Unshakable Cloud Foundations: Elevate Your AWS with Integration Testing

The final installment of our blog series on AWS testing methodologies focuses on integration testing. This crucial phase ensures that all components of your application work together seamlessly in a live environment, simulating real-world usage with production code and test data. Below is an outline designed to guide the creation of a comprehensive and informative […]

Turbocharge your functional tests with LocalStack for AWS

A deep dive into functional testing for AWS development Introduction In our exploration of advanced testing techniques for AWS development, we’ve delved into powerful tools like moto for unit testing and pytest.mark.parametrize for enhancing test coverage and efficiency. Building on this foundation, we turn our focus to a pivotal tool that bridges the gap between […]

Advanced Unit Testing in AWS

Leveraging Moto and Pytest Introduction In the world of AWS development, ensuring the reliability, efficiency, and correctness of your cloud-based applications is paramount. As cloud solutions grow increasingly complex, so too does the challenge of effectively testing these systems. Traditional testing methods often fall short in the face of AWS’s vast and intricately interconnected services. […]

Mounting EFS Volume to Batch Jobs in AWS

Introduction In the realm of distributed computing and batch processing, operational challenges frequently arise that necessitate innovative solutions. A particular challenge we encountered involved a scenario where multiple jobs within our AWS environment were generating tens of thousands of files and storing them in an Amazon S3 bucket. Subsequently, a specific job was tasked with […]

Revolutionizing Data Management in AWS: The Case for Apache Iceberg Over Traditional Table Formats

Introduction In the digital era, where data is king, the choice of table format for data storage and processing is crucial. Common file formats like CSV, Avro, and Parquet have long been the go-to solutions in various data handling scenarios. However, with the evolving needs of big data and cloud computing, newer and more efficient […]

Boost AI Fairness and Explainability with Amazon SageMaker Clarify

From hiring decisions to loan approvals and even healthcare recommendations, machine learning (ML) impacts our lives daily. Fairness and explainability are crucial in this context. Fairness means data is balanced, and model predictions are fair across groups. Checking for fairness ensures that negative outcomes are fair across all groups, such as age or gender. Explainability […]

Creating Custom Hadoop Events in EventBridge on AWS

Introduction: Event driven architecture as defined by Amazon is a system whose architecture uses events to trigger and communicate between decoupled services and is common in modern applications built with microservices. An event is a change in state or an update. Event-driven architectures have three key components: event producers, event routers, and event consumers. A […]