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  2. Testing, Deployment, and Maintenance
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  4. Software Deployment Best Practices in 2023

Software Deployment Best Practices in 2023

Explore the best software development practices that are the proven catalysts for innovation and growth.

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Hiren Dhaduk user avatar
Hiren Dhaduk
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Apr. 28, 23 · Opinion
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Deployment is the day when the software is finally released to the world. 

Yet, as Stackify CEO Matt Watson said, organizations lack confidence in deployment. One of the greatest strengths of agile is the ability to deploy rapidly. However, moving too fast and without following the right processes, one can witness problems like downtime, errors, and poor user experience.  

In addition, software deployment includes various activities like installing, configuring, testing, and monitoring the performance of newly deployed environments. For instance, there are a few practices for deploying software like A/B testing, Shadow Deployment, Grey Box Testing, Black Box Testing, White Box Testing, etc.

Here are the best practices that can assist you with an effective software deployment:

Separate Clusters for Non-Production and Production

Having an enormous cluster often creates problems for security and resource consumption. Therefore it is crucial to have two clusters at the minimum – one for production and another for non-production.

Here is how you can separate clusters for production and non-production:

  • When using Kubernetes, use the K8 cluster for each environment.
  • Keep all the clusters in different namespaces.
  • Give access to the production cluster to fewer people.
  • Iterate faster to prevent production failure.

Carefully Collect Deployment Metrics

Kubernetes clusters have distributed services that support dynamic software. Therefore, it becomes crucial to have appropriate metrics to enable the applications to adapt to traffic. In addition, metrics can help measure the success of the deployment, enabling continuous monitoring of the performance of an application.

Follow these ways to collect Kubernetes clusters with ease:

  • Deploy Kubernetes cluster to run commands.
  • Use kubectl get to run commands against Kubernetes clusters and query the metrics API.
  • Retrieve compact metric snapshots.
  • Query resource allocations
  • Employ the Kubernetes dashboard to browse cluster objects.

Implement a Continuous Integration Server

A continuous integration server is software that centralizes all of your integration processes and provides a dependable building environment. In addition, it is highly adaptable and allows you to create different projects for various platforms.

The most critical consideration when utilizing a CI server is having a clean machine ready for installation. An environment free of excessive tools, environment variables, and other customizations is essential for running the CI server and overall process properly.

Here are the practices to run a continuous integration smoothly:

  • Frequently commit codes
  • Fix broken builds as soon as possible
  • Write unit tests
  • Ensure all tests must be passed
  • Avoid breaking code

Use of Deployment Checklist

Every task constituting multiple steps seems complex to accomplish unless you have a process. The same goes for deploying new software too. Preparing an app deployment checklist ensures that all the critical tasks are completed with utmost precision. Also, it is a must for one to be aware of the application's KPI.

Based on the above two parameters, you can make customized checklists for software deployment catered to your team's needs. 

Consider Applying Resource Limits

If you are deploying your application to Kubernetes, there is no resource limiter by default. Without a limiter, your application can consume the entire cluster's resources, disrupting the production cluster's performance. That's why it is crucial to have resource limiters to avoid such circumstances. 

When setting limits, it is important to consider potential traffic and load bursts. Although Kubernetes is known to provide resource elasticity, maintaining a balance is important. Setting the limit too low can lead to application crashes, and setting it too high can make the cluster becomes inefficient.

Automate Your Deployment Process

Manually deploying can work, but it is not the right way to do it. When a  complex process like deployment is done by hand, it leaves too much room for human error. Automating deployment processes reduces errors and speeds up deployments making the process convenient for your team. 

Automation can be deployed simply by using scripts to deploy specific actions in a specific environment. Many advanced CI/CD tools in the market support automated deployment. 

Black box Kubernetes Software deployment clusters Production (computer science) White box (software engineering)

Published at DZone with permission of Hiren Dhaduk. See the original article here.

Opinions expressed by DZone contributors are their own.

Related

  • Scaling Microservices With Docker and Kubernetes on Production
  • The Production-Ready Kubernetes Service Checklist
  • Multi-Cluster Kubernetes Sealed Secrets Management in Jenkins
  • Kubernetes Deployments With DMZ Clusters: An Essential Guide

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