Source of legacy application
Cloud / Knowledge library
Google Compute Engine
Runs customizable virtual machines on Google Cloud infrastructure
Why learn Google Compute Engine?
Teams use Google Compute Engine to adopt virtual machine compute without building the complete underlying platform themselves.
The problem it solves
Runs configurable operating-system virtual machines
Where it came from
Google Compute Engine is Google Cloud's offering for virtual machine compute. Its closest catalog counterparts are Azure Virtual Machines and Amazon EC2; they address the same broad need but are not feature-for-feature identical.
Build your understanding
Work through these exercises in order. Try the task before opening a reference.
- Explain the main responsibility of Google Compute Engine.
- Choose a workload that fits Google Compute Engine.
- Identify one operational tradeoff of Google Compute Engine.
- Compare Google Compute Engine with Azure Virtual Machines.
- Compare Google Compute Engine with Amazon EC2.
Documentation and sources
- Google Cloud products at a glance (docs.cloud.google.com)
Connect the ideas
Alternatives
Real World Example
Legacy Application Migration to Compute Engine
Enterprises maintaining monolithic legacy applications that require specific OS configurations and persistent storage environments.
The business problem
High operational overhead and lack of flexibility when managing on-premises hardware for legacy applications that cannot be easily containerized.
How this topic solves it
Compute Engine provides customizable virtual machines that allow businesses to lift and shift legacy workloads into a managed cloud environment, retaining full control over the OS and network stack while gaining infrastructure scalability.
- Assess the legacy application requirements including CPU, RAM, and disk storage needs.
- Create a custom machine image or select a pre-configured OS image within Compute Engine.
- Configure Virtual Private Cloud (VPC) settings to ensure secure network connectivity.
- Deploy the virtual machine instance and attach persistent disks for data storage.
- Verify application functionality and performance within the new virtualized environment.
The flow shows how legacy applications move from on-premises to a cloud-based VM instance.
Customizable virtual machine
Attached block storage
Software-defined networking
- On-Premises Server → Migrates workload → Compute Engine VM
- Compute Engine VM → Mounts storage → Persistent Disk
- Compute Engine VM → Connects to network → VPC Network
Expected business outcome
Improved infrastructure agility and reduced maintenance burden by offloading hardware lifecycle management to Google Cloud.
Limitations and checks
Compute Engine requires manual management of the guest operating system, including patching and security updates, which can be checked by monitoring OS-level logs and security compliance reports.