AWS Big Data Blog

Category: AWS Lambda

Backup and Restore - Pre

Disaster recovery strategies for Amazon MWAA – Part 1

In the dynamic world of cloud computing, ensuring the resilience and availability of critical applications is paramount. Disaster recovery (DR) is the process by which an organization anticipates and addresses technology-related disasters. For organizations implementing critical workload orchestration using Amazon Managed Workflows for Apache Airflow (Amazon MWAA), it is crucial to have a DR plan […]

Enable metric-based and scheduled scaling for Amazon Managed Service for Apache Flink

Thousands of developers use Apache Flink to build streaming applications to transform and analyze data in real time. Apache Flink is an open source framework and engine for processing data streams. It’s highly available and scalable, delivering high throughput and low latency for the most demanding stream-processing applications. Monitoring and scaling your applications is critical […]

Introducing shared VPC support on Amazon MWAA

In this post, we demonstrate automating deployment of Amazon Managed Workflows for Apache Airflow (Amazon MWAA) using customer-managed endpoints in a VPC, providing compatibility with shared, or otherwise restricted, VPCs. Data scientists and engineers have made Apache Airflow a leading open source tool to create data pipelines due to its active open source community, familiar […]

Spark on AWS Lambda: An Apache Spark runtime for AWS Lambda

Spark on AWS Lambda (SoAL) is a framework that runs Apache Spark workloads on AWS Lambda. It’s designed for both batch and event-based workloads, handling data payload sizes from 10 KB to 400 MB. This post highlights the SoAL architecture, provides infrastructure as code (IaC), offers step-by-step instructions for setting up the SoAL framework in your AWS account, and outlines SoAL architectural patterns for enterprises.

Unstructured Data Management - AWS Native Architecture

Unstructured data management and governance using AWS AI/ML and analytics services

In this post, we discuss how AWS can help you successfully address the challenges of extracting insights from unstructured data. We discuss various design patterns and architectures for extracting and cataloging valuable insights from unstructured data using AWS. Additionally, we show how to use AWS AI/ML services for analyzing unstructured data.

Operational Data Processing Framework for Modern Data Architectures

Simplify operational data processing in data lakes using AWS Glue and Apache Hudi

AWS has invested in native service integration with Apache Hudi and published technical contents to enable you to use Apache Hudi with AWS Glue (for example, refer to Introducing native support for Apache Hudi, Delta Lake, and Apache Iceberg on AWS Glue for Apache Spark, Part 1: Getting Started). In AWS ProServe-led customer engagements, the use cases we work on usually come with technical complexity and scalability requirements. In this post, we discuss a common use case in relation to operational data processing and the solution we built using Apache Hudi and AWS Glue.

Monitor data pipelines in a serverless data lake

AWS serverless services, including but not limited to AWS Lambda, AWS Glue, AWS Fargate, Amazon EventBridge, Amazon Athena, Amazon Simple Notification Service (Amazon SNS), Amazon Simple Queue Service (Amazon SQS), and Amazon Simple Storage Service (Amazon S3), have become the building blocks for any serverless data lake, providing key mechanisms to ingest and transform data […]

Automate secure access to Amazon MWAA environments using existing OpenID Connect single-sign-on authentication and authorization

Customers use Amazon Managed Workflows for Apache Airflow (Amazon MWAA) to run Apache Airflow at scale in the cloud. They want to use their existing login solutions developed using OpenID Connect (OIDC) providers with Amazon MWAA; this allows them to provide a uniform authentication and single sign-on (SSO) experience using their adopted identity providers (IdP) […]

Extract time series from satellite weather data with AWS Lambda

Extracting time series on given geographical coordinates from satellite or Numerical Weather Prediction data can be challenging because of the volume of data and of its multidimensional nature (time, latitude, longitude, height, multiple parameters). This type of processing can be found in weather and climate research, but also in applications like photovoltaic and wind power. […]

Centralize near-real-time governance through alerts on Amazon Redshift data warehouses for sensitive queries

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud that delivers powerful and secure insights on all your data with the best price-performance. With Amazon Redshift, you can analyze your data to derive holistic insights about your business and your customers. In many organizations, one or multiple Amazon Redshift data warehouses […]