Compute Engine Instance

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  1. Compute Engine Instance – Technical Documentation

This document provides a comprehensive technical overview of the Compute Engine Instance, a foundational server configuration offered within the larger Cloud Platform. It details the hardware specifications, performance characteristics, recommended use cases, comparative analysis, and maintenance considerations for this versatile server offering. This documentation is intended for system administrators, DevOps engineers, and IT professionals responsible for deploying and managing applications on the platform.

1. Hardware Specifications

The Compute Engine Instance is highly configurable, allowing users to tailor the hardware to their specific workload requirements. Below is a detailed breakdown of the available options as of October 26, 2023. Note that specifications are subject to change and users should always consult the official Compute Engine Documentation for the most up-to-date information.

1.1 CPU

Compute Engine offers a wide variety of CPU families, broadly categorized as:

  • **E2:** Cost-optimized, general-purpose CPUs based on Intel Xeon Scalable processors. Suitable for web servers, development environments, and small databases.
  • **N1:** General-purpose CPUs based on Intel Xeon Platinum processors. A balance of performance and cost. Ideal for most enterprise workloads.
  • **N2:** Higher-performance CPUs based on Intel Xeon Platinum processors with improved clock speeds and cache sizes compared to N1.
  • **N2D:** CPUs based on AMD EPYC™ 7002 Series processors, offering competitive performance and value.
  • **C2:** Compute-optimized CPUs based on Intel Xeon Scalable processors. Designed for compute-intensive workloads like High-Performance Computing (HPC) and gaming.
  • **C2D:** Compute-optimized CPUs based on AMD EPYC™ 7003 Series processors, offering even higher compute density.
  • **H3:** High-memory CPUs designed for in-memory databases, large caches, and analytics workloads. Based on Intel Xeon Platinum processors.
  • **Tau T2D:** Designed for scale-out workloads, offering a balance of performance and cost. Based on AMD EPYC™ 7003 Series processors.

The number of vCPUs available per instance varies depending on the machine type selected. Machine types are predefined configurations that combine CPU and memory. For example, an `n1-standard-1` instance has 1 vCPU, while an `n1-highmem-8` instance has 8 vCPUs. See Machine Types for a complete list. CPU features include support for Advanced Vector Extensions (AVX) and Advanced Encryption Standard New Instructions (AES-NI) for performance optimization in specific workloads.

1.2 Memory (RAM)

Memory options range from 3.75 GB to 4 TB, depending on the machine type chosen. Memory is generally DDR4, but H3 machine types utilize DDR4 with higher speeds and capacities. The memory-to-CPU ratio is configurable within certain limits, allowing users to optimize for memory-bound or CPU-bound applications. Virtual Memory is also supported, extending available memory using disk space.

1.3 Storage

Compute Engine offers several storage options:

  • **Persistent Disk (PD):** Block storage that persists data even when the instance is stopped. Offers various performance tiers:
   *   **Standard PD:** Lowest cost, suitable for sequential workloads and backups.
   *   **Balanced PD:**  Best price/performance ratio for general-purpose workloads.
   *   **SSD PD:**  High performance, ideal for databases and latency-sensitive applications.
   *   **Extreme PD:** Highest performance for demanding applications requiring extremely low latency.
  • **Local SSD:** High-performance, ephemeral storage directly attached to the host machine. Data is lost when the instance is stopped or terminated. Suitable for temporary caches and scratch space.
  • **Hyperdisk:** Ultra-high performance block storage with independent scaling of capacity and IOPS. Offers Extreme and Max performance tiers.
  • **Filestore:** Network File System (NFS) service for shared file storage. Useful for collaborative workflows and content management. See Storage Options for detailed comparisons.

1.4 Networking

All Compute Engine instances have a virtual network interface with a guaranteed minimum bandwidth of 1 Gbps to the public internet. Higher bandwidth options are available through Virtual Private Cloud (VPC) networking and network peering. Google’s global network provides low-latency connectivity and high throughput. Instances can be assigned static or ephemeral external IP addresses. VPC Firewall Rules provide granular control over network traffic.

1.5 Hardware Acceleration

Compute Engine supports hardware acceleration for specific workloads:

  • **GPUs:** NVIDIA Tesla GPUs (various models) are available for machine learning, scientific computing, and graphics-intensive applications. See GPU Instances for details.
  • **TPUs:** Tensor Processing Units (TPUs) are custom-designed hardware accelerators optimized for machine learning workloads.
  • **Sole-Tenant Nodes:** Allow users to allocate dedicated physical servers for compliance or licensing reasons.

1.6 Detailed Specification Table

Feature E2-medium N1-standard-1 N2-standard-2 C2-standard-4 H3-standard-8
vCPUs 2 1 2 4 8
Memory (GB) 4 3.75 8 16 52
CPU Architecture Intel Xeon Scalable Intel Xeon Platinum Intel Xeon Platinum Intel Xeon Scalable Intel Xeon Platinum
Disk Options Standard PD, SSD PD, Local SSD Standard PD, SSD PD, Local SSD Standard PD, SSD PD, Local SSD, Hyperdisk Standard PD, SSD PD, Local SSD, Hyperdisk Standard PD, SSD PD, Local SSD, Hyperdisk
Network Bandwidth (Gbps) 1 1 1 1 1
GPU Support No No Optional Optional Optional

2. Performance Characteristics

The performance of a Compute Engine Instance is highly dependent on the chosen hardware configuration and the workload being executed.

2.1 Benchmark Results

  • **SPEC CPU 2017:** N2 instances generally outperform N1 instances by 15-20% in SPEC CPU 2017 benchmarks. C2 instances provide even higher single-core performance, particularly for floating-point workloads.
  • **IOPS:** SSD Persistent Disks deliver consistent IOPS performance, typically exceeding 30,000 IOPS. Extreme PD and Hyperdisk offer significantly higher IOPS, reaching hundreds of thousands of IOPS.
  • **Network Throughput:** Instances consistently achieve close to 1 Gbps network throughput. VPC network peering and higher bandwidth options can increase throughput to 10 Gbps or higher.
  • **Machine Learning:** Instances equipped with GPUs or TPUs demonstrate significant performance gains in machine learning training and inference tasks. Performance scales linearly with the number of accelerators.

2.2 Real-World Performance

  • **Web Servers:** E2 instances provide sufficient performance for low-to-medium traffic web servers. N1 or N2 instances are recommended for higher traffic and more complex web applications.
  • **Databases:** SSD Persistent Disks are essential for database performance. H3 instances are ideal for in-memory databases like Redis or Memcached.
  • **Big Data Analytics:** C2 or N2 instances with large amounts of memory are well-suited for big data analytics workloads. Hyperdisk can provide the necessary IOPS for demanding data processing tasks.
  • **Gaming Servers:** C2 instances offer the low latency and high clock speeds required for responsive gaming server performance.

2.3 Performance Monitoring

Stackdriver Monitoring provides detailed performance metrics for Compute Engine instances, including CPU utilization, memory usage, disk I/O, and network traffic. These metrics can be used to identify performance bottlenecks and optimize resource allocation. Cloud Profiler can be used to identify performance hotspots in application code.

3. Recommended Use Cases

  • **Web Hosting:** E2 and N1 instances are cost-effective options for hosting websites and web applications.
  • **Application Servers:** N1, N2, and C2 instances are suitable for running application servers, such as Java, Python, or Node.js applications.
  • **Databases:** SSD Persistent Disks and H3 instances are recommended for running databases like MySQL, PostgreSQL, and MongoDB.
  • **Big Data Analytics:** C2 and N2 instances with large amounts of memory and high-performance storage are ideal for big data analytics workloads.
  • **Machine Learning:** GPU and TPU instances are essential for machine learning training and inference.
  • **Gaming Servers:** C2 instances provide the low latency and high clock speeds required for responsive gaming server performance.
  • **Development and Testing Environments:** E2 instances are a cost-effective option for development and testing environments.
  • **CI/CD Pipelines:** Compute Engine instances can be used to build and run continuous integration and continuous delivery pipelines. Cloud Build integrates well with Compute Engine.

4. Comparison with Similar Configurations

Compute Engine instances compete with similar offerings from other cloud providers, such as:

  • **Amazon EC2:** Offers a wide range of instance types similar to Compute Engine.
  • **Microsoft Azure Virtual Machines:** Provides comparable virtual machine offerings.
Feature Compute Engine Amazon EC2 Microsoft Azure Virtual Machines
General Purpose N1, N2, E2 M5, M6i D2s, D3
Compute Optimized C2, C2D C5, C6i NC series
Memory Optimized H3 R5, R6i E series
GPU Instances NVIDIA Tesla GPUs NVIDIA Tesla GPUs NVIDIA Tesla GPUs
Pricing Model Sustained Use Discounts, Committed Use Discounts, Spot VMs On-Demand, Reserved Instances, Spot Instances Pay-as-you-go, Reserved VM Instances, Spot VMs
    • Key Differentiators:**
  • **Sustained Use Discounts:** Compute Engine automatically applies discounts for instances that run for a significant portion of the month.
  • **Custom Machine Types:** Allows users to define custom CPU and memory configurations beyond predefined machine types. See Custom Machine Types.
  • **Global Network:** Google’s global network provides low-latency connectivity and high throughput.
  • **Live Migration:** Compute Engine can live migrate instances without downtime for certain maintenance events.

5. Maintenance Considerations

5.1 Cooling

Compute Engine instances are housed in Google’s data centers, which are equipped with advanced cooling systems. Users do not need to worry about cooling infrastructure. However, it’s important to be mindful of CPU utilization, as high CPU usage can generate significant heat.

5.2 Power Requirements

Power consumption is managed by Google’s data center infrastructure. Users are billed based on resource usage, including CPU, memory, and storage.

5.3 Operating System Updates

Users are responsible for applying operating system updates and security patches to their Compute Engine instances. Image Management provides tools for creating and managing custom images with pre-installed software and configurations. Consider using Managed Instance Groups to automate updates across multiple instances.

5.4 Backup and Disaster Recovery

Regular backups are essential for data protection. Compute Engine integrates with Cloud Storage for storing backups. Consider implementing a disaster recovery plan using regional persistent disks or cross-region replication. Snapshots are a quick and easy way to create point-in-time backups of persistent disks.

5.5 Monitoring and Alerting

Implement robust monitoring and alerting to proactively identify and address performance issues or security threats. Cloud Monitoring provides comprehensive monitoring capabilities. Configure alerts to notify you of critical events.

5.6 Security Considerations

  • **Firewall Rules:** Configure VPC Firewall Rules to restrict network access to your instances.
  • **Identity and Access Management (IAM):** Use IAM to control access to Compute Engine resources.
  • **Security Keys:** Use security keys to protect SSH access to your instances.
  • **Vulnerability Scanning:** Regularly scan your instances for vulnerabilities using tools like Security Command Center.


Intel-Based Server Configurations

Configuration Specifications Benchmark
Core i7-6700K/7700 Server 64 GB DDR4, NVMe SSD 2 x 512 GB CPU Benchmark: 8046
Core i7-8700 Server 64 GB DDR4, NVMe SSD 2x1 TB CPU Benchmark: 13124
Core i9-9900K Server 128 GB DDR4, NVMe SSD 2 x 1 TB CPU Benchmark: 49969
Core i9-13900 Server (64GB) 64 GB RAM, 2x2 TB NVMe SSD
Core i9-13900 Server (128GB) 128 GB RAM, 2x2 TB NVMe SSD
Core i5-13500 Server (64GB) 64 GB RAM, 2x500 GB NVMe SSD
Core i5-13500 Server (128GB) 128 GB RAM, 2x500 GB NVMe SSD
Core i5-13500 Workstation 64 GB DDR5 RAM, 2 NVMe SSD, NVIDIA RTX 4000

AMD-Based Server Configurations

Configuration Specifications Benchmark
Ryzen 5 3600 Server 64 GB RAM, 2x480 GB NVMe CPU Benchmark: 17849
Ryzen 7 7700 Server 64 GB DDR5 RAM, 2x1 TB NVMe CPU Benchmark: 35224
Ryzen 9 5950X Server 128 GB RAM, 2x4 TB NVMe CPU Benchmark: 46045
Ryzen 9 7950X Server 128 GB DDR5 ECC, 2x2 TB NVMe CPU Benchmark: 63561
EPYC 7502P Server (128GB/1TB) 128 GB RAM, 1 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (128GB/2TB) 128 GB RAM, 2 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (128GB/4TB) 128 GB RAM, 2x2 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (256GB/1TB) 256 GB RAM, 1 TB NVMe CPU Benchmark: 48021
EPYC 7502P Server (256GB/4TB) 256 GB RAM, 2x2 TB NVMe CPU Benchmark: 48021
EPYC 9454P Server 256 GB RAM, 2x2 TB NVMe

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⚠️ *Note: All benchmark scores are approximate and may vary based on configuration. Server availability subject to stock.* ⚠️

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