DEV Community: Timilehin Olatunde

How to Create a Resource Group in Azure

Timilehin Olatunde — Fri, 11 Apr 2025 00:14:08 +0000

What is Azure Resource Group?
Azure Resource Groups: Organizing & Managing Cloud Resources Efficiently.

A Resource Group is a logical unit where related Azure resources—such as virtual machines, databases, storage accounts, and networking components—are grouped together.

A resource group is like a folder that helps you organize and manage cloud resources (like virtual machines, databases, network interfaces, etc.) that share a common lifecycle.

🔹 Think of it as a folder that holds all resources associated with a specific application, project, or department.
🔹 Helps with simplified management, cost tracking, and lifecycle organization.
🔹 Deleting a Resource Group also removes all resources inside it—making cleanup easier!

📦 Common Use Cases:
Grouping resources for a single application (e.g., web app + database + storage).

Managing permissions and access via Role-Based Access Control (RBAC).
Applying policies or tags to track cost, location, environment (e.g., dev/test/prod).
Facilitating resource deployment and deletion — you can delete everything in the group at once.

🛠️ Example:
Imagine you're deploying an e-commerce site:

You create a resource group called EcomRG

Inside it, you include:
A web app
Azure SQL Database
Azure Storage account
Virtual Network
Application Gateway

Now you can manage everything under one roof.

✅ Why It's Important:
Helps enforce security, cost control, and operational efficiency.

Simplifies DevOps, automation, and infrastructure-as-code deployments.

STEPS TO CREATE AZURE RESOURCE GROUP
Prerequisite: Have an Azure account
Step 1
Login into your Azure account from portal.azure.com and you will see the page below:

Step 2
Click on Resource Group as depicted with the arrow

Your will notice that the "resource Group" has been created as shown with the arrow below

Step 3
Next is to click "Create" as shown with the arrow in other to create a new Resource Group

Then a new page as shown below is displayed as below, where you can now create your Resource Group:

Step 4
Then Name your Resource Group. lets give it a name "EcomRG" and select the region where you want to keep your resources as below. I have chosen west Europe. (Choose the location closest to you or to your customers or where the required resources are available)

Step 5
We have done everything at this page. Next is to click "Review and Create"

Then Click "Create" to finally create the Resource Group

Step 6
Click "Go to Resource Group"

Now, you can see the the EcomRG resource group has been created as highlighted below and there is no resources created yet. You can now go ahead and create your resources.

I hope you enjoy the simple process I took you through. Do like and comment on this post to encourage me do more

How to spin a Windows Virtual Machine in Azure

Timilehin Olatunde — Thu, 06 Mar 2025 22:44:44 +0000

What is an Azure Virtual Machine?
An Azure Virtual Machine (Azure VM) is a cloud-based, on-demand computing resource provided by Microsoft Azure. It allows users to run applications and workloads on a virtualized server without needing to maintain physical hardware. Azure VMs provide scalability, flexibility, and cost-efficiency for various computing needs, such as hosting applications, databases, and development environments.

Step 1
Create a free trial account in Azure (portal.azure.com). A free trial account provides a subscription and $200 Azure credits

Step 2
Login into the azure account you just created. To achieve this, you must provide your username and password

Step 3
In the Search Engine, type "Virtual Machine" and you will see the Virtual machine coming up as the first on the list, then you choose it

Now it displays and give option to create a virtual machine as below:

Step 4
Click the "Create" button to start the Virtual Machine creation Process and choose create a virtual machine hosted by Azure as in below picture

Now after clicking the above, the page below will appear

Step 5
Configure your project details which consist of Subscription and resource group as depicted in the above picture. Lets leave the subscription name as default. Then click on "create new" to name the "Resource group" as "test_group"

Step 6
Configure the Instance Details
As a computer always have a name, so is a virtual machine too because its also a computer too. So I have name this VM as "JohnsonVM" as seen below:

Step 7
Now, its time to choose the Operating System OS on the VM. I have chosen Windows 11 as below and leave others as default including the size

Step 8
The next step is to configure Administrator account which are the username and the password. Also, as depicted in the green box below, you also need to select Port, You will recall that our computers has inbound ports. Here we choose Remote Desktop Protocol (RDP) for the windows OS

Step 9
Confirm Licensing and click Next till you get to "Monitoring"

Disable Monitoring until the VM is running. Then Review and create

To show that you have successfully been validated, it will display "Validation passed". Then you can now proceed to "Create"

It will let you know that your deployment is in Progress

Now you will notive the green mark showing you have successfully deployed your Virtual machine. The next step is to click and go to "Go to resource" button to access the VM we have just created.

You will now see that the status is Running and you also have a public IP address so it can be accessible anywhere in the world

At the top left of the screen above with the green arrow, you can now connect to access your Virtual Machine and the screen below will be displayed

Click on "Select" to see the Native RDP. Then ensure you see that the configure prerequisites for native RDP has turned to "Configure". Then Click "Download RDP file"

When you click on "Dowload RDP file", you will see the screen below

Then Enter your Administrator Password to loginin

WELCOME TO YOUR NEW VIRTUAL MACHINE

I hope you enjoy the steps and you found it easy. Do follow me for more steps on how to make cloud computing easy

Important Concept in Cloud Computing

Timilehin Olatunde — Thu, 06 Mar 2025 00:39:01 +0000

What is Cloud computing?
Cloud computing is the delivery of computing services (such as servers, storage, databases, networking, software, and analytics) over the internet instead of relying on local servers or personal devices.

The idea of cloud computing comes from On-premise virtualization. Cloud computing can be seen as Virtualization in the cloud. I am going to explain virtualization and its benefits in this article.

Key Features of Cloud Computing:

On-Demand Access – Users can access resources anytime without physical hardware unlike Virtualization where you need to stack and maintain physical hardware.
Scalability – Resources can scale up or down based on demand unlike virtualization where you are fixed up and limited to the capacity of your on-premise devices- storage/servers.
Pay-as-You-Go – Users pay only for what they use, reducing costs. In virtualization, you pay for what you dont use as equipment are purchased in advance irrespective of variation in demand.
Remote Accessibility – Services are accessible from anywhere with an internet connection.
Automatic Updates – Cloud providers handle software and security updates.

1. What is Virtualization?
Virtualization is the process of creating a virtual (software-based) version of computing resources, such as servers, storage, networks, or operating systems, instead of using physical hardware. Its on-premise and It allows multiple virtual instances to run on a single physical machine, improving efficiency, scalability, and cost-effectiveness.

2. Scalability
Scalability in cloud computing refers to the ability of a system, application, or infrastructure to handle increasing workloads by adding or adjusting resources dynamically. It ensures that cloud services can grow (or shrink) efficiently based on demand, improving performance, cost efficiency, and reliability.

Scalability in Cloud Computing
Scalability in cloud computing refers to the ability of a system, application, or infrastructure to handle increasing workloads by adding or adjusting resources dynamically. It ensures that cloud services can grow (or shrink) efficiently based on demand, improving performance, cost efficiency, and reliability.

Types of Scalability in Cloud Computing

Vertical Scalability (Scaling Up/Down)

Increases or decreases the power of an existing cloud resource (e.g., adding more CPU, RAM, or storage to a server).
Example: Upgrading a virtual machine (VM) from 4GB RAM to 16GB RAM.
Use Case: Useful for applications with predictable, resource-intensive workloads.

Horizontal Scalability (Scaling Out/In)

Expands or reduces the number of cloud resources to handle workload changes.
Example: Adding more virtual servers (VMs) in a load-balanced environment.
Use Case: Ideal for distributed applications, microservices, and web applications with fluctuating traffic.

Auto-Scaling

Automated scaling based on real-time demand using predefined policies.
Example: AWS Auto Scaling automatically adds or removes EC2 instances based on CPU usage.
Use Case: Used for applications with unpredictable traffic spikes (e.g., e-commerce sites during Black Friday).

Benefits of Cloud Scalability

✅ Cost Efficiency – Pay only for the resources you use (pay-as-you-go model).
✅ High Performance – Ensures applications run smoothly under varying loads.
✅ Flexibility & Agility – Adjusts resources dynamically to meet business needs.
✅ Disaster Recovery – Allows quick recovery by scaling resources when needed.
✅ Global Reach – Supports multi-region scaling for global applications

3. Agility
Agility in cloud computing refers to the ability of businesses and IT teams to rapidly develop, test, deploy, and scale applications or services in response to changing demands. It enables organizations to innovate faster, reduce time to market, and adapt to new opportunities or challenges with minimal friction.

Key Aspects of Cloud Agility
Rapid Provisioning

Instantly deploy resources like virtual machines, databases, and storage without waiting for hardware setup.
Example: Launching an AWS EC2 instance in minutes instead of waiting weeks for a physical server.

On-Demand Scaling

Adjust cloud resources automatically based on traffic or workload changes.
Example: A retail website scales up its cloud servers during Black Friday and scales down afterward to save costs.

Flexible Resource Allocation

Organizations can easily switch between computing power, storage, and network resources based on current needs.
Example: A company can move workloads between AWS, Azure, and Google Cloud based on cost efficiency and performance.

Continuous Integration & Deployment (CI/CD)

Developers can build, test, and deploy applications faster using DevOps tools in the cloud.
Example: Using AWS CodePipeline or Azure DevOps to automate software updates without downtime.

Benefits of Cloud Agility
✅ Faster Innovation – Experiment and launch new services without heavy upfront costs.
✅ Cost Savings – Pay only for what you use, avoiding unnecessary infrastructure investments.
✅ Competitive Advantage – React to market changes faster than competitors using traditional IT.
✅ Improved Productivity – Automate processes, reduce manual intervention, and free up IT teams.
✅ Disaster Recovery & Business Continuity – Quickly adapt to failures, ensuring minimal downtime.

Examples of Cloud Agility in Action
Netflix: Uses AWS to dynamically scale resources based on streaming demand.
Spotify: Deploys new music features rapidly using Google Cloud’s Kubernetes engine.
Tesla: Updates software over the air for its vehicles using agile cloud infrastructure.

4. High Availability
High Availability (HA) in cloud computing refers to the ability of a system or service to remain operational and accessible without significant downtime or disruptions, even in the event of failures. It ensures that applications and data are always available to users, maintaining business continuity.

Key Components of High Availability
Redundancy

Multiple instances of resources (servers, databases, networks) are deployed across different locations to prevent a single point of failure.
Example: AWS stores copies of data across multiple Availability Zones (AZs) to ensure reliability.

Failover Mechanisms

When a failure occurs, traffic is automatically redirected to a backup system or server.
Example: A load balancer detects a server failure and reroutes traffic to a healthy server.

Load Balancing

Distributes network traffic across multiple servers to prevent overload and improve performance.
Example: AWS Elastic Load Balancer (ELB) spreads requests across multiple EC2 instances to prevent downtime.

Multi-Region Deployment

Services are deployed in multiple geographic regions to ensure availability even if one region fails.
Example: A banking application runs in both Azure UK South and Azure West Europe to prevent outages.

Disaster Recovery (DR)

Backup strategies (e.g., snapshots, replication) ensure that data can be restored in case of failure.
Example: Amazon RDS Multi-AZ automatically replicates databases to another availability zone.

Benefits of High Availability
✅ Minimal Downtime – Ensures services are always available to users.
✅ Improved Performance – Load balancing and redundancy enhance system responsiveness.
✅ Business Continuity – Prevents revenue loss and reputational damage from outages.
✅ Scalability & Flexibility – Allows systems to grow while maintaining reliability.
✅ Automatic Recovery – Self-healing mechanisms minimize manual intervention.

5. Fault Tolerant
Fault Tolerance in cloud computing refers to a system’s ability to continue operating without disruption even when failures occur in its components. It ensures that cloud services remain functional despite hardware failures, software bugs, or network outages.

6. Global Reach
Global Reach & Accessibility

Cloud services allow businesses to deploy applications and serve users worldwide without investing in physical infrastructure.
Example: A startup in the UK can instantly deploy its app to data centers in the US, Asia, and Europe via Google Cloud Platform (GCP).

7. What is the difference between Elasticity and Scalability
Scalability – Handles Long-Term Growth
Definition: Scalability is the cloud system's ability to increase or decrease resources (CPU, RAM, storage, etc.) to meet growing demand over time.
Purpose: Designed for predictable, steady growth.
Types:
Vertical Scalability (Scaling Up/Down): Upgrading a single machine (e.g., increasing RAM, CPU power).
Horizontal Scalability (Scaling Out/In): Adding more machines (e.g., increasing the number of servers).
Example:
A growing e-commerce website adds more virtual machines (VMs) on AWS as the number of users increases over months or years.

_ Elasticity – Handles Short-Term Spikes_
Definition: Elasticity refers to the cloud system’s ability to dynamically allocate or remove resources automatically based on real-time demand.
Purpose: Ideal for sudden, unpredictable workload spikes.
Key Feature: Auto-scaling occurs instantly when demand rises or falls.
Example:
A ticket booking website auto-scales its server capacity during a flash sale, then reduces resources when traffic drops after the sale ends.