Improving Application Performance

What is Performance?

Application performance refers to how well your software application operates across various metrics. It encompasses several key aspects:

• Responsiveness: How quickly the application responds to user actions.
• Stability: The consistency of the application under varying workloads.
• Scalability: The ability to handle increasing volumes of data or user requests.
• Resource Utilization: Efficient usage of CPU, memory, and network bandwidth.
• User Experience: How responsive and smooth the application feels to the end-user.

Performance in Backend Applications

For backend applications, performance can be measured in terms of:

• System responsiveness under a given workload:
  • Backend data volume
  • Request volume
• Hardware configurations:
  • Type and capacity of CPUs, memory, and storage

Spotting a Performance Problem

Detecting performance issues requires vigilance and understanding of your system’s baseline behavior.

Key Methods to Identify Performance Problems:

1. Monitoring Metrics:

   • Increased response times: Slower page loads, delayed input processing, or unresponsive applications.
   • High error rates: Frequent crashes, failed transactions, or application errors.
   • Resource utilization spikes: High CPU or memory usage, excessive network consumption.
   • Log analysis: Review logs for errors or performance-related events.

2. User Feedback:

   • Reports of slow or unresponsive behavior.
   • An increase in support tickets related to performance issues.

3. Proactive Checks:

   • Load testing to simulate heavy usage.
   • Performance profiling to identify bottlenecks.
   • Benchmarking to set performance baselines.

4. Visual Indicators:

   • Slow loading animations, progress bars, or lag in the UI can signal performance degradation.

Note: Every performance problem often results from a queue forming somewhere in the system.

Common Areas of Queue Build-up

Queues or bottlenecks can build up in various parts of the system:

1. Network:

   • Increased latency: Longer ping times, slower uploads/downloads, frequent timeouts.
   • Packet loss: Data packets getting dropped, requiring retransmission.
   • Full send/receive buffers: Queues filling up, delaying data transfer.

2. Database:

   • Slow query execution: Long query times can delay page loading.
   • Connection pool exhaustion: All connections in use, preventing new requests.
   • Disk I/O bottlenecks: Slow read/write operations impacting database responsiveness.

3. Operating System:

   • High CPU utilization.
   • Memory exhaustion leading to performance lags.
   • Process wait times caused by resource contention.

4. Application Code:

   • Inefficient algorithms.
   • Redundant calculations or code deadlocks that slow down execution.

Root Causes of Queue Build-up

• Poorly Written Code: Inefficient algorithms, unnecessary calculations, or poor memory management.
• External Dependencies: Relying on slow or resource-intensive services.
• Database Access: Multiple requests waiting for database connections.
• Sequential Task Execution: Tasks coded to run sequentially can form bottlenecks in high-load situations.

Principle: Avoid building queues during system design, and identify where queues are forming in existing systems.

Performance Principles

To improve performance, consider the following core principles:

1. Efficiency: Reduce response time for individual requests by optimizing:

   • Resource Utilization: Efficient use of CPU, memory, and network resources.
   • Logic: Using optimized algorithms and database queries.
   • Data Storage: Efficient data structures and well-designed database schemas.
   • Caching: Reducing repetitive data fetching by storing frequently accessed data.

2. Concurrency: Improve response time for concurrent requests by:

   • Leveraging multi-core hardware.
   • Writing software that can utilize multiple cores, including:
     • Non-blocking queues.
     • Logical coherence in task execution.

3. Capacity: Enhance hardware resources when necessary to improve performance.

   • Additional CPU, memory, disk, or network bandwidth can alleviate resource-related bottlenecks.

Performance Measurement Metrics

When optimizing performance, track the following key metrics:

1. Latency: Measures how quickly the system responds to requests. Lower latency improves user experience.
2. Throughput: Measures the number of requests handled per unit of time, reflecting the system's concurrency handling capacity.
3. Errors: Tracks error rates to maintain functional correctness and reliability.
4. Resource Saturation: Indicates resource usage percentages (CPU, memory, network), signaling if resources are fully utilized or underutilized.
5. Tail Latency: Measures response times of the slowest requests (e.g., 99th percentile), providing a clearer picture of performance under peak load.

Additional Considerations

• Define realistic metric targets based on user base and workload.
• Continuously monitor to identify trends, bottlenecks, and issues before they impact users.
• Remember that optimizing one metric may affect others, so take a holistic approach.

Reducing Latency in Key System Areas

1. Network Latency:

   • TCP Connection Pooling: Reuse existing connections to reduce setup time.
   • Persistent Connections: Avoid repeated handshakes by maintaining persistent connections.
   • Data Caching: Use CDN and caching to minimize round-trips for static data.
   • Minimize HTTP Requests: Combine resources to reduce round-trips.
   • Optimize DNS Resolution: Use CDNs to minimize DNS lookup times.

2. Memory Access Latency:

   • Avoid Memory Bloat: Limit data stored in memory.
   • Garbage Collection Optimization: Choose low-pause GC algorithms.
   • Batch Processing: Process data in batches to improve memory efficiency.
   • Database Normalization: Reduce redundant data storage.
   • Memory-First Processing: Prioritize in-memory data processing over disk access.

3. Disk Access Latency:

   • Sequential & Batch I/O: Disk operations are faster sequentially; batch requests together.
   • Async Logging: Offload logging to separate threads.
   • Cache Static Content: Cache static data on the client-side or CDN.
   • Use SSDs: SSDs provide faster access times compared to HDDs.

4. CPU Latency:

   • Efficient Algorithms: Optimize algorithms and code to reduce CPU load.
   • Batch and Async I/O: Batch processing and async I/O reduce CPU context-switching.
   • Thread Pool Tuning: Configure thread pools for optimal performance.

5. Reducing Tail Latency:

   • Optimize Slowest Requests: Focus on the highest-latency requests (e.g., 99th percentile).
   • Queue Management: Prevent requests from forming long queues.
   • Network Caching: Use CDN to cache frequently accessed content near users.

CPU Latency Diagram

Process P1           Process P2
(Executing)           (Idle)
     ↓                    ↓
Interrupt or            Interrupt or
System Call           System Call
     ↓                    ↓
Save state to PCB1     Save state to PCB2
     ↓                    ↓
Reload state from      Reload state from
      PCB2               PCB1
     ↓                    ↓
   (Idle)               (Executing)

Explanation:

1. Process P1 (Executing): The CPU is running Process P1 until an interrupt or system call occurs.
2. Interrupt/System Call: This event triggers a context switch to another process.
3. Save State to PCB1: The CPU saves the state of Process P1 (e.g., register values, program counter) to PCB1 (Process Control Block).
4. Switch to Process P2: The CPU loads the state of Process P2 from PCB2, which was previously idle.
5. Process P2 (Executing): Process P2 resumes execution while Process P1 is now idle.
6. This cycle repeats as needed, depending on system events like interrupts or system calls.

TCP Handshake Diagram

    Client                                  Server
       |                                       |
       | --------- SYN (seq=100) ------------> |
       |                                       |
       | <-------- SYN-ACK (seq=200, ack=101)  |
       |                                       |
       | --------- ACK (seq=101, ack=201) ---->|
       |                                       |
       |        Connection Established         |

Explanation:

• SYN: Synchronize packet to initiate a connection.
• SYN-ACK: Synchronize Acknowledgment packet to acknowledge the client’s SYN.
• ACK: Acknowledgment packet confirming connection establishment.

TLS Handshake Diagram

    Client                                        Server
       |                                            |
       | ------- Client Hello ---------------------> |
       |                                            |
       | <------- Server Hello --------------------  |
       |                                            |
       | <------- Certificate ---------------------  |
       |                                            |
       | <------- Server Key Exchange -------------- |
       |                                            |
       | <------- Server Hello Done ---------------- |
       |                                            |
       | ------- Client Key Exchange --------------> |
       |                                            |
       | ------- Change Cipher Spec ---------------> |
       |                                            |
       | ------- Encrypted Handshake Msg ----------> |
       |                                            |
       | <------- Change Cipher Spec --------------- |
       |                                            |
       | <------- Encrypted Handshake Msg ----------|
       |                                            |
       |         Secure Connection Established       |

Explanation:

• Client Hello: Client initiates the handshake by sending supported protocols, ciphers, and other configurations.
• Server Hello: Server responds with chosen protocol and cipher settings.
• Certificate: Server sends its SSL/TLS certificate.
• Key Exchanges: Client and server exchange keys for encryption.
• Change Cipher Spec: Both client and server signal readiness to start secure communication.
• Encrypted Handshake Message: Final confirmation to establish a secure connection.

Conclusion

Improving application performance requires a strategic approach to both system design and optimization. By monitoring key metrics, identifying bottlenecks, and applying targeted solutions across different system components, you can ensure your application runs efficiently, provides a smooth user experience, and scales effectively with demand.