Migration tools are at the center of migration execution. They allow you to move your existing workloads to Google Cloud and to take advantage of Google Cloud managed services when you modernize your infrastructure.
This document presents the main tools that Google Cloud professional service teams use during migration projects.
Google Cloud tools
This table presents some of the migration tools available in Google Cloud.
- On-premises VMware VMs
- VMs from other cloud environments
- On-premises VMware VMs
- VMware VMs running in alternate clouds
Based on the nature of the workloads that you want to migrate, you might want to integrate other tools with your migration tools architecture. The following list includes additional migration tools:
- Storage Transfer Service lets you bring data to Cloud Storage from other cloud providers, online resources, or local data (for example: S3, Blob, Data Lake, on-premises file systems).
- Transfer Appliance is a hardware appliance you can use to migrate large volumes of data (recommended for data that exceeds 20 TBs and up to 1 petabyte) to Google Cloud without disrupting business operations.
- Image Import lets you to import virtual disks in your on-premises environment with software and configurations that you need (a.k.a. golden disks or golden images) into Google Cloud and uses the resulting image to create virtual machines. The tool supports most virtual disk file formats, including VMDK and VHD.
Third-party tools
The following list includes third-party migration tools. The list is meant as a reference only, and doesn't represent a statement of support by Google.
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RackWare Management Module (RMM) is a fully-automated enterprise-grade migration solution that lets you migrate physical and virtual servers from any data center or public cloud into Google Cloud. It is listed in Google Cloud Marketplace, and you can purchase a license in two ways:
- Within the Cloud Marketplace, by selecting RackWare Cloud Migration SaaS and API .
- Directly from RackWare, by selecting RackWare Cloud Migration Virtual Machine .
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SUREedge is a tool that lets you migrate physical and virtual environments to Google Cloud when Migrate to Virtual Machines might not be a fit, for example for on-premises non-vSphere virtualized environments.
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Data Validation Tool is an open sourced Python CLI tool based on the Ibis framework that compares heterogeneous data source tables with multi-leveled validation functions. Data validation is a critical step in a Data Warehouse, Database or Data Lake migration project.
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HarbourBridge: Spanner Evaluation and Migration is a standalone open source tool for Spanner evaluation and migration, using data from an existing PostgreSQL, MySQL, SQL Server, Oracle or DynamoDB database.
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HBase Tools help HBase users with migrations to Bigtable.
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Migrate Hive tables to BigQuery framework migrates data from Hive to BigQuery using Cloud SQL to keep track of the migration progress.
Build and deploy automation and CI/CD tools
The automation of building and deployment within a CI/CD framework is an essential part of the migration process.
Cloud Build is a service that executes your builds on Google Cloud. Cloud Build can import source code from Cloud Storage, Cloud Source Repositories, GitHub, or Bitbucket, execute a build to your specifications, and produce artifacts such as Docker containers or Java archives.
Artifact Registry provides a single location for managing packages and Docker container images. It integrates with CI/CD tools and Google Cloud runtime environments so that you can manage the full artifact lifecycle.
Cloud Deploy is a managed service that automates delivery of your applications to a series of target environments in a defined promotion sequence.
If you have containerized applications, you can deploy them with Kubernetes and managed services such as Google Kubernetes Engine . To deploy into a serverless environment, you can use tools such as App Engine flexible environment , Cloud Run functions , and Cloud Run .
Testing tools
As you migrate workloads to Google Cloud, you need to test these workloads for specific functional and non-functional scenarios with a view to measure and mitigate the impact on functionality, integration, security, performance, and availability.
The choice of testing tools depends on several factors, such as the following:
- Compatibility with technology stacks of workloads
- Degree of test automation
- Integration with CI/CD framework
- Defect logging and management
- Test project and program management
