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Kubernetes in the wild report 2023

Dynatrace

The report also reveals the leading programming languages practitioners use for application workloads. are the top 3 programming languages for Kubernetes application workloads. Of the organizations in the Kubernetes survey, 71% run databases and caches in Kubernetes, representing a +48% year-over-year increase.

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Geek Reading - Week of June 5, 2013

DZone

These items are a combination of tech business news, development news and programming tools and techniques. Using MongoDB as a cache store ( Architects Zone – Architectural Design Patterns & Best Practices). These items are the fruits of those ideas, the items I deemed worthy from my Google Reader feeds. Hacker News).

Java 244
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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Effective management of memory stores with policies like LRU/LFU proactive monitoring of the replication process and advanced metrics such as cache hit ratio and persistence indicators are crucial for ensuring data integrity and optimizing Redis’s performance. Cache Hit Ratio The cache hit ratio represents the efficiency of cache usage.

Metrics 130
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What is session replay? Discover user pain points with session recordings

Dynatrace

In practice, session recording solutions make use of the document object model (DOM), which is a programming interface for web pages and document. Streamlined asset caching: Asset caching is critical for creating accurate replays. Make sure you know what assets your replay tool is recording and how you can access them.

Mobile 247
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USENIX SREcon APAC 2022: Computing Performance: What's on the Horizon

Brendan Gregg

I'm now program co-chair for SREcon 2023 APAC, and our 2023 conference is June 14-16 in Singapore. And now, helping bring USENIX conferences to Australia by giving the first keynote: I could not have scripted or expected it. The call for participation ends on March 2nd 23:59 SGT!

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The Amazing Evolution of In-Memory Computing

ScaleOut Software

From Distributed Caches to Real-Time Digital Twins. In general terms, in-memory computing refers to the related concepts of (a) storing fast-changing data in primary memory instead of in secondary storage and (b) employing scalable computing techniques to distribute a workload across a cluster of servers.

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The Amazing Evolution of In-Memory Computing

ScaleOut Software

From Distributed Caches to Real-Time Digital Twins. In general terms, in-memory computing refers to the related concepts of (a) storing fast-changing data in primary memory instead of in secondary storage and (b) employing scalable computing techniques to distribute a workload across a cluster of servers.