Startups Using Jenkins in Boston

Via their job posts and information submitted by startups themselves, these are the Boston Jenkins startups we've found.

Interested in other technologies? Browse or search all of the built-in-boston tech stacks we've curated.

“Predictive analytics platform for retail merchandise planning and product assortment optimization.”

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“Find, compare, and review doctors.” Reviews are individually human-moderated.

Tech Stack Highlights

Ruby On Rails – We use RoR for our core site implementation, enabling users to search for medical Providers and easily leave ratings & reviews. Our web pages are built using Bootstrap, HAML, SASS and Javascript technologies. We’ve built a data model system in Python that replaces ActiveRest. That model system is shared as a reusable Library by many of our other applications.

Postgres & Redis – All this is backed up by RDS instances in AWS running PostgresDB. We heavily use Redis and SOLR for data caching and queue management.

Flask/Python – The rest of our apps and services – Email systems, data analysis, internal tools – all run in Python based Flask/Flask-Restless environments.

ELK – Our logging system is run as an Elasticsearch-Logstash-Kibana stack utilizing Filebeat and Logspout for streaming the log output. From this stack we’ve also created a comprehensive Technical SEO Dashboard where we can monitor crawlers and their activity and measure the cause & effect on new site features.

DevOps – Our apps are deployed using Docker Swarm orchestration via Ansible scripts for independence from specific cloud providers. We’ve built a structure with Docker in a Blue/Green deployment methodology so there is zero downtime when releasing code updates. The system is front ended with Jenkins-CI for automated execution of Unit/Integration/Acceptance test suites.

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Developing self-driving technologies for fully-autonomous electric vehicle fleets.

Technologies: , , , , , ,
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Platform aggregating and analyzing footwear and apparel fit data, providing retailers with tools to offer “highly personalized fit ratings and size recommendations to shoppers.”

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Enterprise cloud storage as a fully managed service.

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KAYAK for car insurance. Quick, personalized car insurance quotes from multiple providers.

Tech Stack Highlights

Python – We’re using python for our core app, with Django/DRF powering our REST API, NLTK for NLP, and pandas running high-performance real time data analysis to calculate things like RateRank and savings estimates. We use Vagrant and Ansible for IT automation, and Jenkins and Selenium for QA automation and deployment to our AWS environment.

MariaDB – Our database runs Maria on RDS, for optimal MySQL-syntax performance. We crunch a lot of data in each query, so performance is key. Some of our queries approach 100 lines long, with multiple nested queries, dozens of joins, and layered aggregation, and we run some queries thousands of times per day.

Backbone – Backbone provided us “just enough” structure for our highly custom front-end MVC, while allowing us to build our own proprietary routing & workflow engine around it. We’re using epoxy for 2-way data-binding, and jQuery + Bootstrap plugins, in addition to dozens of proprietary UI components.

Bootstrap – Our mobile-first-responsive CSS uses Bootstrap as a baseline, but builds upon it to form a highly-customized, well-organized extensible style-guide with our own unique components and layouts. We’re using SASS class-extension, selector-nesting, and custom mixins under the hood to generate our CSS.

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Interactive content creation platform for marketers, integrated with lead capture & marketing automation tools.

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Cybersecurity platform to detect threats coming from compromised user accounts.

Tech Stack Highlights

Apache Spark – We use Spark, Spark Streaming, and the Apache Kafka frameworks for fast in-memory compute, real-time streaming, and lambda architecture. These technologies power our cyber threat detection, remediation and visualization software.

Cassandra – Our platform relies on Apache Cassandra NoSQL database for long-term data analytics and reporting. We use Elasticsearch for real-time search and analysis and Redis for in-memory cache.

Docker – We’re built on a Docker container micro-services architecture and Ansible DevOps orchestration framework for flexible bare-metal, virtual machine & cloud deployments.

Angular.js – We use the Angular front-end framework with D3.js, and NodeJS on the backend.

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3D printing of metal parts.

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“A machine learning platform for data scientists of all skill levels to build and deploy accurate predictive models.”

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