Problems

Compute/CPU

If you suspect your CPU resources are slow, the following actors may be affecting your server performance.

CPU Problem	Description
Insufficient Clock Speed	The clock speed of the CPU is too low to execute a workload efficiently.
Insufficient Cache Memory	The amount of cache memory available is insufficient to execute a workload efficiently.
High Power Consumption	The power consumption of the CPU is too high to execute a workload efficiently.
Instruction Mix	The instructions used to execute a workload are not optimal for performance.
Context Switches	Too many context switches are required to execute a workload, resulting in lower performance.
Memory Bandwidth	The memory bandwidth available is insufficient to execute a workload efficiently.
Memory Latency	The latency of memory accesses is too high to execute a workload efficiently.
I/O Bandwidth	The I/O bandwidth available is insufficient to execute a workload efficiently.
I/O Latency	The latency of I/O operations is too high to execute a workload efficiently.
Network Latency	The latency of network requests is too high to execute a workload efficiently.
Insufficient Threads	The number of threads available is insufficient to execute a workload efficiently.
Insufficient Cores	The number of cores available is insufficient to execute a workload efficiently.
Data Dependency	There is a data dependency between instructions, resulting in lower performance.
Out-of-Order Execution	The CPU cannot execute instructions out-of-order, resulting in lower performance.
Branch Prediction	The CPU cannot accurately predict branches, resulting in lower performance.
Compute Intensive	The workload is compute intensive, resulting in lower performance.
Memory Intensive	The workload is memory intensive, resulting in lower performance.
I/O Intensive	The workload is I/O intensive, resulting in lower performance.
Network Intensive	The workload is network intensive, resulting in lower performance.
Thermal Throttling	The CPU is throttling due to excessive heat, resulting in lower performance.

Compute/Memory

Memory Problem	Description
Insufficient Memory	The amount of memory available is insufficient to execute a workload efficiently.
Memory Bandwidth	The memory bandwidth available is insufficient to execute a workload efficiently.
Memory Latency	The latency of memory accesses is too high to execute a workload efficiently.
Memory Contention	Multiple threads are competing for access to the same memory, resulting in lower performance.
Memory Corruption	The data in memory is corrupted, resulting in lower performance.
Memory Fragmentation	Memory is fragmented, resulting in lower performance.
Memory Leaks	Memory leaks are occurring, resulting in lower performance.
Memory Overcommitment	Memory is overcommitted, resulting in lower performance.
Memory Interleaving	Memory interleaving is not optimal, resulting in lower performance.
Memory Throttling	Memory throttling is occurring, resulting in lower performance.
Memory Bank Contention	Multiple memory banks are competing for access, resulting in lower performance.
Memory Refresh	Memory refresh cycles are taking too long, resulting in lower performance.
Memory Scrubbing	Memory scrubbing is not optimal, resulting in lower performance.
Memory Error Correction	Memory error correction is not optimal, resulting in lower performance.
Memory Clock Speed	The memory clock speed is too low to execute a workload efficiently.

AWS Lambda

There are several potential reasons why an AWS Lambda function may be running slowly:

• Cold starts
  • If your Lambda function has not been invoked recently, it may experience a cold start, which can add extra latency.
• Limited resources
  • If your Lambda function is running on a low-memory instance, it may be limited in its ability to process requests quickly.
• Network Latency
  • If your Lambda function is running in a remote region or is dependent on other services that are running in a remote region, the network latency can be an issue.
• High number of parallel execution
  • If there is a high number of parallel executions of the same function, it can cause slow down due to the shared resources.
• Dependency on external service
  • If your Lambda function is dependent on an external service, and that service is slow to respond, it can cause the Lambda function to be slow.
• To troubleshoot the issue, you can check the CloudWatch logs for the Lambda function to see if there are any error messages or latency issues. Additionally, you can use the AWS X-Ray service to trace the requests to your Lambda function and identify any bottlenecks.
• You can also try to optimize your function code, for example, by caching data that is used frequently, reducing the number of external requests, or using smaller libraries. Also, you can consider to use provisioned concurrency to avoid cold starts.
• It's also a good practice to monitor the performance of your Lambda function using metrics such as error rate, invocation count, and duration to detect any changes in behavior.