What is Connection Pooling?
Connection pooling is a mechanism that allows the reuse of established database connections. Instead of creating and destroying connections for each database request (which is resource-intensive), a pool of connections is maintained, and these connections are shared among requests.
Benefits of Using Connection Pooling
✅Performance:
Reuses existing connections to avoid the overhead of frequently opening and closing them.
✅Scalability:
Manages multiple simultaneous requests efficiently with limits like Min Pool Size and Max Pool Size.
✅Resource Management:
Max Pool Size: Prevents overloading the database.
Min Pool Size: Ensures connections are available during high traffic.
✅Reduced Latency:
Pre-created connections allow quicker database access, improving response times.
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Connection pooling is a mechanism that allows the reuse of established database connections. Instead of creating and destroying connections for each database request (which is resource-intensive), a pool of connections is maintained, and these connections are shared among requests.
Benefits of Using Connection Pooling
✅Performance:
Reuses existing connections to avoid the overhead of frequently opening and closing them.
✅Scalability:
Manages multiple simultaneous requests efficiently with limits like Min Pool Size and Max Pool Size.
✅Resource Management:
Max Pool Size: Prevents overloading the database.
Min Pool Size: Ensures connections are available during high traffic.
✅Reduced Latency:
Pre-created connections allow quicker database access, improving response times.
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✅ The Circuit Breaker pattern prevents repeated calls to failing services in distributed systems, handling failures gracefully and avoiding cascading issues.
Example Scenario
Imagine an e-commerce system where the payment gateway might become unavailable. A circuit breaker prevents the system from continuously sending payment requests, which could worsen the problem.
💡Above is a simplified implementation using a Policy library like Polly, which is commonly used for implementing the Circuit Breaker pattern in .NET applications.
How It Works
1️⃣ The Polly Circuit Breaker policy monitors exceptions.
2️⃣ After 3 consecutive failures, the circuit breaker transitions to the Open State.
3️⃣ In the Open State, requests are immediately blocked for 10 seconds.
4️⃣ After 10 seconds, it transitions to the Half-Open State, allowing a few test requests.
5️⃣ If a test request succeeds, the circuit breaker resets to the Closed State.
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Example Scenario
Imagine an e-commerce system where the payment gateway might become unavailable. A circuit breaker prevents the system from continuously sending payment requests, which could worsen the problem.
💡Above is a simplified implementation using a Policy library like Polly, which is commonly used for implementing the Circuit Breaker pattern in .NET applications.
How It Works
1️⃣ The Polly Circuit Breaker policy monitors exceptions.
2️⃣ After 3 consecutive failures, the circuit breaker transitions to the Open State.
3️⃣ In the Open State, requests are immediately blocked for 10 seconds.
4️⃣ After 10 seconds, it transitions to the Half-Open State, allowing a few test requests.
5️⃣ If a test request succeeds, the circuit breaker resets to the Closed State.
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✅In-Memory Cache
Cache stored within the memory of the application (e.g., server's RAM).Limited to the application instance. If the app restarts, the cache is lost. Faster since it's local to the application. Limited by the memory of the single application server. Only supports a single application instance.
✅Redis Cache
External cache server that stores data in memory and can be accessed by multiple applications. Persistent across application restarts, accessible from multiple servers. Slightly slower because it's accessed over the network. Highly scalable across multiple servers. Allows multiple applications/instances to share the same cache.
💡Key Considerations
1.Use in-memory cache for simple, single-server applications or temporary caching.
2.Use Redis cache for distributed systems or when multiple servers need to share the same cached data.
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Cache stored within the memory of the application (e.g., server's RAM).Limited to the application instance. If the app restarts, the cache is lost. Faster since it's local to the application. Limited by the memory of the single application server. Only supports a single application instance.
✅Redis Cache
External cache server that stores data in memory and can be accessed by multiple applications. Persistent across application restarts, accessible from multiple servers. Slightly slower because it's accessed over the network. Highly scalable across multiple servers. Allows multiple applications/instances to share the same cache.
💡Key Considerations
1.Use in-memory cache for simple, single-server applications or temporary caching.
2.Use Redis cache for distributed systems or when multiple servers need to share the same cached data.
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Pooling Pattern
✅ The pooling pattern is a design technique where a finite set of reusable objects (or resources) is maintained in a pool. Instead of creating and destroying objects repeatedly, the system reuses objects from the pool, improving performance and resource management.
How It Works
💡Initialization: A pool is created with a predefined number of objects (e.g., database connections, threads, or sockets).
💡Checkout: When a client needs an object, it "borrows" one from the pool.
💡Usage: The client uses the borrowed object for its operation.
💡Check-in: After use, the object is returned to the pool, making it available for others.
✨Key Pros and Cons
Pros
Boosts performance by reusing objects.
Efficiently manages limited resources.
Reduces object creation and garbage collection.
Cons
Adds complexity to implementation.
Risk of delays if the pool size is insufficient.
Memory can be wasted on idle objects
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✅ The pooling pattern is a design technique where a finite set of reusable objects (or resources) is maintained in a pool. Instead of creating and destroying objects repeatedly, the system reuses objects from the pool, improving performance and resource management.
How It Works
💡Initialization: A pool is created with a predefined number of objects (e.g., database connections, threads, or sockets).
💡Checkout: When a client needs an object, it "borrows" one from the pool.
💡Usage: The client uses the borrowed object for its operation.
💡Check-in: After use, the object is returned to the pool, making it available for others.
✨Key Pros and Cons
Pros
Boosts performance by reusing objects.
Efficiently manages limited resources.
Reduces object creation and garbage collection.
Cons
Adds complexity to implementation.
Risk of delays if the pool size is insufficient.
Memory can be wasted on idle objects
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Setting a Timeout in HttpClient
✅ The timeout feature of HttpClient is crucial for ensuring your application remains responsive, especially when dealing with external web services that might be slow or unavailable. Always set a reasonable timeout to prevent your app from hanging and offer a better user experience.
Why Set a Timeout?
A timeout ensures that if a request takes too long, your app doesn’t get stuck waiting forever. It's essential for maintaining responsiveness in your app.
💡Key Points:
Timeout: Set the time limit for how long a request should wait for a response.
Exception: If the request exceeds the timeout, a TaskCanceledException is thrown.
Adjust as Needed: Increase or decrease timeout duration depending on your app’s needs.
✨ Why It’s Important:
Prevents unresponsive apps.
Improves user experience.
Keeps control over external requests.
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✅ The timeout feature of HttpClient is crucial for ensuring your application remains responsive, especially when dealing with external web services that might be slow or unavailable. Always set a reasonable timeout to prevent your app from hanging and offer a better user experience.
Why Set a Timeout?
A timeout ensures that if a request takes too long, your app doesn’t get stuck waiting forever. It's essential for maintaining responsiveness in your app.
💡Key Points:
Timeout: Set the time limit for how long a request should wait for a response.
Exception: If the request exceeds the timeout, a TaskCanceledException is thrown.
Adjust as Needed: Increase or decrease timeout duration depending on your app’s needs.
✨ Why It’s Important:
Prevents unresponsive apps.
Improves user experience.
Keeps control over external requests.
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✅ RestSharp is a powerful library that simplifies HTTP requests in .NET. It automatically handles serialization & deserialization, making API calls much easier than HttpClient.
💡Why use RestSharp?
✔️ Easy-to-use API
✔️ Auto JSON serialization/deserialization
✔️ Supports authentication, retries, and custom headers
✔️ More readable & concise than HttpClient
✔️ Handles API authentication easily
✔️ Built-in JSON handling
💡 Key Features of RestSharp
▫️Easy API Calls: Makes GET, POST, PUT, DELETE requests simple.
▫️Serialization & Deserialization: Supports automatic JSON/XML serialization.
▫️Authentication Support: Handles OAuth, Basic, Bearer Token, etc.
▫️Automatic Parameter Handling: Easily adds URL/query/body parameters.
▫️Asynchronous Requests: Supports async API calls with await.
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💡Why use RestSharp?
✔️ Easy-to-use API
✔️ Auto JSON serialization/deserialization
✔️ Supports authentication, retries, and custom headers
✔️ More readable & concise than HttpClient
✔️ Handles API authentication easily
✔️ Built-in JSON handling
💡 Key Features of RestSharp
▫️Easy API Calls: Makes GET, POST, PUT, DELETE requests simple.
▫️Serialization & Deserialization: Supports automatic JSON/XML serialization.
▫️Authentication Support: Handles OAuth, Basic, Bearer Token, etc.
▫️Automatic Parameter Handling: Easily adds URL/query/body parameters.
▫️Asynchronous Requests: Supports async API calls with await.
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String vs. StringBuilder in C#
✅In C#, both string and StringBuilder are used to handle text, but they behave differently in terms of performance and mutability. Let’s explore the differences with a simple example.
🔹 Immutable string (Slow for Modifications)
A string is immutable, meaning that every modification creates a new string in memory.
📌 Explanation:
Each time we append " World", a new string is created in memory.
The old string remains in memory until garbage collection removes it, which slows down performance when dealing with many modifications.
🔹 Mutable StringBuilder (Faster for Modifications)
StringBuilder is mutable, meaning it modifies the existing object instead of creating a new one.
📌 Explanation:
StringBuilder does not create a new object on each modification.
It modifies the same memory location, making it much faster and memory-efficient for large-scale string operations.
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✅In C#, both string and StringBuilder are used to handle text, but they behave differently in terms of performance and mutability. Let’s explore the differences with a simple example.
🔹 Immutable string (Slow for Modifications)
A string is immutable, meaning that every modification creates a new string in memory.
📌 Explanation:
Each time we append " World", a new string is created in memory.
The old string remains in memory until garbage collection removes it, which slows down performance when dealing with many modifications.
🔹 Mutable StringBuilder (Faster for Modifications)
StringBuilder is mutable, meaning it modifies the existing object instead of creating a new one.
📌 Explanation:
StringBuilder does not create a new object on each modification.
It modifies the same memory location, making it much faster and memory-efficient for large-scale string operations.
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✅In C#, == and .Equals() are used to compare objects, but they work differently depending on the type being compared.
🔹== Operator:
Compares references by default (checks if two objects are the same in memory).
For value types (like int, float, struct), compares values directly.
Can be overridden for custom class comparisons.
🔹.Equals() Method:
Inherits from Object; compares references by default, like ==.
Often overridden (e.g., string, int) to compare values, not references.
💡When to Use:
==: For reference comparison or value types.
.Equals(): For comparing object contents/values, especially in reference types.
✨Key Takeaways:
==: Reference comparison by default; can be overridden for custom types.
.Equals(): Value comparison for value types and can be overridden for reference types to compare actual content.
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🔹== Operator:
Compares references by default (checks if two objects are the same in memory).
For value types (like int, float, struct), compares values directly.
Can be overridden for custom class comparisons.
🔹.Equals() Method:
Inherits from Object; compares references by default, like ==.
Often overridden (e.g., string, int) to compare values, not references.
💡When to Use:
==: For reference comparison or value types.
.Equals(): For comparing object contents/values, especially in reference types.
✨Key Takeaways:
==: Reference comparison by default; can be overridden for custom types.
.Equals(): Value comparison for value types and can be overridden for reference types to compare actual content.
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✅Optimizing HttpClient Management in .NET
Socket exhaustion occurs when too many open sockets exceed system limits, leading to connection failures. This happens if you create and dispose of HttpClient instances in a loop (e.g., inside a using block), preventing socket reuse and causing port exhaustion.
💡Solutions to Prevent Socket Exhaustion:
1️⃣ Using IHttpClientFactory:
IHttpClientFactory is an interface that is used to automatically manage the lifecycle and configuration of HttpClient instances. It prevents socket exhaustion and properly handles DNS changes.
2️⃣ Using SocketsHttpHandler for Fine-Grained Configuration:
When using HttpClient as Singleton or Static, you can use SocketsHttpHandler along with settings like PooledConnectionLifetime to optimize connections and network resources.
SocketsHttpHandler gives you more control over network resources, helping resolve issues like socket exhaustion and DNS changes management.
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Socket exhaustion occurs when too many open sockets exceed system limits, leading to connection failures. This happens if you create and dispose of HttpClient instances in a loop (e.g., inside a using block), preventing socket reuse and causing port exhaustion.
💡Solutions to Prevent Socket Exhaustion:
1️⃣ Using IHttpClientFactory:
IHttpClientFactory is an interface that is used to automatically manage the lifecycle and configuration of HttpClient instances. It prevents socket exhaustion and properly handles DNS changes.
2️⃣ Using SocketsHttpHandler for Fine-Grained Configuration:
When using HttpClient as Singleton or Static, you can use SocketsHttpHandler along with settings like PooledConnectionLifetime to optimize connections and network resources.
SocketsHttpHandler gives you more control over network resources, helping resolve issues like socket exhaustion and DNS changes management.
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Retry pattern
✅ The RetryAsync method retries an operation (in this case, DoUnstableOperation) up to a specified number of times (maxRetryAttempts) with a delay (pauseBetweenFailures) between each attempt. You can modify the pauseBetweenFailures to increase after each retry for exponential backoff If the operation succeeds within the retry limit, it prints a success message; otherwise, it reports the failure.
✅ Useful for handling transient faults such as network failures, API timeouts, or database connection drops.
Avoids failing immediately on the first failure, improving resilience of the system.
💡Also, you can use Polly to implement the Retry pattern.
✅ The RetryAsync method retries an operation (in this case, DoUnstableOperation) up to a specified number of times (maxRetryAttempts) with a delay (pauseBetweenFailures) between each attempt. You can modify the pauseBetweenFailures to increase after each retry for exponential backoff If the operation succeeds within the retry limit, it prints a success message; otherwise, it reports the failure.
✅ Useful for handling transient faults such as network failures, API timeouts, or database connection drops.
Avoids failing immediately on the first failure, improving resilience of the system.
💡Also, you can use Polly to implement the Retry pattern.
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✅Polly is a powerful library for handling errors and implementing resilient patterns like retries, circuit breakers, and timeouts in .NET. It's most effective when used with HttpClientFactory for managing HttpClient instances efficiently.
📌Explanation:
HttpClientFactory: It's the best practice to use HttpClientFactory when working with Polly and HttpClient. This ensures that HttpClient instances are managed efficiently, preventing socket exhaustion and improving performance.
Retry Policy: Retries the request up to 3 times if it fails.
Circuit Breaker: Prevents further requests if 3 failures occur within a minute.
Timeout Policy: Cancels the request if it takes longer than 10 seconds.
Fallback Policy: Returns a default response if all retries and circuit breakers fail.
By combining these policies and using HttpClientFactory, you can create a robust and efficient error-handling strategy for your HTTP requests in .NET.
📌Explanation:
HttpClientFactory: It's the best practice to use HttpClientFactory when working with Polly and HttpClient. This ensures that HttpClient instances are managed efficiently, preventing socket exhaustion and improving performance.
Retry Policy: Retries the request up to 3 times if it fails.
Circuit Breaker: Prevents further requests if 3 failures occur within a minute.
Timeout Policy: Cancels the request if it takes longer than 10 seconds.
Fallback Policy: Returns a default response if all retries and circuit breakers fail.
By combining these policies and using HttpClientFactory, you can create a robust and efficient error-handling strategy for your HTTP requests in .NET.
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✅Keyed Services in .NET 8 – A Solution for Multiple Implementations of an Interface!
Have you ever needed an interface with multiple implementations? For example, a notification system that sends messages via both SMS and Email. The challenge is:
🔹 How do we specify which implementation to use in Dependency Injection (DI)?
🔹 Why were old methods like Factory Pattern or Named Services problematic?
🔹 What smart solution does .NET 8 offer?
🚀 The answer: Keyed Services! This new feature in .NET 8 allows us to register multiple implementations of the same interface using unique keys, making it easy to retrieve the desired one wherever needed.
📌 Conclusion
🔹 Keyed Services in .NET 8 make it easy to manage multiple implementations of an interface.
🔹 This approach improves flexibility and code readability while reducing complexity.
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Have you ever needed an interface with multiple implementations? For example, a notification system that sends messages via both SMS and Email. The challenge is:
🔹 How do we specify which implementation to use in Dependency Injection (DI)?
🔹 Why were old methods like Factory Pattern or Named Services problematic?
🔹 What smart solution does .NET 8 offer?
🚀 The answer: Keyed Services! This new feature in .NET 8 allows us to register multiple implementations of the same interface using unique keys, making it easy to retrieve the desired one wherever needed.
📌 Conclusion
🔹 Keyed Services in .NET 8 make it easy to manage multiple implementations of an interface.
🔹 This approach improves flexibility and code readability while reducing complexity.
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✅As our applications grow, their complexity grows as well. Without clear structure, we face code that is hard to test, maintain, or extend.
SOLID principles offer proven guidelines to design flexible, modular, and maintainable software systems.
🧩 S — Single Responsibility Principle (SRP)
A class should have only one reason to change.
Each class should be responsible for one specific task.
When a class handles multiple concerns, it becomes harder to test, understand, and modify.
✅ Real-World Example
A poor design would do all(Fetch,Format,Export,Send Data) of that in one class.
A better design would follow SRP:
Easier Testing: You can now test EmailSender independently without worrying about the entire report generation.
Flexibility: If you need to export to Excel instead of PDF, you only need to change the PdfExporter class.
Clearer Code: Anyone reading the code can immediately understand the responsibilities of each class.
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SOLID principles offer proven guidelines to design flexible, modular, and maintainable software systems.
🧩 S — Single Responsibility Principle (SRP)
A class should have only one reason to change.
Each class should be responsible for one specific task.
When a class handles multiple concerns, it becomes harder to test, understand, and modify.
✅ Real-World Example
A poor design would do all(Fetch,Format,Export,Send Data) of that in one class.
A better design would follow SRP:
Easier Testing: You can now test EmailSender independently without worrying about the entire report generation.
Flexibility: If you need to export to Excel instead of PDF, you only need to change the PdfExporter class.
Clearer Code: Anyone reading the code can immediately understand the responsibilities of each class.
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🔗 more tips: t.me/DotNetTipsChl
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✅Clean Architecture Tip: Use DI in Your Factory!
In Clean Architecture, the goal is to separate responsibilities, reduce coupling, and build systems that are testable and easy to extend.
One area that often violates this principle is the way we implement factories.
In "Tight Coupling in Static Factories", we're directly newing up classes inside the factory.
This introduces tight coupling, and the factory knows too much about its dependencies.
In Inject Dependencies into Your Factory,Refactor the factory to rely on the DI container instead.
🔍This Works Better
Looser Coupling: The factory doesn’t directly depend on specific implementations.
Better Testability: Easier to mock or replace dependencies in tests.
Open for Extension: You can add new strategies without changing the factory.
Lifecycle Management: DI handles scopes like Singleton / Scoped/ Transient.
📌DI in factories isn’t a trick it’s a solid move for maintainable architecture
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In Clean Architecture, the goal is to separate responsibilities, reduce coupling, and build systems that are testable and easy to extend.
One area that often violates this principle is the way we implement factories.
In "Tight Coupling in Static Factories", we're directly newing up classes inside the factory.
This introduces tight coupling, and the factory knows too much about its dependencies.
In Inject Dependencies into Your Factory,Refactor the factory to rely on the DI container instead.
🔍This Works Better
Looser Coupling: The factory doesn’t directly depend on specific implementations.
Better Testability: Easier to mock or replace dependencies in tests.
Open for Extension: You can add new strategies without changing the factory.
Lifecycle Management: DI handles scopes like Singleton / Scoped/ Transient.
📌DI in factories isn’t a trick it’s a solid move for maintainable architecture
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✅Why Should You Make Your Classes Immutable?
Immutable classes — objects that can’t be modified after creation — are a powerful concept every developer should understand.
📌 Instead of allowing anyone to change a class's properties freely, you assign all values once, usually through the constructor.
✅ Benefits of Immutable Classes
Safety: No accidental data changes
Testability: Easier to write predictable unit tests
Thread Safety: Great for multi-threaded environments
Maintainability: Easier to debug and reason about
🔥 Pro Tip:
When you want to "change" something in a record, just create a new modified copy using with:
Now you have a new object, and the original remains unchanged.
📌 Bottom Line:
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Immutable classes — objects that can’t be modified after creation — are a powerful concept every developer should understand.
📌 Instead of allowing anyone to change a class's properties freely, you assign all values once, usually through the constructor.
✅ Benefits of Immutable Classes
Safety: No accidental data changes
Testability: Easier to write predictable unit tests
Thread Safety: Great for multi-threaded environments
Maintainability: Easier to debug and reason about
🔥 Pro Tip:
When you want to "change" something in a record, just create a new modified copy using with:
Now you have a new object, and the original remains unchanged.
📌 Bottom Line:
Immutability = safer, cleaner, more professional code.🔗 more videos: youtube.com/@mnegah
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✅Clean Code in Action: Open/Closed Principle with Strategy Pattern
One of the most important SOLID principles is the Open/Closed Principle:
“Software entities should be open for extension, but closed for modification.”
But how do we apply that in real-world code?
Use Case: Shipping Cost Calculator
Let’s say you need to calculate shipping costs based on different shipping types (Standard, Express, etc.).
In bad design, Every time a new type is added, you modify this method. That breaks OCP and leads to fragile code.
In better design, Now you can extend the system by adding new strategies, not modifying existing code. That’s OCP in action!
Bonus Tip: Combine with Factory Pattern
To dynamically select a strategy at runtime (e.g., based on user input), use a factory to resolve the correct strategy — while still keeping your system extensible and loosely coupled.
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One of the most important SOLID principles is the Open/Closed Principle:
“Software entities should be open for extension, but closed for modification.”
But how do we apply that in real-world code?
Use Case: Shipping Cost Calculator
Let’s say you need to calculate shipping costs based on different shipping types (Standard, Express, etc.).
In bad design, Every time a new type is added, you modify this method. That breaks OCP and leads to fragile code.
In better design, Now you can extend the system by adding new strategies, not modifying existing code. That’s OCP in action!
Bonus Tip: Combine with Factory Pattern
To dynamically select a strategy at runtime (e.g., based on user input), use a factory to resolve the correct strategy — while still keeping your system extensible and loosely coupled.
🔗 more videos: youtube.com/@mnegah
🔗 more tips: t.me/DotNetTipsChl
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✅Abstraction: The Power Behind Clean and Scalable Architecture
Abstraction isn't just a concept — it's a cornerstone of clean, maintainable, and scalable software.
If you’ve ever used HttpClient, ILogger, or even Stream, you’ve already used Abstraction.
What Is Abstraction?
It’s working with something without knowing how it works.
Just like:
You drive a car without understanding its engine.
You save data to a Stream without caring whether it writes to disk, memory, or network.
🔁 Want to switch from file to cloud storage?
Just change the injected implementation — no need to touch ReportService!
💡 Why It Matters:
-Enables loose coupling
-Improves testability
-Supports Dependency Injection
-Foundation of the SOLID principles
🎯 Final Thought
Abstraction is the art of hiding complexity and exposing simplicity.
Once you understand it, other patterns like Strategy, Factory, and Clean Architecture feel natural.
🔗 more videos: youtube.com/@mnegah
🔗 more tips: t.me/DotNetTipsChl
Abstraction isn't just a concept — it's a cornerstone of clean, maintainable, and scalable software.
If you’ve ever used HttpClient, ILogger, or even Stream, you’ve already used Abstraction.
What Is Abstraction?
It’s working with something without knowing how it works.
Just like:
You drive a car without understanding its engine.
You save data to a Stream without caring whether it writes to disk, memory, or network.
🔁 Want to switch from file to cloud storage?
Just change the injected implementation — no need to touch ReportService!
💡 Why It Matters:
-Enables loose coupling
-Improves testability
-Supports Dependency Injection
-Foundation of the SOLID principles
🎯 Final Thought
Abstraction is the art of hiding complexity and exposing simplicity.
Once you understand it, other patterns like Strategy, Factory, and Clean Architecture feel natural.
🔗 more videos: youtube.com/@mnegah
🔗 more tips: t.me/DotNetTipsChl
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✅ When a Child Class Breaks the Rules Liskov Substitution Principle in Action
🔍 What Is the Liskov Substitution Principle (LSP)?
"Objects of a subclass should be replaceable for objects of the superclass without breaking the application."
That means: if your code works with a base class, it should also work smoothly with any of its derived classes—without throwing errors or changing behavior.
What’s Wrong Here?
The CashPayment class is pretending to be a proper payment method but can’t actually process payments.
This violates LSP because you can't substitute the base class with its child safely.
How to Fix It
Instead of forcing every payment type into one base class, use an interface for only those that can process payments:
💡 Key Takeaways
Never force subclasses to implement behavior they can't support
Use interfaces or better-designed base classes
Following LSP keeps your code robust, predictable, and extendable
🔗 more videos: youtube.com/@mnegah
🔗 more tips: t.me/DotNetTipsChl
🔍 What Is the Liskov Substitution Principle (LSP)?
"Objects of a subclass should be replaceable for objects of the superclass without breaking the application."
That means: if your code works with a base class, it should also work smoothly with any of its derived classes—without throwing errors or changing behavior.
What’s Wrong Here?
The CashPayment class is pretending to be a proper payment method but can’t actually process payments.
This violates LSP because you can't substitute the base class with its child safely.
How to Fix It
Instead of forcing every payment type into one base class, use an interface for only those that can process payments:
💡 Key Takeaways
Never force subclasses to implement behavior they can't support
Use interfaces or better-designed base classes
Following LSP keeps your code robust, predictable, and extendable
🔗 more videos: youtube.com/@mnegah
🔗 more tips: t.me/DotNetTipsChl
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✅ Native AOT in .NET: How to Build Blazing Fast Apps
Native AOT (Ahead-Of-Time) compilation is a key feature in .NET 8, compiling your apps into native machine code at publish time instead of runtime. This removes the JIT (Just-In-Time) compiler, offering great performance boosts:
🔹 Faster startup times
🔹 Smaller executables
🔹 Lower memory usage
🔹 No .NET runtime needed on target machine
✅ Ideal for:
- Microservices and cloud-native apps
- Command-line tools (CLI)
- High-performance APIs
- Apps deployed at scale
- Restricted environments (no JIT)
Not ideal for:
- Apps relying heavily on reflection or dynamic code
- Complex desktop apps with runtime behaviors
Important Notes
- Reflection: Native AOT lacks full support for dynamic reflection by default. You may need 'rd.xml' or trimming configuration.
- Testing: Full testing is crucial. Behavior may differ from JIT-compiled apps.
more videos: youtube.com/@mnegah
more tips: t.me/DotNetTipsChl
Native AOT (Ahead-Of-Time) compilation is a key feature in .NET 8, compiling your apps into native machine code at publish time instead of runtime. This removes the JIT (Just-In-Time) compiler, offering great performance boosts:
🔹 Faster startup times
🔹 Smaller executables
🔹 Lower memory usage
🔹 No .NET runtime needed on target machine
✅ Ideal for:
- Microservices and cloud-native apps
- Command-line tools (CLI)
- High-performance APIs
- Apps deployed at scale
- Restricted environments (no JIT)
Not ideal for:
- Apps relying heavily on reflection or dynamic code
- Complex desktop apps with runtime behaviors
Important Notes
- Reflection: Native AOT lacks full support for dynamic reflection by default. You may need 'rd.xml' or trimming configuration.
- Testing: Full testing is crucial. Behavior may differ from JIT-compiled apps.
more videos: youtube.com/@mnegah
more tips: t.me/DotNetTipsChl
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✅ 𝐆𝐫𝐞𝐚𝐭 𝐧𝐞𝐰𝐬: Google has a lot of free AI courses
It requires neither prerequisites nor costs. You can also start from scratch.
The 10 courses I recommend:
🔹 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐨𝐟 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈
A short and fluent course, you will learn to build an AI app with Google tools. About 45 minutes.
Link: https://lnkd.in/dTS4MGpW
🔹 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐨𝐟 𝐋𝐚𝐫𝐠𝐞 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐌𝐨𝐝𝐞𝐥𝐬 (𝐋𝐋𝐌)
You'll quickly understand what an LLM is, where it's used, and how to make it better. About 45 minutes.
Link: https://lnkd.in/dsye9hKm
🔹 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐥𝐞 𝐀𝐈
It tells you how Google implements the principles of responsible AI in its products; you will learn about the 7 principles.
Link: https://lnkd.in/dhXaURQE
🔹 𝐅𝐮𝐧𝐝𝐚𝐦𝐞𝐧𝐭𝐚𝐥𝐬 𝐨𝐟 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞
A brief summary of the LLM and Responsible AI courses.
Link: https://lnkd.in/dqe834b5
🔹 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐈𝐦𝐚𝐠𝐞 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧
Introduction to Diffusion Models: Stars of the AI Imaging World.
Link: https://lnkd.in/dX-ieCJd
To view the rest of the content, click the link below
https://shorturl.at/cWMnO
It requires neither prerequisites nor costs. You can also start from scratch.
The 10 courses I recommend:
🔹 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐨𝐟 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈
A short and fluent course, you will learn to build an AI app with Google tools. About 45 minutes.
Link: https://lnkd.in/dTS4MGpW
🔹 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐨𝐟 𝐋𝐚𝐫𝐠𝐞 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐌𝐨𝐝𝐞𝐥𝐬 (𝐋𝐋𝐌)
You'll quickly understand what an LLM is, where it's used, and how to make it better. About 45 minutes.
Link: https://lnkd.in/dsye9hKm
🔹 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐢𝐛𝐥𝐞 𝐀𝐈
It tells you how Google implements the principles of responsible AI in its products; you will learn about the 7 principles.
Link: https://lnkd.in/dhXaURQE
🔹 𝐅𝐮𝐧𝐝𝐚𝐦𝐞𝐧𝐭𝐚𝐥𝐬 𝐨𝐟 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞
A brief summary of the LLM and Responsible AI courses.
Link: https://lnkd.in/dqe834b5
🔹 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐈𝐦𝐚𝐠𝐞 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧
Introduction to Diffusion Models: Stars of the AI Imaging World.
Link: https://lnkd.in/dX-ieCJd
To view the rest of the content, click the link below
https://shorturl.at/cWMnO
lnkd.in
LinkedIn
This link will take you to a page that’s not on LinkedIn
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