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Migrating Critical Traffic At Scale with No Downtime?—?Part 2

The Netflix TechBlog

Migrating Critical Traffic At Scale with No Downtime — Part 2 Shyam Gala , Javier Fernandez-Ivern , Anup Rokkam Pratap , Devang Shah Picture yourself enthralled by the latest episode of your beloved Netflix series, delighting in an uninterrupted, high-definition streaming experience. This is where large-scale system migrations come into play.

Traffic 279
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What is a Distributed Storage System

Scalegrid

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130
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Consistent caching mechanism in Titus Gateway

The Netflix TechBlog

In the time since it was first presented as an advanced Mesos framework, Titus has transparently evolved from being built on top of Mesos to Kubernetes, handling an ever-increasing volume of containers. This blog post presents how our current iteration of Titus deals with high API call volumes by scaling out horizontally.

Cache 224
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Edgar: Solving Mysteries Faster with Observability

The Netflix TechBlog

Edgar helps Netflix teams troubleshoot distributed systems efficiently with the help of a summarized presentation of request tracing, logs, analysis, and metadata. Edgar captures 100% of interesting traces , as opposed to sampling a small fixed percentage of traffic. by Elizabeth Carretto Everyone loves Unsolved Mysteries.

Latency 296
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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key Takeaways Critical performance indicators such as latency, CPU usage, memory utilization, hit rate, and number of connected clients/slaves/evictions must be monitored to maintain Redis’s high throughput and low latency capabilities. Similarly, an increased throughput signifies an intensive workload on a server and a larger latency.

Metrics 130
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Compression Methods in MongoDB: Snappy vs. Zstd

Percona

Compression in any database is necessary as it has many advantages, like storage reduction, data transmission time, etc. Storage reduction alone results in significant cost savings, and we can save more data in the same space. When this data block is read, it decompresses it in memory and presents it to the incoming request.

Storage 105
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What Is a Workload in Cloud Computing

Scalegrid

While managing cloud workloads offers numerous benefits, it also presents several challenges such as security risks, compliance issues, and resource optimization, which can be addressed effectively with tools like ScaleGrid, offering features like encryption, disaster recovery, and real-time resource optimization for diverse databases.

Cloud 130