Google Compute Engine delivers configurable virtual machines running in Google’s data centers with access to high-performance networking infrastructure and block storage solutions. Features include custom machine types, preemptible instances, and automatic discounts for sustained use.
What is Google Compute Engine?
Google Compute Engine is the Infrastructure-as-a-Service (IaaS) offering from Google Cloud Platform, providing fully configurable virtual machines (VMs) in Google’s global data centers. As the foundation for cloud infrastructures, Compute Engine offers complete control over operating systems, network configuration, and storage architecture.
The platform distinguishes itself through a comprehensive portfolio of machine types optimized for different workload requirements. General-purpose families (N1, N2, N2D, E2) suit standard applications with balanced CPU-to-memory ratios. Compute-optimized instances (C2, C2D) deliver the highest performance per core for compute-intensive tasks like scientific calculations or rendering. Memory-optimized machines (M1, M2) provide up to 12 TB of RAM, ideal for in-memory databases like SAP HANA or large caching systems. Accelerator-optimized instances (A2) with NVIDIA A100 GPUs address machine learning and high-performance computing workloads.
Significant cost advantages emerge through flexible pricing models. Spot VMs offer up to 91% discounts compared to regular instances for fault-tolerant batch workloads that can handle interruptions. Committed Use Discounts grant up to 57% price reductions with 1-year or 3-year commitments. Sustained Use Discounts are applied automatically when VMs run continuously throughout a month. Per-second billing ensures you only pay for actually consumed resources. Custom Machine Types enable precise right-sizing through individual configuration of vCPUs and RAM, avoiding overprovisioning. Live Migration enables maintenance operations without downtime by transparently moving running VMs to different hardware.
Compute Engine Compared
vs. AWS EC2: Compute Engine offers simpler pricing models with automatic Sustained Use Discounts without upfront commitment, while AWS Reserved Instances require manual planning. Live Migration for maintenance-free updates is standard at Google, optional at AWS.
vs. Azure Virtual Machines: Google excels in performance for big data and ML workloads and offers simpler network configuration. Azure shines in Windows integration and hybrid scenarios with on-premises infrastructure.
vs. STACKIT Compute Engine: STACKIT guarantees complete data sovereignty in Germany, GCP offers global reach with 40+ regions and deeper integration with cloud-native services like BigQuery or Vertex AI.
Common Use Cases
Web Applications and E-Commerce Platforms
Managed Instance Groups automatically scale during traffic spikes from sales promotions or events. Global Load Balancing distributes requests to instances in multiple regions for low latency. An online shop uses N2 instances in Frankfurt and Belgium with Cloud CDN for static content, achieving 99.99% availability at 40% lower costs than on-premises.
Relational Databases and Data Warehousing
N2 instances with Local SSDs deliver six-figure IOPS for PostgreSQL or MySQL clusters. Memory-optimized M2 instances with up to 12 TB RAM host large SAP HANA systems or in-memory databases. Persistent Disk snapshots automate backups without performance degradation.
High-Performance Computing and Scientific Simulations
C2 instances with 60 vCPUs and 3.8 GHz all-core turbo accelerate CFD simulations, genome sequencing, or financial modeling. Preemptible VMs reduce costs for batch jobs by 80%. A research institute runs Monte Carlo simulations on 1,000+ Spot VMs, paying only for actually used compute time.
Rendering Farms and Media Production
Compute-optimized C2D instances with AMD EPYC processors accelerate 3D rendering and video transcoding. Spot VMs enable cost-effective render farms that automatically switch to regular instances during capacity shortages. A VFX studio renders animated films 60% faster than with on-premises hardware at 45% lower costs.
SAP Workloads and Enterprise Applications
Certified M1 and M2 instances meet SAP HANA hardware requirements for production environments with up to 12 TB RAM. SUSE Linux Enterprise Server and Red Hat Enterprise Linux as certified OS images. Committed Use Discounts reduce TCO for 3-year planning by up to 57%. A mid-sized company migrates SAP ERP to M2 instances and eliminates hardware refresh cycles.
Windows Server Migration and Legacy Modernization
Sole-Tenant Nodes enable Bring-Your-Own-License (BYOL) for Windows Server and SQL Server to reduce licensing costs. Automated OS patching with OS Config Management reduces administrative overhead. A financial services company migrates 200+ Windows Server 2012 VMs to Compute Engine and uses Extended Security Updates during modernization.
Disaster Recovery and Business Continuity
Snapshots and Machine Images replicate VMs to secondary regions for Recovery Point Objectives (RPO) under 15 minutes. Persistent Disk Replication synchronizes data regionally or multi-regionally. An insurance company implements DR for critical workloads with automatic failover, reducing RTO from 4 hours to 20 minutes.
Best Practices for Compute Engine
Leverage Right-Sizing with Recommender API
Google Cloud Recommender analyzes actual resource utilization and suggests optimized machine types. VMs consistently running under 60% CPU utilization should be migrated to smaller instances. Custom Machine Types avoid overprovisioning through exact adjustment of vCPUs and RAM. Monitor for 14 days before right-sizing to obtain representative data.
Deploy Spot VMs for Fault-Tolerant Batch Workloads
Rendering, ETL pipelines, scientific simulations, or CI/CD jobs benefit from up to 91% cost savings. Implement checkpointing to preserve progress during interruptions. Combine Spot VMs in Managed Instance Groups with regular instances as fallback. Spot VMs are unsuitable for databases or stateful web servers.
Commit to Committed Use Discounts for Predictable Workloads
Production systems with predictable baseline loads justify 1-year or 3-year commitments for up to 57% discounts. Commitments apply per project and region but can be flexibly used with automatic application to matching instances. Combine commitments with Spot VMs for peak loads.
Use Custom Machine Types Instead of Overprovisioning
Predefined Machine Types offer fixed CPU-to-RAM ratios that often don’t fit optimally. Custom Machine Types allow 1 vCPU with 6.5 GB RAM or 32 vCPUs with 29 GB RAM for specialized workloads. Cost savings of 20-40% compared to next-larger Predefined Type possible.
Enable Live Migration for High Availability
Live Migration moves running VMs without downtime during host maintenance or hardware failures. Enabled by default for VMs without Local SSDs or GPUs. For critical workloads, Live Migration should be explicitly verified as brief performance degradation may occur during migration.
Automatically Receive Sustained Use Discounts
Automatic discounts of up to 30% for VMs running over 25% of a month. No upfront commitment required, discount is calculated hourly and applied monthly. Combinable with Committed Use Discounts for maximum cost reduction. Keep instances running instead of daily stops to maximize discount.
Automate OS Patching with OS Config Management
OS Patch Management automates security updates for Linux and Windows without manual intervention. Patch baselines define approved updates, maintenance windows control time frames. VM Manager provides compliance reports on patch status. Reduces security risks and administrative overhead for fleets with hundreds of VMs.
Integration with innFactory
As a Google Cloud partner, innFactory supports you with Compute Engine: architecture design for optimal machine type selection, migration from on-premises or other clouds, cost optimization through Committed Use Discounts and right-sizing, automation with Terraform and Infrastructure as Code.
Contact us for a consultation on Google Compute Engine.
Available Tiers & Options
General Purpose (E2, N2, N2D, N1)
- Best price-performance
- Flexible configurations
- Suitable for most workloads
- Not optimized for specific use cases
Compute Optimized (C2, C2D)
- Highest performance per core
- Ideal for compute-intensive workloads
- Higher cost
- Limited to specific use cases
Memory Optimized (M1, M2)
- Up to 12 TB of memory
- Ideal for in-memory databases
- Expensive
- Limited availability
Accelerator Optimized (A2)
- Optimized for ML training and inference
- NVIDIA A100 GPUs
- Very expensive
- Limited availability
Typical Use Cases
Technical Specifications
Frequently Asked Questions
Which machine type should I choose for my application?
General Purpose (N2, E2) suit most web servers and applications with balanced CPU/RAM ratios. Compute-optimized C2/C2D for compute-intensive jobs like rendering or HPC. Memory-optimized M1/M2 for in-memory databases (SAP HANA, Redis) with high RAM requirements. A2 with GPUs for ML training. Custom Machine Types for special requirements.
What is the difference between Spot VMs and Preemptible VMs?
Spot VMs are the evolution of Preemptible VMs with more flexible runtime (no 24-hour limit) and dynamic pricing. Both offer massive discounts (up to 91%) for interruptible workloads. Spot VMs have no guaranteed maximum runtime but can be terminated anytime with 30 seconds notice. Use Spot VMs for new projects.
How do Committed Use Discounts work and when are they worthwhile?
With Committed Use Discounts, you commit to using a specific amount of vCPUs and RAM in a region for 1 or 3 years. Discounts up to 57% compared to on-demand pricing. Worthwhile for predictable baseline loads in production environments. Commitments flexibly apply to different machine types. Combine with Spot VMs for peak loads.
What does Live Migration mean and when is it used?
Live Migration transparently moves running VMs to different physical hardware during maintenance operations without stopping or restarting the VM. Google performs Live Migration automatically during host maintenance. Performance degradation during migration (few seconds) is minimal. Not available for VMs with Local SSDs, GPUs, or Sole-Tenant Nodes.
What Persistent Disk options exist and how do I choose?
Standard Persistent Disk for archiving and backups (cheap, slow). Balanced Persistent Disk for most production workloads (good price-performance ratio). SSD Persistent Disk for databases with high IOPS requirements. Extreme Persistent Disk for maximum performance (100,000+ IOPS). Local SSDs for highest performance with temporary data (lost on VM stop).
How do I optimize Compute Engine costs?
Right-sizing with Recommender API to avoid overprovisioning. Spot VMs for batch workloads (up to 91% discount). Committed Use Discounts for predictable baseline loads (up to 57% discount). Custom Machine Types instead of Predefined Types. Stop instances outside business hours. Sustained Use Discounts through continuous operation. Preemptible/Spot VMs in Managed Instance Groups as autoscaling target.
Can I bring my own Windows Server licenses (BYOL)?
Yes, with Sole-Tenant Nodes you can use your own Windows Server and SQL Server licenses. Sole-Tenant Nodes are physical servers reserved exclusively for your project. Required for licensing models that mandate dedicated hardware. Alternative are Google-provided Premium Images with included licenses (higher costs but simpler).
What GPU options does Compute Engine offer?
NVIDIA Tesla K80 (legacy), P4, P100, T4, V100, A100 available. A2 instances with up to 16x A100 GPUs for ML training. T4 for inference and cost-effective workloads. GPU availability varies by region, EU regions have limited selection. GPUs can be added to existing N1 instances. Preemptible GPUs for up to 73% discount on batch workloads.
How does automatic scaling work with Compute Engine?
Managed Instance Groups enable autoscaling based on CPU utilization, HTTP Load Balancing metrics, or Custom Metrics from Cloud Monitoring. Define minimum, maximum, and target utilization. Autoscaler adds VMs under high load and removes them under low load. Health checks automatically replace failed instances. Combinable with Spot VMs for cost-effective scaling.
What are Shielded VMs and Confidential VMs?
Shielded VMs provide Secure Boot, vTPM, and Integrity Monitoring to protect against rootkits and bootkits. Enable for compliance-critical workloads. Confidential VMs encrypt data during processing in RAM using AMD SEV. Protects against physical access to hardware. Confidential VMs use N2D instances and have slight performance overhead (5-10%).
