Ecotrak Use Case
A SaaS Company
Requirements: Optimizing Archival and Retrieval of Files
Solutions: Multi-Class AWS Storage
Introduction
Ecotrak is a SaaS company, providing its customers with solutions hosted on Amazon Web Services (AWS), utilizing Amazon Simple Storage Service (Amazon S3) to house their data. They have multiple Amazon S3 buckets containing terabytes of data. Prior to engaging with Cloudify, Ecotrak, storage all the objects/files in Amazon S3 Standard storage class. Cloudify analyzed the access patterns of objects, as how frequently they are being accessed within different time periods e.g. 30, 90 and 180 days. On the basis of the results Cloudify recommended to move objects, as per their access frequency, to other classes of storage. Objects being frequently accessed and within 30 days’ time period in Amazon S3 Standard storage class, for files that are more than 90, 180 days of access, Ecotrak via automation will put infrequently accessed files for archival utilizing Amazon S3 Glacier and S3 Glacier Deep Archive.. The analysis of buckets and transitions were done using python scripts and AWS’s best practices for Amazon S3 lifecycle management.
Solutions, Deliverable, Recommended AWS Best Practices, and Costs savings
Cloudify executed scripts and efficiently analyzed EcoTrak’s Amazon S3 buckets by automatically gathering their names, calculating total storage size and object count and assessing access frequency over various time periods. Cloudify identified objects with low access rates within the last 30, 90, 180, and more than 180 days, highlighting potential candidates for archival or use of Amazon Cloudify analyzed around 28 million objects. Cloudify script generated structured output (CSV/JSON) for subsequent analysis and integration into reporting or lifecycle management policies, optimizing storage management and costs.. Security and performance are always examined and are optimized by using AWS best practices in IAM set up and security.
Expert configuration and setup, Ongoing maintenance and troubleshooting:
Cloudify offers ongoing maintenance and troubleshooting services to ensure optimal performance and address any issues that may arise during ongoing usage of AWS solutions. Cloudify adheres to Zero trust and IAM methodology for each individual use case to follow AWS best practices in this regards. Resource optimization: Cloudify regularly review Amazon S3 storage usage patterns to identify underutilized resources or inefficient configurations. By optimizing resource allocation and implementing best practices, Ecotrak saved money without compromising performance. Lifecycle management: Cloudify leverage Amazon S3 Intelligent Tiering to automatically transition data to less expensive storage classes (e.g. Amazon S3 Infrequent Access and Amazon S3 Glacier Deep Archive) when it is no longer actively used. This helps minimize storage costs while ensuring data availability.
Pricing
Cloudify employs a comprehensive capacity planning approach and AWS costs analysis to ensure that Amazon S3 storage capacity aligns closely with Clients’ requirements, avoiding both underutilization and excessive costs. This involves a combination of demand-based, buffer-based, and time-based strategies, tailored to the specific needs of our customer. Cloudify meticulously analyzed historical data usage patterns to identify trends, peak usage periods, and average consumption rates. This data-driven approach provides valuable insights for capacity planning. Capacity planning recommendations were made. Cloudify provide solutions for storage and databases deployment to our client with the optimize and best choices in terms of resources to get best performance in minimum cost.
Metrics
Cloudify establishes regular cadence, as we do for all our clients, to review internal performance and identify opportunities for cost optimization within Ecotrak Amazon S3 storage. This includes conducting periodic reviews of billing data, analyzing resource utilization, and identifying potential inefficiencies via our extensive use of AI based tools. Cloudify used lifecycle management, best practices, access patterns, and further automation of the storage management to achieve costs savings, performance improvement, and the transitioned the objects into the optimized storage classes. After Cloudify analyzed all objects and utilized AWS calculator, Cloudify presented a 22% savings to the client.
Summary
Cloudify can optimize your Amazon Web Services storage consumption according to AWS best practices methodologies and optimize your costs. Please contact us at info@cloudifyinc.com for a free consultation.