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Showing posts with the label API Design

Observability Done Right: Best Practices and Anti-Patterns for Effective System Monitoring

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  WHAT Observability is a concept that refers to the ability to gain insights into the behavior and performance of complex systems. In the context of software engineering, observability involves the collection, analysis, and visualization of data from software applications, infrastructure, and other components of a system. In the animal kingdom, observability plays a critical role in survival, allowing animals to monitor their surroundings, detect threats, and find food. Dolphins use echolocation to observe their surroundings. They emit high-frequency sounds that bounce off objects, allowing them to create a 3D map of their environment. Thanks for reading Knowledge Cafe! Subscribe for free to receive new posts and support my work. Subscribed WHY In today's era, architectures are becoming increasingly large, complex, and fast-paced due to the faster development and deployment of software by distributed teams with the help of DevOps, continuous delivery, and agile development methodo...
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Under the Hood: Understanding the Gossip Protocol in Apache Cassandra

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  Gossip Protocol Apache Cassandra is a highly scalable and distributed NoSQL database management system designed to handle large amounts of data across many commodity servers. It was developed at Facebook and later became an Apache Software Foundation project. Cassandra offers a number of key features, including: Linear scalability, high availability, Predictive data consistency, flexible data modeling and high performance. What is Gossip Protocol The Gossip protocol is a key component of the Apache Cassandra distributed database system. It is used for node communication and failure detection within the cluster. The following is how it works: Each node in the Cassandra cluster maintains a list of all other nodes in the cluster and information about their status. The Gossip protocol operates in rounds, where each node sends its state information to a randomly selected set of other nodes. The receiving nodes update their state information based on the information received from their...
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Unlocking the Potential of Your Web Application with a CDN

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  What is CDN A Content Delivery Network (CDN) plays an important role in application scaling by helping to distribute the load of an application across multiple servers in different geographic locations. This can help to improve the performance and availability of the application for users around the world. When a user requests a piece of content, the CDN will redirect the request to the server that is closest to the user, reducing the latency and improving the overall user experience. This is particularly important for applications that serve a large number of users or handle a high volume of traffic, as it can help to prevent any single server from becoming overwhelmed and causing the application to become unavailable. Additionally, CDN also helps to reduce the load on the origin server by caching frequently-requested content on the CDN’s edge servers. This can help to prevent the origin server from becoming a bottleneck and ensure that it is able to handle the traffic and reque...
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The Importance of Load Balancing in Building Scalable Applications

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                                     What is Load balancer? In the context of application auto scaling, a load balancer is used to distribute incoming traffic to multiple instances of an application. As the traffic to the application increases, more instances of the application are automatically spawned to handle the additional load, and the load balancer automatically directs traffic to these new instances. Conversely, as traffic decreases, instances that are no longer needed are terminated, and the load balancer stops directing traffic to them. This allows the system to automatically scale up or down based on network traffic. Client side Load balancing Client-side load balancing is a technique where the client is responsible for distributing incoming requests to different servers. This is typically done by the client using a load balancing algorithm to select the server to whi...
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Effective rate limiting strategies for Spring Boot applications

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  What is Rate Limiting? Rate limiting is a technique to control the rate of access to APIs. It enforces a limit on the number of API calls that a client can make within a specific time period. This helps protect the API from excessive usage, whether it is accidental or intentional. Rate limiting is a key technique in managing and protecting APIs, it helps to prevent overuse, defend against DDoS attacks, enforce fair usage, improve scalability, and facilitate billing. Rate Limiting Algorithms There are several algorithms that can be used to implement rate limiting, including: Token Bucket:  This algorithm works by allowing a certain number of requests (tokens) to be made within a specific time period. When a request is made, a token is removed from the bucket. If the bucket is empty, the request is denied. Leaky Bucket:  This algorithm is similar to the token bucket, but instead of denying requests when the bucket is empty, it allows the requests to be made, but at a slow...
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Building Scalable and Resilient Systems

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What is Event Driven Architecture (EDA) In an event-driven architecture, events are the primary unit of communication between different components of a system. Event producers generate events, which are then sent to an event router or message broker. The event router filters and routes the events to the appropriate event consumers, which take appropriate action based on the events they receive. This decoupling of event producers and consumers allows for a loosely coupled and asynchronous communication between different parts of the system, making it more scalable, flexible, and resilient. The event-driven architecture is well-suited for real-time systems such as IoT, online gaming, financial trading, and real-time analytics. Ways to Implement EDA Event-driven architecture (EDA) can be implemented in a variety of ways, depending on the specific requirements of the system. Here are a few common ways to implement EDA: Using a message broker:  A message broker, such as Apache Kafka or ...
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