Our client is a North American company that strives to revolutionize the way we think about food and health by leveraging deep research. To realize this bold vision, the customer applies cutting-edge data science & machine learning techniques powered by modern tools and cloud-native services to analyze the millions of molecules that exist across human food ration.
The client came with a request to automate and unify the deployment process of serverless applications on AWS Lambda. Having manual deployments before, the customer was facing inconveniences and difficulties, including non-uniform environment setup (versions of Serverless, Python, Node, and so on were inconsistent) and inability to control the environment changes in one place.
For deployment of serverless applications on AWS Lambda, the team created the automation GitLab pipeline.
All secrets are encrypted and securely stored in GitLab. The pipeline allows the customer to deploy applications to multiple environments – development or production. The serverless configs are stored in the project code and used for GitLab pipelines. There is also configured automatic deployment allowing to apply changes made to the master branch.
The developed solution helped the client resolve dependency conflicts, use GitLab pipelines as a single point of control for deployment processes, and, thus, monitor the detailed history of changes.
The client experienced the need to automate the deployment process of microservices and simplify the release process. One of the requirements was to migrate Docker containers to AWS ECS and move existing infrastructure to Terraform.
The client had a manual multi-environment infrastructure deployment аnd no continuous integration & continuous deployment automation. That significantly impacted the speed of product development, release, and delivery cadence of new application versions in general. Besides, it required a considerable part of the development team capacity to process it manually.
The client faced the need to automate multi-environment continuous integration and deployment process of microservices, move the front-end part to CDN as well as deploy multi-environment infrastructure as a code.
The client had high costs for development, deployment, and, most importantly, operation of the data platform including Data Lake, Ingestion, and ML Pipelines. The pipelines were mostly running in EC2 instances, which led to the increased cost of operations and required a significant amount of time to deploy and test the pipelines in lower environments.
The client needed to strengthen collaboration within the data scientists team by moving research capabilities into cloud workloads. Besides, they wanted to automate and unify the deployment process of AWS resources. That, in turn, would decrease the time and effort required for a team of data scientists to build and test their models.
CI/CD (Continuous Integration/Continuous Deployment) offers a seamless bridge from development to deployment. Further, in the evolving world of mobile app development, efficiency and adaptability are key.
At Matoffo, we specialize in customizing CI/CD solutions that cater to cross-platform mobile application development. We focus on improving the technical workflow and enhancing our client’s overall business performance and user experience.
Our primary goal is value delivery for the client by resolving technical challenges and assisting them to achieve their objectives. AWS cloud solutions are great toolset which we use to make it happens, primary by outstanding agility, where companies could scale up cloud resources as needed and significantly decrease time from idea to market as well as seamless adopt rapidly growing tech capabilities to transform their businesses to be competitive in the market.
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