You might be considering a migration to Google Cloud to boost the scalability, flexibility, security, or cost-efficiency of your IT infrastructure. Or you might be looking to unlock advanced capabilities not possible in your traditional IT environment, such as advanced analytics or artificial intelligence, to transform your data into actionable insights.
But before embarking on a cloud migration, it’s essential to develop an end-to-end migration strategy so you can fully understand what’s involved, mitigate any potential issues before they arise, and ensure a smooth and successful transition. This involves developing a roadmap from start to finish (and beyond) for migrating any applications, databases, or services into a cloud-based environment.
Just like any journey, there may be bumps along the way, but a clear roadmap will help you overcome obstacles and guide you in the right direction.
Define Clear Goals
It’s important to set clear objectives for the migration aligned with your business goals. This starts with a workload assessment. Which workloads should be moved to the cloud? Which are a priority? And which cloud strategy is the best fit for each workload? There’s no one size fits all migration approach, and different workloads may require different approaches. Work with key stakeholders to determine the migration paths for each one, considering time, budget, and resources.
Choose a Cloud Migration Strategy
There are various migration approaches, from a lift-and-shift to refactoring (optimizing the existing code), re-platforming (migrating to a new platform with only minimal changes to the code), and re-architecting (altering the code to a new application architecture). A technical assessment of your existing applications and database environment can help you determine the right migration approach for different workloads. For example, dependencies between applications and data systems could impact your decision.
Optimize and Prepare Your Current Environment
Optimize existing applications and databases before migration. This includes cleaning and validating data to address any errors, duplicates, or inconsistencies to ensure data is accurate, consistent, and complete. Poor data quality can lead to potentially costly issues down the road. It’s also important to minimize any technical debt, which can reduce agility and introduce security risks. In addition, ensure that applications are cloud-ready, which may require re-architecting. For example, how much storage and bandwidth does a specific workload need? If it’s not cloud-ready, that could impact cost and performance in the cloud.
Leverage Google Cloud’s Native Tools and Services
Google Cloud has a number of tools and services that can streamline the migration process and reduce downtime. For example, BigQuery Migration Service can be used to migrate existing data warehouses to BigQuery, while Database Migration Service is useful for databases like MySQL, PostgreSQL, SQL Server, and Oracle. Many other tools are available, depending on the type of migration. For example, Google Compute Engine (GCE) helps migrate virtual machines (VMs) to Compute Engine via a simple lift-and-shift migration with minimal downtime. For more information, Google Migration Center provides tools, best practices, and guidance for migrating applications and infrastructure workloads to Google Cloud.
Ensure Robust Security and Compliance
During a migration, you’ll want to ensure that your data isn’t being exposed to potential risks, like unauthorized access or cyberattacks. Identify any potential threats or unintentional risks that could expose your data during the migration process, and ensure that security measures are in place—including data encryption, IAM, and compliance checks—to mitigate any issues. Encrypting data in transit and at rest (when stored in the cloud) ensures that data is unreadable to unauthorized parties. Google Cloud also offers tools such as identity and access management, encryption key management, and data loss management.
Conduct Thorough Testing and Validation
It’s important to conduct testing and validation at each step of the migration journey. This can help to identify potential issues early in the process—before they become larger (and potentially more costly). This includes performance benchmarking (to determine if a workload is performing as expected) and user acceptance testing (to ensure users can continue to do their work in the new environment as expected). You’ll also want to validate migrated data to ensure it is accurate and complete, in case there were any issues during the migration process.
Plan for Continuous Optimization Post-Migration
Once you’ve migrated your workloads successfully into the cloud, you’ll want to ensure those workloads are optimized. And Google Cloud makes it easy, with several monitoring and analytics tools that can provide continuous performance optimization. For example, Google Cloud Monitoring can help to track the performance of applications (say, if there’s unusually high response times) and alert you when issues occur. And Google’s Recommenders analyze usage patterns and offer recommendations on how to optimize your environment for better performance and cost efficiencies. Continuous optimization can help to ensure long-term success on Google Cloud.
Getting started
While Google offers a myriad of tools to smooth what can often be a complex migration process, getting the most out of these tools does require intimate knowledge of the Google Cloud ecosystem. A Google Cloud partner like Pythian can help you align your migration strategy with your targeted business goals and ensure your data is optimally positioned to realize productivity gains, cost efficiencies, and application modernization. With more than 25 years of database and cloud experience, we can help you reach your cloud migration and modernization goals.
Contact Pythian for expert support in planning and executing your Google Cloud migration.
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