Category: Amazon Simple Storage Services (S3)

Infrastructure and operation teams are often challenged with getting a full view into their IT environments to do monitoring and troubleshooting. New monitoring technologies are needed to provide an integrated view of all components of an IT infrastructure and application system. Datadog provides intelligent application and service monitoring by bringing together data from servers, databases, […]

The ability to query data and perform ad hoc analysis across multiple platforms and data stores with a single tool brings immense value to the big data analytical arena. As organizations build out data lakes with increasing volumes of data, there is a growing need to combine that data with large amounts of data in […]

I was working with a customer who was just getting started using AWS, and they wanted to understand how to query their AWS service logs that were being delivered to Amazon Simple Storage Service (Amazon S3). I introduced them to Amazon Athena, a serverless, interactive query service that allows you to easily analyze data in […]

In part 1 of this series, we demonstrated building an end-to-end data lifecycle management system integrated with a data lake house implemented on Amazon Simple Storage Service (Amazon S3) with Amazon Redshift and Amazon Redshift Spectrum. In this post, we address the ongoing operation of the solution we built. Data ageing process after a month […]

The continuous growth of data volumes combined with requirements to implement long-term retention (typically due to specific industry regulations) puts pressure on the storage costs of data warehouse solutions, even for cloud native data warehouse services such as Amazon Redshift. The introduction of the new Amazon Redshift RA3 node types helped in decoupling compute from […]

This is a guest post co-authored by Pradip Thoke of Dream11. In their own words, “Dream11, the flagship brand of Dream Sports, is India’s biggest fantasy sports platform, with more than 100 million users. We have infused the latest technologies of analytics, machine learning, social networks, and media technologies to enhance our users’ experience. Dream11 […]

This post is co-written with Damian Grech from FanDuel FanDuel Group is an innovative sports-tech entertainment company that is changing the way consumers engage with their favorite sports, teams, and leagues. The premier gaming destination in the US, FanDuel Group consists of a portfolio of leading brands across gaming, sports betting, daily fantasy sports, advance-deposit […]

Consolidating data from a work management tool like Jira and integrating this data with other data sources like ServiceNow, GitHub, Jenkins, and Time Entry Systems enables end-to-end visibility of different aspects of the software development lifecycle and helps keep your projects on schedule and within budget. Amazon Simple Storage Service (Amazon S3) is an object […]

February 2021 update – Please refer to the post Writing to Apache Hudi tables using AWS Glue Custom Connector to learn about an easier mechanism to write to Hudi tables using AWS Glue Custom Connector. In this post, we include the modified Apache Hudi JARs as an external dependency. The AWS Glue Custom Connector feature […]

Data lakes are a popular choice for organizations to store data around their business activities. Best practice design of data lakes impose that data is immutable once stored, but new regulations such as the European General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), and others have created new obligations that operators now need […]