GITNUX MARKETDATA REPORT 2023
Must-Know Infrastructure Monitoring Metrics
Highlights: The Most Important Infrastructure Monitoring Metrics
- 1. CPU Usage
- 2. Memory Usage
- 3. Disk Usage
- 4. Disk I:
- 5. Network Latency
- 6. Network Throughput
- 7. Network Error Rate
- 8. Response Time
- 9. Application Availability
- 10. Request Rate
- 11. Error Rate
- 12. Load Balancer Metrics
- 13. Database Performance Metrics
- 14. Cache Hit Rate
- 15. Garbage Collection Metrics
Table of Contents
Infrastructure Monitoring Metrics: Our Guide
Effective management of IT systems relies heavily on understanding key metrics to maintain optimal performance and prevent potential issues. In our latest blog post, we delve into the must-know infrastructure monitoring metrics essential for any tech-savvy engineer or IT specialist. From CPU load to memory use and network latency, understanding these metrics will help keep your infrastructure running smoothly and efficiently.
It measures the percentage of time the CPU spends processing non-idle tasks. High CPU usage can indicate excessive workload or inefficient code execution.
It measures the amount of memory currently in use by the system. High memory usage can cause performance issues and slow down the infrastructure.
It measures the proportion of disk space that has been used. High disk usage can indicate insufficient storage capacity or an excessive amount of data stored on the system.
It measures the amount of data read and written to the disk over a specific time. High disk |/O can indicate a bottleneck and slow down the overall system performance.
Network latency measures data travel time in a network. High latency affects web app performance and user experience.
It measures the amount of data transmitted over a network per unit of time. Low network throughput can indicate network congestion or other issues that slow data transmission.
Network Error Rate
It measures the percentage of network requests that result in errors. High network error rates can indicate network stability issues, leading to a poor user experience.
It measures the time taken by a system to process a request and return a response. High response times can lead to slow application performance and customer dissatisfaction.
It measures application accessibility and functionality percentage. Low availability signals system issues impacting user experience.
It measures the number of requests received by an application per unit of time. High request rates can cause performance degradation if the infrastructure is not scaled properly.
It measures the percentage of requests resulting in errors. High error rates can indicate application bugs, configuration issues, or other problems that impact user experience.
Load Balancer Metrics
These metrics assess instance health, request count, and latency for efficient load balancing and workload distribution.
Database Performance Metrics
These metrics measure database operation times, the number of active connections, and query performance to ensure optimal database performance and prevent bottlenecks.
Cache Hit Rate
It measures the ratio of cached requests to total requests. A high rate indicates an efficient caching strategy, reducing the load on the main data source.
Garbage Collection Metrics
These metrics track garbage collection time, collected objects, and freed memory. Monitoring helps spot memory issues and performance impacts.
Frequently Asked Questions
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What are some common Infrastructure Monitoring Metrics?
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How we write these articles
We have not conducted any studies ourselves. Our article provides a summary of all the statistics and studies available at the time of writing. We are solely presenting a summary, not expressing our own opinion. We have collected all statistics within our internal database. In some cases, we use Artificial Intelligence for formulating the statistics. The articles are updated regularly. See our Editorial Guidelines.