5 Operations Each Cloud Architect Must Automate

    5 Operations Each Cloud Architect Must Automate

    Automation is the feature that most clearly distinguishes the cloud from the conventional data centre and serves as its defining characteristic. Developers should make the most of it.

    The modern application development process of a company can benefit greatly from the cloud. The ability to automate crucial actions that traditionally required manual steps is one of the most important advantages.

    Perhaps the most important benefit of using the cloud is automation. Cloud architects succeed in their positions by utilizing automation whenever it is possible.

    What are some of the standard methods for cloud automation that are essential to a cloud architect’s position? When creating, developing, and deploying cloud-hosted applications, every cloud architect should aim to automate the following five tasks.


    The most fundamental and crucial aspect of using the cloud is automated scaling. Scaling is a crucial component of the cloud, whether we’re referring to the elastic scaling included in cloud-native services or the auto-scaling server resources. One of the main motives behind people switching to the cloud in the first place is the need for scalable infrastructure. However, a significant portion of this automated scalability necessitates the swift and painless launch of new server instances, which brings us to the following automation.

    Server provisioning

    Provisioning a new server could take days or weeks in the pre-cloud era. With the help of cloud automation, a server instance that is fully functional and operational and has all necessary software and services installed and running can be created in a matter of minutes. Automated server provisioning is essential for self-healing infrastructures as well as auto-scaling (another form of cloud automation).

    The process of resolving issues in the cloud is altered by terminating a malfunctioning or compromised server instance and allowing automation to replace it with a brand-new server instance. The MTTR (mean time to resolution) of numerous classes of problems and errors can be improved significantly thanks to this capability.

    Increased availability is a benefit of automated server provisioning. A larger number of smaller servers can easily replace a smaller number of larger ones when provisioning is automated. A model like this can significantly increase an application’s availability while minimizing the effects of failures.

    Infrastructure creation

    To get a cloud application running and serving users, automatic server provisioning is not sufficient in and of itself. Additionally, businesses must set up their load balancers, firewalls, network segments, databases, and any other services like queues and caches that the application depends on. If done manually, all of this provisioning can take a long time.

    It might take days or longer to set up all the required components if IT teams were deploying in an on-premises data centre. However, in the cloud, a method of automation called infrastructure as code (IaC) enables the provisioning of application infrastructure using API calls.

    The infrastructure provisioning process gains special advantages from infrastructure as code, such as change control and approval, change tracking, and infrastructure code reuse. Only in a data centre that functions like a cloud, where infrastructure APIs enable automated infrastructure creation, is infrastructure as code feasible.

    Code Deployment

    Pipelines for automated code deployment are not only found in the cloud. Automated code deployments are a logical extension for cloud-enabled applications, and cloud architects heavily rely on them given the widespread use of other forms of automation.

    The CI/CD pipeline is one of the most widely used techniques for automating code deployment. Continuous Integration/Continuous Delivery, also known as CI/CD, is a model that enables automatic code deployments based on code checked into a software version control system to be applied to production applications (again, such as Git).

    Automated deployments may be timed (daily, hourly, etc.) or triggered whenever a change is made to the code base and made available for deployment, depending on the application and business policies.

    Native cloud services

    The automated dynamic scaling that is integrated into many cloud services is a type of automation that is frequently disregarded. To manage the scaling requirements of the dynamic applications that use them, cloud databases (such as Amazon DynamoDB), cloud data storage (such as Amazon S3), and cloud queuing services (such as Amazon Simple Queue Service) all heavily rely on automation.

    Because S3 is straightforward, secure, dependable, simple to integrate, and automatic in its functionality, cloud architects frequently prefer to use it instead of building their own data store from local drive storage on compute instances (for example).

    The same can be said for a large number of other services offered by public clouds. By utilizing them, IT teams profit from strong automation that operates in the background.

    One of the distinguishing features of the cloud is automation. It’s one of the features that sets the cloud apart from a conventional data centre. The use of automation in all cloud-based applications should be enabled, expanded, supported, and encouraged by a good cloud architect.

    A good cloud architect will automate as much as they can, to put it simply. They are motivated by the power of cloud-based automation, and they like to use it in original and fascinating ways. It is the foundation of the most effective application deployments.