Tag: performance

Feed: Recent Announcements. Previously, gathering performance data on a database required configuration and maintenance of monitoring applications and related resources. Correlating performance data took hours without specialized expertise. To find a query of interest, such as a stuck or long-running SQL query, meant investigating each query one at a time. RDS Performance Insights allows non-experts and experts to identify top SQL loads and from where they originated on a visual dashboard in seconds. Now, RDS Performance Insights supports segmenting the performance data by database name. You can determine if a specific database is generating unusual high load, or is executing ... Read More

Feed: Recent Announcements. Previously, gathering performance data on a database required configuration and maintenance of monitoring applications and related resources. Correlating performance data took hours without specialized expertise. To find a query of interest, such as a stuck or long-running SQL query, meant investigating each query one at a time.   RDS Performance Insights allows non-experts and experts to identify top SQL loads and from where they originated on a visual dashboard in seconds. Now, RDS Performance Insights supports segmenting the performance data by additional dimensions, such as database name, application, and session type. You can determine if a specific ... Read More

Feed: Recent Announcements. Amazon SNS and SQS are foundational services used for synchronous service-to-service communication in serverless and microservices architectures. With pub/sub messaging you can design and build with event-driven architectures or decouple applications to increase performance, reliability and scalability. With the new release of the Toolkit, users can poll, publish messages, purge queues and configure triggers for Lambda functions, all from within the IDE. Check out the AWS Toolkit Docs to learn about the various SQS/SNS features in the IDE. CloudWatch Logs Insights enables you to interactively search and analyze your log data in Amazon CloudWatch Logs. You can ... Read More

Feed: AWS Compute Blog. Author: Benjamin Smith. Today, AWS is introducing Synchronous Express Workflows for AWS Step Functions. This is a new way to run Express Workflows to orchestrate AWS services at high-throughput. Developers have been using asynchronous Express Workflows since December 2019 for workloads that require higher event rates and shorter durations. Customers were looking for ways to receive an immediate response from their Express Workflows without having to write additional code or introduce additional services. What’s new? Synchronous Express Workflows allow developers to quickly receive the workflow response without needing to poll additional services or build a custom ... Read More

Feed: AWS Big Data Blog. In May 2020, we announced the general availability of real-time anomaly detection for Elasticsearch. With that release we leveraged the Random Cut Forest (RCF) algorithm to identify anomalous behaviors in the multi-dimensional data streams generated by Elasticsearch queries. We focused on aggregation first, to enable our users to quickly and accurately detect anomalies in their data streams. However, consider the example data in the following table. timestamp avg. latency region 12:00 pm 3.1 Seattle 12:00 pm 4.1 New York 12:00 pm 5.9 Berlin 12:01 pm 2.6 Seattle 12:01 pm 5.3 New York 12:01 pm 5.8 ... Read More

Feed: SAS Blogs. Author: Frank Silva. In football, five out of the 11 players on offense are on the field to accomplish one goal: keep the defenders as far away from the ball as possible.  Sometimes it’s more than five. Teams will bring extra linemen on short-play packages. Tight ends and full backs might check in for extra blocking. Running backs will help in pass protection. And even quarterbacks might throw a hit on a defender every now and then. Blocking is an essential part of the game, so I wanted to explore if investing more in the offensive line ... Read More

Feed: Recent Announcements. Supporting high cardinality data streams is challenging due to its computational and scale demands to handle the complexity of the data. This problem is further exacerbated when operators need to pinpoint anomalous entities from massive datasets in near real-time. Amazon Elasticsearch Service uses a distributed architecture to address the challenges with performance and scalability by disseminating the load across the instances in your domain. Anomaly detection for high cardinality datasets is powered by the Random Cut Forest (RCF) algorithm, a light weight unsupervised machine learning algorithm, proven in production to handle multi-dimensional data streams at scale. The ... Read More

Feed: Planet MySQL; Author: EverSQL; So you thought your database is in good shape, but suddenly your CPU usage spiked and reached 100% at 2AM. How would you go about tracking the root cause and fix it? 1. Locate the root cause If you are using CloudWatch or any infrastructure monitoring solution, you can start your investigation there.To understand what happened in your database, you should enable the slow query log feature on your database. This will capture all the slow log queries into a log, based on a threshold that you define.If you are not sure how to enable ... Read More

Feed: Recent Announcements. Amazon FSx for Lustre, a service that provides high-performance shared storage, now enables you to increase the storage capacity of your file systems with the click of a button, providing you the flexibility to easily respond to your evolving storage needs by increasing file system size in a matter of minutes.  ... Read More

Feed: AWS Big Data Blog. AWS Glue provides a serverless environment to prepare (extract and transform) and load large amounts of datasets from a variety of sources for analytics and data processing with Apache Spark ETL jobs. This posts discusses a new AWS Glue Spark runtime optimization that helps developers of Apache Spark applications and ETL jobs, big data architects, data engineers, and business analysts scale their data processing and batch jobs running on AWS Glue automatically. Customers use Spark for a wide variety of ETL and analytics workloads on datasets with diverse characteristics. They want to ensure fast and ... Read More