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Seeing through hardware counters: a journey to threefold performance increase

The Netflix TechBlog

to a larger AWS instance size, from m5.4xl (16 vCPUs) to m5.12xl (48 vCPUs). A quick canary test was free of errors and showed lower latency, which is expected given that our standard canary setup routes an equal amount of traffic to both the baseline running on 4xl and the canary on 12xl. let’s call it GS2?—?to

Hardware 363
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Migrating Netflix to GraphQL Safely

The Netflix TechBlog

The control group’s traffic utilized the legacy Falcor stack, while the experiment population leveraged the new GraphQL client and was directed to the GraphQL Shim. To determine customer impact, we could compare various metrics such as error rates, latencies, and time to render.

Traffic 358
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Netflix at AWS re:Invent 2019

The Netflix TechBlog

by Shefali Vyas Dalal AWS re:Invent is a couple weeks away and our engineers & leaders are thrilled to be in attendance yet again this year! Netflix shares how Amazon EC2 Auto Scaling allows its infrastructure to automatically adapt to changing traffic patterns in order to keep its audience entertained and its costs on target.

AWS 38
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Ciao Milano! – An AWS Region is coming to Italy!

All Things Distributed

Today, I am happy to announce our plans to open a new AWS Region in Italy! The AWS Europe (Milan) Region is the 25th AWS Region that we've announced globally. It's the sixth AWS Region in Europe, joining existing regions in France, Germany, Ireland, the UK, and the new Region that we recently announced in Sweden.

AWS 165
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Bring Your Own Cloud (BYOC) vs. Dedicated Hosting at ScaleGrid

Scalegrid

Each of these models is suitable for production deployments and high traffic applications, and are available for all of our supported databases, including MySQL , PostgreSQL , Redis™ and MongoDB® database ( Greenplum® database coming soon). AWS , Azure. AWS , Azure. AWS , Azure. AWS , Azure. AWS , Azure.

Cloud 242
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Rapid Event Notification System at Netflix

The Netflix TechBlog

We thus assigned a priority to each use case and sharded event traffic by routing to priority-specific queues and the corresponding event processing clusters. This separation allows us to tune system configuration and scaling policies independently for different event priorities and traffic patterns.

Systems 334
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Build and operate multicloud FaaS with enhanced, intelligent end-to-end observability

Dynatrace

For example, to handle traffic spikes and pay only for what they use. These functions are executed by a serverless platform or provider (such as AWS Lambda, Azure Functions or Google Cloud Functions) that manages the underlying infrastructure, scaling and billing. Scale automatically based on the demand and traffic patterns.