Azure is one of the most popular cloud platforms, and many learners are
eager to get started. However, beginners often feel overwhelmed due to the
wide range of services and concepts. If you have no prior experience in cloud
computing or Azure, the best place to start is with Azure Fundamentals
(AZ-900). In this blog series, we will cover both theoretical concepts and
practical hands-on exercises to help you build a strong foundation in
Microsoft Azure.
We will also provide a real-world,
enterprise-level roadmap to guide your learning journey step by
step.
For Phase 1 (Cloud Fundamentals) the topics I listed are sufficient to understand Azure basics, but if your
goal is to prepare properly for Microsoft Certified:
Azure Fundamentals (AZ-900) and to build a solid base for
later phases, you should expand Phase 1 slightly.
Think of
Phase 1 as “cloud literacy +
Azure platform orientation.
Below is a complete but still
beginner-level Phase 1 syllabus.
Phase 1 — Azure
Fundamentals (Expanded)
Focus on understanding how the
Microsoft Azure ecosystem works.
Fundamentals of Azure like -
1) Fundamentals of Cloud
2) Different types of services in
the cloud
3) Different types of services which are present in
azure with each categories : Compute, Storage, Networking, storage services
and a wide verity of other categories.
This would help you get a
quick start into azure.
- Define cloud computing.
- Describe the shared responsibility model.
- Define cloud models, including public, private, and hybrid.
- Identify appropriate use cases for each cloud model.
- Describe the consumption-based model.
- Compare cloud pricing models.
Define Cloud Computing - Cloud computing is a technology
with delivery of computing services over the internet and allow the user to
access and use computing resources such as servers, storage, database,
networking, software over the internet. Usually on a pay-as-you-go
basis.
Cloud services also expand the
traditional IT offerings to include things like internet of things (IoT),
machine learning (ML) and artificial intelligence (AI). Services is providing
over the internet so it doesn't have to be constrained by physical
infrastructure the same way that a traditional datacenter is.
If
you need to increase your IT infrastructure rapidly, you don't
have to wait to build a new datacenter.
CapEx vs OpEx in azure
In this CapEx capital expenditure, this is the classic old
model. Its a huge onetime purchase of a physical things in company own for
years. A whole building, data center build-out, fleet of vehicles, giant rack
of computer servers.
These assets lose value over time. That's
called depreciation. Cost type upfront, one time investment.
In
this OpEx operational expenditure, this is involves paying for
services ona usage-based, subscription model (eg. pay-as-you-go virtual
machines, Storage costs, SaaS applications). Azure enables a
shift to OpEx, enhancing flexibility, eliminating upfront costs, and improving agility.
Why shift to OpEx in azure ?
Quickly deploy resources without waiting for procurement with pay
only for what we use policy, rather than buying for peak demand.
It
is easily scale up or down as needs change.
☁️ Key Characteristics of Cloud Computing in Azure
when using Microsoft Azure, you get several powerful capabilities
:
1. High Availability
High availability ensures that your application are always up and
running, with minimal downtime.
π Azure achieves this using:
- Multiple data centers (Regions)
- Redundancy (backup systems)
- Load balancing
Example : If one server fails, another automatically takes over.
1) Redundancy - Azure provides high availability and durability by replicating data across
multiple locations, protecting against hardware failures, data center outages,
or regional disasters.
Storage options such as Locally Redundant
Storage (LRS), Zone-redundant storage (ZRS), and Geo-redundant
storage (GRS), providing flexibility to balance cost with data
protection needs.
2) Load Balancer - A load balancer
is service or device that distributes incoming internal traffic across
multiple servers to ensure no single server becomes overwhelmed. It helps
improve the availability, reliability and performance of application by
balancing the load efficiently.
2. Scalability
Scalability means the ability to increase or decrease resources
based on the demand.
π Types:
Vertical scaling ->
Increase power (CPU, RAM)
Horizontal scaling -> Add more servers
π Example:
Your website (hackingtruth.org) gets more users -> you add
more virtual machines.
3. Elasticity
Elasticity is automatic scaling in real-time.
Difference
from scalability :
Scalability -> manual or planned
Elasticity
-> automatic and dynamic
π Example:
Traffic spikes during a sale -> Azure auto-scales resources
-> traffic drops -> resources reduce automatically.
4. Fault Tolerance
Fault tolerance ensures that a system continues to
operate even if part of it fails.
Azure uses :
- Replication
- Availability zones
- Backup systems
π Example:
If one component crashes, the system still works
without interruption.
5. Disaster Recovery (DR)
Disaster recovery is the ability to recover data and systems after
a major failure.
π Covers events like:
Natural
disasters
Data center outages
Cyber attacks
π Azure solutions:
Backup services
Geo-redundancy
Site-recover
π Example:
Entire region goes down -> your app is restored in another
region.
Describe the shared responsibility model
Shared responsibility model in
Microsoft azure defines who is responsible for what when using
cloud services.
It is handles some part of security, and you as a
customer handle the rest.
With the shared responsibility model, these responsibilities get shared between the cloud provider and the
consumer. Physical security, power cooling, and network connectivity are the
responsibility of the cloud provider. just opposite at the same time consumer
is responsible for data and the information stored in the cloud. The consumer
is also responsible for access security, meaning you only give access to those
who need it.
Even for some things, the responsibility depends on the situation.
If you're using a cloud SQL database.
- Microsoft manages the cloud infrastructure.
- You (customer) manage what you deploy and configure.
⚙️ Responsibilities Breakdown
☁️ Microsoft
(Azure) is responsible for:
- Physical data enters.
- Hardware (servers, storage, networking)
- Physical Security
- Power, cooling, and networking infrastructure.
π This is often called:
“Security OF the cloud”
π€ You (Customer) are responsible for:
- Data (your files, databases)
- User access & identify (who can log in)
- Application you deploy
- Configuration of services
π This is often called:
“Security IN the cloud”
With
an on-premises datacenter, you're responsible for everything. With cloud
computing, those responsibilities shift.
- IAAS (Infrastructure as a service)
- PAAS (Platform as a service)
- SAAS (Software as a service)
1) IAAS - Infrastructure as a service places the most
responsibility on the consumer, with the cloud provider being responsible for
the basics of physical security, power and connectivity.
2) SAAS - Software as a service places most of the responsibility with cloud
provider.
3) PAAS - Platform as a service being a middle ground between IaaS and
SaaS, rests somewhere in the middle and evenly distributes responsibility
between the cloud provider and the consumer.
IaaS (Infrastructure as a service)
Example: Virtual Machines
Azure -> Hardware, network
You
-> OS, updates, apps, security
π You have maximum control + maximum responsibility
2. PaaS (platform as a service)
Example: App services, Azure SQL
Azure -> OS, runtime,
infrastructure
You -> Application + data
π Balanced
responsibility
3. SaaS (Software as a service)
Example: Microsoft 365
Azure -> almost everything
You -> data + user access
π
Least responsibility for you
π Simple Analogy
Think of it like housing:
- On-premises → You own the whole house π
- IaaS → You rent a house (you manage inside)
- PaaS → You rent a furnished apartment
- SaaS → You stay in a hotel
π§Ύ Final One-Line Summary
π Azure secures the
infrastructure, you secure your data and configurations.
Cloud Models
The cloud models define the deployment type of cloud resources.
The main cloud models are: public, private and hybrid
1. Public Cloud
- A public cloud is owned and operated by a third party cloud provider, where
services and resources are delivered over the internet.
π Examples:
Gmail, Microsoft Azure, Dropbox etc.
✅ Key Features:
No upfront hardware cost
Pay-as-you-go pricing
Highly
scalable
Managed by provider
π Example:
Hosting a website on Azure without owning
any servers.
2. Private Cloud
A private cloud is used exclusively by a single
organization. Private cloud provides much greater control for the company and
its IT department. However, it also comes with greater cost and fewer of the
benefits of a public cloud deployment. Finally, a private cloud may be hosted
from your on site datacenter.
It can be:
- On-premises (your own data center)
- Or hosted by a cloud provider
Key features:
- Full control over infrastructure
- Higher security and customization
- More expensive than public cloud
π Example:
A bank running its own secure
data center.
3. Hybrid Cloud
A
hybrid cloud is a combination of public cloud + private cloud, allowing data
and applications to be shared between them.
Key features:
- Flexibility
- Data control + scalability
- Best of both worlds
π Example:
- Sensitive data -> private cloud
- Web apps -> public cloud
π Visual Diagram (Blog-Ready)
π§ΎFinal Takeaway
- Public Cloud → Best for scalability and cost
- Private Cloud → Best for control and security
- Hybrid Cloud → Best for flexibility


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