AWS Big Data Blog

Microservice observability with Amazon OpenSearch Service part 2: Create an operational panel and incident report

In the first post in our series , we discussed setting up a microservice observability architecture and application troubleshooting steps using log and trace correlation with Amazon OpenSearch Service. In this post, we discuss using PPL to create visualizations in operational panels, and creating a simple incident report using notebooks. To try out the solution […]

Build the next generation, cross-account, event-driven data pipeline orchestration product

This is a guest post by Mehdi Bendriss, Mohamad Shaker, and Arvid Reiche from Scout24. At Scout24 SE, we love data pipelines, with over 700 pipelines running daily in production, spread across over 100 AWS accounts. As we democratize data and our data platform tooling, each team can create, maintain, and run their own data pipelines […]

Your guide to AWS Analytics at re:Invent 2022

Join the global cloud community at AWS re:Invent this year to meet, get inspired, and rethink what’s possible! Reserved seating is available for registered attendees to secure seats in the sessions of their choice. You can reserve a seat in your favorite sessions by signing in to the attendee portal and navigating to Event > Sessions. For those who can’t […]

Microservice observability with Amazon OpenSearch Service part 1: Trace and log correlation

Modern enterprises are increasingly adopting microservice architectures and moving away from monolithic structures. Although microservices provide agility in development and scalability, and encourage use of polyglot systems, they also add complexity. Troubleshooting distributed services is hard because the application behavioral data is distributed across multiple machines. Therefore, in order to have deep insights to troubleshoot […]

Retain more for less with tiered storage for Amazon MSK

Organizations are adopting Apache Kafka and Amazon Managed Streaming for Apache Kafka (Amazon MSK) to capture and analyze data in real-time. Amazon MSK allows you to build and run production applications on Apache Kafka without needing Kafka infrastructure management expertise or having to deal with the complex overheads associated with running Apache Kafka on your […]

Measure the adoption of your Amazon QuickSight dashboards and view your BI portfolio in a single pane of glass

Amazon QuickSight is a fully managed, cloud-native business intelligence (BI) service. If you plan to deploy enterprise-grade QuickSight dashboards, measuring user adoption and usage patterns is an important ingredient for the success of your BI investment. For example, knowing the usage patterns like geo location, department, and job role can help you fine-tune your dashboards […]

Simplify data analysis and collaboration with SQL Notebooks in Amazon Redshift Query Editor V2.0

Amazon Redshift Query Editor V2.0 is a web-based analyst workbench that you can use to author and run queries on your Amazon Redshift data warehouse. You can visualize query results with charts, and explore, share, and collaborate on data with your teams in SQL through a common interface. With SQL Notebooks, Amazon Redshift Query Editor […]

How The Mill Adventure enabled data-driven decision-making in iGaming using Amazon QuickSight

This post is co-written with Darren Demicoli from The Mill Adventure. The Mill Adventure is an iGaming industry enabler offering customizable turnkey solutions to B2B partners and custom branding enablement for its B2C partners. They provide a complete gaming platform, including licenses and operations, for rapid deployment and success in iGaming, and are committed to […]

Deploy DataHub using AWS managed services and ingest metadata from AWS Glue and Amazon Redshift – Part 2

In the first post of this series, we discussed the need of a metadata management solution for organizations. We used DataHub as an open-source metadata platform for metadata management and deployed it using AWS managed services with the AWS Cloud Development Kit (AWS CDK). In this post, we focus on how to populate technical metadata […]

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 […]