Jupiter closes a 20% to 40% infrastructure spend visibility gap with DoiT
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- Vendor’s data ingested
- From 60% to 100%
- Coverage of data
Meet Apester
New York and Tel Aviv-based Apester helps publishers, advertisers, and businesses tell highly engaging online stories that are mobile friendly, seamlessly integrated with their sites, and can be distributed at scale. From quizzes and polls to innovative visual stories, Apester helps customers get their message across effectively. The company caters to storytellers of all kinds, from big brands like Meredith, BBC Worldwide, and Virgin to individual bloggers. Since its launch in 2014, Apester's comprehensive creation tools have attracted approximately 100 million unique users per month.
The Challenge
Apester's existing BI and data warehousing solution was showing strain under rapid growth. The closed system was becoming expensive and limited analytics capabilities. With user numbers growing and only limited developers, the company needed an easily scalable system that supported open source technology.
The Solution
Apester built a comprehensive Google Cloud solution using Kubernetes Engine as the backbone, Cloud Pub/Sub for messaging, BigQuery for analytics, and Stackdriver for monitoring. The migration moved from virtual machine-based architecture to containerized solutions, unifying infrastructure across teams.
Results
- Tripled customer base while delivering 3.5 billion story experiences in 2017
- Reduced infrastructure costs by 50% through Kubernetes migration
- Cut deployment time from 4 hours to under 1 minute
- Reduced latency by 50% using Google Cloud Network premium tier
- Handles millions of events per hour with BigQuery analytics platform
Infrastructure is not our core business. We want to focus on Apester's needs and improving our application. When the deployment time gets cut from hours to seconds, it means we can focus on our own success.
Or Elimelech, Site Reliability Engineer
What's Next
Apester continues evolving its products using Cloud Natural Language APIs to enhance personalization. Combined with BigQuery data, the company is exploring machine learning capabilities and investing heavily in ML using TensorFlow for its pipeline. This enables Apester to become more responsive to customer needs as its audience expands. The migration solved availability, scalability, and development efficiency challenges, helping keep the company ahead of competition.
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What they say
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Kyle Espinola, Head of Platform Engineering
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Josh Zarrabi, Infrastructure Engineer
“Without PerfectScale by DoiT, I don't know how we would do it. We'd have to have twice the number of people on my team to stay on top of it. With PerfectScale, we can focus on the more strategic issues.”
David Adkins, Director of Software and Platform Engineering
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