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Cloud Database Cost Optimization with FOSS

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Cloud Database Cost Optimization with FOSS
Achieving 60-70% cost savings by transitioning from managed services to a flexible, high-performance open-source solution.
Oct 25, 2024
Cloud-database-Cost-Optimization-with-FOSS

Introduction:

A client faced an unexpected spike in database IOPS (Input/Output Operations Per Second) costs after deploying their data warehouse platform, driven by the increasing demands of frequent data processing. The steep rise in costs forced them to scale back data refresh cycles, impacting their ability to generate timely insights. To address these challenges, a transition from managed services to PostgreSQL on EC2 was proposed, aimed at cutting costs while maintaining high performance and availability.

Business Challenge:

The client experienced a sudden $20,000 monthly increase in database IOPS costs after implementing their data warehouse platform. The hourly data processing requirements consumed a significant amount of IOPS, leading to inflated expenses. To manage these costs, the client had to reduce their data refresh cycle to once per day, limiting their ability to perform timely data analysis and insight generation. In addition to IOPS costs, other expenses such as storage, compute instances, data transfers, and frequent backups were further burdening the system. This situation called for an immediate cost-optimization strategy without compromising system performance.

Solution:

To reduce costs while maintaining high availability and performance, a shift to PostgreSQL deployed on EC2 instances was proposed. This solution provided a more flexible, open-source alternative to managed services like Aurora PostgreSQL, enabling cost control and optimization.

Key advantages of the PostgreSQL on EC2 deployment included:

  • Cost Savings : By deploying PostgreSQL on EC2, significant reductions in IOPS, storage, and compute costs were realized compared to managed services. The ability to right-size EC2 instances to match workload demands offered greater flexibility in resource allocation and pricing, lowering overall cloud expenses.
  • Configuration Flexibility : PostgreSQL on EC2 allowed for more customizable configurations, such as optimized database settings, indexing strategies, and extensions tailored to the client’s unique data processing needs. This customization enhanced the performance of their data warehouse workloads.
  • High Availability : A High Availability (HA) setup was implemented using industry-standard tools, ensuring automatic failover and load balancing. This configuration minimized downtime and ensured consistent data access and reliability, crucial for maintaining the client’s operational efficiency.

Impact:

The implementation of PostgreSQL on EC2 led to substantial cost savings, reduced IOPS expenses, and provided greater control over resource allocation, delivering long-term financial benefits for the client’s data warehouse platform. The transition to EC2 resulted in a 60-70% reduction in monthly cloud expenses, with IOPS costs eliminated entirely. Storage costs were significantly lower compared to the pricing structure of managed services like Aurora. PostgreSQL on EC2 allowed for more efficient data movement within the AWS ecosystem, further reducing data transfer expenses. Since PostgreSQL is an open-source solution, the client avoided the additional fees associated with using managed services, contributing to a significant reduction in operational expenditures.

Following the success of this implementation, the client expanded their open-source strategy, migrating most of their database engines, including NoSQL databases, to open-source alternatives.

Written by

Biswajit Mukhopadhyay
Head - Data and AI
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