re-enabled installation is generally the best option. If you are in production ramped or blue/green release is typically a good choice however, thorough test of the brand new system is required. If we're not sure about the stability of the platform, and what might be the consequences of releasing a brand new versions of the software then a temporary release might be the method to take. This way we allow the user to evaluate the app and its integration with the platform. The information in this post, we've only begun to explore Kubernetes' capabilities. Kubernetes deployments. By combining deployments and all the other Kubernetes capabilities, users are able to develop more robust containerized apps that can meet any requirement.