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Best practices and key metrics for improving mobile app performance

Dynatrace

Mobile applications (apps) are an increasingly important channel for reaching customers, but the distributed nature of mobile app platforms and delivery networks can cause performance problems that leave users frustrated, or worse, turning to competitors. Load time and network latency metrics. Minimize network requests.

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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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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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Netflix Cloud Packaging in the Terabyte Era

The Netflix TechBlog

Uploading and downloading data always come with a penalty, namely latency. The following table breaks down the various processing (including download) and uploading phases within an assembler and packager instance operating on large media files. For write operations, those challenges do not apply.

Cloud 237
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Predictive CPU isolation of containers at Netflix

The Netflix TechBlog

Because microprocessors are so fast, computer architecture design has evolved towards adding various levels of caching between compute units and the main memory, in order to hide the latency of bringing the bits to the brains. This avoids thrashing caches too much for B and evens out the pressure on the L3 caches of the machine.

Cache 251
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What is a Distributed Storage System

Scalegrid

Durability Availability Fault tolerance These combined outcomes help minimize latency experienced by clients spread across different geographical regions. Handling Large Volumes of Data Distributed storage systems employ the technique of data sharding or partitioning to handle immense quantities of information.

Storage 130
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Supercomputing Predictions: Custom CPUs, CXL3.0, and Petalith Architectures

Adrian Cockcroft

In comparison, for Linpack Frontier operates at 68% of peak capacity. Most of the top supercomputers are similar to Frontier, they use AMD or Intel CPUs, with GPU accelerators, and Cray Slingshot or Infiniband networks in a Dragonfly+ configuration.