GCP.Blue

Category: Associate Cloud Engineer

For content relevant to the Associate Cloud Engineer exam.

  • Differentiating Load Balancing Options

    Google Cloud Platform (GCP) offers various load balancing options to distribute traffic across your resources efficiently. To begin differentiating these options, consider the following key aspects:

    1. Traffic Type:
    • HTTP(S) Load Balancing: Ideal for web applications and services using HTTP or HTTPS protocols. It operates at Layer 7 and offers features like content-based routing, session affinity, and URL-based routing.
    • TCP/SSL Load Balancing: Suitable for applications using TCP or SSL protocols, such as databases or custom TCP-based services. It operates at Layer 4 and primarily focuses on balancing TCP connections.
    • Network Load Balancing: Used for extreme performance and scalability scenarios with TCP, UDP, or ESP protocols. It operates at Layer 4 and is typically used for load balancing high-traffic services like gaming servers or media streaming.
    1. Global vs. Regional:
    • Global Load Balancing: Distributes traffic across multiple regions, providing high availability and fault tolerance. It is ideal for applications with a global user base.
    • Regional Load Balancing: Distributes traffic within a specific region, offering lower latency for users within that region. It is suitable for applications targeting users in a particular geographical area.
    1. External vs. Internal:
    • External Load Balancing: Distributes traffic from the internet to your GCP resources. It is used for public-facing applications and services.
    • Internal Load Balancing: Distributes traffic within your Virtual Private Cloud (VPC) network. It is used for load balancing internal services or applications.
    1. Load Balancer Features:
    • Session Affinity: Maintains user sessions on the same backend instance for a consistent user experience.
    • Health Checks: Monitors the health of backend instances and automatically removes unhealthy instances from the load balancer pool.
    • Content-based Routing: Routes traffic based on specific content like HTTP headers, cookies, or URL paths.
    • SSL/TLS Offloading: Offloads SSL/TLS decryption and encryption to the load balancer, reducing the load on backend instances.
    • WebSockets Support: Supports WebSocket connections for real-time communication applications.
    • Logging and Monitoring: Provides detailed logs and metrics for monitoring and troubleshooting load balancer performance.
    • Integration with other GCP services: Integrates with other GCP services like Cloud CDN, Cloud Armor, and Cloud Monitoring for enhanced functionality.

    To start differentiating load balancing options in GCP, you can explore the following resources:

  • Assessing Compute Quotas and Requesting Increases

    When you create a new Google Cloud project, it comes with default quotas that are designed to prevent accidental overuse of resources. However, as your project grows and your resource usage increases, you may find that you need to request additional compute quotas to accommodate your workload.

    To assess your current compute quotas, navigate to the Cloud Console and select your project. From the left-hand menu, click on “IAM & admin” and then select “Quotas”. Here, you can view the current quotas for each Google Cloud service in your project.

    If you find that you need to request additional compute quotas, you can do so by submitting a request through the Cloud Console. Navigate to the “IAM & admin” menu, select “Quotas”, and then click the “Edit Quotas” button. Select the service for which you want to request additional quota, and then click the “Edit Quotas” button again.

    In the quota edit page, you can specify the desired quota limit and provide a justification for the increase. Google Cloud support will then review your request and respond within a few business days.

    It’s important to keep in mind that quota increases are not guaranteed and may depend on factors such as availability of resources and your project’s usage history. It’s also a good practice to regularly monitor your compute usage and adjust your quotas accordingly to avoid unexpected charges and interruptions to your services.

    By effectively managing your compute quotas, you can ensure that your Google Cloud project has the necessary resources to support your workload and avoid potential issues related to resource limitations.

  • Generating/Uploading a Custom SSH Key for Instances

    Secure Shell (SSH) keys offer a robust mechanism for authenticating remote access to your Compute Engine instances. Instead of relying on traditional passwords, SSH keys employ a pair of cryptographic keys: a private key (stored securely on your local machine) and a public key (uploaded to your instance).

    To ensure seamless and secure connections, let’s walk through the steps of generating and uploading a custom SSH key:

    1. Key Generation (Local Machine):
    • Open your terminal or command prompt.
    • Use the ssh-keygen command:
    ssh-keygen -t rsa -b 4096 -C "[email protected]"
    • You’ll be prompted for a file to save the key. If you don’t specify a name, the default is typically ~/.ssh/id_rsa (private key) and ~/.ssh/id_rsa.pub (public key).
    • Optionally, you can set a passphrase for added security.
    1. Upload Public Key (Google Cloud Console):
    • Navigate to the Compute Engine > Metadata section.
    • Click SSH Keys > Edit.
    • Click Add Item.
    • Open your public key file (usually with the .pub extension) in a text editor.
    • Copy the entire contents of the file, including the “ssh-rsa” prefix and your email comment at the end.
    • Paste the key into the text box on the GCP console.
    • Click Save.
    1. Connect via SSH:
    • From your terminal, you can now connect to your instance using the following command, replacing [USERNAME] with your username and [EXTERNAL_IP] with the external IP of your instance:
    ssh [USERNAME]@[EXTERNAL_IP]
    • If you set a passphrase during key generation, you’ll be prompted to enter it.

    Best Practices

    • Safeguard your private key. It’s the equivalent of a password and should never be shared.
    • If you lose your private key, you’ll lose access to any instances associated with it.
    • For multiple users, each should have their own unique SSH key pair.
    • Regularly review and rotate your SSH keys for enhanced security.

    By diligently following these steps and adhering to best practices, you’ll fortify your Compute Engine instances with robust SSH key authentication, ensuring a secure and efficient workflow.

  • Creating an Autoscaled Managed Instance Group Using an Instance Template

    What is an Autoscaled Managed Instance Group?

    An autoscaled MIG is a collection of identical virtual machine (VM) instances that can automatically adjust in size based on demand. This dynamic scaling ensures your applications have the necessary resources during peak traffic while optimizing costs during lulls.

    Prerequisites

    1. Instance Template: Create an instance template that defines the properties of the VMs you want in your MIG (e.g., machine type, boot disk, network configuration).
    2. Health Check: Configure a health check to monitor the health of your instances.
    3. Load Balancer (Optional): If distributing traffic, set up a load balancer.

    Step 1: Create the Managed Instance Group

    • In the GCP Console, go to “Compute Engine” > “Instance groups.”
    • Click “Create instance group.”
    • Choose “Managed instance group” and select your desired zone.
    • Select the “Instance template” you created and specify the initial number of instances.
    • Configure autoscaling:
      • Select “On” to enable autoscaling.
      • Set minimum and maximum instance counts.
      • Define scaling policies based on metrics like CPU utilization or load balancer traffic.
    • Set up autohealing if desired, which will automatically recreate unhealthy instances.
    • Click “Create.”

    Step 2: Verify and Monitor

    • After creation, your MIG will start provisioning instances.
    • Observe the “Instance groups” page to track the group’s status.
    • Monitor the autoscaling logs to see how the group scales up or down.
    • Use the load balancer’s monitoring tools to observe how traffic is distributed (if applicable).

    Example Using the gcloud Tool

    # Create the MIG
gcloud compute instance-groups managed create my-mig \
    --template=my-template \
    --base-instance-name=my-instance \
    --size=2 \
    --zone=us-central1-a

# Set up autoscaling
gcloud compute instance-groups managed set-autoscaling my-mig \
    --max-num-replicas=10 \
    --min-num-replicas=2 \
    --target-cpu-utilization=0.75 \
    --zone=us-central1-a

    Important Considerations

    • Choose the right instance template to match your workload requirements.
    • Carefully consider the autoscaling parameters (min/max instances, metrics, and thresholds) to balance cost and performance.
    • Regularly review logs and monitor metrics to optimize your MIG configuration.

    By following these steps, you can effortlessly create and manage autoscaled instance groups, allowing your applications to adapt to changing demands while maintaining efficiency and cost-effectiveness.

  • Launching a Compute Instance Using the Google Cloud Console and Cloud SDK (gcloud)

    Google Cloud Platform (GCP) offers two primary methods for launching Compute Engine virtual machines (VMs): the Google Cloud Console (web interface) and the Cloud SDK (gcloud command-line tool). This guide demonstrates a hybrid approach, leveraging both tools for streamlined and customizable instance deployment.

    Prerequisites

    1. Active GCP Project: Ensure you have an active Google Cloud Platform project.
    2. SSH Key Pair:
      • If needed, generate an SSH key pair on your local machine using ssh-keygen.
      • Add the public key to your project’s metadata:
        • In the Cloud Console, navigate to Compute Engine > Metadata > SSH Keys.
        • Click “Edit,” then “Add Item,” and paste your public key.
    3. Firewall Rule: Configure a firewall rule permitting ingress SSH traffic (port 22) from your authorized IP address(es).

    Step 1: Initial Configuration (Google Cloud Console)

    1. Open the Cloud Console and navigate to Compute Engine > VM instances.

    2. Click Create Instance.

    3. Provide the following details:

      • Name: A descriptive name for your instance.
      • Region/Zone: The desired geographical location for your instance.
      • Machine Type: Select the appropriate vCPU and memory configuration for your workload.
      • Boot Disk:
        • Image: Choose your preferred operating system (e.g., Ubuntu, Debian).
        • Boot disk type: Typically, “Standard Persistent Disk (pd-standard)” is suitable.
        • Size: Specify the desired storage capacity.
      • Firewall: Enable “Allow HTTP traffic” and “Allow HTTPS traffic” if required.
      • Networking: Adjust network settings if you have specific requirements.
      • Advanced Options (Optional):
        • Preemptibility: If cost optimization is a priority, consider preemptible instances.
        • Availability Policy: For high availability, configure a regional policy.

    4. Click “Create” to initiate instance creation.

    Step 2: Advanced Configuration (Cloud SDK)

    1. Authenticate: Ensure you are authenticated with your GCP project:

      gcloud auth login
gcloud config set project your-project-id

    2. Create Instance: Execute the following gcloud command, replacing placeholders with your specific values:

      gcloud compute instances create instance-name \
    --zone=your-zone \
    --machine-type=machine-type \
    --image=image-name \
    --image-project=image-project \
    --boot-disk-size=disk-sizeGB \
    --boot-disk-type=pd-balanced \
    --metadata-from-file=startup-script=gs://your-bucket/startup.sh \
    --tags=http-server,https-server \
    --maintenance-policy=maintenance-policy \ 
    --preemptible  # (Optional)

    3. Additional Disks (Optional): To attach additional disks, use:

      gcloud compute instances attach-disk instance-name \
   --disk=disk-name \
   --zone=your-zone

    Step 3: Connect via SSH:

    gcloud compute ssh instance-name --zone=your-zone

  • Deploying and Implementing Compute Engine Resources

    Compute Engine is Google Cloud’s infrastructure as a service (IaaS) offering, providing scalable virtual machines and other resources in the cloud.

    Launching a compute instance using the Google Cloud console and Cloud SDK (gcloud)

    One of the most fundamental tasks in Compute Engine is launching a virtual machine instance. This can be done through the Google Cloud console, a web-based interface for managing Google Cloud resources, or through the Cloud SDK, a command-line interface for Google Cloud.

    When launching an instance, you can specify key attributes like the machine type, the operating system image, the disk size and type, and the network configuration. You can also specify SSH keys to enable remote access to the instance.

    Creating an autoscaled managed instance group using an instance template

    Another key feature of Compute Engine is the ability to create managed instance groups. These are groups of virtual machine instances that are automatically scaled up or down based on demand. To create a managed instance group, you first need to create an instance template, which defines the configuration for the instances in the group.

    Once you have an instance template, you can create a managed instance group and configure autoscaling policies based on metrics like CPU utilization or load balancing traffic.

    Generating/uploading a custom SSH key for instances

    SSH keys are used to enable secure remote access to virtual machine instances in Compute Engine. By default, Compute Engine creates a new SSH key pair for each instance, but you can also specify a custom SSH key when launching an instance.

    To generate an SSH key pair, you can use tools like OpenSSH or PuTTYgen. Once you have a key pair, you can upload the public key to Compute Engine and associate it with one or more instances.

    Installing and configuring the Cloud Monitoring and Logging Agent

    Cloud Monitoring and Logging provide powerful tools for monitoring and managing Compute Engine resources. To use these tools, you first need to install and configure the Cloud Monitoring and Logging agent on your virtual machine instances.

    The agent collects metrics and logs from the instance and sends them to Cloud Monitoring and Logging for analysis and visualization. You can configure the agent to collect custom metrics and logs, as well as integrate with third-party monitoring and logging tools.

    Assessing compute quotas and requesting increases

    Finally, it’s important to be aware of the compute quotas and limits that apply to your Google Cloud project. These quotas restrict the number of resources you can create in Compute Engine, such as the number of virtual CPUs, persistent disks, and IP addresses.

    If you need to exceed these quotas, you can request a quota increase through the Google Cloud console. Be sure to provide a detailed justification for the increase, as well as any relevant performance data.

  • Configuring Cloud DNS

    Cloud DNS is a highly available and scalable DNS service that lets you publish your domain names using Google’s infrastructure. It’s built on the same infrastructure that Google uses for its own services, which means you can rely on it for your own applications and services. With Cloud DNS, you can manage your DNS zones and records using a simple web-based interface, command-line tools, or an API.

    One of the key benefits of Cloud DNS is its scalability. It can handle millions of queries per second, making it ideal for large-scale applications and services. It also has built-in redundancy, so you can be sure that your DNS records will be available even in the event of an outage.

    To configure Cloud DNS in your Google Cloud environment, follow these steps:

    • Create a Managed Zone:

      • In the GCP Console, go to the Cloud DNS section.
      • Click “Create Zone.”
      • Choose a zone type (public or private) and enter your domain name.
      • Click “Create” to create the zone and its associated NS and SOA records.

    • Add Record Sets:

      • Within your newly created zone, click “Add record set.”
      • Specify the DNS name, record type (A, AAAA, CNAME, MX, etc.), and TTL.
      • Enter the resource value (IP address, domain name, etc.) and click “Create.”
      • Repeat this for each record you need to add (e.g., A record for your website, MX records for email).

    • Update Name Servers (for Public Zones):

      • If you created a public zone, go to your domain registrar.
      • Replace the existing name servers with the ones provided by Cloud DNS for your zone.

    • Verify DNS Propagation:

      • Use a tool like dig or online DNS checkers to verify that your DNS records are propagating correctly.

    • Integrate with Other GCP Services:

      • If you’re using other GCP services like load balancers or Compute Engine instances, make sure to configure their DNS settings to point to your Cloud DNS records.

    Remember to focus on scalability, redundancy, and reliability when configuring Cloud DNS, and test your DNS configuration to ensure everything is working as expected.

  • Identifying Resource Locations in a Network for Availability

    Identifying resource locations in a network for availability while planning and configuring network resources on GCP involves understanding GCP’s geographical hierarchy, identifying resource types and their availability requirements, determining user locations, planning for high availability and disaster recovery, and using GCP tools to help with location planning.

    Here’s a breakdown of the steps involved:

    1. Understand GCP’s Geographical Hierarchy:

    • Regions: Broad geographical areas (e.g., us-central1, europe-west2). Resources within a region typically have lower latency when communicating with each other.
    • Zones: Isolated locations within a region (e.g., us-central1-a, europe-west2-b). Designed for high availability—if one zone fails, resources in another zone within the same region can take over.

    2. Identify Resource Types and Their Availability Requirements:

    • Global Resources: Available across all regions (e.g., VPC networks, Cloud DNS, some load balancers). Use these for services that need global reach.
    • Regional Resources: Specific to a single region (e.g., subnets, Compute Engine instances, regional managed instance groups, regional load balancers). Use these for services where latency is critical within a particular geographic area.
    • Zonal Resources: Tied to a specific zone (e.g., persistent disks, machine images). Leverage zonal redundancy for high availability within a region.

    3. Determine User Locations:

    • Where are your primary users located? Choose regions and zones close to them to minimize latency.
    • Are your users distributed globally? Consider using multiple regions for redundancy and better performance in different parts of the world.

    4. Plan for High Availability and Disaster Recovery:

    • Multi-Region Deployment: Deploy your application in multiple regions so that if one region becomes unavailable, your services can continue running in another region.
    • Load Balancing: Distribute traffic across multiple zones or regions to ensure that if one instance fails, others can handle the load.
    • Backups and Replication: Regularly back up your data and consider replicating it to another region for disaster recovery.

    5. Use GCP Tools to Help with Location Planning:

    • Google Cloud Console: Provides an overview of resources in different regions and zones.
    • Resource Location Map: Shows the global distribution of Google Cloud resources.
    • Latency Testing: Use tools like ping or traceroute to test network latency between different locations.

    Example Scenario:

    Let’s say you’re building a website with a global audience. You might choose to deploy your web servers in multiple regions (e.g., us-central1, europe-west2, asia-east1) using a global load balancer to distribute traffic. You could then use regional managed instance groups to ensure redundancy within each region.

    Additional Tips:

    • Consider using Google’s Network Intelligence Center for advanced network monitoring and troubleshooting.
    • Leverage Cloud CDN to cache content closer to users and improve performance.
    • Use Cloud Armor to protect your applications from DDoS attacks and other threats.

  • Cloud Filestore for Simpletons

    Cloud Filestore, provided by GCP (Google Cloud Platform), is a storage solution similar to Network File Systems (NFS). It enables you to store various types of data, much like a regular computer filesystem such as the C drive in Windows.

    By attaching Filestore instances to your VMs, you can utilize it as an external file storage device. This is particularly useful when using an instance group with multiple VMs that require access to a shared file system. For instance, if one VM within the group adds a new file to the Filestore instance hosting the file storage system, the other VMs in the group will also have visibility to the newly added file. Cloud Filestore facilitates the seamless sharing of a common file storage system among multiple computers.

    To draw a comparison, consider purchasing a USB flash drive from Amazon with a capacity of 128GB. You load data onto it, plug it into your computer, and it is recognized, allowing you to access the flash drive.

    With Filestore, the concept is similar, but imagine that when you plug the USB flash drive into a port, three other computers can simultaneously access it. It’s like having multiple computers view the contents of the same flash drive in real time. In fact, you can have any number of computers accessing the same flash drive simultaneously.

    Cloud Filestore functions similarly to a network-attached storage device (NAS), where an external hard drive or flash drive is connected to a network for multiple computers to access. In this case, Cloud Filestore serves as Google’s version of a NAS, enabling efficient sharing of files among interconnected systems.