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11 Lessons Learned from The Early Adopters of Cloud Migration

Simform

Cloud migrations need elaborate planning and strategizing to reap the benefits of cloud-based resources. However, it is not that easy to strategize a cloud migration without enough experience in the cloud landscape.

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How Data Inspires Building a Scalable, Resilient and Secure Cloud Infrastructure At Netflix

The Netflix TechBlog

All these micro-services are currently operated in AWS cloud infrastructure. Finally, provisioning our infrastructure itself is also becoming an increasingly complex task, so our data teams contribute to tools for diagnosis and automation of our cloud capacity management.

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How to Optimize Digital Experience and Operations with Dynatrace

Dynatrace

She was speaking about how her team is providing Visibility as a Service (VaaS) in order to continuously monitor and optimize their systems running across private and public cloud environments. Benefits: Cost savings and an easier path to the Cloud. I’ve been advising for optimizing first, then migrating, over the past few years.

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When it Comes to Transformation, it’s OK to Break the Rules.

Tasktop

Lift and shift workloads to the Cloud.”. They unified and re-platformed the majority of their critical business applications to the cloud. Last year at this conference , Pieter walked us through the beginning of this shift, and this year, he offered an update on how things are going and the lessons they’ve learned.

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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

This introductory blog focuses on an overview of our journey. Future blogs will provide deeper dives into each service, sharing insights and lessons learned from this process. Future blogs will provide deeper dives into each service, sharing insights and lessons learned from this process.

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How Netflix Scales its API with GraphQL Federation (Part 2)

The Netflix TechBlog

from our journey implementing it to lessons learned. We migrated the fields exposed by Studio API to individually owned DGSs without breaking the API for consumers. The schema registry also integrates with our CI/CD systems like Spinnaker to automatically setup cloud networking for DGSs.

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Evolution of ML Fact Store

The Netflix TechBlog

We will share how its design has evolved over the years and the lessons learned while building it. We use Keystone as it is easy to use, reliable, scalable, and provides aggregation of facts from different cloud regions into a single AWS region. our fact store that is leveraged to compute ML features offline.

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