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Search at Intercom: Building our Elasticsearch cloud on AWS

Intercom, Inc.

Our product engineers are empowered to build great features, fast. For this reason, we chose to run exclusively on AWS and wherever possible, we make use of battle-tested AWS services, be it RDS Aurora for our relational databases, the Simple Queue Service (SQS) for our async workers or ElastiCache for our caching layer.

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Is your engineering team experiencing alert fatigue? Ask these 8 questions

Intercom, Inc.

Alert fatigue is a common problem among engineering teams that handle operations and maintain infrastructure. The result is lots of semi-meaningful alerts, noise, context-switching, and multitasking for the on-call engineer. Are the steps clear enough to be followed by any engineer on the team? Is the alert still relevant?

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Building a Data Engineering Stack That Boosts Scalability

Chart Mogul

In 2021, ChartMogul experienced a transformative shift in data strategy when we introduced a dedicated data engineering team. Updating the data engineering stack streamlined data processing; reducing the time and effort invested in manual data handling.

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How our infrastructure scales alongside our customers

Intercom, Inc.

This allows us to develop teams of deep domain experts to support and enable product engineers as they build the next generation of Intercom, and provide world class observability tooling, scaling, reliability, and secure-by-default build patterns. . Our tooling allows for high availability.

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Moving ChartMogul to AWS and Kubernetes

Chart Mogul

A few months ago, we retired our last pieces of infrastructure on DigitalOcean, marking our migration to AWS as complete. Our journey was not your regular AWS migration as it involved moving our infrastructure from classic VMs to containers orchestrated by Kubernetes. Ultimately, we decided to go with AWS. Team expertise.

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Cloud Data Lakes - The Future of Large Scale Data Analysis

Tom Tunguz

This modern architecture for data analysis, operational metrics, and machine learning enables companies to process data in new ways. Various roles in your organization, like data scientists, data engineers, application developers, and business analysts, can access data with their choice of analytic tools and frameworks.

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Serverless with AWS Lambda: Reducing metrics reporting lag from hours to seconds at ReSci

ReSci

Author: Avi Sanadhya, ReSci Platform Engineering Team At Retention Science we deliver personalized marketing campaigns powered by machine learning to drive a deeper level of customer engagement. Our AI engine, Cortex, is responsible for billions of predictions daily and hundreds of millions of personalized emails each month.

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