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Google cloud migration will offer several lucrative services to enhance operational efficiency in businesses

If you’re thinking about migrating to Google Cloud, but don’t know where to start, then you’ve come to the right place! This guide will discuss how you can migrate your workloads to the Google Cloud platform in just four simple steps.  

Step 1: Assessing your current environment and workload to be migrated

The first and arguably the most crucial phase of a Google Cloud migration is to assess your current environment and the workloads/applications to be migrated. There are three different types of environments to be considered: 1. On-premise: Both your current environment’s software and hardware elements are hosted and managed on-premises. This provides you control, but also full responsibilities of the environment. 2. Private hosting: The physical infrastructure of the environment is outsourced to an external party, so you don’t have to manage the physical security of the infrastructure. However, software aspects of the environment (including hypervisors and Virtual Machines) are still under your control and responsibilities. 3. Public cloud environment: Your environment is hosted on other cloud services (i.e., Amazon Web Services or Microsoft Azure). Everything is already handled by the cloud vendor, so you only need to care about your workloads. On the other hand, there are also two different types of workloads based on whether they are cloud-native or not: 1. Legacy: Non-cloud-native workloads are developed without considering cloud functionality. Thus, they are more difficult to migrate and run on the Cloud. 2. Cloud-native: This type of workload is already compatible with cloud environments, including Google Cloud, making it easier to migrate to the Cloud and keeping it more secure.  Next, start taking inventory of the workload(s) that you plan to migrate to the Cloud, as well as each of their requirements: hardware, licensing, dependencies, and so on. Ask yourself the following question: 

  • How critical is the workload to the business? How fast would you need the workload to be migrated?
  • How difficult is it to migrate the workload based on the previous assessments?
  • Is the workload dependent on other workloads? (or vice versa whether it’s a dependency on other workloads)

You should also perform a total cost of ownership (TCO) calculation so you can better understand how much the Google Cloud deployment will cost (including maintenance costs). This is especially important when migrating from an on-premises environment to Google Cloud Platform (GCP) or other cloud environments. There are often hidden costs not accounted for when calculating the costs in the old environment.  Based on all these assessments, you can decide on which workload(s) to migrate and prioritize which workload to migrate first.  

Step 2: Planning the migration’s steps

In this phase, the focus is to identify what resources are needed to meet the objective of the Google Cloud migration and prioritize the necessary steps. In most cases, it’s better to perform the easier aspects of the migration first. Doing so can help you gain familiarity with the Google Cloud Platform while also giving you more time to test various aspects of the migration. Specific to Google Cloud, you’ll also need to consider the following elements in your planning:  1. User and service identities: Check out Google’s guide on how to establish IAM (Identity and Access Management) on the Google Cloud Platform 2. Planning hierarchy for resource allocation: On Google Cloud, resource organization hierarchies are structured via organization nodes,folders, and projects. A comprehensive resource organization will help simplify access control/authentication and billing management 3. Defining roles and groups: Define different roles and groups for resource allocation purposes. The focus here is to make sure users can only access information and resources absolutely needed to fulfill their tasks to ensure efficiency and data security 4. Designing network topology: Check out Google’s guide on how to design your Virtual Private Cloud (VPC) to ensure a fast, reliable, and secure network topology  

Step 3: Deployment

This phase, as the name suggests, is about provisioning workloads and resources to prepare for the migration process.  Depending on the number of workloads to migrate and other factors, you may or may not want to use the same deployment approach for your workloads. However, using a single, consistent approach can make the whole process easier and will also provide you with more time to evaluate and improve the deployment process.  Nevertheless, make sure to test and evaluate all resources and configurations before migration. Only move live assets once all configurations are tested and verified to be working as intended. In deploying your workloads, you have two options to consider:

  • Manual deployment: You have more control over the deployment process, and you can fine-tune the configurations as needed. However, it’s more difficult and prone to various errors, and keeping an audit trail for the deployment process can be difficult
  • Automated deployments: You can use tools like Google Deployment Manager to automate the deployment of workloads. This approach will provide more traceability and is more reliable in most cases

Step 4: Optimizing the Google Cloud environment

You can start optimizing your Google Cloud environment mid-migration if you are moving in phases (i.e., after a basic deployment of the priority workloads are already tested and running properly on Google Cloud) or after you finish migrating.  The purpose of the optimization phase is to ensure you are getting the most optimal performance possible, according to your business goals, while using fewer resources.  This phase should also include training your employees for optimal adoption of the Google Cloud environment and ensuring that monitoring (analytics) and logging are in place for all the migrated workloads. You can use multiple solutions and tools to optimize the migration process, including Google’s own Cloud Monitoring tool. Also, you should consider optimizing your costs with autoscaling.   

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