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Building Resilient Public Networking on AWS: Part 4

Xebia

One of the key differences between the approach in this post and the previous one is that here, the Application Load Balancers (ALBs) are private, so the only element exposed directly to the Internet is the Global Accelerator and its Edge locations. These steps are clearly marked in the following diagram.

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SaaS Platfrom Development – How to Start

Existek

DevOps engineers: Optimize infrastructure, manage deployment pipelines, monitor security and performance. They must track key metrics, analyze user feedback, and evolve the platform to meet customer expectations. DevOps tools: Teams apply CI/CD pipelines like GitHub Action or Jenkins to automate workflows and deployments.

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The Network Also Needs to be Observable, Part 2: Network Telemetry Sources

Kentik

Networkers running enterprise and critical service provider infrastructure need infrastructure-savvy analogs of the same observability principles and practices being deployed by DevOps groups. Application layer : ADCs, load balancers and service meshes. Conclusion.

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Moving to the Cloud: Exploring the API Gateway to Success

Daniel Bryant

Most successful organizations base their goals on improving some or all of the DORA or Accelerate metrics. DORA metrics are used by DevOps teams to measure their performance and find out whether they are “low performers” to “elite performers.” You want to maximize your deployment frequency while minimizing the other metrics.

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HCL Commerce Containers Explained

Perficient

It facilitates service discovery and load balancing within the microservices architecture. It includes dashboards for tracking system performance, logs, and metrics to aid in troubleshooting and maintaining system health. Tooling-web : Provides a suite of monitoring and debugging tools for developers and administrators.

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AI-Driven API and Microservice Architecture Design for Cloud

Dzone - DevOps

Here are some key aspects where AI can drive improvements in architecture design: Intelligent planning : AI can assist in designing the architecture by analyzing requirements, performance metrics, and best practices to recommend optimal structures for APIs and microservices.

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Microservices Architectural Design by using Spring Boot

Perficient

with DevOps tools like Jenkins with CI/CD, Docker, Ansible, Kubernetes, or other tools. Load Balancer Client If any microservice has more demand, then we allow the creation of multiple instances dynamically.