Case Study
nClouds AWS Case Study | Nylas
Nylas, founded in 2013, provides an API platform that enables developers to build innovative apps that integrate with 100% of email, calendar, and contacts providers in as little as four lines of code using ready-made SDKs in Node, Java, Python, and Ruby.
The solution allows developers to integrate complex, unstructured communications data into their applications in days, providing secure, pre-built integrations that are SOC 2 certified, GDPR compliant, Privacy Shield certified, and HIPAA- and FINRA-ready. Its communication APIs power communication features in the top SaaS applications globally across more than 22 countries. To learn more, go to https://www.nylas.com/.
Industry
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The Challenge
Featured Services
Faster infrastructure deployment
Enhanced cost optimization
Improved performance efficiency and scalability
CHALLENGE
Nylas wanted faster infrastructure deployment with improved cost optimization, performance efficiency, and scalability by migrating its Heroku workload to a microservices-based Docker environment on AWS.
“nClouds’ work to integrate CI/CD within our deployment pipeline is enabling our fast-growth company to accelerate the delivery of new features. Their expertise in containerization and migrating Heroku to AWS has enhanced our ability to scale to support increased demand as Nylas expands its global reach.”
THE SOLUTION
Nylas needed faster infrastructure deployment with improved cost optimization, performance efficiency, and scalability. To achieve these objectives, Nylas engaged with nClouds to migrate its Heroku workload to a microservices-based Docker environment on AWS.
nClouds applied its code library of best-practices configurations to provide faster infrastructure deployment and generate cost savings.
On AWS, scalable on-demand resources deliver efficiency without sacrificing performance. Separating a monolithic application into multiple containers and microservices enables faster application deployment because developers can work on different components of the application in parallel. Applications and tasks stored in containers can be rapidly scaled up and down.
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