The 4 Phases Of A Successful Cloud Migration (2022)

Phases Of Successful Cloud Migration

As IT infrastructure and applications become more complex, organizations increasingly turn to the cloud for help. Cloud migration involves moving data, applications, and workloads from a local environment to a cloud computing environment. There are four phases of cloud migration: assessment, planning, execution, and optimization.

Assessment is the first phase of cloud migration and involves identifying which workloads and applications are a good fit for the cloud. Developing a migration strategy and roadmap is the second phase of planning. The third phase is execution, which involves moving workloads and applications to the cloud. Optimization is the fourth and final phase and consists in tuning and troubleshooting the migrated workloads and applications.

This blog post offers a high-level overview of our recommended data center migration procedure. Then, in future blog posts, we’ll offer a more precise view of cloud migration’s engineering and program management aspects. 

Phases Of Cloud Migration

Phases Of Cloud Migration

Phase 1: Discovery 

The first step of our cloud migration technique is the Discovery phase. Here we associate with a company’s data center team to recognize and document the entire data center footprint. This consists of understanding the existing hardware mapping, software applications, and storage layers (databases, file shares). Also, the operating systems, networking configurations, security requirements, models of operation (release cadence, how to deploy, escalation management, system maintenance, patching, virtualization, etc.), licensing and compliance requirements, besides other applicable assets.

In this section, our goal is to achieve an in-depth view of all relevant assets and resources of the modern data center footprint. These sources must additionally consist of a resource grouping classification. This can be leveraged in the following phases for dependency mapping and migration wave planning. 

For example, while inventorying a data center, you must identify the many operating environments (non-production vs. production), dependencies (third-party software, domain controllers, etc.), and the business outcome of all applications, along with third-party systems which might be in the migration scope. The major turning points in the Discovery phase of cloud migration are: 

  • Creating a “shared” data center inventory footprint. All groups that might be part of the cloud migration must know the assets and resources to go live. 
  • Completing a preliminary GCP foundations design. This includes figuring out centralized concepts of the GCP organization, including folder structure: Identity and Access Management model, network administration model, and much more.

Phase 2: Planning

The 2nd phase is Planning. Planning leverages the assets and deliverables accumulated in the Discovery phase to create cloud migration waves—logical groupings of sources—to be sequentially deployed into production and non-production environments. 

To follow a general rule, it’s best to target non-production cloud migration waves first, figuring out the sequence of waves to migrate first. 

Here, keep in mind: 

  • Mapping of current server inventory to Google Cloud machine types. Each workload nowadays will usually run on a machine with the same computing power, memory, and disk. 
  • Deadlines – When are my targets for migrating? 
  • Workloads in every grouping. What are my cloud migration waves grouped by? Is it through non-production vs. production applications? Is it by feature (databases vs. file shares vs. applications)? 
  • The cadence of your code releases? Factor in any upcoming code releases as this will affect the decision of whether to migrate sooner or later. 
  • Time for infrastructure deployment and checking out. Factor in adequate time to check your infrastructure before entirely cutting over to Google Cloud
  • A wide variety of application dependencies. The applications with the fewest dependencies are usually appropriate candidates for migration first. In contrast, you can need to wait to migrate an application that relies upon many databases. 
  • Migration complexity and risk – Migrations are usually more successful when you first address the simpler elements of the migration.

Phase 3: Execution 

The 3rd phase is Execution: taking the plans you’ve created and bringing them to fruition. During the Execution phase, you must be cautious about the exact steps you’re taking and the configurations you develop. That’s because you’ll commonly repeat them during the non-production and production cloud migration waves. The Execution section is when you put in place your infrastructure components. IAM, networking, firewall rules, and Service Accounts—ensure they’ve configured appropriately. 

This is likewise when you test the applications on the infrastructure configurations, ensuring they have access to their databases, file shares, web servers, load balancers, Active Directory servers, and more. Execution includes logging and tracking to ensure your application continues to function with the actual performance.

Phase 4: Optimize 

The final phase of the migration venture is Optimization. Once you’ve migrated your workloads to Google Cloud, we recommend a periodic evaluation and planning to optimize them. You may need to remember many optimization activities during this time: 

  • Resize your machine types and disks to save costs or enhance performance. 
  • Try leveraging Terraform for more predictable and agile deployments. 
  • Improve automation to lessen operational overhead 
  • Improve integration with logging, tracking, and alerting tools 
  • Adopt managed offerings to lessen operational overhead.

The Final Verdict

Performing a complete data center migration is a vast but profitable undertaking. You could break down the procedure into stages with these remarkable migration frameworks. This will have you decommission your final data center in no time! Perhaps most importantly, it’s an excellent idea to consider that the cloud isn’t a panacea. It is just a way to ease the management burden of technology. This way, your IT organization can spend time offering you the right technology you want to thrive on instead of simply keeping the lights on.

FAQs

1. What is the objective behind cloud data migration? 

The typical objective of cloud migration is the same as the reasons to utilize the cloud: apply applications and data to the best possible infrastructure based on cost, overall performance, and security factors. 

2. Is it safe to move to the cloud? 

The cloud is a secure place to store mission-critical data. Now, given the growing popularity of the cloud, it surpassed the abilities of most on-premises systems in terms of safety. The recent pandemic gave rise to the ever-growing cloud market, so many IT security businesses decided to focus their RnD efforts on cloud computing security. 

3. Why are more and more organizations undertaking the process of cloud migration these days? 

Agile and flexible solutions are available via the cloud, which might be imperative to fulfilling changing consumer and market demands. For organizations that adopt the phases of cloud migration, the cloud can have a considerable impact. The benefits include the reduced total cost of ownership (TCO), quicker delivery time, and more excellent innovation opportunities.

4. Will I ever run out of storage in the cloud?

Generally, no. In practice, your budget is the limiting factor. However, on-premises storage becomes more expensive and time-consuming as you scale, whereas cloud storage allows you to minimize costs with calculators and alerts.

5. Why is orchestration essential for cloud migration? 

Cloud orchestration enables ensuring statistics integrity and keeping away from deployment errors throughout the migration. Then, it gives many crucial advantages for cloud management: enhanced optimization, visibility and control, long-term money savings, elevated business agility, and lots more.

Leave a Reply

Your email address will not be published.