# Legacy N1 Machine Types Where E2 Would Be Cheaper Canonical: https://www.pointfive.co/efficiency-hub/inefficiencies/legacy-n1-machine-types-where-e2-would-be-cheaper N1 is Compute Engine's first-generation general-purpose series, running on Intel platforms from Ivy Bridge to Skylake. By: PointFive Updated: 2026-09-28 [Cloud Efficiency Hub](https://www.pointfive.co/efficiency-hub) The short version N1 is Compute Engine's first-generation general-purpose series, running on Intel platforms from Ivy Bridge to Skylake. PointFive Research Cloud cost research at PointFive GCP service [GCP Compute Engine](https://www.pointfive.co/efficiency-hub/cloud-services/gcp-compute-engine) Category [Compute](https://www.pointfive.co/efficiency-hub/service-category/compute) Reference CER-0469 Type Outdated Version ## Explanation Why the waste happens and who it affects. Many long-lived VMs, instance templates and GKE node pools still use n1-\* machine types because they were created years ago or copied from old templates. Google describes E2 as the cost-optimized series with the lowest on-demand pricing across general-purpose machine types, and its GKE cost guidance states that E2 machine types offer 31% savings compared to N1. The comparison needs care. The 31% is a list-price comparison: N1 receives sustained use discounts of up to 30% for VMs that run most of the month, while E2 receives none, so a 24/7 on-demand N1 VM can cost about the same as its E2 equivalent. The gap is real where sustained use discounts do not apply: VMs covered by committed use discounts (CUDs and SUDs cannot combine), VMs that run only part of the month, and fleets being re-committed. In those cases staying on N1 pays more for older hardware. ## Billing model The pricing dimensions that drive this cost. Prices are per vCPU-hour and GiB-hour and vary by region. N1 on-demand Billed per second at N1 rates, with automatic sustained use discounts of up to 30% for resources used more than 25% of a month E2 on-demand Lower list price than N1 for comparable shapes, with no sustained use discounts Committed use discounts Resource-based and flexible CUDs apply to both series; SUDs do not apply to usage already covered by CUDs, so under commitments the lower E2 base price carries through Series-specific commitments Resource-based commitments are tied to a machine series, so N1 commitments do not cover E2 usage ## How to detect 4 checks to find it in your estate. - Inventory VMs, instance templates, MIGs and GKE node pools that use n1-\* machine types - For each, check how it is billed: covered by a CUD, running part of the month, or running on-demand all month with the full sustained use discount; the first two are where E2 saves the most - Compare the net monthly price of the N1 shape (after SUD or CUD) with the equivalent E2 shape in the same region - Exclude VMs that need what E2 does not support: GPUs, Local SSDs, sole-tenant nodes, nested virtualization or more than 32 vCPUs; consider N2, N4 or other current series for those ## How to fix 4 ways to remove the waste. - Change suitable VMs to an E2 machine type: stop the VM, set the new machine type (gcloud compute instances set-machine-type), then start it; test performance, since E2 picks the processor (Intel or AMD) for you at creation - Update instance templates, MIGs and GKE node pool definitions so new capacity does not launch on N1 - Align commitment renewals with the migration: let N1 resource-based commitments expire or plan the move with flexible CUDs, which are not tied to a machine series - For performance-sensitive or larger workloads, evaluate current-generation series instead of E2 and compare price for the throughput actually delivered ## Documentation Vendor references for pricing and configuration. - [General-purpose machine family for Compute Engine docs.cloud.google.com](https://docs.cloud.google.com/compute/docs/general-purpose-machines) - [Best practices for running cost-optimized Kubernetes applications on GKE docs.cloud.google.com](https://docs.cloud.google.com/architecture/best-practices-for-running-cost-effective-kubernetes-applications-on-gke) - [Sustained use discounts docs.cloud.google.com](https://docs.cloud.google.com/compute/docs/sustained-use-discounts) - [General Purpose VM pricing cloud.google.com](https://cloud.google.com/products/compute/pricing/general-purpose) ## Related inefficiencies [Browse the library](https://www.pointfive.co/efficiency-hub) - GCP Compute Engine CER-0282 ### [Missed Use of Committed Use Discounts for Compute Engine](https://www.pointfive.co/efficiency-hub/inefficiencies/missed-use-of-committed-use-discounts-for-compute-engine) Workloads with predictable, long-running compute usage continue to run entirely on on-demand pricing instead of leveraging Committed Use Discounts. For stable environments, such as production services or continuously running batch... Compute - GCP Compute Engine CER-0089 ### [Underutilized VM Commitments Due to Architectural Drift](https://www.pointfive.co/efficiency-hub/inefficiencies/underutilized-vm-commitments-due-to-architectural-drift) VM-based Committed Use Discounts in GCP offer cost savings for predictable workloads, but they are rigid: they apply only to specified VM types, quantities, and regions. When organizations evolve their architecture - such as moving to GKE... Compute - GCP Compute Engine CER-0095 ### [Missing Scheduled Shutdown for Non-Production Compute Engine Instances](https://www.pointfive.co/efficiency-hub/inefficiencies/missing-scheduled-shutdown-for-non-production-compute-engine-instances) Development and test environments on Compute Engine are commonly provisioned and left running around the clock, even if only used during business hours. This results in wasteful spend on compute time that could be eliminated by scheduling... Compute --- Source: the public page above. Product screenshots and illustrative interfaces are examples, not live customer data.