hey everyone! today, we’re diving into google cloud platform’s virtual machines (gcp vms)—what they are, why they're useful, and some key tips to consider while creating one.

what is a GCP virtual machine?

a virtual machine (vm) on google cloud platform (gcp) is a customizable computer you can run in the cloud. it's like having a computer on demand that you can configure with specific resources like cpu, memory, and storage. these vms are part of google compute engine and offer the flexibility to handle various workloads—everything from small applications to high-demand databases.

why use gcp vms?

gcp vms provide a scalable, cost-effective way to run applications without needing physical hardware. they’re highly customizable, easily scalable, and allow you to quickly deploy and manage workloads. you only pay for the time you use them, which makes it ideal for both short-term and long-term projects. whether you’re running a website, testing software, or performing data analysis, gcp vms offer a versatile solution.

steps to create a gcp vm

before we get into tips, here’s a quick rundown of how to create a virtual machine on gcp:

go to google cloud console: open the gcp console and select compute engine from the menu.
create a new instance: click on "create instance" to start configuring your vm.
choose a machine type: select the type of machine (cpu, memory, and gpu) based on your workload needs.
select an operating system: choose the os for your vm (e.g., ubuntu, windows server, or custom images).
configure storage: add the necessary storage, and choose between ssd or standard persistent disks.
networking settings: adjust your network settings based on whether you need a public or private ip, firewall rules, and vpc configurations.
create the instance: review your configuration, then click “create” to launch your vm.

now that we’ve covered the basics, let’s talk about what to keep in mind while creating and managing vms on gcp.

key considerations when creating a gcp vm

select the right machine type
gcp offers several machine types optimized for different tasks, including:
- general-purpose: for general workloads with balanced cpu and memory.
- compute-optimized: for cpu-intensive applications like machine learning or data processing.
- memory-optimized: for applications requiring high memory, such as in-memory databases.
- gpu instances: for high-performance computing tasks like deep learning.

make sure to choose the right type for your needs to avoid overspending or under-provisioning.

consider the zone and region
the location of your vm impacts performance and latency, especially if users are located far from the vm’s region. select a region close to your target audience or team. also, be aware that certain services or machine types may not be available in every region.
choose an os and keep it updated
gcp supports many os options like ubuntu, centos, debian, windows server, and more. ensure that your os choice aligns with your application requirements. also, remember to enable automatic updates for security patches and improvements.
configure firewalls and security settings
when you create a vm, gcp allows you to set up firewall rules. only allow access to necessary ports (like http/https for web servers) and disable all unused ports. consider using gcp’s identity and access management (iam) to control who can access and manage the vm, and enable vpc service controls for additional security.
manage storage effectively
gcp offers different types of persistent disks (standard, ssd, balanced). select the storage type based on your performance and budget needs. remember to set up automated backups or snapshots to protect your data. you can also attach additional disks to your vm for scalable storage.
set up auto-scaling and load balancing
if you expect fluctuating traffic, you can set up auto-scaling to add or remove vms automatically. combining this with load balancing ensures that traffic is evenly distributed across your vms, improving performance during peak times and reducing costs when demand is low.
enable monitoring and logging
gcp offers monitoring and logging tools to track your vm’s performance, usage, and health. by enabling these, you can keep an eye on resource utilization, receive alerts for unusual behavior, and optimize your configuration to save costs and improve efficiency.
optimize costs with preemptible vms
preemptible vms are temporary and significantly cheaper than standard vms. they’re great for batch processing or other non-critical tasks. however, be aware that google may shut down preemptible vms at any time, so avoid using them for long-running or essential applications.
use gcp’s identity-aware proxy (iap)
for secure access, consider using gcp’s identity-aware proxy. iap controls access to your vm without requiring a public ip, providing an additional security layer, especially for applications that should only be accessed by certain users.
schedule maintenance windows
gcp occasionally performs maintenance on vms, which may cause brief interruptions. plan for maintenance windows to prevent unexpected downtime and set up automated restarts to resume your services quickly.

creating your first gcp vm: a quick example

to get started with a basic setup, let’s create a gcp vm:

go to gcp console > compute engine > vm instances.
click on "create instance."
name your instance, select the machine type, os, and disk options.
configure any networking or firewall settings you need.
click "create," and your instance will be up and running within minutes!

closing note

gcp vms offer incredible flexibility and scalability, making them ideal for all types of applications. by understanding key factors like machine types, regions, and security settings, you can ensure a secure and optimized setup that fits your project’s needs. take time to experiment with different configurations, explore additional gcp features like load balancing and monitoring, and remember that choosing the right setup is essential for performance and cost efficiency.

with a bit of practice and planning, gcp vms can become a powerful tool.

see ya, happy building :)

always eager to learn and connect with like-minded individuals. happy to connect with you all here!

getting started with GCP virtual machines: things you need to know