Select Language:
The difference in CPU usage you’re seeing between t3.nano and t3a.nano instances mainly comes down to the type of processor they use. T3a instances run on AMD EPYC processors, while T3 instances use Intel processors. This means the two architecture types handle workloads differently, even if the instance size looks the same.
In particular, AMD processors in t3a instances might perform differently with your workload compared to Intel processors. This can cause the CPU usage to be higher in the t3a.nano account. For burstable instances like these, this is important because they work based on a system of CPU credits.
With these instances, there’s a base utilization level of about 5%. When your usage exceeds this level, like the 8% you’re seeing with t3a.nano, the system starts to use up CPU credits. If these credits run out, your instance could slow down as it has less CPU power available.
T3a instances are usually cheaper—about 10% less expensive—compared to standard T3 instances. However, if your workload constantly pushes CPU usage higher, it might run through credits faster, which could lead to performance issues over time.
If you need to keep your CPU usage steady and avoid running out of credits, here are some options to consider:
– Switch back to a t3.nano instance
– Upgrade to a larger instance that has a higher baseline performance level
– Check if there are any Windows-specific processes or scheduled tasks that might be affected by the AMD architecture
These steps can help you manage CPU usage better and ensure smoother performance.
ChatGPT
Perplexity
Gemini AI
Grok AI
