Scalegrid
AUGUST 16, 2021
Data-driven applications span a wide breadth of complexity, from simple microservices to real-time event-driven systems under significant load. Modern application architectures such as the JAMstack enforce the separation […]. Guest post by Ben Hagan from PolyScale.ai
InfoQ
MARCH 15, 2024
Hashnode created a scalable event-driven architecture (EDA) for composing feed data for thousands of users. The company used serverless services on AWS, including Lambda, Step Functions, EventBridge, and Redis Cache. The solution leverages Step Functions' distributed maps feature that enables high-concurrency processing.
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Dynatrace
JANUARY 31, 2024
Retrieval-augmented generation emerges as the standard architecture for LLM-based applications Given that LLMs can generate factually incorrect or nonsensical responses, retrieval-augmented generation (RAG) has emerged as an industry standard for building GenAI applications.
Dynatrace
DECEMBER 21, 2023
Evaluating these on three levels—data center, host, and application architecture (plus code)—is helpful. Application architectures might not be conducive to rehosting. Implement appropriate caching layers (for example, read-only cache for static data). Is the solution to just move all workloads to the cloud?
The Netflix TechBlog
APRIL 27, 2023
Moreover, common database optimizations like caching recently queried data don’t really work for alerting queries because, generally speaking, the last received datapoint is required for correctness. First and foremost, we have successfully alleviated our initial scalability problem with the polling based architecture. OK, Results?
Smashing Magazine
SEPTEMBER 28, 2022
The browser receives a JavaScript bundle and static HTML in a payload, then it will render the DOM and add the listeners and events triggers for reactiveness. Active Memory Caching. When you want to get data that you already had quickly, you need to do caching — caching stores data that a user recently retrieved.
O'Reilly Software
JUNE 12, 2018
The benefits of modeling data as events as a mechanism to evolve our software systems. In fact, before we even had the word microservices in our lexicon, back when it was just good old-fashioned service-oriented architecture, we were talking about data: how to access it, where it lives, who “owns” it.
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