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#5 - Realtor.com Case Study
Co-hosts Joshua Proto and Ryan Jones take a look at a case study about Realtor.com®.
Realtor.com® is a trusted resource for home buyers, sellers, and dreamers, offering a comprehensive database of for-sale properties as well as the information, tools, and professional expertise to help people move confidently through every step of their home journey. But when they needed to move from batch processing to real-time processing they turned to serverless. Was this switch worth it?
Show Notes:
SERVICES USED:
Kinesis data stream
Kinesis firehose
EC2
Lambda
AWS Professional Services
PROBLEMS FACED:
The company’s customers needed to change their ad campaigns in real-time and not have to wait for days or weeks. This required realtor.com to evolve from batch processing to real-time processing.
Realtor.com also felt limited in terms of its ability to effectively support user traffic, which varied depending on the time of day or year.
Growth, however, was becoming increasingly challenging for the company, not only in the number of people using the site but also in the number and complexity of new features we’re developing.
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By Joshua ProtoCo-hosts Joshua Proto and Ryan Jones take a look at a case study about Realtor.com®.
Realtor.com® is a trusted resource for home buyers, sellers, and dreamers, offering a comprehensive database of for-sale properties as well as the information, tools, and professional expertise to help people move confidently through every step of their home journey. But when they needed to move from batch processing to real-time processing they turned to serverless. Was this switch worth it?
Show Notes:
SERVICES USED:
Kinesis data stream
Kinesis firehose
EC2
Lambda
AWS Professional Services
PROBLEMS FACED:
The company’s customers needed to change their ad campaigns in real-time and not have to wait for days or weeks. This required realtor.com to evolve from batch processing to real-time processing.
Realtor.com also felt limited in terms of its ability to effectively support user traffic, which varied depending on the time of day or year.
Growth, however, was becoming increasingly challenging for the company, not only in the number of people using the site but also in the number and complexity of new features we’re developing.