Category: Advanced (300)
Amazon OpenSearch Serverless is an on-demand, auto-scaling configuration for Amazon OpenSearch Service. OpenSearch Serverless enables a broad set of use cases, such as real-time application monitoring, log analytics, and website search. OpenSearch Serverless lets you use OpenSearch without having to worry about scaling and managing an OpenSearch cluster. A collection can be accessed over the […]
Use the new SQL commands MERGE and QUALIFY to implement and validate change data capture in Amazon Redshift
Amazon Redshift has added many features to enhance analytical processing like ROLLUP, CUBE and GROUPING SETS, which were demonstrated in the post Simplify Online Analytical Processing (OLAP) queries in Amazon Redshift using new SQL constructs such as ROLLUP, CUBE, and GROUPING SETS. Amazon Redshift has recently added many SQL commands and expressions. In this post, we talk about two new SQL features, the MERGE command and QUALIFY clause, which simplify data ingestion and data filtering.
Managing configurations for Amazon MSK Connect, a feature of Amazon Managed Streaming for Apache Kafka (Amazon MSK), can become challenging, especially as the number of topics and configurations grows. In this post, we address this complexity by using Terraform to optimize the configuration of the Kafka topic to Amazon S3 Sink connector. By adopting this […]
This is a guest post by Khandu Shinde, Staff Software Engineer and Edward Paget, Senior Software Engineering at Chime Financial. Chime is a financial technology company founded on the premise that basic banking services should be helpful, easy, and free. Chime partners with national banks to design member first financial products. This creates a more […]
Optimize checkpointing in your Amazon Managed Service for Apache Flink applications with buffer debloating and unaligned checkpoints – Part 2
This post is a continuation of a two-part series. In the first part, we delved into Apache Flink‘s internal mechanisms for checkpointing, in-flight data buffering, and handling backpressure. We covered these concepts in order to understand how buffer debloating and unaligned checkpoints allow us to enhance performance for specific conditions in Apache Flink applications. In […]
Optimize checkpointing in your Amazon Managed Service for Apache Flink applications with buffer debloating and unaligned checkpoints – Part 1
This post is the first of a two-part series regarding checkpointing mechanisms and in-flight data buffering. In this first part, we explain some of the fundamental Apache Flink internals and cover the buffer debloating feature. In the second part, we focus on unaligned checkpoints. Apache Flink is an open-source distributed engine for stateful processing over […]
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.
In 2022, we told you about the new enhancements we made in Amazon EMR Managed Scaling, which helped improve cluster utilization as well as reduced cluster costs. In 2023, we are happy to report that the Amazon EMR team has been hard at work. We worked backward from customer requirements and launched multiple new features to enhance your Amazon EMR on EC2 clusters capacity management and scaling experience. Let’s dive deeper and discuss the new Amazon EMR on EC2 features in detail.
This blog post presents an architecture solution that allows customers to extract key insights from Amazon S3 access logs at scale. We will partition and format the server access logs with Amazon Web Services (AWS) Glue, a serverless data integration service, to generate a catalog for access logs and create dashboards for insights.
Amazon’s serverless Apache Kafka offering, Amazon Managed Streaming for Apache Kafka (Amazon MSK) Serverless, is attracting a lot of interest. It’s appreciated for its user-friendly approach, ability to scale automatically, and cost-saving benefits over other Kafka solutions. However, a hurdle encountered by many users is the requirement of MSK Serverless to use AWS Identity and Access Management (IAM) access control. At the time of writing, the Amazon MSK library for IAM is exclusive to Kafka libraries in Java, creating a challenge for users of other programming languages. In this post, we aim to address this issue and present how you can use Amazon API Gateway and AWS Lambda to navigate around this obstacle.