Summer of 2022, I completed an internship with AWS in Herndon, VA. I was assigned to a Data Lake Accelerator project for one of the government agencies which was very exciting and a great experience.
During my internship, I learned AWS processes, different recoding practices, cloud architecture, and how to code better. In addition, I experienced the corporate culture and engaged with the knowledgeable developers that work for AWS.
My role responsibilities consisted of deploying data lake infrastructure, automatically build, test, and deploy new or changed versions of the application from the version control system. I utilized AWS CodeCommit and CodePipeline to set up a CI/CD to help automate multiple steps to automate builds, push code to a repository and then deploy to your updated code to AWS. This helps minimize potential mistakes as opposed to running multiple manual steps Automate deployment to different stages (dev, staging, and production).
I learned AWS CDK and used it to deploy pipelines. The AWS Cloud Development Kit (AWS CDK) is an open-source software development framework to define cloud infrastructure in familiar programming languages and provision it through AWS CloudFormation. The AWS CDK consists of three major components: The core framework for modeling reusable infrastructure components, A CLI for deploying CDK applications, the AWS Construct Library, a set of high-level components that abstract cloud resources and encapsulate proven defaults. The CDK makes it easy to deploy an application to the AWS Cloud from your workstation by simply running CDK deploy. This is good when you’re doing initial development and testing, but you should deploy production workloads through more reliable, automated pipelines.
At some point of the project, I was instructed to test Glue ETL process and querying data information using Athena. AWS Glue is a serverless data integration service that makes it easy for analytics users to discover, prepare, move, and integrate data from multiple sources. You can use it for analytics, machine learning, and application development. It also includes additional productivity and data ops tooling for authoring, running jobs, and implementing business workflows.
Athena helps to analyze unstructured, semi-structured, and structured data stored in Amazon S3. Athena integrates with the AWS Glue Data Catalog, which offers a persistent metadata store for your data in Amazon S3. This allows you to create tables and
query data in Athena based on a central metadata store available throughout your Amazon Web Services account.
As part of my internship, I attended daily 1:1 and scheduled team meeting on Jira (project management skills software), gathered with my internship team to discuss other projects of interest. This gave me the opportunity to take in all of the feedback and put it into practice.
Coming into this internship with zero experience, I definitely feel this internship provided me with the tools I need to grow my career as a solution architect and developer.
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