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  1. This post is the second part of our two-part series on the latest performance improvements of stateful pipelines. The first part of this... View the full article
  2. Introduction Apache Spark™ Structured Streaming is a popular open-source stream processing platform that provides scalability and fault tolerance, built on top of the S... View the full article
  3. The 2023 Accelerate State of DevOps Report has arrived. This long-running research effort has shown how software delivery performance positively impacts organizational performance. Using the insights into concrete practices that drive performance, you can impact your commercial and non-commercial goals. The full report is available from the DORA website, but in this article, you'll find an overview of some key changes the survey used to collect data this year. You'll also discover why we can welcome back the elite performance cluster and why this group can inspire improvements across many industries. View the full article
  4. AWS Network Load Balancer (NLB) now supports Availability Zone DNS affinity, disable connection termination for unhealthy targets, and UDP connection termination by default. View the full article
  5. Jaeger has gained significant popularity in the software development community due to its powerful capabilities and ease of integration with various programming languages and frameworks. With the rise of microservices and cloud-native applications, Jaeger has become a crucial tool for developers and system administrators to gain insights into the performance and behavior of their applications. How do you make Jaeger even more effective for monitoring and troubleshooting distributed applications, especially in high-traffic, demanding environments where a high-performance storage solution is critical? Use the best-performing Jaeger storage backend that you can find. View the full article
  6. Here is a list of checklist to improve MySQL query performance... View the full article
  7. Cloud-native application development in AWS often requires complex, layered architecture with synchronous and asynchronous interactions between multiple components, e.g., API Gateway, Microservices, Serverless Functions, and system of record integration. Performance engineering requires analysis of the performance and resiliency of each component level and the interactions between these. While there is guidance available at the technical implementation of components, e.g., for AWS API Gateway, Lambda functions, etc., it still mandates understanding and applying end-to-end best practices for achieving the required performance requirements at the overall component architecture level. This article attempts to provide some fine-grained mechanisms to improve the performance of a complex cloud-native architecture flow curated from the on-ground experience and lessons learned from real projects deployed on production. The mission-critical applications often have stringent nonfunctional requirements for concurrency in the form of transactions per second (henceforth called “tps”). A proven mechanism to validate the concurrency requirement is to conduct performance testing. View the full article
  8. WebSocket is a common communication protocol used in web applications to facilitate real-time bi-directional data exchange between client and server. However, when the server has to maintain a direct connection with the client, it can limit the server’s ability to scale down when there are long-running clients. This scale down can occur when nodes are underutilized during periods of low usage. In this post, we demonstrate how to redesign a web application to achieve auto scaling even for long-running clients, with minimal changes to the original application... View the full article
  9. This article provides an overview of the strategies for optimizing AI system performance in edge AI deployments.View the full article
  10. Amazon OpenSearch Service now provides new Auto-Tune metrics and improved Auto-Tune events that give you better visibility into the cluster performance optimizations made by Auto-Tune. View the full article
  11. As we close out 2022, we at DevOps.com wanted to highlight the most popular articles of the year. Following is the latest in our series of the Best of 2022. A technology company’s most valuable assets are its people and data, especially data about the organization itself. By knowing what data to track over time, […] The post Best of 2022: How DORA Metrics Can Measure and Improve Performance appeared first on DevOps.com. View the full article
  12. As your application needs change, Amazon EBS Elastic Volumes allows you to easily increase capacity, tune performance, and change the type of Amazon EBS volumes. Customers are using EBS Elastic Volumes to migrate to gp3 volumes and save up to 20% per GB compared to gp2 volumes. View the full article
  13. The Amazon Redshift ODBC driver is now open source and available for the user community under the Apache-2.0 license. With this release, customers will gain enhanced visibility to the driver implementation and can contribute to its development. Users can browse the code for the ODBC driver on the relevant AWS GitHub repository, submit driver functionality enhancements through Github pull requests, and report issues for review. View the full article
  14. Amazon Redshift has improved the performance of Redshift’s classic resize feature and increased the flexibility of the cluster snapshot restore operation. Redshift classic resize is used to resize a cluster in scenarios where you need to change the instance type or transition to a configuration that cannot be supported by elastic resize. Previously, this can take the cluster offline for many hours during resize, but now the cluster can typically be available to process queries in minutes. Clusters can also be resized when restoring from a snapshot and in those cases there could be restrictions. View the full article
  15. The Amazon EMR runtime for Apache Spark is a performance optimized runtime environment for Apache Spark, available and turned on by default on Amazon EMR clusters 5.28 onward. Amazon EMR runtime for Spark is up to 32x faster with 100% API compatibility with open source Spark. View the full article
  16. Amazon Relational Database Service (Amazon RDS) Performance Insights now allows you to choose retention periods for your performance history that range from one month up to 24 months. You can also use the RDS Performance Insights free tier, which includes seven days of performance data history and one million API requests per month. We have also adjusted the pricing model, resulting in reduced pricing of 24-month retention for most instance types. View the full article
  17. Amazon Relational Database Service (Amazon RDS) Performance Insights now makes it easier for you to see the database performance metrics for the exact timeframe you want to analyze, by choosing a custom time window within your retention period. Previously, you could only see metrics in Performance Insights by choosing relative time intervals such as the past 1 hour, the past 24 hours, etc. Amazon RDS Performance Insights is a database performance tuning and monitoring feature of Amazon RDS and Amazon Aurora that helps you quickly assess the load on your database and determine when and where to take action. This helps non-experts to measure database performance with an easy-to-understand dashboard that visualizes database load. With one click, you can add a fully-managed performance monitoring solution to your Amazon Aurora clusters and Amazon RDS instances. Amazon RDS Performance Insights automatically gathers all necessary performance metrics and visualizes them in a dynamic dashboard on the Amazon RDS console. You can identify your database’s top performance bottlenecks from a single graph. View the full article
  18. StarTree Cloud is Built on the Same Technology Used by LinkedIn and Uber to Democratize Data and Empower More Users with Fresh Insights Mountain View, CA, June 9, 2021 — StarTree, Inc. today announced the commercial availability of its “blazing-fast” cloud analytics-as-a-service platform, making it easier for organizations to share self-service analytics with their most important external […] The post StarTree Announces Commercial Availability of User-Facing Analytics Platform Raising the Bar for Speed, Scalability and Performance appeared first on DevOps.com. View the full article
  19. Amazon EC2 now provides additional network performance metrics to help customers gain more insights into instance network performance. Five new metrics provide customers visibility when their instances exceed network allowances defined by AWS. This visibility helps you proactively resolve application performance issues and right size your instance fleets based on your desired network performance. View the full article
  20. Amazon EMR now supports Amazon EC2 M6g, C6g and R6g instances with EMR Versions 6.1.0, 5.31.0 and later. These instances are powered by AWS Graviton2 processors that are custom designed by AWS utilizing 64-bit ArmNeoverse cores to deliver the best price performance for cloud workloads running in Amazon EC2. Please read our blog for more information. View the full article
  21. Amazon RDS Performance Insights supports additional dimensions to identify the source of high-frequency, long-running, and stuck SQL queries faster. The new Performance Insights dimensions are available on Amazon RDS for PostgreSQL and Amazon Aurora with PostgreSQL compatibility. View the full article
  22. Amazon RDS Performance Insights supports an additional dimension to identify the source of high-frequency, long-running, and stuck SQL queries faster. The new Performance Insights dimension is available on Amazon RDS for MySQL, Amazon Aurora with MySQL compatibility, and Amazon RDS for MariaDB. View the full article
  23. We are pleased to announce the release of NICE DCV version 2020.2 with the following new features: DCV Session Manager - It is an optional component that provides REST APIs to create and manage the lifecycle of a session across a fleet of DCV servers. It is available at no cost for AWS customers running DCV on Amazon EC2 instances and for on-prem customers with DCV Plus and DCV Professional Plus licenses.* Improved support for high-frame rate use cases - DCV frame rate limiter is now set to 60 FPS, by default, for console sessions on servers and Amazon EC2 instances with an NVIDIA GPU. Furthermore, by enabling the new QUIC-based transport protocol, customers running high frame rate, highly dynamic workloads, such as gaming, can experience more fluid and responsive streaming quality, especially under sub-optimal network conditions. Support for SLES 15 and Ubuntu 20.4 - Customers can now use DCV server and client components on SUSE Linux Enterprise 15 and Ubuntu 20.4 hosts. Smart Card Redirection for Windows server - Applications running in a remote Windows session can now use smart cards connected to the customer's client machine. This feature was already available for Linux servers. View the full article
  24. In this step by a step tutorial that illustrates how to integrate and use Locus to test microservices running in a Kubernetes cluster, we will cover the following topics: View the full article
  25. We are excited to announce the availability of Amazon EC2 P4d instances, the next generation of GPU-based instances that provide the best performance for machine learning (ML) training and high performance computing (HPC) in the cloud for applications such as natural language processing, object detection and classification, seismic analysis, and genomics research. P4d instances are powered by the latest NVIDIA A100 Tensor Core GPUs and provide first in the cloud 400 Gbps instance networking with support for Elastic Fabric Adapter (EFA) and NVIDIA GPUDirect RDMA (remote direct memory access) to enable efficient scale-out of multi-node ML training and HPC workloads. View the full article
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