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Save Money in AWS RDS: Don’t Trust the Defaults

Percona

Default settings can help you get started quickly – but they can also cost you performance and a higher cloud bill at the end of the month. Want to save money on your AWS RDS bill? I’ll show you some MySQL settings to tune to get better performance, and cost savings, with AWS RDS. Buffer Pool Size | 92.0G

AWS 122
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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. It helps developers and operators identify and troubleshoot issues, optimize performance and improve user experience. Scale automatically based on the demand and traffic patterns. The elasticity of serverless services helps organizations scale as needed.

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TCP: Out of Memory — Consider Tuning TCP_Mem

DZone

This application was running on multiple AWS EC2 instances behind Elastic Load Balancer. All other application instances were handling the traffic properly. Recently we experienced an interesting production problem. The application was running on a GNU/Linux OS, Java 8, Tomcat 8 application server.

Tuning 164
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AWS re:Invent 2017: How Netflix Tunes EC2

Brendan Gregg

My last talk for 2017 was at AWS re:Invent, on "How Netflix Tunes EC2 Instances for Performance," an updated version of my [2014] talk. Our team looks after the BaseAMI, kernel tuning, OS performance tools and profilers, and self-service tools like Vector. Casey Rosenthal (traffic and chaos) Models of Availability.

Tuning 61
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How Dynatrace boosts production resilience with Site Reliability Guardian

Dynatrace

Validation tasks are then extended left to cover performance testing and release validation in a pre-production environment. While the first guardian validates the traffic, the second guardian checks the business transactions generated during the observation period. The functionality is implemented via an automated workflow.

DevOps 183
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AWS re:Invent 2017: How Netflix Tunes EC2

Brendan Gregg

My last talk for 2017 was at AWS re:Invent, on "How Netflix Tunes EC2 Instances for Performance," an updated version of my [2014] talk. Our team looks after the BaseAMI, kernel tuning, OS performance tools and profilers, and self-service tools like Vector. Casey Rosenthal (traffic and chaos) Models of Availability.

Tuning 52
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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

A lenient trace data sampling policy generates a large number of traces in each service container and can lead to degraded performance of streaming services as more CPU, memory, and network resources are consumed by the tracer library. This setup of chained Mantis jobs allows us to scale each data processing component independently.