How Digital Signatures Work
Forward Proxy vs Reverse Proxy
Cloud Comparison
12 Microservices Best Practices
12 Microservices Best Practices You Need to Know
→ Single Responsibility: Keep your services focused on one task to enhance maintainability.
→ Containers: Use containers to package applications and dependencies for consistent environments.
→ Orchestration: Manage and coordinate multiple services effectively using orchestration tools.
→ Resilience and Fault Tolerance: Build robust systems that can handle failures gracefully.
→ Scalability: Design your services to scale easily when user demand increases.
→ CI/CD: Implement continuous integration and delivery for faster and more reliable software updates.
→ Observability: Monitor and analyze system performance to identify and troubleshoot issues.
→ Security: Prioritize security measures to protect your services and data.
→ API Gateway: Use an API gateway to manage and route traffic to your microservices.
→ Stateless: Design services to be stateless for better scalability and efficiency.
→ DB Per Service: Isolate data storage by assigning a separate database for each service.
→ Event Driven Architecture: Use event-driven approaches for better communication between services.
Software Architectural Patterns
These patterns are crucial in designing robust software systems.
→ Event Driven: This pattern allows different components to communicate through events.
→ Monolithic: All parts of the application are combined into a single unit, making it easier to manage but harder to scale.
→ Microservices: This approach breaks down the application into smaller, independent services, enhancing flexibility and scaling.
→ MVC (Model-View-Controller): This pattern separates data processing, user interface, and user input to make systems more manageable.
→ Master-Slave: This method distributes tasks among servers, improving performance and reliability.
#SoftwareArchitecturalPatterns #SoftwarePatterns #architecture
Pass by Reference & Pass by Value
In Java, everything is passed by value, including object references. When you pass an object x to a method, you are passing a copy of the reference to the object, not the actual object itself. This means:
1. If you modify the object via the reference (e.g., x.setName(“newName”);), the changes will affect the original object because both the original reference and the copied reference point to the same object in memory.
2. If you reassign the reference inside the method (e.g., x = y;), the reassignment only affects the copy of the reference. The original reference outside the method remains unchanged.
Scalability
A Crash Course on Architectural Scalability
Scalability is the ability of a system to handle an increased workload without losing performance.
However, we can also look at scalability in terms of the scaling strategy.
Scalability is the system’s ability to handle an increased workload by repeatedly applying a cost-effective strategy. This means it can be difficult to scale a system beyond a certain point if the scaling strategy is not financially viable.
Three main bottlenecks to scalability are:
1 – Centralized components: This can become a single point of failure
2 – High Latency Components: These are components that perform time-consuming operations.
3 – Tight Coupling: Makes the components difficult to scale Therefore, to build a scalable system, we should follow the principles of statelessness, loose coupling, and asynchronous processing. Some common techniques for improving scalability are as follows:
- Load Balancing: Spread requests across multiple servers to prevent a single server from becoming a bottleneck.
- Caching: Store the most commonly request information in memory.
- Event-Driven Processing: Use an async processing approach to process long-running tasks.
- Sharding: Split a large dataset into smaller subsets called shards for horizontal scalability.
The Generative AI Landcape
Generative AI and LLMs are fast becoming a game-changer in the business world. Everyone wants to learn more about it. The landscape covers the following points:
1 – What is GenAI?
2 – Foundational Models and LLMs
3 – “Attention is All You Need” and its impact
4 – GenAI vs Traditional AI
5 – How to train a foundation model?
6 – The GenAI Development Stack (LLMs, Frameworks, Programming Languages, etc.)
7 – GenAI Applications
8 – Designing a simple GenAI application
9 – The AI Engineer Job Role
8 Popular Network Protocols
