Cloud Infrastructure & Migrations

Secure and Seamless Infrastructure as Code

Regardless of where you are in your cloud journey, Waterloo Data can help you with the following:

Infrastructure as code

Cloud independent and avoiding vendor lock-in

CI/CD pipelines

Keeping your systems up to date at all times

Security and authentication

Fast and secure giving you a peace of mind

Storage

File system configuration, on-demand compute clusters, on-premise application migration to cloud

Our first deployments to the cloud were on Rackspace and Amazon Web Services back in 2009

As former dot com and web 2.0 engineers we instantly recognized the value behind virtualized compute and storage solutions offered as a managed service. Rackspace was early to the party but AWS soon overwhelmed them, and over the past 13 years we have seen an incredible amount of innovation as we have watched AWS, Microsoft, and Google become the dominant platforms. Our commercial software and SaaS clients were the first to go all-in on cloud adoption. Our corporate clients in Healthcare, Financial Services, and Commercial Real Estate have been a little late to the game but can no longer ignore the economics of cloud adoption and have moved aggressively in the past few years to catch up.

Image of servers stacked together
Hybrid Clouds, Tailored Solutions

We have helped many organizations migrate to hybrid cloud environments leveraging services from Amazon, Google, and Microsoft.  Recently, we helped a high frequency trading firm overcome the limitations of their on-prem infrastructure by creating a high performance, hybrid-cloud solution leveraging AWS. This platform was used by data scientists to analyze trade execution pathways across various exchanges.

Given the sensitive nature of our client’s business, we implemented a “zero trust” environment with a Layer 7 firewall that interrogated every packet flowing between their on-prem and AWS environments. This proved to be very challenging when it came to certificate validation and managing external resources available via the internet. We also had to develop a custom library in python that managed SSO between Snowflake, their on-prem Active Directory, and AWS. Using Elastic Map Reduce we created a high performance, on-demand ETL layer that was responsible for terabytes of daily processing.  Access for data scientists was provided via Jupyter notebooks. All of our cloud infrastructure was automated via Terraform.

Chat with an Expert

Contact Us Today

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.