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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

which is difficult when troubleshooting distributed systems. 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. Investigating a video streaming failure consists of inspecting all aspects of a member account.

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Dynatrace adds support for AWS Transit Gateway with VPC Flow Logs

Dynatrace

VPC Flow Logs is a feature that gives you the capability to capture more robust IP traffic data that traverses your VPCs. These include Source IP, destination IP, transport protocol, source port, and destination port. What is VPC Flow Logs. Dynatrace-detected problems are used to report and alert on abnormal situations.

AWS 214
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Kubernetes vs Docker: What’s the difference?

Dynatrace

Think of containers as the packaging for microservices that separate the content from its environment – the underlying operating system and infrastructure. Just like shipping containers revolutionized the transportation industry, Docker containers disrupted software. In production, containers are easy to replicate. Networking.

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Towards a Reliable Device Management Platform

The Netflix TechBlog

The Partner Infrastructure team at Netflix provides solutions to support these two significant efforts by enabling device management at scale. Together, they form the Device Management Platform, which is the infrastructural foundation for Netflix Test Studio (NTS).

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Stuff The Internet Says On Scalability For March 8th, 2019

High Scalability

All of the heavy-lifting infrastructure was already in place for it. There was already a payment system — it was called the credit card. There was already a transportation network called the US Postal Service, and Royal Mail, and Deutsche Post, all over the world, that could deliver our packages.

Internet 146
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Delta: A Data Synchronization and Enrichment Platform

The Netflix TechBlog

Another issue exists for the capture of schema changes, where some systems, like MySQL, don’t support transactional schema changes [1][2]. By their nature, they can only rely on the lowest common denominator of participating systems. That system quickly grew very complex and became difficult to maintain.

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Let's talk about Kafka

Particular Software

While Kafka can deal with high traffic volumes, the right partition strategy is a key factor and will have a major impact on the scalability and elasticity of the whole system. Unlike Kafka, consumers can be added and removed at any point in time without any impact on the topology of the queuing system.