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Implementing a Self-Healing Infrastructure With Kubernetes and Prometheus

DZone

Furthermore, with the increased adoption of microservices and containerization , the need for a reliable infrastructure that can automatically detect and recover from failures has become critical. Kubernetes provides a highly scalable and flexible platform for managing containerized applications.

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Tips for Building a Scalable Payment Architecture

DZone

That’s why it is important to have a scalable infrastructure that will allow you to accommodate those needs — especially nowadays, when integrating with payment services has become more accessible than ever.

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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

Now let’s look at how we designed the tracing infrastructure that powers Edgar. This insight led us to build Edgar: a distributed tracing infrastructure and user experience. Our distributed tracing infrastructure is grouped into three sections: tracer library instrumentation, stream processing, and storage.

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Flexible, scalable, self-service Kubernetes native observability now in General Availability

Dynatrace

To solve this problem , Dynatrace offers a fully automated approach to infrastructure and application observability including Kubernetes control plane, deployments, pods, nodes, and a wide array of cloud-native technologies. None of this complexity is exposed to application and infrastructure teams.

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What is hyperconverged infrastructure? Realizing the benefits of HCI

Dynatrace

Therefore, they need an environment that offers scalable computing, storage, and networking. That’s where hyperconverged infrastructure, or HCI, comes in. What is hyperconverged infrastructure? For organizations managing a hybrid cloud infrastructure , HCI has become a go-to strategy. Realizing the benefits of HCI.

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The Power of Caching: Boosting API Performance and Scalability

DZone

Reduced server load: By serving cached content, the load on the server is reduced, allowing it to handle more requests and improving overall scalability. Cost savings: Caching can reduce the computational resources required for data processing and lower infrastructure costs by minimizing the need for expensive server resources.

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In-House Model Serving Infrastructure for GPU Flexibility

DZone

Many organizations rely on cloud services like AWS, Azure, or GCP for these GPU-powered workloads, but a growing number of businesses are opting to build their own in-house model serving infrastructure. Why Choose In-House Model Serving Infrastructure?