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Migrating Netflix to GraphQL Safely

The Netflix TechBlog

Before GraphQL: Monolithic Falcor API implemented and maintained by the API Team Before moving to GraphQL, our API layer consisted of a monolithic server built with Falcor. A single API team maintained both the Java implementation of the Falcor framework and the API Server. To launch Phase 1 safely, we used AB Testing.

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Redis vs Memcached in 2024

Scalegrid

Key Takeaways Redis offers complex data structures and additional features for versatile data handling, while Memcached excels in simplicity with a fast, multi-threaded architecture for basic caching needs. Redis is better suited for complex data models, and Memcached is better suited for high-throughput, string-based caching scenarios.

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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

It requires specialized talent, a new technology stack to manage and deploy models, an ample budget for rising compute costs, and end-to-end security. million AI server units annually by 2027, consuming 75.4+ Many organizations haven’t even considered which use cases will bring them the biggest return on AI investment.

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Redis® Monitoring Strategies for 2024

Scalegrid

Identifying key Redis® metrics such as latency, CPU usage, and memory metrics is crucial for effective Redis monitoring. To monitor Redis® instances effectively, collect Redis metrics focusing on cache hit ratio, memory allocated, and latency threshold.

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Migrating Critical Traffic At Scale with No Downtime?—?Part 1

The Netflix TechBlog

It provides a good read on the availability and latency ranges under different production conditions. These include options where replay traffic generation is orchestrated on the device, on the server, and via a dedicated service. Also, since this logic resides on the server side, we can iterate on any required changes faster.

Traffic 339
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Dynamic Content Vs. Static Content: What Are the Main Differences

IO River

These are unchanging entities, served straight off the server, pre-generated, and devoid of server-side processing. They cache static content and enable lightning-fast delivery around the globe.This symbiosis reduces server load, boosts loading times, and ensures efficient content distribution.

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Designing Instagram

High Scalability

When the server receives a request for an action (post, like etc.) When a user requests for feed then there will be two parallel threads involved in fetching the user feeds to optimize for latency. We will use a cache having an LRU based eviction policy for caching user feeds of active users. High Level Design.

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