Scenario 3: EC2 Instance Performance Degradation Under Heavy Load

(Mindmap and Audio Discussion is a paid feature)

Problem:

• An EC2 instance running a critical service shows high latency during peak usage.
  
  

• Users experience slow responses or the application becomes unresponsive.
  
  

Step-by-Step Troubleshooting:

1. Analyze CloudWatch Metrics:
   
   

   • Check CPU utilization to see if it is consistently high.
     
     

   • Monitor memory usage if custom metrics are configured, as CloudWatch does not show memory by default.
     
     

   • Review disk I/O metrics to identify if read or write operations are a bottleneck.
     
     

   • Examine network throughput for spikes or limits being reached.
     
     

   • Identify if any single resource (CPU, memory, disk, network) is saturated.
     
     

2. Inspect Application and System Logs:
   
   

   • Look for signs of inefficient application processes such as long-running queries or operations.
     
     

   • Check for memory leaks indicated by gradually increasing memory usage.
     
     

   • Review OS-level logs for resource exhaustion errors like out-of-memory (OOM) kills or disk full errors.
     
     

   • Ensure there are no failed dependencies or services that the application relies on.
     
     

3. Evaluate Scaling Options:
   
   

   • Consider vertical scaling by upgrading the instance to one with more vCPU, memory, or network bandwidth.
     
     

   • Evaluate horizontal scaling by distributing the load across multiple instances using an Auto Scaling group.
     
     

   • Use Elastic Load Balancing (ELB) to balance traffic between instances if scaling horizontally.
     
     

   • Ensure that Auto Scaling policies are configured based on CloudWatch alarms to handle peak loads automatically.
     
     

4. Review Instance Configuration:
   
   

   • Verify that enhanced networking (ENA) is enabled for better network performance.
     
     

   • Check if Elastic Block Store (EBS) optimization is enabled for higher I/O throughput.
     
     

   • Tune OS parameters, such as increasing the limit for file descriptors or adjusting kernel settings for performance.
     
     

   • Ensure that swap space is configured correctly if needed, but avoid relying heavily on swap.
     
     

5. Plan for Optimizing Code:
   
   

   • Identify inefficient code paths or queries that could be optimized.
     
     

   • Implement caching layers (e.g., Memcached or Redis) to reduce repeated processing.
     
     

   • Use content delivery networks (CDNs) for static content if applicable.
     
     

   • Optimize database queries and consider using read replicas for database scaling.
     
     

   • Profile the application to find bottlenecks and address them at the code level.
     
     

Key AWS Terms:

• CloudWatch: AWS monitoring service for collecting and tracking metrics.
  
  

• Auto Scaling: Automatically adjusts the number of EC2 instances based on demand.
  
  

• ENA (Elastic Network Adapter): Provides high-performance networking for EC2 instances.
  
  

• EBS Optimization: Enhances I/O performance between EC2 and EBS.
  
  

• Elastic Load Balancer (ELB): Distributes incoming application traffic across multiple targets.
  
  

Interview Insight:

• When an EC2 instance shows degraded performance, I start by reviewing CloudWatch metrics to pinpoint the saturated resource.
  
  

• I combine system and application log analysis to understand if the issue is infrastructure or application-related.
  
  

• Based on findings, I decide whether to scale vertically for quick relief or implement horizontal scaling for long-term stability.
  
  

• Additionally, I assess application performance and recommend optimizations or caching to minimize resource load.