AWS Big Data Blog

Category: Technical How-to

Deploy DataHub using AWS managed services and ingest metadata from AWS Glue and Amazon Redshift – Part 1

Many organizations are establishing enterprise data warehouses, data lakes, or a modern data architecture on AWS to build data-driven products. As the organization grows, the number of publishers and subscribers to data and the volume of data keeps increasing. Additionally, different varieties of datasets are introduced (structured, semistructured, and unstructured). This can lead to metadata […]

Common streaming data enrichment patterns in Amazon Kinesis Data Analytics for Apache Flink

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Stream data processing allows you to act on data in real time. Real-time data analytics can help you have on-time and optimized responses while improving overall customer […]

Build, Test and Deploy ETL solutions using AWS Glue and AWS CDK based CI/CD pipelines

AWS Glue is a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, machine learning (ML), and application development. It’s serverless, so there’s no infrastructure to set up or manage. This post provides a step-by-step guide to build a continuous integration and continuous delivery (CI/CD) pipeline using AWS […]

Diagram to illustrate soft multi-tenancy

Design considerations for Amazon EMR on EKS in a multi-tenant Amazon EKS environment

Many AWS customers use Amazon Elastic Kubernetes Service (Amazon EKS) in order to take advantage of Kubernetes without the burden of managing the Kubernetes control plane. With Kubernetes, you can centrally manage your workloads and offer administrators a multi-tenant environment where they can create, update, scale, and secure workloads using a single API. Kubernetes also […]

Choose the k-NN algorithm for your billion-scale use case with OpenSearch

April 2024: This post was reviewed for accuracy. February 2023: This post was reviewed and updated for accuracy of the code. When organizations set out to build machine learning (ML) applications such as natural language processing (NLP) systems, recommendation engines, or search-based systems, often times k-Nearest Neighbor (k-NN) search will be used at some point […]

Interactively develop your AWS Glue streaming ETL jobs using AWS Glue Studio notebooks

Enterprise customers are modernizing their data warehouses and data lakes to provide real-time insights, because having the right insights at the right time is crucial for good business outcomes. To enable near-real-time decision-making, data pipelines need to process real-time or near-real-time data. This data is sourced from IoT devices, change data capture (CDC) services like […]

Enable federation to Amazon QuickSight accounts with Ping One

Amazon QuickSight is a scalable, serverless, embeddable, machine learning (ML)-powered business intelligence (BI) service built for the cloud that supports identity federation in both Standard and Enterprise editions. Organizations are working towards centralizing their identity and access strategy across all of their applications, including on-premises, third-party, and applications on AWS. Many organizations use Ping One […]

Temperature visualization - colorful

Visualize Amazon S3 data using Amazon Athena and Amazon Managed Grafana

Grafana is a popular open-source analytics platform that you can employ to create, explore, and share your data through flexible dashboards. Its use cases include application and IoT device monitoring, and visualization of operational and business data, among others. You can create your dashboard with your own datasets or publicly available datasets related to your […]

Apache Hadoop Yarn Architecture Diagram

Configure Hadoop YARN CapacityScheduler on Amazon EMR on Amazon EC2 for multi-tenant heterogeneous workloads

Apache Hadoop YARN (Yet Another Resource Negotiator) is a cluster resource manager responsible for assigning computational resources (CPU, memory, I/O), and scheduling and monitoring jobs submitted to a Hadoop cluster. This generic framework allows for effective management of cluster resources for distributed data processing frameworks, such as Apache Spark, Apache MapReduce, and Apache Hive. When […]

Best practices to optimize cost and performance for AWS Glue streaming ETL jobs

AWS Glue streaming extract, transform, and load (ETL) jobs allow you to process and enrich vast amounts of incoming data from systems such as Amazon Kinesis Data Streams, Amazon Managed Streaming for Apache Kafka (Amazon MSK), or any other Apache Kafka cluster. It uses the Spark Structured Streaming framework to perform data processing in near-real […]