Case Study Detail

Company name: Close Up Foundation

Case Study Title: EC2 Web Server Performance Issues

Case Study Short Description: Close Up Foundation had a variety of problems in its WordPress-based web server, and with its attempt to migrate to AWS services.

Date Start: June 2021

Date Stop: July 2021

Country of Work: USA/Washington DC

Industry Vertical: Education – Non Profit

Problem Statement/ Definition

Problem Statement/Definition: Performance Issue of an Amazon EC2 Instance

Problem Statement:

The current Amazon EC2 instance used in our application is experiencing performance issues, negatively impacting the application’s responsiveness and user experience. We need to investigate and address the performance problems to ensure optimal performance and meet our application’s requirements.

Objectives:

• Identify the root cause(s) of the performance issue on the Amazon EC2 instance.
• Resolve the performance problems to restore optimal performance and improve user experience.
• Implement measures to prevent similar performance issues from recurring in the future.

Approach:

• Performance Monitoring and Analysis: Collect and analyze performance metrics, such as CPU utilization, memory usage, disk I/O, and network latency, to identify patterns, bottlenecks, and potential causes of the performance issue.
• Application Profiling: Profile the application’s code, database queries, and resource usage to identify any inefficient or resource-intensive operations that could be causing performance degradation.
• System Optimization: Optimize the Amazon EC2 instance’s configuration and resource allocation, ensuring appropriate instance type, size, and scaling settings to meet the application’s performance requirements.
• Performance Tuning: Identify and implement performance optimizations, such as query optimization, caching mechanisms, or code refactoring, to improve the application’s responsiveness and reduce latency.
• Testing and Validation: Conduct rigorous testing to verify the effectiveness of the implemented optimizations and ensure that the application’s performance meets the desired objectives.

By addressing the performance issue on the Amazon EC2 instance through a systematic approach, we aim to restore optimal performance, enhance user experience, and ensure the reliable operation of our application.

Proposed Solution & Architecture

Proposed Solution & Architecture: Optimization of Underperforming AWS EC2 Instance

1. Performance Analysis and Monitoring:
Conduct a thorough performance analysis of the underperforming EC2 instance. Monitor key performance metrics such as CPU utilization, memory usage, disk I/O, and network latency using AWS CloudWatch or third-party monitoring tools. Identify performance bottlenecks and areas for improvement.
2. Vertical Scaling:
Assess the resource utilization of the EC2 instance and consider scaling up vertically by choosing a larger instance size with higher CPU and memory capacity. This will provide the application with more resources to handle increased workload and improve overall performance.
3. Horizontal Scaling
Evaluate the application’s architecture for potential horizontal scaling opportunities. If the workload can be distributed across multiple instances, consider implementing an auto-scaling group using Amazon EC2 Auto Scaling. This allows for automatic scaling of the application based on predefined policies and helps handle varying levels of traffic efficiently.
4. Instance Type Optimization:
Review the workload characteristics and requirements of the application. Evaluate the suitability of different EC2 instance types, taking into account factors such as CPU, memory, storage, and network performance. Consider instances optimized for specific workloads, such as compute-optimized or memory-optimized instances, to better align with the application’s needs.
5. Elastic Load Balancing:
Introduce an Elastic Load Balancer (ELB) to evenly distribute incoming traffic across multiple EC2 instances. This load balancing mechanism improves performance and provides fault tolerance by automatically routing requests to healthy instances. ELB also enables seamless scaling and simplifies the management of traffic distribution.
6. Caching and Content Delivery:
Implement caching mechanisms to reduce the load on the EC2 instance and improve response times. Utilize services like Amazon ElastiCache for in-memory caching of frequently accessed data or Amazon CloudFront for content delivery network (CDN) caching to serve static assets and improve overall application performance.
7. Database Optimization:
Evaluate the database performance and optimize it to reduce query response times. Implement techniques such as query optimization, indexing, and database scaling to ensure efficient data retrieval and storage. Consider utilizing managed database services like Amazon RDS or Amazon Aurora for better performance, automated backups, and scalability.
8. Content and Application Optimization:
Analyze the application code and optimize it for performance. Identify resource-intensive operations, inefficient algorithms, or redundant code that could be impacting the overall performance. Employ techniques such as code profiling, performance testing, and code refactoring to enhance the application’s efficiency.
9. Automated Monitoring and Alerting:
Set up proactive monitoring and alerting systems to detect performance anomalies and respond to issues promptly. Configure alarms and notifications based on specific performance thresholds to ensure timely intervention and mitigation of potential performance bottlenecks.
10. Continuous Optimization:
Establish a continuous optimization process to regularly assess the performance of the EC2 instance and make necessary adjustments. Continuously monitor and analyze performance metrics, review application architecture, and leverage AWS services and best practices to fine-tune performance over time.
By implementing these proposed solutions and optimizing the architecture of the underperforming EC2 instance, it is possible to enhance its performance, scalability, and overall reliability, ensuring a smooth and efficient operation of the application.

Outcomes of Project & Success Metric

Here are some of outcomes of a project and their corresponding success metrics:

1. Outcome: Increase in sales revenue.

Success Metric: Percentage increase in sales revenue compared to the previous year or a predetermined target.

2. Outcome: Improved customer satisfaction.

Success Metric: Increase in customer satisfaction scores or ratings based on surveys or feedback.

3. Outcome: Cost reduction.

Success Metric: Percentage decrease in operational costs or expenses compared to the baseline or a predetermined target.

4. Outcome: Increased website traffic.

Success Metric: Percentage increase in website traffic or unique visitors over a specific period of time.

5. Outcome: Enhanced employee productivity.

Success Metric: Percentage increase in individual or team productivity measured by key performance indicators (KPIs) or completed tasks.

6. Outcome: Successful completion of project milestones.

Success Metric: Achievement of predefined project milestones within the given timeframe.

7. Outcome: Improved product quality.

Success Metric: Reduction in product defects or customer complaints, measured as a percentage or absolute numbers.

8. Outcome: Enhanced brand recognition.

Success Metric: Increase in brand awareness or brand recognition measured through surveys, market research, or social media engagement.

9. Outcome: Successful implementation of a new system or technology.

Success Metric: Timely completion of system implementation, minimal disruptions during the transition, and user satisfaction surveys.

10. Outcome: Increased market share.

Success Metric: Percentage increase in market share compared to competitors or growth in market share within a specific period.

These are just a few examples, and the specific outcomes and success metrics will vary depending on the nature of the project and its objectives. It’s important to define clear and measurable success metrics at the beginning of a project to track progress and determine if the project has achieved its intended outcomes.

Describe TCO Analysis Performed (EC2)

TCO (Total Cost of Ownership) analysis for AWS EC2 instances involves evaluating the overall costs associated with utilizing EC2 instances throughout their lifecycle. Here is an overview of the TCO analysis performed for AWS EC2 instances:
Resource Costs:
Calculate the cost of EC2 instances based on their instance type, size, and usage. Consider the pricing model (On-Demand, Reserved, or Spot instances) and estimate the expected utilization levels. Take into account any discounts or savings plans available for Reserved instances to optimize costs.
Storage Costs

Assess the storage requirements for the EC2 instances. Consider the cost of Amazon Elastic Block Store (EBS) volumes or other storage options (such as Amazon S3 for object storage). Estimate the amount of storage needed and the associated costs based on the chosen storage type and capacity.

Network Costs

Evaluate the network traffic and data transfer costs for EC2 instances. Consider the data transfer volume within AWS regions, between regions, and to the internet. Assess the costs associated with data transfer using AWS Direct Connect or Virtual Private Network (VPN) connections, if applicable.

Data Transfer and Bandwidth Costs:

Analyze the costs of inbound and outbound data transfer to and from EC2 instances. Take into account the data transfer rates, data transfer between AWS services, and data transfer outside of AWS (e.g., to clients or other data centers). Estimate the associated costs based on the data transfer volume and regions involved.

Load Balancing Costs

Analyze the costs of inbound and outbound data transfer to and from EC2 instances. Take into account the data transfer rates, data transfer between AWS services, and data transfer outside of AWS (e.g., to clients or other data centers). Estimate the associated costs based on the data transfer volume and regions involved.

Management and Operations Costs
Evaluate the costs associated with managing and operating EC2 instances. This includes factors like monitoring, troubleshooting, patching, and system administration. Consider the use of AWS services like Amazon CloudWatch or third-party monitoring tools for cost estimation.
Instance Lifecycle Costs

Estimate the costs associated with instance lifecycle management. This includes costs for provisioning, deprovisioning, and resizing instances as workload requirements change. Consider automation and DevOps practices that can optimize these costs and improve efficiency.

Optimization Opportunities

Identify potential optimization opportunities to reduce costs. This may involve rightsizing instances, leveraging AWS Cost Explorer to analyze usage patterns, utilizing instance types with lower costs, or utilizing Spot instances for cost savings during non-critical workloads.

Long-Term Projections

Project the TCO over a specified time period, considering factors like anticipated growth, changes in usage patterns, and pricing adjustments. This helps in understanding the long-term financial implications of utilizing EC2 instances.

CO Comparison
Compare the TCO of EC2 instances with alternative deployment options, such as managed services or serverless architectures. Consider the trade-offs between costs, operational complexity, scalability, and performance to make informed decisions.

By performing a comprehensive TCO analysis for AWS EC2 instances, organizations can evaluate the total cost implications and make informed decisions about resource allocation, optimization strategies, and selecting the most cost-effective solution for their workloads.

Lessons Learned

Lessons Learned when Addressing AWS EC2 Performance Issues

Comprehensive Monitoring:
Lesson: Implementing comprehensive monitoring of EC2 instances is crucial for early detection and resolution of performance issues. By monitoring key performance metrics and leveraging AWS CloudWatch or third-party monitoring tools, we can proactively identify bottlenecks, resource utilization problems, or any anomalies affecting the instance’s performance.

Right-sizing Instances:
Lesson: Properly sizing EC2 instances based on workload requirements is essential. When addressing performance issues, it is important to assess whether the current instance size adequately meets the application’s needs. Conducting load testing and performance analysis helps determine if vertical scaling (choosing a larger instance) or horizontal scaling (distributing workload across multiple instances) is necessary to optimize performance.

Utilizing Auto Scaling:
Lesson: Leveraging Amazon EC2 Auto Scaling for workload fluctuations is beneficial. Implementing auto-scaling groups allows us to automatically add or remove EC2 instances based on predefined scaling policies. By dynamically adjusting instance capacity to match demand, we can ensure optimal performance during peak periods and cost efficiency during low-demand periods.

Load Balancing:
Lesson: Incorporating Elastic Load Balancer (ELB) can significantly improve performance and availability. By distributing incoming traffic across multiple EC2 instances, ELB balances the load and provides fault tolerance. Utilizing ELB ensures that the application can handle increased traffic and automatically directs requests to healthy instances, optimizing performance and enhancing overall user experience.

Database Optimization:
Lesson: Optimizing the database layer is crucial for EC2 performance. Analyzing and optimizing database queries, employing proper indexing strategies, and utilizing managed database services (e.g., Amazon RDS or Amazon Aurora) can significantly enhance performance. By reducing query response times and ensuring efficient data retrieval, the overall application performance can be improved.

Caching Mechanisms:
Lesson: Implementing caching mechanisms reduces the load on EC2 instances and improves response times. Utilizing services like Amazon ElastiCache or content delivery networks (CDNs) such as Amazon CloudFront helps cache frequently accessed data and static assets. This minimizes the need for repetitive data retrieval and accelerates content delivery, resulting in enhanced performance.

Application Code Optimization:
Lesson: Optimizing the application code is essential for efficient resource utilization. Regularly reviewing and optimizing code, employing best practices, and leveraging performance profiling tools help identify and address resource-intensive operations, inefficient algorithms, or redundant code. Code optimization reduces processing time, enhances responsiveness, and improves overall performance.

Continuous Improvement:
Lesson: Embrace a culture of continuous improvement to address evolving performance challenges. Regularly review performance metrics, conduct periodic load testing, and stay updated with AWS service enhancements and best practices. By continually optimizing the EC2 instances and the application architecture, we can proactively address performance issues and deliver an optimized user experience.

Documentation and Knowledge Sharing:
Lesson: Document lessons learned, best practices, and optimization techniques for future reference and knowledge sharing. Creating a centralized repository of performance-related information and sharing it with the team helps streamline troubleshooting efforts and facilitates the adoption of proven strategies for addressing EC2 performance issues.

By applying these lessons learned, organizations can effectively address AWS EC2 performance issues, enhance application performance, and ensure a seamless user experience. Regular monitoring, right-sizing instances, leveraging scalability features, optimizing databases and code, and fostering a culture of continuous improvement are key factors in maintaining optimal EC2 performance.

New Implementation or Migration from another Solution?

Type: Migration from another Solution

Migration from Underperforming EC2 Instance to Another Solution

Scenario:
We have identified an underperforming EC2 instance that is negatively impacting our application’s performance and user experience. To address this issue, we have decided to migrate to another solution that can better meet our performance requirements. Here is an example of the migration process:

• Evaluation and Requirements Gathering:

  Conduct a thorough evaluation of the application’s performance requirements and identify the shortcomings of the existing EC2 instance. Determine the specific performance metrics that need improvement, such as response times, scalability, or resource utilization.

• Solution Selection

  Explore alternative solutions that align with the performance requirements and address the identified shortcomings. Consider AWS services like AWS Elastic Beanstalk, AWS Lambda, or AWS Fargate, which offer managed environments with built-in scalability and performance optimizations.

• Architecture Design

  Design the target architecture that optimizes performance and scalability. Consider decoupling components, implementing microservices architecture, leveraging serverless computing, or utilizing managed database services to improve performance and resource utilization.

• Data Migration

  Plan and execute the migration of data from the existing EC2 instance to the new solution. Identify the appropriate method for data transfer, such as database replication, data export/import, or utilizing AWS Database Migration Service (DMS) for database migration. Ensure data integrity and consistency during the migration process.

• Application Migration

  Develop a migration plan to move the application from the underperforming EC2 instance to the new solution. This may involve refactoring or rearchitecting the application code to be compatible with the target solution. Leverage deployment tools like AWS CodeDeploy or AWS CloudFormation for automated and consistent application deployment.

• Testing and Validation

  Conduct thorough testing to validate the performance improvements achieved with the migration. Perform load testing, stress testing, and monitor key performance indicators to ensure the new solution meets or exceeds the performance requirements. Address any issues identified during testing before proceeding to production.

• Cut-Over and Go-Live

  Coordinate the cut-over from the underperforming EC2 instance to the new solution. Plan a maintenance window to minimize user impact and ensure a seamless transition. Update DNS records or load balancer configurations to route traffic to the new solution. Monitor the application closely post-migration to identify any post-migration issues and promptly address them.

• Performance Monitoring and Optimization

  Implement robust performance monitoring and optimization practices for the new solution. Utilize AWS CloudWatch or third-party monitoring tools to track key performance metrics and proactively address any performance bottlenecks. Continuously monitor and optimize the application code, database performance, and resource utilization to ensure ongoing optimal performance.

• Documentation and Knowledge Transfer

  Document the migration process, including the challenges faced, lessons learned, and best practices. Share this knowledge within the team to facilitate future migrations or optimizations. This documentation can serve as a valuable reference for troubleshooting or scaling the new solution.

By migrating from the underperforming EC2 instance to a solution that better meets the performance requirements, organizations can significantly improve their application’s performance, user experience, and overall efficiency. The migration process involves careful evaluation, solution selection, architecture design, data and application migration, thorough testing, and ongoing performance optimization.