How to Create a VM on Google Cloud Platform: 10 Simple Steps.

preemptible Vms

How to create a VM on GCP is one of the basics of the Google Cloud platform. Virtual machines (VMs) play a crucial role in delivering scalable and flexible computing resources in cloud infrastructure.  A Virtual machine (VM) is created through the compute Engine. It consists of a virtual CPU, some amount of memory, disk surge, and an IP address

Basically, there are ways on how to create a VM through the compute Engine on the Google Cloud Platform. And also through the command-line interface including CloudShell, for example: $ gcloud compute instance create (instance-name). You can also create the VM from REST API with many VM options like project, region, zone, subnetwork, machine type, Disk options, IP region. The main components of a Virtual Machine (VM) are;
1. CPU
2. Memory
3. Disk
4. Network

Virtual machines are defined based on these main components. Virtual Machines are also defined according to machine type. First, is the Predefined machine Types, This is the ratio of GB of memory per CPU. Predefined machine types include;

  • Standard
  • High Memory
  • High-CPU
  • Memory Optimize
  • Computer Optimize
  • Shared-Core
    The second is the Custom Machine types. By choosing Custom machine type you will have to specify the amount of memory and number of vCPUs. Each virtual machine comes in various sizes and specifications allowing cloud users to choose the best VM that matches the workload, speed, compute intensiveness, storage, capacity, and networking capabilities. For instance, VMs offer different numbers of virtual CPUs (vCPUs), which determine the processing power allocated to the VM. This can range from single-core VMs for lightweight tasks to multi-core VMs for resource-intensive applications. The Smallest type is the micro VM which shares a CPU with other VMs

How to Create a VM on GCP. 10 simple steps.

These are 10 simple steps on how to create a VM on the GCP.

  1. Step One: Navigate the GCP Menu on the left-hand side of the Google Platform. you can access the GCP from here.
  2. Step Two: Scroll down the menu to Compute Engine and place your cursor.
  3. Step Three: Click on the VM Instances on the dialogue box that pops up on the right
  4. Step Four: Click ‘Create’
  5. Step Five: Specify the following values, and leave the remaining settings as their default
    Name – (Give your VM a name)
    Region – (Select a region eg US-Central1)
    Zone – (Select a zone eg US-Central1-a)
    Choose a Machine type( Note that cost is adjusted based on region and machine type selected)
    – Boot Disk – (Select a boot image eg Debian GNU/Linux9(Stretch)
    – Identity and API – (Click on Access, then Access Scopes to set Access for each API)
    Storage – (Select – read-write)
  6. Step Six: Click Management, Security, Disks, Networking
  7. Step Seven: Click on Disks, then on ‘Add new Disk’ (to add more disks to be used eg for game storage if there is a need)
  8. Step Eight: Specify the following values and leave the remaining settings as their default
    – Name – (name your new disk)
    – Disk type – (select a disk type eg SSD Persistent Disk)
    – Source type – ( select ‘None'(Blank disk)
    – Size(GB) – (select the size in GB eg 50GB
    – Encryption – (Choose encryption to secure your data eg Google-Managed Key)
    Click done – ( this action will create the disk and automatically attach it to the VM when the VM is created)
  9. Step Nine: Click on ‘Network details interface’ to choose your network.
  10. Step Ten: Click ‘Done’ and wait a few minutes for your VM to be created. Once it is created you will see a notification that your VM has been successfully created

Conclusion

Congratulations, on learning how to create a VM on GCP. This will help you in working with the Google Cloud infrastructures as a Virtual machine is a core cloud vital. This will empower you to adapt effectively to the rapidly changing demands of cloud technology. Whether you are running standard applications, diving into complex simulations, or processing vast amounts of data, learning how to create virtual machines in the cloud will boost your confidence in working with the GCP on your cloud computing journey.

GCP Routes and Firewall Rules: A Simple Guide to Cloud Security.

GCP Routes

GCP Routes and Firewall Rules are two fundamental components that play a pivotal role in establishing secure and efficient communication within GCP. To the cloud newbies, these two concepts might sound like complex technical jargon, but as much as possible I will shed light on their significance through straightforward explanations and relatable use cases.

What are GCP Routes?

Let’s start by understanding the concept of GCP Route. Imagine you want to embark on a road trip across a region of the country. Basically, before you start driving, you need to know which highways and roads will take you from your point of origin to your destination. In the same manner, GCP routes serve as the virtual pathways that guide network traffic from source to destination.

In GCP, a route is a mapping of an IP range to a destination. It determines how data packets travel between different virtual machines (VMs), networks, and even across regions. Every GCP network has Routes that let instances in a network send traffic directly to each other. A network also has a default route that directs packets to destinations that are outside the network. And firewall rules that must also allow the packet traffic. In a nutshell, GCP Routes define the paths that network traffic should follow, allowing seamless communication within the GCP ecosystem. Think of routes as the GPS navigation system for your cloud infrastructure.

GCP Routes Use Case: Multi-Region Deployment

Routes map traffic to destination networks like traffic egressing a VM are forwarded to the most specific route. GCP Routes are created when a subnet is created and enable VMs on the same network to communicate. Route destination is in CIDR notation, and traffic is only delivered to the destination if it matches a firewall rule. A route applies to an instance if the network and instance tag match, and if there are no instance tags specified they are routed to all instances in that network. Let’s say you’re running a web application that needs to be highly available across multiple regions. You have instances of your application hosted in both the US and Europe. To ensure a smooth user experience, you can create custom routes that direct traffic to the closest available instance based on the user’s location. This not only improves latency but also enhances overall application performance.

GCP Routes

Understanding Firewall Rules

GCP Firewall rules act as the gatekeepers that control incoming and outgoing traffic. Just as a physical firewall prevents unauthorized access to a building, GCP firewall rules prevent unauthorized or potentially harmful network traffic from entering or leaving your virtual infrastructure. Firewall rules protect your VM instances from approved connections. Connections are allowed or denied at the instance level. It implies denying all ingress and allowing all egress.

GCP’s firewall rules are highly configurable and can be applied at various levels – project-wide, network-wide, or even on a specific VM instance. These rules determine which IP addresses, protocols, and ports are allowed or blocked, creating a secure barrier around your virtual assets.

GCP firewall rules are stateful. Firewall rules imply that if a connection is allowed between a source and a target, or a target and destination then all subsequent traffic in either direction will be allowed. Firewall rules allow bi-directional traffic. A firewall rule consists of the following parameters;
1). Direction of the rules
2) Source of the direction
3) Protocol end-point
4) Action of the rule
5) Priority
6) Rule Assignment

firewall rules

firewall rules

Use Case: Application Security

Consider you’re running a database server on a VM instance within GCP. To safeguard sensitive data, you can configure firewall rules that only allow traffic from specific IP addresses or a defined range. This prevents unauthorized access attempts and ensures that only authorized users or applications can communicate with your database server.

GCP Routes and Firewall Rules Synergy

To understand the full picture, let’s combine routes and firewall rules in a practical scenario. Imagine you’re deploying a cloud-based application that consists of multiple tiers: a web frontend, an application backend, and a database.
1. Web Frontend: This is the point where user requests are received. You create firewall rules to allow HTTP and HTTPS traffic from the internet while blocking other unnecessary traffic. The routes ensure that the incoming requests are correctly directed to the appropriate instances of your web frontend.
2. Application Backend: The frontend communicates with the backend to process user requests. Firewall rules restrict direct external access to the backend, only allowing traffic from the frontend. Routes guide traffic from the frontend instances to the backend instances seamlessly.
3. Database: The application backend interacts with the database to retrieve and store data. Firewall rules permit only the backend instances to communicate with the database instances. Routes ensure that the database requests are efficiently routed to the respective database instances.

By combining routes and firewall rules, you’ve established a secure and efficient communication framework for your application within GCP.

Best Practices for Implementing Routes and Firewall Rules

While understanding the concepts is essential, implementing them effectively is equally crucial. When working with GCP routes and firewall rules, it is important you follow some of the best practices available. Some of the best practices include;
1. Apply the Least Privilege Principle: Apply the principle of least privilege when configuring firewall rules. Only allow the minimum necessary traffic to reduce the attack surface.
2. Logging and Monitoring: Enable logging and monitoring for both routes and firewall rules. This helps you keep track of traffic patterns, identify potential security threats, and troubleshoot any issues.
3. Periodic Review: Routinely review your routes and firewall rules to ensure they’re up to date with your application’s needs. Remove any rules or routes that are no longer necessary to maintain a tidy and secure setup.
4. Documentation: Maintain clear and organized documentation of your routes and firewall rules. This documentation will be invaluable for both your team and any future administrators.

Conclusion

GCP routes and firewall rules are strategic cloud services that facilitate secure and efficient communication between your virtual resources. Understanding their roles and implications can empower you to architect robust and reliable cloud solutions. Just as a well-planned road trip relies on accurate directions and secure paths, your cloud journey within GCP depends on the strategic implementation of routes and firewall rules. So, armed with this newfound knowledge, you’re now ready to navigate the cloud with confidence and security.

Compute Engine: 1 Reliable Backbone of Google Cloud Architecture

Google Cloud Compute Engine

Compute Engine is a powerful Infrastructure as a Service (IaaS) solution at the core of Google Cloud architecture that allows you to run VM on-demand in the cloud. The Compute Engine is a core vital service within the Google Cloud ecosystem, providing virtual machines (VMs) that enable users to run workloads in a scalable and customizable environment.

This service offers a highly flexible approach to provisioning computing resources. It allows users to select the number of CPU cores, memory, and storage based on their specific needs. The service supports a variety of operating systems and offers pre-configured images to speed up the setup process. This level of flexibility and choice empowers users to configure virtual machines that align precisely with their computational needs.

Google Cloud Architecture

The Cloud Compute Engine is a powerful tool underlying Google Cloud architecture. This service is bolstered by Google’s extensive experience in managing large-scale data centers and distributed systems. Using the Xen hypervisor virtualization ensures isolation and security for each VM. Google’s high-speed network backbone further guarantees low-latency communication between VM instances, thus, making it suitable for data-intensive and latency-sensitive applications. Google’s compute engine underlying architecture forms the basis for creating virtual machines that deliver consistent performance and reliability in cloud computing.

Benefits of Google Cloud Compute Engine

  1. Scalability:
    Scalability is a vital attribute of cloud computing, and Compute Engine performs optimally in this regard. Users can effortlessly scale their computing resources up or down based on demand, ensuring optimal performance during peak times while avoiding unnecessary costs during lulls.
  2. Ability to Customize:
    Compute Engine enables users to define VMs with precise specifications, from CPU and memory to storage and GPU. This customization allows for the creation of tailored environments for various workloads, from web hosting to complex scientific simulations.
  3. It is Cost-Efficient:
    The pay-as-you-go pricing model of Compute Engine ensures cost-efficiency. Users are billed only for the resources they use, eliminating the need for large upfront investments in hardware.
  4. It is Reliable:
    Leveraging Google’s global data center infrastructure, Compute Engine offers robust reliability through data replication and automatic backup. This is critical for businesses requiring high availability.
  5. Security:
    Security is a paramount concern in cloud computing. Hence, it provides multiple layers of security, including data encryption at rest and in transit, secure boot, and firewall controls, ensuring the integrity and confidentiality of data.
  6. Preemptible VMs:
    For cost-sensitive workloads, preemptible VMs offer a compelling solution. These instances are available at a significantly reduced cost but can be preempted by Google with short notice. They are suitable for fault-tolerant tasks that can be interrupted and resumed.
  7. Elastic Load Balancing:
    Compute Engine integrates seamlessly with Google’s load-balancing service, distributing incoming traffic across multiple VM instances to ensure high availability and fault tolerance.
  8. Hybrid Connectivity:
    Businesses with existing on-premises infrastructure can establish hybrid connections by utilizing its Virtual Private Cloud (VPC) network and VPN solution

Academic Significance

However, beyond its evident commercial applications, Google Cloud Compute Engine holds substantial implications for academia and research endeavors:

  1. Scientific Simulations: Compute-intensive scientific simulations, such as climate modeling or particle physics simulations, can be performed efficiently on the high-performance VMs offered by Compute Engine.
  2. Big Data Analysis: Researchers dealing with large datasets can harness the scalability of Compute Engine to process and analyze data, enabling insights that were previously unattainable.
  3. Machine Learning and AI:
    Training complex machine learning models requires substantial computational resources. Compute Engine’s customizable VMs equipped with GPUs can accelerate the training process, fostering breakthroughs in AI research.
  4. Collaboration:
    Compute Engine facilitates collaboration among researchers by providing a unified platform where computational resources can be shared, leading to accelerated knowledge exchange and innovation.

Conclusion

Google Cloud Compute Engine is a monumental testament to the evolution of cloud computing. Its flexible and scalable nature, coupled with the reliability and security offered by Google’s infrastructure, makes it a formidable choice for businesses seeking to optimize their operations. Moreover, it has the potential to revolutionize academic and research landscapes reaffirming its significance beyond the commercial realm. As cloud computing continues to rapidly evolve, Compute Engine is poised to play an important role in shaping the future of computing, demonstrating the remarkable synergy between technological innovation and academic exploration.

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