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The Power of Caching: Boosting API Performance and Scalability

DZone

Benefits of Caching Improved performance: Caching eliminates the need to retrieve data from the original source every time, resulting in faster response times and reduced latency. Reduced server load: By serving cached content, the load on the server is reduced, allowing it to handle more requests and improving overall scalability.

Cache 246
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Redis vs Memcached in 2024

Scalegrid

In this comparison of Redis vs Memcached, we strip away the complexity, focusing on each in-memory data store’s performance, scalability, and unique features. can enhance Redis by handling management tasks, backups, and scalability, facilitating global reach and easy cloud integration for global businesses.

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

The Netflix TechBlog

The first phase involves validating functional correctness, scalability, and performance concerns and ensuring the new systems’ resilience before the migration. It provides a good read on the availability and latency ranges under different production conditions. We will examine these alternatives in the upcoming sections.

Traffic 339
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Dynatrace supports the newly released AWS Lambda Response Streaming

Dynatrace

Now, customers can use streamed responses to build more responsive applications by sending partial responses to clients as the response becomes available. Customers can use AWS Lambda Response Streaming to improve performance for latency-sensitive applications and return larger payload sizes. What is a Lambda serverless function?

Lambda 212
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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. These storage nodes collaborate to manage and disseminate the data across numerous servers spanning multiple data centers.

Storage 130
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Benchmark (YCSB) numbers for Redis, MongoDB, Couchbase2, Yugabyte and BangDB

High Scalability

Redis Server: 5.07, x86/64. MongoDB server: 4.4.2, BangDB server: 2.0.0, We note that for MongoDB update latency is really very low (low is better) compared to other dbs, however the read latency is on the higher side. Again Yugabyte latency is quite high. The latency table for test D is as below.