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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Redis® is an in-memory database that provides blazingly fast performance. This makes it a compelling alternative to disk-based databases when performance is a concern. Redis returns a big list of database metrics when you run the info command on the Redis shell. This blog post lists the important database metrics to monitor.

Metrics 130
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Key Advantages of DBMS for Efficient Data Management

Scalegrid

If you’re considering a database management system, understanding these benefits is crucial. DBMS enhances data security with encryption, implements various access controls, and enables improved data sharing and concurrent access, thus facilitating quick response to changes and maintaining consistent database accuracy.

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

Percona

MySQL performance tuning offers several significant advantages for effective database management and optimization. Enhanced Database Efficiency By adjusting configuration settings, you can markedly enhance the overall efficiency of your MySQL database. Experiencing database performance issues?

Tuning 52
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MySQL Key Performance Indicators (KPI) With PMM

Percona

As a MySQL database administrator, keeping a close eye on the performance of your MySQL server is crucial to ensure optimal database operations. This includes metrics such as query execution time, the number of queries executed per second, and the utilization of query cache and adaptive hash index.

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How Data Inspires Building a Scalable, Resilient and Secure Cloud Infrastructure At Netflix

The Netflix TechBlog

the order of the rows on your Netflix home page, issuing content licenses when you click play, finding the Open Connect cache closest to you with the content you requested, and many more). Can we adjust our auto-scaling policies to be more efficiency without risking our availability during traffic spikes?

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Percentiles don’t work: Analyzing the distribution of response times for web services

Adrian Cockcroft

There is no way to model how much more traffic you can send to that system before it exceeds it’s SLA. I presented this analysis of response time distributions talk in 2016 — at Microxchg in Berlin ( video ). For high traffic systems, processing the individual response times for each request may be too much work.

Lambda 98
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AWS EKS Monitoring as a Self-Service with Dynatrace

Dynatrace

REDIS for caching. Thanks to PurePath, architects can validate how transactions flow from service-to-service and how traffic gets routed through service mashes (AWS App Mesh, Istio, Linkerd) or proxies. Dynatrace’s Response Time Hotspot Analysis automates the hotspot detection in highly distributed systems. 3 Log Analytics.

AWS 127