Information Technology | Database Consulting Services
Customer success story
FYI Docs boosts PostgreSQL performance and slashes cloud spend.
FYI Docs eliminates AWS Aurora bottlenecks to scale accounting operations worldwide
Pythian partitioned a 3TB+ database to eliminate query slowdowns and ensure seamless cloud access for over 250 million documents.
Faced with intermittent AWS Aurora slowdowns and surging cloud costs from exponential data growth, FYI Docs partnered with Pythian to resolve critical infrastructure strains that internal troubleshooting couldn't fix. Pythian conducted a comprehensive health check and deployed production-level optimizations, including large-table partitioning and autovacuum tuning. This stabilized the system, equipped the internal team with vital architectural knowledge, and established a scalable foundation for long-term product growth.
“Pythian was invaluable in resolving our database performance challenges. It came at the right time with the right experience for the project, allowing our team to focus on innovation and platform development. Between identifying the core and working with our team to implement recommendations, it isn’t just a service provider—it's a strategic advisor and synergistic partner. Collaborating with Pythian supports FYI Docs’ ability to scale our infrastructure over the next five years.”
Alan McLeod
Chief Technology Officer, FYI Docs
950
Accouns experience improved
250M+
Documents accessible
15,000
User experience optimized
Reclaim cloud infrastructure predictability with PostgreSQL performance tuning experts.
Rising data volumes compromised performance while escalating cloud spend.
Pythian diagnosed critical bottlenecks to transform a strained database into a high-performance data foundation to accelerate with agility and data volume growth.
Rapid growth compromised database efficiency
Rapid growth paired with the expansion of the PostgreSQL database on AWS Aurora precipitated significant challenges that threatened to impact customer experience through query slowdowns.
Increased and unpredictable cloud costs
FYI Docs saw its AWS Aurora PostgreSQL cloud costs rise disproportionately, despite forecasting growth, leaving internal teams with no clear explanation for the spending surge.
Data accumulation triggered performance crashes
At over three terabytes, the database caused slow response times, crashes, and errors for internal teams, threatening customer experience and hindering sales, support, and training.
Reactive patching failed to prevent disruption
Existing temporary fixes were insufficient, meaning a lasting database performance solution was needed to prevent future disruptions.
AWS assessment uncovers infrastructure bottlenecks
Pythian conducted a thorough analysis of the AWS environment to expose underlying operational strains. The targeted health check identified performance gaps across security configurations, platform monitoring systems, and overall infrastructure stability. These findings provided a clear optimization roadmap tailored to the unique configuration of the environment. By pinpointing heavy indexing and unoptimized autovacuum processes, the assessment laid the foundation for immediate database remediation.
Sandbox testing validates code before live deployment
Pythian engineers implemented critical performance tuning directly across production database instances in both Sydney and London. The optimization strategy applied hash partitioning to large, overextended data tables to maximize query processing efficiency. Concurrently, the team fine-tuned autovacuum processes to keep database maintenance running smoothly without draining system resources. These targeted updates eliminated query hangups and restored reliable system responsiveness across millions of documents.
Global database tuning eliminates query hangups
Pythian engineers implemented critical performance tuning directly across production database instances in both Sydney and London. The optimization strategy applied hash partitioning to large, overextended data tables to maximize query processing efficiency. Concurrently, the team fine-tuned autovacuum processes to keep database maintenance running smoothly without draining system resources. These targeted updates eliminated query hangups and restored reliable system responsiveness across millions of documents.
Targeted AWS right-sizing stabilizes cloud expenses
Technical consultants analyzed active operational patterns to align provisioned cloud resources directly with actual database demand. Scaling down over-provisioned AWS instance sizes eliminated unnecessary overhead and brought immediate structural efficiency to cloud operations. This initiative lowered recurring infrastructure fees and stabilized overall operational expenses. The resulting predictability equipped internal leadership with the insight needed to project future cloud infrastructure budgets accurately.
.svg){kind=small}
.svg){kind=small}