The US Real Estate industry has long relied on home listings provided through multiple listing services (MLS). Over the last 10+ years, a competitive digital MLS market has evolved, with providers introducing enhanced data services designed to improve buyer and broker experiences. Competition among MLS providers has led to the augmentation of home listing information, including property history, public school rankings, points of interest, neighborhood profiles, market statistics, and future home value projections. These data services, combined with digital experience, elevate consumer expectations and heighten competition within the Real Estate market.
Movoto, an online real estate agency, aimed to simplify real estate dealings for its users. However, with their growth, the accumulation of property-related data skyrocketed. This burgeoning data included detailed attributes like property history, neighborhood profiles, and crucial market statistics. The existing infrastructure became strained under the weight, leading to challenges in efficiently extracting prompt and relevant insights for the management team. More critically, home-buyers and brokers started experiencing a decline in their digital experience. Lag times in data retrieval were observed, which not only hampered real-time insights but also noticeably slowed down the website's response times, creating an unpredictable and often frustrating user journey.
Addressing Movoto's data challenges required a strategic DevOps approach with AWS:
The adoption of DevOps methodologies resulted in:
Reducing Deployment Time by 50% and Increasing System Availability by 20%
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Improving Deployment Frequency by 50% and Reducing Infrastructure Costs by 30%
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Reducing Build Time by 65% and Slashing Deployment Time by 80%
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Reducing Deployment Time by 40% and Cost Savings by 30%
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Improving Application Performance by 50% and Cost Savings by 30%
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Increasing Deployment Frequency by 200% and Reducing Infrastructure Costs by 30%
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Cutting Infrastructure Provisioning Time by 60% and Reducing Product Feature Release Time by 30%
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