Recap on system design for this week:

  • REST API Architecture style

  • Caching strategies Part 1 (5 strategies)

  • Differences Between API Gateway and Load Balancer

  • Linux commands. Part 1 (37 commands)

  • Diagram as Code

1. REST API Architecture style

1.1. Message formats:

  • XML

  • JSON

  • Other

1.2. ✅ Advantages:

  • Stateless: Scales easily

  • Cacheable: Improved performance

  • Uniform Interface: Standardized use

  • Scalable: Supports high request volumes

  • Interoperable: Works well with HTTP

  • Simple: Uses standard HTTP methods

  • Widely Adopted: Many resources available

1.3. ❌ Disadvantages

  • Over/Under-fetching: Fixed data returns

  • Multiple Endpoints: More requests for complex data

  • Versioning Issues: Changes can break clients

  • Limited Flexibility: Fixed data structures

  • Performance: Multiple trips for complex data.

  • Stateful Limitations: Not ideal for real-time operations

  • Nested Resource Complexity: Harder to manage nested data

1.4. 📋 Use cases

  • Web Applications. Backend for web apps with CRUD operations.

  • Mobile Apps. Backend support for mobile app data needs.

  • Public APIs. Offer services to third-party developers.

  • Integration. Connect different systems or services.

  • Content Delivery. Distribute content to various platforms.

  • Data Storage. Backend for apps needing database access.

  • E-Commerce. Manage products, orders, and user accounts.

  • Social Media Platforms. Handle user data, posts, and interactions.

  • IoT Devices. Communicate with and manage IoT devices.

  • Legacy System Interface. Modern interface for older systems.

❓ What API architecture style are you guys currently utilizing in your system?

2. Caching strategies: Cache Aside (Lazy Loading), Read-Through, Write-Through, Write-Around, Write-Behind (Write-Back)

2.1. 💤📌Cache-Aside (Lazy Loading)

  • Data is loaded into the cache on demand. If data is not found in the cache, the application retrieves it from the datastore and then stores it in the cache.

  • Pros:

    • 🎯 Only requested data is cached.

    • 🔄 Cache can be easily refreshed.

  • Cons:

    • ❌ Initial cache miss incurs a latency penalty.

    • 🔄 Manual intervention required for cache updates.

2.2. 📖🔍Read-Through

  • The cache is responsible for loading data from the datastore when a cache miss occurs.

  • Pros:

    • 🔄 Automatic data loading.

    • 🎯 Consistent cache and datastore data.

  • Cons:

    • ❌ Initial cache miss can slow down the application.

2.3. ✍️🔍Write-Through

  • Data is written to both the cache and the datastore synchronously (simultaneously).

  • Pros:

    • ✅ Immediate data consistency.

    • 🔄 Automatic data updates.

  • Cons:

    • ❌ Slower write operations due to dual writes.

2.4. ✏️🔄 Write-Around

  • Data is written directly to the datastore, bypassing the cache. The cache is updated later or during subsequent read operations.

  • Pros:

    • ⚡ Faster initial write operations.

    • 🎯 Reduces cache churn for less frequently accessed data.

  • Cons:

    • ❌ Subsequent reads might suffer from cache misses.

2.5. ✏️🔙Write-Behind (Write-Back)

  • Data is first written to the cache, and then asynchronously written to the datastore.

  • Pros:

    • ⚡ Fast write operations.

    • 🔄 Asynchronous updates optimize datastore writes.

  • Cons:

    • ❌ Risk of data loss if cache fails before async write.

❓ What combination of caching strategies are you guys currently implementing in your system?

3. Differences Between API Gateway and Load Balancer

While both API Gateways and Load Balancers manage incoming requests, they serve different primary roles. In many architectures, especially in microservices, you'll often find both an API gateway and a load balancer working in tandem. An API Gateway focuses on API management, offering a suite of tools for processing and directing API calls. In contrast, a Load Balancer's main job is to distribute traffic to ensure optimal server performance and availability.

API Gateway: 🌐 Primary Role: Manages and processes API requests.

🔹 Functions:

  • 🚦 Request Routing: Directs requests to the appropriate service.

  • 🧩 API Composition: Aggregates data from multiple services.

  • ⏳ Rate Limiting: Limits request frequency.

  • 🔒 Security: Manages authentication and API keys.

  • 🚀 Caching: Improves response times with stored data.

  • 🔄 Request/Response Transformation: Modifies data formats.

  • 📊 Analytics & Monitoring: Tracks API usage.

  • 🔍 Service Discovery: Identifies available services.

  • ❌ Error Handling & Retry: Manages failed requests.

  • 🔧 Protocol Translation: Converts communication protocols.

🔹 Use Cases: Microservices, API management, data aggregation, securing APIs.

Load Balancer: ⚖️ Primary Role: Distributes incoming network traffic.

🔹 Functions:

  • 🌊 Traffic Distribution: Prevents server overloads.

  • ❤️ Health Checks: Monitors server health.

  • 🔐 SSL Termination: Handles SSL/TLS processing.

  • 🧬 Session Persistence: Maintains client-server connection.

  • 📡 Layer 4 and Layer 7 Load Balancing: Operates at transport and application layers.

🔹 Use Cases: High availability, fault tolerance, application scaling, large-scale web traffic management.

Key Differences:

  • 🎯 Focus: API gateway = API management. Load balancer = traffic distribution.

  • 🔍 Granularity: API gateway = fine-grained control. Load balancer = broader network level.

  • 🛠️ Features: API gateway = tailored for API management. Load balancer = traffic and health management.

In modern architectures, especially microservices, both API gateways and load balancers often work together. The load balancer manages traffic, while the API gateway handles API requests.

❓ Are you guys utilizing both API gateways and load balancers in your infrastructure?

4. Linux commands. Part 1 (37 commands).

File Operations 📂:

  • ls 📄: List directory contents

    • Example: ls -l

  • cp 📋: Copy files and directories

    • Example: cp source.txt destination.txt

  • mv 🚚: Move or rename files and directories

    • Example: mv oldname.txt newname.txt

  • rm 🗑️: Remove files or directories

    • Example: rm unwanted.txt

  • touch ✍️: Create an empty file

    • Example: touch newfile.txt

  • cat 📖: Concatenate and display file content

    • Example: cat file.txt

Directory Operations 📁:

  • pwd 📍: Print working directory

    • Example: pwd

  • cd 🚪: Change directory

    • Example: cd /home/user/documents

  • mkdir 🆕📁: Make directories

    • Example: mkdir new_directory

  • rmdir 🚫📁: Remove empty directories

    • Example: rmdir empty_directory

System Info ℹ️:

  • uname 🖥️: Display system information

    • Example: uname -a

  • top 📊: Display system tasks

    • Example: top

  • df 💽: Disk space usage of file system

    • Example: df -h

  • free 🧠: Display memory usage

    • Example: free -m

  • ps 🔄: Display process status

    • Example: ps aux

Permissions 🔒:

  • chmod 🔑: Change file mode bits

    • Example: chmod 755 script.sh

  • chown 👤: Change file owner and group

    • Example: chown user:group file.txt

  • chgrp 👥: Change group ownership

    • Example: chgrp group file.txt

Networking 🌐:

  • ping 📡: Send ICMP ECHO_REQUEST to network hosts

    • Example: ping google.com

  • netstat 🌐📊: Network statistics

    • Example: netstat -tuln

  • ifconfig 🌐🛠️: Display or configure a network interface

    • Example: ifconfig eth0

  • ssh 🛡️: Secure shell client (remote login program)

    • Example: ssh user@hostname

  • scp 📤: Secure copy (remote file copy program)

    • Example: scp file.txt user@hostname:/path/

Compression/Archiving 🗜️:

  • tar 📦: Tape archiver

    • Example: tar -czvf archive.tar.gz folder/

  • gzip 🗜️: Compress or expand files

    • Example: gzip file.txt

  • gunzip 🗜️🔓: Decompress files

    • Example: gunzip file.txt.gz

  • zip 🤐: Package and compress files

    • Example: zip archive.zip file1.txt file2.txt

  • unzip 🤐🔓: Extract compressed files in a ZIP archive

    • Example: unzip archive.zip

Package Management 📦:

  • apt-get 📥: APT package handling utility (Debian-based systems)

    • Example: sudo apt-get install package_name

  • yum 📥: Package manager for RPM-based systems

    • Example: sudo yum install package_name

  • dpkg 📥: Package manager for Debian

    • Example: sudo dpkg -i package.deb

Text Processing 🔍:

  • grep 🔎: Search text

    • Example: grep "pattern" file.txt

  • sed ✂️: Stream editor

    • Example: sed 's/old/new/g' file.txt

  • awk 📝: Pattern scanning and text processing language

    • Example: awk '{print $1}' file.txt

Help & Output 📘:

  • man 📚: Display manual pages

    • Example: man ls

  • echo 🔊: Display a line of text

    • Example: echo "Hello, World!"

Process Management ❌:

  • kill ☠️: Terminate processes

    • Example: kill -9 12345 (where 12345 is a process ID)

❓ Which Linux commands do you find most frequently used in your daily operations?

5. Diagram as Code

Diagrams (Diagram as Code) allows you to create cloud system architecture diagrams using Python.

Originally designed for quick prototyping of new architectures without specialized design tools, it can also be employed to visualize or describe existing systems. The tool is versatile, supporting a wide range of major cloud providers like AWS, Azure, GCP, Kubernetes, Alibaba Cloud, and Oracle Cloud, as well as On-Premise nodes, SaaS platforms, and key programming languages and frameworks. One of its standout features is its compatibility with version control systems, enabling you to track changes to your architecture diagrams over time. Note: While Diagrams excels at creating architecture diagrams, it neither manages actual cloud resources nor generates cloud formation or terraform scripts. For a deeper dive, check out the optional 6-minute video below.

❓ Which tool or software are you guys utilizing to generate diagrams programmatically?

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