EC2 Equivalent in GCP
Google Compute Engine is the direct ec2 equivalent in gcp for running virtual machines. You set up these machines by picking a machine type, disk image, and network. Teams often copy their old cloud habits when they move to Google Cloud. They assign broad project roles to get machines running fast. When roles are too broad, one person or app can change every server. How the ec2 equivalent in gcp works Amazon EC2 and Google Compute Engine both run virtual servers in the cloud. Both tools let y
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Google Compute Engine is the direct ec2 equivalent in gcp for running virtual machines. You set up these machines by picking a machine type, disk image, and network. Teams often copy their old cloud habits when they move to Google Cloud. They assign broad project roles to get machines running fast. When roles are too broad, one person or app can change every server.
How the ec2 equivalent in gcp works
Amazon EC2 and Google Compute Engine both run virtual servers in the cloud. Both tools let you pick processor counts, memory sizes, and Linux or Windows images. The main difference sits in how the two clouds group resources and permissions. In Amazon Web Services, resources live inside accounts and virtual private clouds. In Google Cloud, every virtual machine lives inside a project. A project groups your servers, disks, networks, and team permissions in one place.
Networking also works in a slightly different way here. In Google Cloud, a virtual network spans all regions by default. Subnets stay regional, so machines in different regions talk over private links without extra setup. Firewall rules attach to network tags or service accounts instead of security groups. You tag a machine, and the matching firewall rule opens the network port.
Machine login also uses a distinct flow. Instead of downloading static key files, teams use cloud identity roles to log in. Google Cloud can push short SSH keys to the machine metadata when a user connects. Each virtual machine can also hold a service account. This account gives the running app a role to read storage buckets or databases.
What native cloud roles solve and what they miss
Native project roles and OS Login solve the problem of sharing static SSH key files. You can grant a team member a role that lets them log into servers. When someone leaves the team, you remove their cloud role. They lose server login rights right away.
Service accounts also stop teams from saving database keys inside app files. Still, teams often pick the default compute service account during setup. That default role often has editor rights across the whole project. Anyone who logs into that machine inherits those wide project permissions.
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Even with strict cloud roles, a big gap remains during live work. Cloud roles only decide who can open a shell or connect to a database. Once a session starts, the cloud role does not check what commands run. An engineer with valid login rights can still run a bad command by mistake. They can read raw tables with user emails, phone numbers, or card numbers. Cloud audit logs show who logged into the machine, not which shell commands ran.
How to map EC2 habits to Google Cloud safely
When you move workloads, translate each part of your old setup with care. Map your old instance types to matching Google Cloud machine families based on workload needs. Replace security groups with firewall rules that target specific service accounts, not broad network ranges. Create a fresh, custom service account for each app tier. Give that account only the exact roles it needs to read its own data. Turn off the default compute service account so nobody uses it by accident.
Next, separate machine login rights from admin rights. Give developers standard user roles on the virtual machines instead of root access. Route private machine traffic through internal tunnels so servers do not need public IP addresses. Still, network tunnels and cloud roles only guard the front door. Teams still need a way to inspect individual commands and mask sensitive fields in results.
Govern statements and responses across databases and APIs
Good config and scoped roles are needed setup. They do not check single queries in flight or mask sensitive fields in returned rows. Across Postgres, MySQL, SQL Server, MongoDB, ClickHouse, Kubernetes APIs, SSH, and internal HTTP endpoints, hoop.dev sits inline in the protocol beside each supported service as an open-source proxy, a sidecar for your database or API. For every query or command an AI agent or engineer runs against production, hoop.dev decides to pass, mask, block, or hold it for human approval.
First, hoop.dev guardrails block banned queries before they run or hold risky ones for review, and hoop.dev data masking rewrites matched sensitive values in responses in memory. Furthermore, hoop.dev holds SOC 2 Type II and is open source on GitHub.
Frequently asked questions
What is the exact match for EC2 security groups in Google Cloud?
Google Cloud uses VPC firewall rules instead of security groups. You apply these rules to specific machines using network tags or target service accounts.
How do I handle SSH keys on Google Compute Engine?
You do not need to manage static key files by hand. Enable the OS Login feature to tie Linux user accounts directly to cloud identity roles.
What replaces an EC2 instance profile in Google Cloud?
A Google Cloud service account replaces the instance profile. You attach the service account to the virtual machine and grant it specific project roles.