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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. These essential data points heavily influence both stability and efficiency within the system.

Metrics 130
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Maximizing Performance of AWS RDS for MySQL with Dedicated Log Volumes

Percona

A Dedicated Log Volume (DLV) is a specialized storage volume designed to house database transaction logs separately from the volume containing the database tables. DLVs are particularly advantageous for databases with large allocated storage, high I/O per second (IOPS) requirements, or latency-sensitive workloads.

AWS 94
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How To Scale a Single-Host PostgreSQL Database With Citus

Percona

Rather than listing the concepts, function calls, etc, available in Citus, which frankly is a bit boring, I’m going to explore scaling out a database system starting with a single host. And now, execute the benchmark: -- execute the following on the coordinator node pgbench -c 20 -j 3 -T 60 -P 3 pgbench The results are not pretty.

Database 102
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Redis vs Memcached in 2024

Scalegrid

This article will explore how they handle data storage and scalability, perform in different scenarios, and, most importantly, how these factors influence your choice. It uses a hash table to manage these pairs, divided into fixed-size buckets with linked lists for key-value storage. High data availability is achieved.

Cache 130
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Characterizing, modeling, and benchmarking RocksDB key-value workloads at Facebook

The Morning Paper

Characterizing, modeling, and benchmarking RocksDB key-value workloads at Facebook , Cao et al., Or in the case of key-value stores, what you benchmark. So if you want to design a system that will offer good real-world performance, it’s really useful to have benchmarks that accurately represent real-world workloads.

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Grafana Dashboards: A PoC Implementing the PostgreSQL Extension pg_stat_monitor

Percona

Querying the data While it is reasonable to create panels showing real-time load in order to explore better the types of queries that can be run against pg_stat_monitor, it is more practical to copy and query the data into tables after the benchmarking has completed its run. A script executing a benchmarking run: #!/bin/bash

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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

which is difficult when troubleshooting distributed systems. If we had an ID for each streaming session then distributed tracing could easily reconstruct session failure by providing service topology, retry and error tags, and latency measurements for all service calls.