Remove Microservices Remove Scalability Remove Systems Review
article thumbnail

The Cake is NOT a Lie: 5 Java Frameworks to Support Your Microservices Architecture

OverOps

The microservices trend is becoming impossible to ignore,” I wrote in 2016. Back then, many would have argued this was just another unbearable buzzword, but today many organizations are reaping the very real benefits of breaking down old monolithic applications, as well as seeing the very real challenges microservices can introduce.

article thumbnail

Should I use microservices?

O'Reilly Media - Ideas

Considerations for when—and when not—to apply microservices in your organization. Despite the drive in some quarters to make microservice architectures the default approach for software, I feel that due to their numerous challenges, adopting them still requires careful thought. Where microservices don’t work well.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Comprehensive Guide to Microservices Testing: Ensuring Reliable and Scalable Software

Dzone - DevOps

Microservices architecture has become extremely popular in recent years because it allows for the creation of complex applications as a collection of discrete, independent services. The distributed nature of microservices, however, presents special difficulties for testing and quality control.

article thumbnail

Building Shared State Microservices for Distributed Systems Using Kafka Streams

Confluent

The Kafka Streams API boasts a number of capabilities that make it well suited for maintaining the global state of a distributed system. At Imperva, we took advantage of Kafka Streams to build shared state microservices that serve as fault-tolerant, highly available single sources of truth about the state of objects in our system.

article thumbnail

Microservices, Apache Kafka, and Domain-Driven Design

Confluent

Microservices have a symbiotic relationship with domain-driven design (DDD)—a design approach where the business domain is carefully modeled in software and evolved over time, independently of the plumbing that makes the system work. In these projects, microservice architectures use Kafka as an event streaming platform.

article thumbnail

Orchestrate generative AI workflows with Amazon Bedrock and AWS Step Functions

AWS Machine Learning - AI

Using Amazon Bedrock, you can easily experiment with and evaluate top FMs for your use case, privately customize them with your data using techniques such as fine-tuning and Retrieval Augmented Generation (RAG), and build agents that execute tasks using your enterprise systems and data sources.

article thumbnail

Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

Each component in the previous diagram can be implemented as a microservice and is multi-tenant in nature, meaning it stores details related to each tenant, uniquely represented by a tenant_id. This in itself is a microservice, inspired the Orchestrator Saga pattern in microservices.