Why Event-Driven Microservices Teams Move Faster
Escaping the monolith didn’t just simplify architecture—it unlocked speed, flexibility, and hiring freedom for Busie.
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Modern Software Development For Today's Systems & Applications
Top Microservices Examples & Guides - DreamFactory
DreamFactory is a secure, self-hosted enterprise data access platform that provides governed API access to any data source, connecting enterprise applications and on-prem LLMs with role-based access and identity passthrough. During the last 10 years, microservices-based applications have benefited global enterprises by providing them with massive scalability, greater agility, more highly available systems, and improved operational efficiency.
Beyond End-to-End: Why Your Microservices Need Contract Testing
You push a small code update. Your unit tests are green, and the functional tests pass. You feel confident. The release pipeline triggers, and the new feature hits production. Ten minutes later, your monitoring dashboard lights up with errors. The frontend team updated a User ID field from an integer to a string, and your backend service just choked on it. In a monolithic design, the compiler or a rudimentary integration suite often identifies these issues.
How to Integrate Monitoring Tools with Microservices
Monitoring microservices is challenging but essential for maintaining system performance and reliability. Unlike traditional applications, microservices require tracking individual services, their interactions, and the infrastructure they run on. Here's what you need to know: To succeed, instrument your services early, set clear Service Level Objectives (SLOs), and ensure your tools scale with your architecture.
Microservices Performance Anti-Patterns - The 7 Mistakes That Tank Your Distributed Systems
You’ve done everything right. You’ve broken down your monolith, containerised your services, set up your orchestration and deployed to the cloud. Your architecture diagram looks beautiful. So why is your system crawling at a snail’s pace during peak hours? Here’s the uncomfortable truth: most microservices performance problems aren’t caused by bad technology choices.
Why I Switched From Rest Assured To Keploy For Microservices Testing
If you’ve been using Rest Assured for API testing, you know how powerful it is. The syntax looks simple and easier to understand, but things get interesting when you have to write test cases and mocks for a microservices application that has more than 2 services. In this blog, I am exactly sharing my pain of writing Rest Assured test cases for a microservices application and why I switched to Keploy not because I am working here, but to show you the real pain points Keploy solves.
Microservices Architecture for FinTech Applications: Benefits and Implementation Guide
Why should FinTech leaders care? Consider this: around 71% of organizations have adopted microservices (partially or fully), citing gains in agility, scalability, and resilience. And when done right, microservices can decrease overhead costs by up to half and boost developer productivity by 50%.
Troubleshooting Microservices with AI
Ever found yourself saying, "But it works on my machine!" when a bug pops up in a microservices environment? It's a common and frustrating problem. Unlike a monolithic application, microservices are a collection of independently deployed services that communicate with each other. This complexity makes it difficult to reproduce real-world issues on your local machine, as you may not have all the necessary services and dependencies running. But what if you could take a snapshot of a running application's behavior and bring it home for debugging?
Cache Miss Handling in Microservices
When a cache miss occurs in a microservices architecture, the system fails to retrieve requested data from the cache, leading to slower performance as the data must be fetched from the database or other sources. Handling these misses efficiently is key to maintaining system speed and reliability. Here's a quick summary of the main strategies: Cache-Aside Pattern: The application fetches data from the database on a miss, stores it in the cache, and serves it to the user.
Optimizing IoT Protocols for Edge Microservices
Choosing the right IoT protocol for edge microservices can save energy, reduce latency, and improve efficiency. Here's a quick guide: MQTT: Lightweight and energy-efficient, ideal for resource-constrained devices. AMQP: Reliable and secure, great for mission-critical applications but resource-intensive. CoAP: Best for low-power, low-bandwidth devices with minimal energy needs. HTTP/REST: Widely compatible but consumes more energy and bandwidth.