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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. offers the Software Watchdog specifically designed for this purpose.

Metrics 130
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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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MySQL Performance Tuning 101: Key Tips to Improve MySQL Database Performance

Percona

This results in expedited query execution, reduced resource utilization, and more efficient exploitation of the available hardware resources. This not only enhances performance but also enables you to make more efficient use of your hardware resources, potentially resulting in cost savings on infrastructure.

Tuning 52
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The Various Methods to Backup and Restore ProxySQL

Percona

The proxy is designed to run continuously without needing to be restarted. sec) Conclusion These methods provide solutions for ProxySQL backups and restores, which play a pivotal role in safeguarding the integrity of your data and providing defense against various disasters, hardware malfunctions, data loss, and corruption.

Traffic 107
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Current status, needs, and challenges in Heterogeneous and Composable Memory from the HCM workshop (HPCA’23)

ACM Sigarch

using Compute Express Link or CXL), organizing memory components for optimal performance, adapting system software traditionally designed for homogeneous memory systems, and developing memory abstractions and programming constructs for HCM management. About CXL hardware availability with academia. Using emulation (e.g.

Latency 52
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Seeing through hardware counters: a journey to threefold performance increase

The Netflix TechBlog

At Netflix, we periodically reevaluate our workloads to optimize utilization of available capacity. We also see much higher L1 cache activity combined with 4x higher count of MACHINE_CLEARS. a usage pattern occurring when 2 cores reading from / writing to unrelated variables that happen to share the same L1 cache line.

Hardware 363
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Building an elastic query engine on disaggregated storage

The Morning Paper

This paper describes the design decisions behind the Snowflake cloud-based data warehouse. This paper presents Snowflake design and implementation along with a discussion on how recent changes in cloud infrastructure (emerging hardware, fine-grained billing, etc.) From shared-nothing to disaggregation. Workload characteristics.

Storage 112