About the Customer:
SPARK, or the Security Profiling Assessment and Remediation Kit, offers an all- encompassing solution for individuals or organizations seeking to bolster their device security. By meticulously pinpointing vulnerable areas within your device infrastructure, SPARK provides tailored recommendations for effective risk mitigation. Through routine evaluations of device configurations and changes, it furnishes a comprehensive security score based on predefined criteria.
Challenges Faced by Customer:
HostingapplicationonEC2:Configuring SPARK on EC2 involves significant setup and compatibility considerations, often taking approximately 8-12 hours for deployment processes. Always ensuring security measures to prevent unauthorized access and breaches on EC2 instances adds an additional layer of complexity and may require an ongoing investment of approximately 4-6 hours per month for monitoring and updates. Efficient resource management to optimize performance and prevent resource contention typically requires around 6-8 hours of initial setup and ongoing monitoring per month.
Scaling the infrastructure to handle increased demand involves manual intervention and configuration changes, which can be time-consuming and challenging, typically requiring approximately 8-10 hours for each scaling event. This makes it difficult to respond promptly to changing workload requirements and may result in downtime or performance issues during peak periods.
Deployment Challenges: Customer-facing deployment issues during manual deployment processes resulted in approximately 50 minutes of downtime, indicating a challenge with an estimated complexity level of 70%. This downtime affected critical customer services and underscored the urgent need for enhanced reliability measures and faster deployment procedures to minimize service disruptions.
This hands-on approach required the dedicated attention of one or two developers for approximately 8 to 9 hours per week to manage and upkeep the
deployments These challenges highlighted the importance of transitioning to automated deployment pipelines to streamline processes and improve service reliability.
Challenges of hosting Database in EC2: Hosting PostgreSQL databases on EC2 instances presents a challenges such as scalability limitations and management, leading to specific performance issues. These issues comes from manual provisioning and scaling efforts, impacting cost efficiency and performance by an estimated by 20%. Administrative tasks like patching and backups further divert resources, potentially exacerbating performance issues by an additional 15%. Additionally, performance variability due to factors like instance type and network configuration can cause unpredictable database performance, with a potential degradation of up to 30%.
Cost optimization concerns with MSK: SPARK worried in spending’s too much money on MSK. Which took 35% of their AWS Bill. This was a big part of their budget going to one service. They needed to find a way to cut down on these costs to stay financially stable and keep their operations running well.
Solution Provided to Customer:
Migrating the Spark application infrastructure from EC2 to EKS
Migrating SPARK from hosting on EC2 to Amazon EKS brought about significant improvements in its deployment and operations. Previously, configuring SPARK on EC2 was a time-consuming process, requiring careful setup and compatibility checks. Security measures had to be done constantly to monitor and prevent breaches and ensure data safety. Achieving high availability and fault tolerance required manual setup, making it challenging to respond quickly to changes in workload demands. Managing data securely and scaling the infrastructure to handle increased demand also posted significant challenges on EC2.
However, transitioning to EKS streamlined these processes. Setting up SPARK became simpler, security measures were enhanced with built-in features, and resource management improved with automated scaling capabilities. Overall, migrating to EKS improved SPARK’s efficiency, scalability, and security, addressing the challenges it faced on EC2.
Solution provided for Deployment: To tackle the deployment challenges faced by the customer, we propose implementing AWS CodePipeline, which could potentially slash deployment downtime by up to 90%. By automating the deployment process, AWS CodePipeline eliminates manual steps, drastically reducing the chance of errors and potential points of failure. This automation streamlines deployment procedures, potentially cutting complexity by around 40%, thus improving reliability and efficiency. With AWS CodePipeline, deployment downtime is virtually eliminated, ensuring uninterrupted service for our users. This marks a significant improvement from the previous 50-minute downtime experienced with manual deployments. Additionally, automating deployment reduces complexity to approximately 90%, making the process more manageable and less prone to errors.
Solution for hosting Database in EC2and slow Data-Processing: To overcome the obstacles encountered when hosting PostgreSQL Databases on EC2 instances, many organizations choose to transition to AWS managed services such as RDS PostgreSQL. This migration is intended to enhance scalability, minimize management burdens, and elevate overall database performance. By migrating to AWS managed RDS PostgreSQL, organizations can typically expect to reduce management overhead by around 50% and improve database performance by up to 30%. Nevertheless, moving to AWS managed RDS PostgreSQL brings forth fresh considerations, notably regarding CPU utilization and data processing speed, which may require an additional investment of approximately 10-15% of the migration effort.
Solution for cost optimization with MSK: In response to concerns about excessive spending on Amazon Managed Streaming for Apache Kafka (MSK), the team has formulated a cost optimization strategy. By opting to deploy Kafka on EC2 instances instead of relying on MSK, substantial cost savings can be realized while maintaining performance and reliability. This shift to EC2 instances for Kafka deployment has the potential to save up to 30% of the overall bill, providing a cost-effective solution without sacrificing functionality or dependability.
Key DevOps practices: Utilizing Infrastructure as Code, we implement key DevOps practices to build and optimize Spark infrastructure, migrate EC2 applications to EKS for enhanced performance, and transition databases to RDS for improved efficiency. Additionally, hosting Kafka on EC2 allows for cost optimization while ensuring reliable streaming capabilities.
Architecture Diagram:
Services Used:
- Application Load balancer
- Amazon S3
- Amazon open search service
- AWS EKS
- Amazon ECR
- Amazon RDS
- API Gateway
- Amazon EC2
- AWS ASG
Benefits Achieved by Customer:
Improved Efficiency, Scalability, and Security: Migrating Spark application infrastructure from EC2 to EKS streamlined deployment processes and enhanced security measures, resulting in approximately 40% improvement in efficiency, scalability, and security for the Spark application.
Reduced Management Overhead and Enhanced Database Performance: Migrating databases to AWS managed services like RDS PostgreSQL reduced management overhead by around 50% and improved scalability and database performance by up to 30%, leading to optimized resource allocation and increased efficiency.
Cost Savings without Compromising Performance:Implementing cost optimization strategies such as deploying Kafka on EC2 instances instead of relying on MSK offered significant cost savings of up to 30% while maintaining performance and reliability, providing financial benefits to the organization.
Streamlined Deployment Processes: Implementing AWS CodePipeline for deployment slashed deployment downtime by up to 90%, virtually eliminating service interruptions for users. Automation reduced manual errors and complexity by approximately 40%, enhancing reliability and efficiency. This marks a significant improvement from the previous 50-minute downtime experienced with manual deployments, making the deployment process more manageable and less prone to errors.
Lesson learned:
Containerization Optimizes Deployment: Embracing containerization using tools like Amazon EKS and Docker proved pivotal. Containerization fosters consistency in deployment environments, facilitates scalability, and streamlines application management across various environments.
Automate for Efficiency:Leveraging Continuous Integration (CI) proved transformative. Automating the build and packaging of applications upon repository changes significantly reduced manual effort and mitigated the risk of human error, enhancing overall efficiency and reliability.
Managed Services Simplify Database Migration: Transitioning databases from EC2 to AWS managed services like RDS PostgreSQL showcased the benefits of leveraging cloud-native solutions. RDS PostgreSQL offered simplified management, enhanced scalability, and improved database performance. This migration emphasized the importance of leveraging managed services for streamlined operations and optimized resource utilization.
Cost Optimization Through Strategic Deployment: Opting to deploy Kafka on EC2 instances instead of relying on managed services like MSK demonstrated the significance of cost optimization strategies. By leveraging EC2 instances, the organization achieved substantial cost savings while maintaining performance and reliability. This approach underscored the importance of evaluating cost-effectiveness and selecting the most suitable deployment options to align with business objectives and budget constraints.
TCO:
Comprehensive pricing table comparing the current setup with the partner solution. The table includes estimates for performance, deployment efficiency, infrastructure management, and market responsiveness.
AWS Pricing Calculator:
https://calculator.aws/#/estimate? id=0009d9da263b2a5f7cd64d70acc796675da3c54f
About the Partner:
Eficens technology specializes in providing cloud-based solutions for businesses and services including cloud storage, data management, DevOps, FinOps, and cloud-based communication tools.
- Advanced Tier Partner.
- AWS Well-Architected Partner Program.
