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Mastering Hybrid Cloud Strategy

Scalegrid

Mastering Hybrid Cloud Strategy Are you looking to leverage the best private and public cloud worlds to propel your business forward? A hybrid cloud strategy could be your answer. Understanding Hybrid Cloud Strategy A hybrid cloud merges the capabilities of public and private clouds into a singular, coherent system.

Strategy 130
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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.

Strategy 130
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The Three Cs: Concatenate, Compress, Cache

CSS Wizardry

Given that 66% of all websites (and 77% of all requests ) are running HTTP/2, I will not discuss concatenation strategies for HTTP/1.1 Plotted on the same horizontal axis of 1.6s, the waterfalls speak for themselves: 201ms of cumulative latency; 109ms of cumulative download. 4,362ms of cumulative latency; 240ms of cumulative download.

Cache 291
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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing systems, designed for continuous, low-latency processing, demand swift recovery mechanisms to tolerate and mitigate failures effectively. After failures, Kafka Streams’ partition assignment strategy, triggered by rebalances, causes its executions to accumulate more lag. This significantly increases event latency.

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

The Netflix TechBlog

Our previous blog post presented replay traffic testing — a crucial instrument in our toolkit that allows us to implement these transformations with precision and reliability. Migrating Persistent Stores Stateful APIs pose unique challenges that require different strategies. But what happens when this machinery needs a transformation?

Traffic 279
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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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Scalable Annotation Service?—?Marken

The Netflix TechBlog

The service should be able to serve real-time, aka UI, applications so CRUD and search operations should be achieved with low latency. Our service will be used by a lot of internal UI applications hence the latency for CRUD and search operations must be low. Search latency for the generic text queries are in milliseconds.