4 Steps to a Successful Google Cloud Migration
There used to be times when the main question you would ask yourself was, “Should I keep my workloads and data on-premise or should I move to the cloud?” Today, this is still a viable question, but it is much more complicated. It is no longer a question of either/or.
You can adopt a hybrid approach, and leverage both the cloud and on-premise components. You can migrate everything to the cloud, but you can leverage multiple cloud vendors and create your own multicloud architecture.
The abundance of choices when it comes to infrastructure and architecture is incredible. It’s giving everyone the opportunity to find the right solution for their projects. However, it can also make the decision-making process longer and complex.
This article focuses on Google Cloud Platform (GCP), and strives to provide you with basic guidelines for how to migrate your workloads to GCP. You will note that half of this methodology is dedicated to planning, and the rest to deployment and maintenance. This is to express the importance of planning. When planning a complex operation one must dedicate mple time to planning.
What Is Google Cloud?
Google Cloud Platform (GCP) is a public cloud service offered by Google. With it you can store data in the cloud, host virtual machines (VMs), deploy applications, perform analytics and more. In particular, GCP services focus on supporting containerized, cloud-native workloads and the development and deployment of machine learning models.
GCP is currently the smallest of the top three public cloud providers but offers several competitive features. These include:
- Private global network — GCP is based on Google’s global, private, fiber-optic network. This network provides direct interconnectivity between data centers.
- Security — includes built-in security features that apply the same capabilities as are used for Google’s own services, including those used for Google Search, Docs, and Gmail.
- Migration tools — a variety of migration tools are available, including live migration features, on-premise appliances, and migration engines.
Why You Should Move to Google Cloud Platform
When selecting a cloud provider, choosing the right one for your needs can be a difficult choice. Below are a few reasons why GCP might be the right choice for you.
Innovation and AI
Google Cloud has taken significant efforts to position itself as a top choice for AI and machine learning (ML) workflows. In GCP, you have access to a wide variety of services, including AI as a Service (AIaaS) APIs, pre-configured models, and optimized resources.
These services enable you to easily integrate AI capabilities into your workflows and products. This easy integration helps speed innovation and grants access to functionalities that might not otherwise be available.
Flexibility
In GCP, you can manage your cloud deployments independently for greater control or to use managed services for less responsibility. This enables all levels of organizations to access cloud benefits. GCP also recently released Google Anthos, a service supporting hybrid deployments for even more flexibility.
Additionally, GCP provides significant support for containers and the Kubernetes orchestration platform. With this support, you can smoothly distribute workloads and easily deploy applications across multiple environments.
Cost savings
Cost savings are a claim of most cloud services and GCP is no different in some respects. By moving data and workloads to the cloud, you can eliminate the costs of much of your infrastructure and hardware. GCP deployments enable you to only pay for the resources you’re using and eliminate costs wasted on underused resources.
Additionally, many GCP services are priced by the second, as compared to by the minute or hour like competitors’ services. GCP resources also tend to be cheaper than comparable services, sometimes by as much as 40 to 50%.
Google Cloud Migration Steps
Once you’ve decided that Google Cloud Platform is the right option for you, you can begin planning your migration. While every migration is different, Google recommends breaking your transition into the following four steps:
1) Assess
During the assessment phase, you need to take an inventory of your current systems, determine your goals for migration, and come up with a budget for your migration. It’s important to be thorough during this phase to minimize surprises later on and ensure that you are not wasting your efforts and time.
Before you move on from this phase, you should have a clear understanding of what you expect to gain from the cloud, what cloud expertise you currently have in-house, and how long you have to migrate. You should also know what applications and data you need to move, whether these assets can be moved as is or if assets need to be modified, and what regulations may apply.
2) Plan
In the planning phase, you need to take the information gathered in the assessment phase and map it to resources, configurations, and a timeline. You should figure out what resources are needed to meet the goals you determined and prioritize the order of your provisioning.
In general, it’s best to plan your easiest migration aspects first, such as simple storage resources and basic networks. These resources are typically simpler to configure and can help you gain familiarity with managing services in GCP. By starting small, you can also more easily test and refine your configurations.
3) Deploy
Once your plan is complete, you can begin provisioning and configuring your resources in preparation for migration. Make sure to test these resources and configurations before moving live assets. Doing so can help you prevent accidental data loss or security breaches.
After your configurations are tested and verified to be working as expected, you can begin migrating your data and workloads. Like with planning, start with your simplest tasks and refine your process as you go. Make sure to test any data or applications to ensure that assets were transferred successfully before transferring workloads.
During deployment, you have several options for moving assets. The method that is best for you depends on your level of in-house expertise or your ability to hire managed services. Here are two options to consider:
- Manual deployments — enable you to easily adjust settings and configurations as you go but are prone to error, misconfiguration, and poor documentation of processes. This method is not recommended for most deployments.
- Automated deployments — based on automated creation and deployment of artifacts. This method is achieved with continuous integration and continuous delivery (CI/CD) pipelines or other scripted toolchains. You can also use Google Deployment Manager to help automate the deployment of your applications.
4) Optimize
After you finish migrating, or mid-migration if you are moving in phases, you should begin focusing on optimizing your configurations. Optimizing helps ensure that you are getting the performance you expect at the cost you anticipated.
There are multiple services and tools you can use to help with optimization, including Google Cloud Monitoring. Whichever tools you use, make sure that tools provide visibility of your environments and can alert to changes in performance. If you’re unsure how to get started, the GCP documentation offers some specific processes you can use.
Conclusion
GCP can be incredibly useful, especially for those of you interested in AI. As expected from the company that maintains perhaps the most used AI in the world, GCP is situated as a top provider of AI and machine learning, including AIaaS. However, you’d do well by checking out any service before committing. GCP offers free tiers that you can use to check out services. You can use this tier during your planning stage, to ensure that future deployments go smoothly.
