This part will cover the last three considerations when creating and running an automated, cloud-based pipeline.
3. It's All About Continuous Improvement
Steep Learning Curves
Before you start creating your cloud-based pipeline, there is some learning you have to do. It might be learning Kubernetes, AWS products, Google Cloud products, Microsoft Azure products, etc. As a community, we must spend time to explore new technologies, learn how to apply them, and how to advance these skills in our industry, even if it takes us weeks to find out and understand how to deploy such technology.
(Source: Valamis)
Keep Fail-Safes in Mind
In general, you should inspect ways your application might fail if a configuration file is changed or a file is incorrectly updated to the pipeline. Therefore, spend time on planning and you can limit the possibility of this happening.
4. Enable Self-Service Features
Rapid Onboarding to New Teams and Pipelines
Adding a role to your architecture should be simple and easy when you onboard new engineers. Spending countless hours accessing things can hinder the process for you and your new team members as they took to start development immediately.
Visibility of Applications
Your team should be provided with tools to monitor their application day-to-day. You can also utilize integrations to run audits on your application's health.
5. Track Your Pipeline, Microservices, and Compliance Policies
The Importance of Dashboards
Having a general-purpose dashboard to manage or view your clusters will allow you to troubleshoot defects and manage clusters' health of all your applications. Having a birds-eye view of all microservices running and an easy dashboard to view will make your life much simpler.
Enforce Policies: Approval Gates, Compliance Checks, and ACLs
Setting up roles for your engineering team and understanding the roles everyone will have to the application is very important. Finally, you should set-up compliance checks to keep track of roles and their access to the application.
Source: Dzone
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