Compute Engine: Choosing the right machine family and type
Choosing the right VM family is the first step in driving efficiency for your workloads. For organizations that want to run virtual machines (VMs) in Google Cloud, Compute Engine offers multiple machine families to choose from, each suited for specific workloads and applications. Within every machine family there is a set of machine types that offer a prescribed combination of processor and memory configuration.
General purpose - These machines balance price and performance and are suitable for most workloads including databases, development and testing environments, web applications, and mobile gaming.
Compute-optimized - These machines provide the highest performance per core on Compute Engine and are optimized for compute-intensive workloads, such as high performance computing (HPC), game servers, and latency-sensitive API serving.
Memory-optimized - These machines offer the highest memory configurations across our VM families with up to 12 TB for a single instance. They are well-suited for memory-intensive workloads such as large in-memory databases like SAP HANA and in-memory data analytics workloads.
Accelerator-optimized - These machines are based on the NVIDIA Ampere A100 Tensor Core GPU. With up to 16 GPUs in a single VM, these machines are suitable for demanding workloads like CUDA-enabled machine learning (ML) training and inference, and HPC.
General purpose Family
These machines provide a good balance of price and performance, and are suitable for a wide variety of common workloads. You can choose from four general purpose machine types:
For flexibility, general purpose machines come as predefined (with a preset number of vCPUs and memory), or can be configured as custom machine types. Custom machine types allow you to independently configure CPU and memory to find the right balance for your application, so you only pay for what you need.
E2 offers the lowest total cost of ownership (TCO) on Google Cloud with up to 31% savings compared to the first generation N1. E2 VMs run on a variety of CPU platforms (across Intel and AMD), and offer up to 32 vCPUs and 128GB of memory per node.
N2 introduced the 2nd Generation Intel Xeon Scalable Processors (Cascade Lake) to Compute Engine’s general purpose family. Compared with first-generation N1 machines, N2s offer a greater than 20% price-performance improvement for many workloads and support up to 25% more memory per vCPU.
N2D VMs are built on the latest 2nd Gen AMD EPYC (Rome) CPUs, and support the highest core count and memory of any general-purpose Compute Engine VM. N2D VMs are designed to provide you with the same features as N2 VMs including local SSD, custom machine types, and transparent maintenance through live migration.
N1s are first-generation general purpose VMs and offer up to 96 vCPUs and 624GB of memory . For most use cases we recommend choosing one of the second-generation general purpose machine types above. For GPU workloads, N1 supports a variety of NVIDIA GPUs.
Compute-optimized machines focus on the highest performance per core and the most consistent performance to support real-time applications performance needs. Based on 2nd Generation Intel Xeon Scalable Processors (Cascade Lake), and offering up to 3.8 GHz sustained all-core turbo, these VMs are optimized for compute-intensive workloads such as HPC, gaming (AAA game servers), and high-performance web serving. Compute-optimized machines produce a greater than 40% performance improvement compared to the previous generation N1 and offer higher performance per thread and isolation for latency-sensitive workloads. Compute-optimized VMs come in different shapes ranging from 4 to 60 vCPUs, and offer up to 240 GB of memory. You can choose to attach up to 3TB of local storage to these VMs for applications that require higher storage performance.
Memory-optimized machine types offer the highest memory in our VM family. With VMs that range in size from 1TB to 12TBs of memory, and offer up to 416 vCPUs, these VMs offer the most compute and memory resources of any Compute Engine VM offering. They are well suited for large in-memory databases such as SAP HANA, as well as in-memory data analytics workloads. M1 VMs offer up to 4TB of memory, while M2 VMs support up to 12TB of memory.
M1 and M2 VM types also offer the lowest cost per GB of memory on Compute Engine, making them a great choice for workloads that utilize higher memory configurations with low compute resources requirements. For workloads such as Microsoft SQL Server and similar databases, these VMs allow you to provision only the compute resources you need as you leverage larger memory configurations.
M1 and M2 VMs offer up to 30% sustained use discounts and are also eligible for committed use discounts, bringing additional savings of up to >60% for three-year commitments.
The accelerator-optimized family is the latest addition to the Compute Engine portfolio. A2s are currently available via our alpha program, with public availability expected later this year. The A2 is based on the latest NVIDIA Ampere A100 GPU and was designed to meet today’s most demanding applications such as machine learning and HPC. A2 VMs were the first NVIDIA Ampere A100 Tensor Core GPU-based offering on a public cloud.
Product Manager, Compute Engine
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