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Showing posts with the label Solution Architect

Service Mesh - Kubernetes

Service Mesh A service mesh is an architectural pattern for microservices deployments . It’s primary goal is to make service-to-service communications secure, fast, and reliable. In a service mesh architecture, microservices within a given deployment or cluster interact with each other through sidecar proxy’s. The security and communication rules behind these interactions are directed through a control plane. The developer can configure and add policies at the control plane level, and abstract the governance considerations behind microservices, regardless of the technology used to build. Popular Service Mesh frameworks, such as Istio, have emerged to help organizations implement these architectural patterns.  A service mesh is a dedicated infrastructure layer that controls service-to-service communication within a distributed application. This method enables separate parts of an application to communicate with each other. Service meshes appear commonly in concert with cloud-native ...

Differences between RabbitMQ, Apache Kafka, and ActiveMQ?

RabbitMQ , known for flexibility and support for multiple messaging protocols, is ideal for complex routing, message prioritization, and reliable delivery in microservices architectures. However, it may not handle high-throughput scenarios as efficiently as Kafka.   On the other hand, Apache Kafka , a distributed streaming platform, excels in high-throughput and fault-tolerant messaging, making it perfect for real-time data processing and analytics. Kafka typically outperforms RabbitMQ and ActiveMQ in high-volume scenarios due to its distributed nature. ActiveMQ , a Java-based message broker supporting the Java Message Service API, is favored in traditional enterprise messaging scenarios requiring robust security and transactional messaging. While offering good performance and enterprise features, ActiveMQ may not match Kafka's throughput capabilities in streaming scenarios. Each platform has its strengths and best-fit scenarios. Understanding their architectures and performance c...

Performance Tuning in Mule4 Applications

To achieve optimal performance from your Mule applications, you must evaluate both the applications themselves and the environment in which they run. Although Mule 4 is designed to tune itself, your applications might exhibit performance issues due to their initial construction or dependencies. Similarly, for on-premises installations, you might need to tune the environment itself so that your Mule applications can take full advantage of it. Because many variables influence it, tuning the performance of your application requires some trial and error. You can simplify performance tuning by using documented best practices and testing your applications in ideal test environments. The following recommendations come from the Development and Services Engineering teams and benchmarking efforts by MuleSoft Performance Engineering. Optimizing the performance of your Mule apps requires the following actions: Applying tuning recommendations at the application level        ...

Integration Design Patterns

Understanding Integration Design Patterns: Integration design patterns serve as reusable templates for solving common integration problems encountered in software development. They encapsulate best practices and proven solutions, empowering developers to architect complex systems with confidence. These patterns abstract away the complexities of integration, promoting modularity, flexibility, and interoperability across components. Most Common Integration Design Patterns: Point-to-Point Integration: Point-to-Point Integration involves establishing direct connections between individual components. While simple to implement, this pattern can lead to tight coupling and scalability issues as the number of connections grows. Visualizing this pattern, imagine a network of interconnected nodes, each communicating directly with specific endpoints. Publish-Subscribe (Pub/Sub) Integration: Pub/Sub Integration decouples producers of data (publishers) from consumers (subscribers) through a central ...

SAGA Design Pattern - Microservices.

Saga design pattern: Implement each business transaction that spans multiple services as a saga. A saga is a sequence of local transactions. Each local transaction updates the database and publishes a message or event to trigger the next local transaction in the saga. If a local transaction fails because it violates a business rule then the saga executes a series of compensating transactions that undo the changes that were made by the preceding local transactions. There are two ways of coordination sagas:  Choreography - each local transaction publishes domain events that trigger local transactions in other services Orchestration - an orchestrator (object) tells the participants what local transactions to execute Choreography based SAGA: An e-commerce application that uses this approach would create an order using a choreography-based saga that consists of the following steps:The Order Service receives the POST /orders request and creates an Order in a PENDING state It then emit...

Architectural constraints of API / Rest API principles

REST API (also called a RESTful API or RESTful web API) is an application programming interface (API) that conforms to the design principles of the representational state transfer (REST) architectural style. REST APIs provide a flexible, lightweight way to integrate applications and to connect components in microservices architectures. REST stands for Representational State Transfer, a term coined by Roy Fielding in 2000. It is an architecture style for designing loosely coupled applications over the network, that is often used in the development of web services. REST does not enforce any rule regarding how it should be implemented at the lower level, it just put high-level design guidelines and leaves us to think of our own implementation. Let’s start with standard design-specific stuff to clear what ‘Roy Fielding’ wants us to build. Then we will discuss my thoughts, which will be more towards finer points while you design your RESTful APIs. Architectural Constraints: REST defines 6 ...

Microservices design patterns

Microservices design pattern Next :  saga-design-pattern-microservices

How to Monitor application ?

Summery :  Dashboards. Event-Driven Alerts Logging System Tools for Monitoring Integrations (you can add from exchange). Live Demo  Logging & monitoring Tools  Splunk: Splunk is an enterprise software company that makes machine data accessible, usable and valuable to everyone. Manily used for log management. AppDynamics: Application monitoring. Datadog is used for observability and monitoring.

Best Practices in Logging

Summery :  Follow best practices in logging, such as avoiding logging sensitive information and using appropriate log levels for different scenarios. use asynchronous logging over synchronous with a minimum logging level of WARN for a production application. In some cases, enable INFO logging level when you need to confirm events such as successful policy installation or to perform troubleshooting. Avoid logging sensitive information. Using correlation identifier to trace system calls across application layers. Use categories to turn on/off logging during runtime, for eg we need diff. log level for Dev & PROD.  If a flow uses several loggers, add some fixed text in the logger’s message to identify where it was generated. 

MQ-Based Integration vs. REST API-Based Integration: Choosing the Right Path for Your Architecture

In today's interconnected world, integration is at the heart of seamless operations.  Two of the most popular methods for connecting systems are  1. Message Queue (MQ)-based integration  2. REST API-based integration. But how do you choose the right one for your needs? 🔄 MQ-Based Integration : - Asynchronous Communication : Ensures reliability and resilience, allowing systems to communicate without waiting for an immediate response. Perfect for handling high volumes of data and complex workflows. - Decoupled Systems : MQ allows systems to operate independently, reducing dependencies and enhancing scalability. - Guaranteed Delivery : Messages are queued and delivered even if the destination system is temporarily unavailable, ensuring that no data is lost. 🌐 REST API-Based Integration : - Synchronous Communication : Ideal for real-time, request-response interactions where immediate feedback is needed. - Ease of Use : REST APIs are widely adopted, easy to implement, and pe...