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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data. This significantly increases event latency.

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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. It can achieve impressive performance, handling up to 50 million operations per second.

Metrics 130
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Site reliability engineering: 5 things you need to know

Dynatrace

Site reliability engineering (SRE) is the practice of applying software engineering principles to operations and infrastructure processes to help organizations create highly reliable and scalable software systems. Shift-left using an SRE approach means that reliability is baked into each process, app and code change.

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Mastering MongoDB® Timeout Settings

Scalegrid

For example, if there’s some trouble connecting due to networking problems or excessive load requests from customers present on the server’s side, that might result in a resolution-related delay causing a subsequent timeout problem. x+ in Java). Modifying this setting does affect performance.

Java 130
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Site reliability engineering: 5 things to you need to know

Dynatrace

Site reliability engineering (SRE) is the practice of applying software engineering principles to operations and infrastructure processes to help organizations create highly reliable and scalable software systems. Shift-left using an SRE approach means that reliability is baked into each process, app and code change.

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

Brendan Gregg

My personal opinion is that I don't see a widespread need for more capacity given horizontal scaling and servers that can already exceed 1 Tbyte of DRAM; bandwidth is also helpful, but I'd be concerned about the increased latency for adding a hop to more memory. Ford, et al., “TCP

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How to use Server Timing to get backend transparency from your CDN

Speed Curve

Cue server-timing headers Historically, when looking at page speed, we've had the tendency to ignore TTFB when trying to optimize the user experience. desc="Time to process request at origin" NOTE: This is not a new API. Latency – How much time does it take to deliver a packet from A to B. I mean, why wouldn't we?

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