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AI-Driven API and Microservice Architecture Design for Cloud

Dzone - DevOps

Incorporating AI into API and microservice architecture design for the Cloud can bring numerous benefits. Automated scaling : AI can monitor usage patterns and automatically scale microservices to meet varying demands, ensuring efficient resource utilization and cost-effectiveness.

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OpenTelemetry for Microservices Tracing and Observability

Dzone - DevOps

They observe the telemetry data (logs, metrics, traces) emitted from the application/microservice using various observability tools and make informed decisions regarding scaling, maintaining, or troubleshooting applications in the production environment.

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5 You’re Probably F**king Up Your Microservices

OverOps

It seems like everyone is into microservices these days, and monolith architectures are slowly fading into obscurity. With Microservices, though, there seems to be more consensus that the trend is here to stay. With Microservices, though, there seems to be more consensus that the trend is here to stay. It makes sense.

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When Should We Move to Microservices?

Dzone - DevOps

One of the more interesting discussions that came out of that article (and video) is the inverse discussion: when is it right to still pick microservices? But there are still general rules of thumb and global metrics we can use. Before we get into these problems, we need to understand what it means to have a microservice architecture.

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Monitoring AWS Container Environments at Scale

Particularly well-suited for microservice-oriented architectures and agile workflows, containers help organizations improve developer efficiency, feature velocity, and optimization of resources. Key metrics to monitor when leveraging two container orchestration systems. Containers power many of the applications we use every day.

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API Testing Automation – Benefits, Metrics, and how to use for Microservices

Newgen Software

The post API Testing Automation – Benefits, Metrics, and how to use for Microservices appeared first on Newgen. Applications talk to each other using intermediary software, an API, or an Application Programming Interface. For example, each time we listen […]. Digital Process Automation: Top 6 Benefits.

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Fixing Bottlenecks in Your Microservices App Flows

Dzone - DevOps

Significance of Bottleneck Analysis in Microservices Bottleneck analysis has become a significant part of microservices development for many reasons. Metrics such as response time, error rate, and throughput can be used to identify and isolate the bottlenecks to improve the application's overall performance. Such as: 1.