Remove articles deploying-your-microservices
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Simplifying Kubernetes Deployments: An In-Depth Look at Helm

Dzone - DevOps

In this article, we will delve deeply into Helm and explore how it facilitates the easier management of Kubernetes deployments. It's great for running microservices and any other stateless applications. However, managing deployments becomes a big challenge as your Kubernetes system gets more extensive and complicated.

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Microservices Deployment Models

Dzone - DevOps

Microservices are a popular architectural pattern for building large-scale, complex applications. They provide a way to break down a monolithic application into smaller, more manageable services that can be developed, tested, and deployed independently. Containerization Containerization is a popular way to deploy microservices.

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Fast Deployments of Microservices Using Ansible and Kubernetes

Dzone - DevOps

Does the time your CI/CD pipeline takes to deploy hold you back during development testing? This article demonstrates a faster way to develop Spring Boot microservices using a bare-metal Kubernetes cluster that runs on your own development machine.

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5 Testing Strategies For Deploying Microservices

DevOps.com

With rigorous development and pre-production testing, your microservices will perform as they should. However, microservices need to be continuously tested against actual end-user activity to adapt the application to changing preferences and requests.

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Unlocking the Power of AI with a Real-Time Data Strategy

CIO

Streaming data technologies unlock the ability to capture insights and take instant action on data that’s flowing into your organization; they’re a building block for developing applications that can respond in real-time to user actions, security threats, or other events. Kubernetes is a key tool to help do away with the siloed mindset.

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Moving to the Cloud: Exploring the API Gateway to Success

Daniel Bryant

An API gateway is a front door to your applications and systems. The fundamentals of API gateway technology have evolved over the past ten years, and adopting cloud native practices and technologies like continuous delivery, Kubernetes, and HTTP/3 adds new dimensions that need to be supported by your chosen implementation.

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Supporting Diverse ML Systems at Netflix

Netflix Tech

Since its inception , Metaflow has been designed to provide a human-friendly API for building data and ML (and today AI) applications and deploying them in our production infrastructure frictionlessly. In this article, we cover a few key integrations that we provide for various layers of the Metaflow stack at Netflix, as illustrated above.

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