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Consistent caching mechanism in Titus Gateway

The Netflix TechBlog

We introduce a caching mechanism in the API gateway layer, allowing us to offload processing from singleton leader elected controllers without giving up strict data consistency and guarantees clients observe. When a new leader is elected it loads all data from external storage. The cache is kept in sync with the current leader process.

Cache 224
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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.

Cache 130
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Designing Instagram

High Scalability

Machine Learning Engineer at Amazon and has led several machine-learning initiatives across the Amazon ecosystem. FUN FACT : In this talk , Rodrigo Schmidt, director of engineering at Instagram talks about the different challenges they have faced in scaling the data infrastructure at Instagram. This is a guest post by Ankit Sirmorya.

Design 334
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MezzFS?—?Mounting object storage in Netflix’s media processing platform

The Netflix TechBlog

Mounting object storage in Netflix’s media processing platform By Barak Alon (on behalf of Netflix’s Media Cloud Engineering team) MezzFS (short for “Mezzanine File System”) is a tool we’ve developed at Netflix that mounts cloud objects as local files via FUSE. Disk Caching? — ? Regional caching? —?Netflix Replays? —?More

Media 214
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Netflix Cloud Packaging in the Terabyte Era

The Netflix TechBlog

From chunk encoding to assembly and packaging, the result of each previous processing step must be uploaded to cloud storage and then downloaded by the next processing step. Uploading and downloading data always come with a penalty, namely latency.

Cloud 237
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Improved Alerting with Atlas Streaming Eval

The Netflix TechBlog

Engineers want their alerting system to be realtime, reliable, and actionable. A few years ago, we were paged by our SRE team due to our Metrics Alerting System falling behind — critical application health alerts reached engineers 45 minutes late! It opens doors to support more exciting use-cases.

Storage 288
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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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