Introduction

MongoDB provides a variety of design patterns to help you model data efficiently for real-world use cases. Below are 12 key patterns every developer should know, each illustrated with practical examples.

Table of Contents

• 1. Attribute Pattern
• 2. Computed Pattern
• 3. Bucket Pattern
• 4. Schema Versioning Pattern
• 5. Tree Pattern
• 6. Subset Pattern
• 7. Approximation Pattern
• 8. Outlier Pattern
• 9. Polymorphic Pattern
• 10. Extended Reference Pattern
• 11. Pre-aggregation Pattern
• 12. Document Versioning Pattern

1. Attribute Pattern

Scenario:

An online store has multiple product categories, such as smartphones, laptops, and clothing. Each category contains items with a wide range of attributes. For example:

Introduction

MongoDB provides a variety of design patterns to help you model data efficiently for real-world use cases. Below are 12 key patterns every developer should know, each illustrated with practical examples.

Table of Contents

• 1. Attribute Pattern
• 2. Computed Pattern
• 3. Bucket Pattern
• 4. Schema Versioning Pattern
• 5. Tree Pattern
• 6. Subset Pattern
• 7. Approximation Pattern
• 8. Outlier Pattern
• 9. Polymorphic Pattern
• 10. Extended Reference Pattern
• 11. Pre-aggregation Pattern
• 12. Document Versioning Pattern

1. Attribute Pattern

Scenario:

An online store has multiple product categories, such as smartphones, laptops, and clothing. Each category contains items with a wide range of attributes. For example:

Introduction

MongoDB provides a variety of design patterns to help you model data efficiently for real-world use cases. Below are 12 key patterns every developer should know, each illustrated with practical examples.

Table of Contents

• 1. Attribute Pattern
• 2. Computed Pattern
• 3. Bucket Pattern
• 4. Schema Versioning Pattern
• 5. Tree Pattern
• 6. Subset Pattern
• 7. Approximation Pattern
• 8. Outlier Pattern
• 9. Polymorphic Pattern
• 10. Extended Reference Pattern
• 11. Pre-aggregation Pattern
• 12. Document Versioning Pattern

1. Attribute Pattern

Scenario:

An online store has multiple product categories, such as smartphones, laptops, and clothing. Each category contains items with a wide range of attributes. For example:

Introduction

Automating the build and deployment of Docker images using GitHub Actions and AWS Elastic Container Registry (ECR) significantly streamlines your software delivery process.

By integrating these powerful tools, developers benefit from reduced manual intervention, minimized errors, and accelerated deployment cycles.

GitHub Actions automates your build workflow whenever code changes, while AWS ECR securely stores and manages your container images, ensuring reliability and scalability.

In this guide, you’ll learn step-by-step how to effortlessly set up continuous integration and continuous deployment (CI/CD) to AWS ECR, maximizing your development efficiency.

Ubuntu 22.04.3 LTS - Windows Subsystem for Linux - AMD64

1. Install & Config AWS CLI

sudo snap install aws-cli --classic
aws --version
which aws

Configure AWS account

aws configure
AWS Access Key ID [None]: xxxxxxxxxxxx
AWS Secret Access Key [None]: xxxxxxxxxxxxxxxx+xxxxxx
Default region name [None]: ap-southeast-1
Default output format [None]: json

You can verify your aws account:

cat ~/.aws/credentials
cat ~/.aws/config
aws ec2 describe-vpcs

2. Install kubectl CLI

kubectl is the command-line interface (CLI) tool used to interact with Kubernetes clusters. It allows developers and operators to manage cluster resources, inspect states, deploy applications, and perform administrative tasks.

1. Introduction

• Why exposing services matters in Kubernetes:

  • Your workloads are useless if no one can reach them. Service abstraction lets you decouple pod lifecycles from stable endpoints.

• Overview of Service types vs. Ingress:

  • Services give every workload an IP; Ingress turns a set of Services into a coherent, externally reachable API surface.

2. Kubernetes Service Types Explained

a. ClusterIP

- Exposes the Service on a cluster-internal IP
- Accessible **only inside** the cluster
- Typical use: 
    - Internal-only services 
    - Microservices talking to each other

b. NodePort

- Exposes the Service on each node’s IP at a static port (the NodePort)
- Accessible from outside the cluster: same VPC or the internet (depending on firewall/Security Group rules)
- Reachable via **NodeIP:NodePort** (port range 30000 - 32767)
- Typical use:
    - Simple setups, debugging, or in environments without cloud LBs. 
    - Quick test or direct access, not recommended for production internet-facing apps.

c. LoadBalancer

- Creates a cloud load balancer (cloud provider integration, e.g., AWS ALB).
- Assigns a public IP and routes traffic to your Service.
- Accessible from the internet.
- Typical use: exposing production workloads to the internet (websites, APIs).

d. ExternalName

- Maps the Service to an external DNS name.
- Used for routing cluster traffic to resources outside Kubernetes.
- Not used for exposing services to the internet.
- Typical use: referencing services outside the cluster by DNS name(database,SaaS endpoints).

3. Ingress

• Ingress is a Kubernetes resource that manages external HTTP/HTTPS traffic
  • Receives incoming requests from outside the cluster
  • Routes them to the right Service based on rules (URL path, host, headers…)
• Typical flow: User → ALB/NLB/NGINX (provisioned by the Ingress Controller) → Service → Pods.
• Ingress Controller:
  • A pod/deployment running inside your cluster
  • monitors your Ingress resources.
  • configures and manages actual routing rules on a cloud load balancer
• Ingress Class:
  • a way to specify which Ingress Controller is responsible for handling a particular Ingress resource

4. Curious question

Q: Why Do You Need Ingress? A: Without Ingress, to expose multiple applications or services externally, you would need many individual LoadBalancer services, which becomes expensive and complex quickly.

Ubuntu 22.04.3 LTS - Windows Subsystem for Linux - AMD64

1. Install & Config AWS CLI

sudo snap install aws-cli --classic
aws --version
which aws

Configure AWS account

aws configure
AWS Access Key ID [None]: xxxxxxxxxxxx
AWS Secret Access Key [None]: xxxxxxxxxxxxxxxx+xxxxxx
Default region name [None]: ap-southeast-1
Default output format [None]: json

You can verify your aws account:

cat ~/.aws/credentials
cat ~/.aws/config
aws ec2 describe-vpcs

2. Install kubectl CLI

kubectl is the command-line interface (CLI) tool used to interact with Kubernetes clusters. It allows developers and operators to manage cluster resources, inspect states, deploy applications, and perform administrative tasks.

Table of Contents

• 1. Introduction
  • Why concurrency and parallelism matter
  • Key differences between concurrency and parallelism
• 2. Concurrency in Golang
  • Goroutines
  • Channels
  • Example code
• 3. Concurrency in Python
  • Threads
  • Asyncio: Concurrency for IO-bound Work
  • Example code
• 4. Parallelism in Golang
  • Go Scheduler: The G-M-P Model
  • Example code
• 5. Parallelism in Python
  • The GIL and Its Impact
  • Multiprocessing for Real Parallelism
  • Example code
• 6. Conclustion

1. Introduction

- Why concurrency and parallelism matter:

Modern software isn’t just about doing one thing at a time. From high-traffic web servers and real-time analytics, to background processing and automation, today’s applications often need to handle multiple tasks “at once.” Whether it’s serving thousands of user requests, processing large datasets, or running background jobs, your program’s ability to efficiently juggle several operations can be the difference between fast, scalable software and a sluggish, unresponsive system.

Introduction

Automating the build and deployment of Docker images using GitHub Actions and AWS Elastic Container Registry (ECR) significantly streamlines your software delivery process.

By integrating these powerful tools, developers benefit from reduced manual intervention, minimized errors, and accelerated deployment cycles.

GitHub Actions automates your build workflow whenever code changes, while AWS ECR securely stores and manages your container images, ensuring reliability and scalability.

In this guide, you’ll learn step-by-step how to effortlessly set up continuous integration and continuous deployment (CI/CD) to AWS ECR, maximizing your development efficiency.

Introduction

Automating the build and deployment of Docker images using GitHub Actions and AWS Elastic Container Registry (ECR) significantly streamlines your software delivery process.

By integrating these powerful tools, developers benefit from reduced manual intervention, minimized errors, and accelerated deployment cycles.

GitHub Actions automates your build workflow whenever code changes, while AWS ECR securely stores and manages your container images, ensuring reliability and scalability.

In this guide, you’ll learn step-by-step how to effortlessly set up continuous integration and continuous deployment (CI/CD) to AWS ECR, maximizing your development efficiency.

Ubuntu 22.04.3 LTS - Windows Subsystem for Linux - AMD64

1. Install & Config AWS CLI

sudo snap install aws-cli --classic
aws --version
which aws

Configure AWS account

aws configure
AWS Access Key ID [None]: xxxxxxxxxxxx
AWS Secret Access Key [None]: xxxxxxxxxxxxxxxx+xxxxxx
Default region name [None]: ap-southeast-1
Default output format [None]: json

You can verify your aws account:

cat ~/.aws/credentials
cat ~/.aws/config
aws ec2 describe-vpcs

2. Install kubectl CLI

kubectl is the command-line interface (CLI) tool used to interact with Kubernetes clusters. It allows developers and operators to manage cluster resources, inspect states, deploy applications, and perform administrative tasks.

Introduction

Automating the build and deployment of Docker images using GitHub Actions and AWS Elastic Container Registry (ECR) significantly streamlines your software delivery process.

By integrating these powerful tools, developers benefit from reduced manual intervention, minimized errors, and accelerated deployment cycles.

GitHub Actions automates your build workflow whenever code changes, while AWS ECR securely stores and manages your container images, ensuring reliability and scalability.

In this guide, you’ll learn step-by-step how to effortlessly set up continuous integration and continuous deployment (CI/CD) to AWS ECR, maximizing your development efficiency.

Table of Contents

• 1. Introduction
  • Why concurrency and parallelism matter
  • Key differences between concurrency and parallelism
• 2. Concurrency in Golang
  • Goroutines
  • Channels
  • Example code
• 3. Concurrency in Python
  • Threads
  • Asyncio: Concurrency for IO-bound Work
  • Example code
• 4. Parallelism in Golang
  • Go Scheduler: The G-M-P Model
  • Example code
• 5. Parallelism in Python
  • The GIL and Its Impact
  • Multiprocessing for Real Parallelism
  • Example code
• 6. Conclustion

1. Introduction

- Why concurrency and parallelism matter:

Modern software isn’t just about doing one thing at a time. From high-traffic web servers and real-time analytics, to background processing and automation, today’s applications often need to handle multiple tasks “at once.” Whether it’s serving thousands of user requests, processing large datasets, or running background jobs, your program’s ability to efficiently juggle several operations can be the difference between fast, scalable software and a sluggish, unresponsive system.

Table of Contents

• 1. Introduction
  • Why understanding networking is crucial for backend developers
  • Short comparison of TCP and UDP
• 2. Deep Dive into TCP
  • 2.1. When to Use TCP?
  • 2.2. TCP Handshake: SYN, SYN-ACK, ACK
  • 2.3. Error Handling & Retransmission
  • 2.4. Advantages & Limitations of TCP
  • 2.5. TCP Code Examples in Golang
• 3. Deep Dive into UDP
  • 3.1. When to Use UDP?
  • 3.2. Stateless Communication and Speed
  • 3.3. Why UDP Doesn’t Guarantee Delivery
  • 3.4. Advantages & Limitations of UDP
  • 3.5. UDP Code Examples in Golang
• 4. Advanced Topics
  • 4.1. Concurrent TCP and UDP Servers Using Goroutines
  • 4.2. Implementing Protocol Buffers or JSON Data Serialization with TCP/UDP
  • 4.3. Handling Scalability and Performance Tuning
• 5. Best Practices & Common Pitfalls
  • 5.1. Resource Management and Avoiding Memory Leaks
  • 5.2. Handling Network Errors Gracefully
  • 5.3. Security Considerations in Networking
• 6. Conclusion
  • Summary of Key Learnings
  • Guidance for Choosing TCP vs UDP

1. Introduction

- Why understanding networking is crucial for backend developers

In today’s connected world, backend developers are expected to build reliable, scalable, and high-performance systems. Whether you’re designing REST APIs, microservices, real-time chat apps, or distributed systems, a solid understanding of computer networking is essential. Knowing how data is transmitted, how connections are established, and what trade-offs exist between reliability and speed empowers you to make better architectural decisions and debug network issues effectively.

1. Introduction

• Why exposing services matters in Kubernetes:

  • Your workloads are useless if no one can reach them. Service abstraction lets you decouple pod lifecycles from stable endpoints.

• Overview of Service types vs. Ingress:

  • Services give every workload an IP; Ingress turns a set of Services into a coherent, externally reachable API surface.

2. Kubernetes Service Types Explained

a. ClusterIP

- Exposes the Service on a cluster-internal IP
- Accessible **only inside** the cluster
- Typical use: 
    - Internal-only services 
    - Microservices talking to each other

b. NodePort

- Exposes the Service on each node’s IP at a static port (the NodePort)
- Accessible from outside the cluster: same VPC or the internet (depending on firewall/Security Group rules)
- Reachable via **NodeIP:NodePort** (port range 30000 - 32767)
- Typical use:
    - Simple setups, debugging, or in environments without cloud LBs. 
    - Quick test or direct access, not recommended for production internet-facing apps.

c. LoadBalancer

- Creates a cloud load balancer (cloud provider integration, e.g., AWS ALB).
- Assigns a public IP and routes traffic to your Service.
- Accessible from the internet.
- Typical use: exposing production workloads to the internet (websites, APIs).

d. ExternalName

- Maps the Service to an external DNS name.
- Used for routing cluster traffic to resources outside Kubernetes.
- Not used for exposing services to the internet.
- Typical use: referencing services outside the cluster by DNS name(database,SaaS endpoints).

3. Ingress

• Ingress is a Kubernetes resource that manages external HTTP/HTTPS traffic
  • Receives incoming requests from outside the cluster
  • Routes them to the right Service based on rules (URL path, host, headers…)
• Typical flow: User → ALB/NLB/NGINX (provisioned by the Ingress Controller) → Service → Pods.
• Ingress Controller:
  • A pod/deployment running inside your cluster
  • monitors your Ingress resources.
  • configures and manages actual routing rules on a cloud load balancer
• Ingress Class:
  • a way to specify which Ingress Controller is responsible for handling a particular Ingress resource

4. Curious question

Q: Why Do You Need Ingress? A: Without Ingress, to expose multiple applications or services externally, you would need many individual LoadBalancer services, which becomes expensive and complex quickly.

Ubuntu 22.04.3 LTS - Windows Subsystem for Linux - AMD64

1. Install & Config AWS CLI

sudo snap install aws-cli --classic
aws --version
which aws

Configure AWS account

aws configure
AWS Access Key ID [None]: xxxxxxxxxxxx
AWS Secret Access Key [None]: xxxxxxxxxxxxxxxx+xxxxxx
Default region name [None]: ap-southeast-1
Default output format [None]: json

You can verify your aws account:

cat ~/.aws/credentials
cat ~/.aws/config
aws ec2 describe-vpcs

2. Install kubectl CLI

kubectl is the command-line interface (CLI) tool used to interact with Kubernetes clusters. It allows developers and operators to manage cluster resources, inspect states, deploy applications, and perform administrative tasks.

Ubuntu 22.04.3 LTS - Windows Subsystem for Linux - AMD64

1. Install & Config AWS CLI

sudo snap install aws-cli --classic
aws --version
which aws

Configure AWS account

aws configure
AWS Access Key ID [None]: xxxxxxxxxxxx
AWS Secret Access Key [None]: xxxxxxxxxxxxxxxx+xxxxxx
Default region name [None]: ap-southeast-1
Default output format [None]: json

You can verify your aws account:

cat ~/.aws/credentials
cat ~/.aws/config
aws ec2 describe-vpcs

2. Install kubectl CLI

kubectl is the command-line interface (CLI) tool used to interact with Kubernetes clusters. It allows developers and operators to manage cluster resources, inspect states, deploy applications, and perform administrative tasks.

1. Introduction

• Why exposing services matters in Kubernetes:

  • Your workloads are useless if no one can reach them. Service abstraction lets you decouple pod lifecycles from stable endpoints.

• Overview of Service types vs. Ingress:

  • Services give every workload an IP; Ingress turns a set of Services into a coherent, externally reachable API surface.

2. Kubernetes Service Types Explained

a. ClusterIP

- Exposes the Service on a cluster-internal IP
- Accessible **only inside** the cluster
- Typical use: 
    - Internal-only services 
    - Microservices talking to each other

b. NodePort

- Exposes the Service on each node’s IP at a static port (the NodePort)
- Accessible from outside the cluster: same VPC or the internet (depending on firewall/Security Group rules)
- Reachable via **NodeIP:NodePort** (port range 30000 - 32767)
- Typical use:
    - Simple setups, debugging, or in environments without cloud LBs. 
    - Quick test or direct access, not recommended for production internet-facing apps.

c. LoadBalancer

- Creates a cloud load balancer (cloud provider integration, e.g., AWS ALB).
- Assigns a public IP and routes traffic to your Service.
- Accessible from the internet.
- Typical use: exposing production workloads to the internet (websites, APIs).

d. ExternalName

- Maps the Service to an external DNS name.
- Used for routing cluster traffic to resources outside Kubernetes.
- Not used for exposing services to the internet.
- Typical use: referencing services outside the cluster by DNS name(database,SaaS endpoints).

3. Ingress

• Ingress is a Kubernetes resource that manages external HTTP/HTTPS traffic
  • Receives incoming requests from outside the cluster
  • Routes them to the right Service based on rules (URL path, host, headers…)
• Typical flow: User → ALB/NLB/NGINX (provisioned by the Ingress Controller) → Service → Pods.
• Ingress Controller:
  • A pod/deployment running inside your cluster
  • monitors your Ingress resources.
  • configures and manages actual routing rules on a cloud load balancer
• Ingress Class:
  • a way to specify which Ingress Controller is responsible for handling a particular Ingress resource

4. Curious question

Q: Why Do You Need Ingress? A: Without Ingress, to expose multiple applications or services externally, you would need many individual LoadBalancer services, which becomes expensive and complex quickly.

1. Introduction

• Why exposing services matters in Kubernetes:

  • Your workloads are useless if no one can reach them. Service abstraction lets you decouple pod lifecycles from stable endpoints.

• Overview of Service types vs. Ingress:

  • Services give every workload an IP; Ingress turns a set of Services into a coherent, externally reachable API surface.

2. Kubernetes Service Types Explained

a. ClusterIP

- Exposes the Service on a cluster-internal IP
- Accessible **only inside** the cluster
- Typical use: 
    - Internal-only services 
    - Microservices talking to each other

b. NodePort

- Exposes the Service on each node’s IP at a static port (the NodePort)
- Accessible from outside the cluster: same VPC or the internet (depending on firewall/Security Group rules)
- Reachable via **NodeIP:NodePort** (port range 30000 - 32767)
- Typical use:
    - Simple setups, debugging, or in environments without cloud LBs. 
    - Quick test or direct access, not recommended for production internet-facing apps.

c. LoadBalancer

- Creates a cloud load balancer (cloud provider integration, e.g., AWS ALB).
- Assigns a public IP and routes traffic to your Service.
- Accessible from the internet.
- Typical use: exposing production workloads to the internet (websites, APIs).

d. ExternalName

- Maps the Service to an external DNS name.
- Used for routing cluster traffic to resources outside Kubernetes.
- Not used for exposing services to the internet.
- Typical use: referencing services outside the cluster by DNS name(database,SaaS endpoints).

3. Ingress

• Ingress is a Kubernetes resource that manages external HTTP/HTTPS traffic
  • Receives incoming requests from outside the cluster
  • Routes them to the right Service based on rules (URL path, host, headers…)
• Typical flow: User → ALB/NLB/NGINX (provisioned by the Ingress Controller) → Service → Pods.
• Ingress Controller:
  • A pod/deployment running inside your cluster
  • monitors your Ingress resources.
  • configures and manages actual routing rules on a cloud load balancer
• Ingress Class:
  • a way to specify which Ingress Controller is responsible for handling a particular Ingress resource

4. Curious question

Q: Why Do You Need Ingress? A: Without Ingress, to expose multiple applications or services externally, you would need many individual LoadBalancer services, which becomes expensive and complex quickly.

Table of Contents

• 1. Introduction
  • Why concurrency and parallelism matter
  • Key differences between concurrency and parallelism
• 2. Concurrency in Golang
  • Goroutines
  • Channels
  • Example code
• 3. Concurrency in Python
  • Threads
  • Asyncio: Concurrency for IO-bound Work
  • Example code
• 4. Parallelism in Golang
  • Go Scheduler: The G-M-P Model
  • Example code
• 5. Parallelism in Python
  • The GIL and Its Impact
  • Multiprocessing for Real Parallelism
  • Example code
• 6. Conclustion

1. Introduction

- Why concurrency and parallelism matter:

Modern software isn’t just about doing one thing at a time. From high-traffic web servers and real-time analytics, to background processing and automation, today’s applications often need to handle multiple tasks “at once.” Whether it’s serving thousands of user requests, processing large datasets, or running background jobs, your program’s ability to efficiently juggle several operations can be the difference between fast, scalable software and a sluggish, unresponsive system.

Table of Contents

• 1. Introduction
  • Why concurrency and parallelism matter
  • Key differences between concurrency and parallelism
• 2. Concurrency in Golang
  • Goroutines
  • Channels
  • Example code
• 3. Concurrency in Python
  • Threads
  • Asyncio: Concurrency for IO-bound Work
  • Example code
• 4. Parallelism in Golang
  • Go Scheduler: The G-M-P Model
  • Example code
• 5. Parallelism in Python
  • The GIL and Its Impact
  • Multiprocessing for Real Parallelism
  • Example code
• 6. Conclustion

1. Introduction

- Why concurrency and parallelism matter:

Modern software isn’t just about doing one thing at a time. From high-traffic web servers and real-time analytics, to background processing and automation, today’s applications often need to handle multiple tasks “at once.” Whether it’s serving thousands of user requests, processing large datasets, or running background jobs, your program’s ability to efficiently juggle several operations can be the difference between fast, scalable software and a sluggish, unresponsive system.

1. Introduction

• Why exposing services matters in Kubernetes:

  • Your workloads are useless if no one can reach them. Service abstraction lets you decouple pod lifecycles from stable endpoints.

• Overview of Service types vs. Ingress:

  • Services give every workload an IP; Ingress turns a set of Services into a coherent, externally reachable API surface.

2. Kubernetes Service Types Explained

a. ClusterIP

- Exposes the Service on a cluster-internal IP
- Accessible **only inside** the cluster
- Typical use: 
    - Internal-only services 
    - Microservices talking to each other

b. NodePort

- Exposes the Service on each node’s IP at a static port (the NodePort)
- Accessible from outside the cluster: same VPC or the internet (depending on firewall/Security Group rules)
- Reachable via **NodeIP:NodePort** (port range 30000 - 32767)
- Typical use:
    - Simple setups, debugging, or in environments without cloud LBs. 
    - Quick test or direct access, not recommended for production internet-facing apps.

c. LoadBalancer

- Creates a cloud load balancer (cloud provider integration, e.g., AWS ALB).
- Assigns a public IP and routes traffic to your Service.
- Accessible from the internet.
- Typical use: exposing production workloads to the internet (websites, APIs).

d. ExternalName

- Maps the Service to an external DNS name.
- Used for routing cluster traffic to resources outside Kubernetes.
- Not used for exposing services to the internet.
- Typical use: referencing services outside the cluster by DNS name(database,SaaS endpoints).

3. Ingress

• Ingress is a Kubernetes resource that manages external HTTP/HTTPS traffic
  • Receives incoming requests from outside the cluster
  • Routes them to the right Service based on rules (URL path, host, headers…)
• Typical flow: User → ALB/NLB/NGINX (provisioned by the Ingress Controller) → Service → Pods.
• Ingress Controller:
  • A pod/deployment running inside your cluster
  • monitors your Ingress resources.
  • configures and manages actual routing rules on a cloud load balancer
• Ingress Class:
  • a way to specify which Ingress Controller is responsible for handling a particular Ingress resource

4. Curious question

Q: Why Do You Need Ingress? A: Without Ingress, to expose multiple applications or services externally, you would need many individual LoadBalancer services, which becomes expensive and complex quickly.

Table of Contents

• 1. Introduction
  • Why understanding networking is crucial for backend developers
  • Short comparison of TCP and UDP
• 2. Deep Dive into TCP
  • 2.1. When to Use TCP?
  • 2.2. TCP Handshake: SYN, SYN-ACK, ACK
  • 2.3. Error Handling & Retransmission
  • 2.4. Advantages & Limitations of TCP
  • 2.5. TCP Code Examples in Golang
• 3. Deep Dive into UDP
  • 3.1. When to Use UDP?
  • 3.2. Stateless Communication and Speed
  • 3.3. Why UDP Doesn’t Guarantee Delivery
  • 3.4. Advantages & Limitations of UDP
  • 3.5. UDP Code Examples in Golang
• 4. Advanced Topics
  • 4.1. Concurrent TCP and UDP Servers Using Goroutines
  • 4.2. Implementing Protocol Buffers or JSON Data Serialization with TCP/UDP
  • 4.3. Handling Scalability and Performance Tuning
• 5. Best Practices & Common Pitfalls
  • 5.1. Resource Management and Avoiding Memory Leaks
  • 5.2. Handling Network Errors Gracefully
  • 5.3. Security Considerations in Networking
• 6. Conclusion
  • Summary of Key Learnings
  • Guidance for Choosing TCP vs UDP

1. Introduction

- Why understanding networking is crucial for backend developers

In today’s connected world, backend developers are expected to build reliable, scalable, and high-performance systems. Whether you’re designing REST APIs, microservices, real-time chat apps, or distributed systems, a solid understanding of computer networking is essential. Knowing how data is transmitted, how connections are established, and what trade-offs exist between reliability and speed empowers you to make better architectural decisions and debug network issues effectively.

Table of Contents

• 1. Introduction
  • Why understanding networking is crucial for backend developers
  • Short comparison of TCP and UDP
• 2. Deep Dive into TCP
  • 2.1. When to Use TCP?
  • 2.2. TCP Handshake: SYN, SYN-ACK, ACK
  • 2.3. Error Handling & Retransmission
  • 2.4. Advantages & Limitations of TCP
  • 2.5. TCP Code Examples in Golang
• 3. Deep Dive into UDP
  • 3.1. When to Use UDP?
  • 3.2. Stateless Communication and Speed
  • 3.3. Why UDP Doesn’t Guarantee Delivery
  • 3.4. Advantages & Limitations of UDP
  • 3.5. UDP Code Examples in Golang
• 4. Advanced Topics
  • 4.1. Concurrent TCP and UDP Servers Using Goroutines
  • 4.2. Implementing Protocol Buffers or JSON Data Serialization with TCP/UDP
  • 4.3. Handling Scalability and Performance Tuning
• 5. Best Practices & Common Pitfalls
  • 5.1. Resource Management and Avoiding Memory Leaks
  • 5.2. Handling Network Errors Gracefully
  • 5.3. Security Considerations in Networking
• 6. Conclusion
  • Summary of Key Learnings
  • Guidance for Choosing TCP vs UDP

1. Introduction

- Why understanding networking is crucial for backend developers

In today’s connected world, backend developers are expected to build reliable, scalable, and high-performance systems. Whether you’re designing REST APIs, microservices, real-time chat apps, or distributed systems, a solid understanding of computer networking is essential. Knowing how data is transmitted, how connections are established, and what trade-offs exist between reliability and speed empowers you to make better architectural decisions and debug network issues effectively.