EC2 Equivalent in Google Cloud
Google Compute Engine is the direct ec2 equivalent in google cloud. It lets you spin up and run virtual machines on Google servers. Teams often set up these machines by copying their old AWS patterns. They create a few broad roles and share SSH keys across the team. When roles are too broad, any user can change disks or network rules. A single leaked key can expose every virtual machine in the project. How the ec2 equivalent in google cloud works Compute Engine runs virtual machines inside a
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Google Compute Engine is the direct ec2 equivalent in google cloud. It lets you spin up and run virtual machines on Google servers. Teams often set up these machines by copying their old AWS patterns. They create a few broad roles and share SSH keys across the team. When roles are too broad, any user can change disks or network rules. A single leaked key can expose every virtual machine in the project.
How the ec2 equivalent in google cloud works
Compute Engine runs virtual machines inside a Google Cloud project. In AWS, you pick an instance type and an Amazon Machine Image. In Google Cloud, you pick a machine type and a boot disk image. Both services let you choose the CPU count and memory size. You also attach block storage disks to hold your app data.
Networking works in a slightly different way between the two clouds. AWS ties a subnet to a single availability zone inside one region. Google Cloud lets a virtual network span across many regions at once. Subnets in Google Cloud cover an entire region instead of one zone. Firewall rules attach to network tags or service accounts on the machines.
Identity and login setups also differ between the two cloud providers. AWS relies on key pairs or instance profiles to grant machine access. Google Cloud can manage SSH keys through project metadata or OS Login. OS Login links a Linux user account to a Google identity. Admins assign roles at the project, folder, or machine level. A service account gives the virtual machine its own identity for API calls.
Managing machine roles and login boundaries
Teams moving from AWS often recreate their old security groups and roles. They attach a default service account to every new virtual machine. This default account often has broad project editor permissions by mistake. If an attacker enters one machine, they can reach other cloud services. You should create custom service accounts with minimal roles for each app.
Human logins need the same level of care during daily work. OS Login helps by tying SSH access to cloud identity roles. You can require two-factor checks before a user opens an SSH connection. You can also remove a user from the cloud team to cut access. The cloud platform then removes their public keys from the machines.
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What native cloud controls solve and what they miss
Native identity roles solve the problem of who can reach a machine. Firewall rules and private networks stop outside traffic from hitting open ports. OS Login and IAM roles check the user before the shell starts. They also log the moment a user opens a new SSH connection.
Still, native cloud roles leave an operational gap after login finishes. IAM decides who logs in, not what commands run inside the shell. Once a developer has root access, they can run any command. They can read local app files or dump data from local disks. Standard cloud logs do not show every command or database query run. They also cannot mask sensitive fields like emails, phone numbers, or card numbers. Teams need controls that check actions in flight, not just at login.
Add runtime guardrails and masking beside your databases and APIs
Login rules, role grants, and CI checks govern who connects to your stack. Yet any allowed script, engineer, or AI agent still runs commands with the full scope of its role. For workloads on Postgres, MySQL, SQL Server, MongoDB, ClickHouse, Kubernetes, SSH, or internal HTTP services, hoop.dev sits beside the service as an open-source proxy, a sidecar for your database or API.
Before a query runs, hoop.dev guardrails check the statement against your rules. An AI Analyzer you configure can score intent or hold risky calls for human review. Next, hoop.dev data masking rewrites sensitive fields in responses, and each verdict is logged per listener. Explore the MIT-licensed project on GitHub.
Frequently asked questions
How do AWS instance types map to Google Compute Engine?
Both clouds group machines by general purpose, memory, and CPU needs. You pick a machine series in Google Cloud that matches your workload size. You can also build a custom machine with exact CPU and RAM counts.
What replaces AWS security groups in Google Cloud?
Google Cloud uses VPC firewall rules instead of AWS security groups. You apply these rules to specific machines using target tags or service accounts. This lets you control traffic without building complex subnet layouts.
How should teams handle SSH keys on Compute Engine?
Teams should turn on the OS Login feature instead of pasting static keys. OS Login ties SSH access directly to your cloud user roles. When someone leaves the team, revoking their cloud role blocks their SSH access.