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Found 14 results

  1. Amazon Web Services
    Today, Amazon Kinesis Data Streams adds the ability for you to run SQL queries with one click in the AWS Management Console using Amazon Managed Service for Apache Flink. With this new capability, you can easily analyze and visualize the data in your streams in real-time. View the full article
  2. cloudonaut
    How do you monitor a container workload running on ECS (Elastic Container Service) and Fargate with on-board resources? Here are the prioritized aspects when it comes to monitoring containers on AWS... Event-driven monitoring with EventBridge Monitoring entry points like ALB, SQS, and Kinesis Monitoring inter-service communication (Service Connect) Observing container utilization Collecting and analyzing container logs View the full article
  3. Amazon Web Services
    Amazon Kinesis Data Firehose now integrates with Amazon MSK to offer a fully managed solution that simplifies the processing and delivery of streaming data from Amazon MSK Apache Kafka clusters into data lakes stored on Amazon S3. With just a few clicks, Amazon MSK customers can continuously load data from their desired Apache Kafka clusters to their Amazon S3 bucket, eliminating the need to develop or run their own connector applications. View the full article
  4. Amazon Web Services
    Amazon Kinesis Data Analytics is now authorized as FedRAMP Moderate in US East (Ohio), US East (N. Virginia), US West (N. California), US West (Oregon) and as FedRAMP High in AWS GovCloud (US-West) and AWS GovCloud (US-East). View the full article
  5. Amazon Web Services
    You can now publish the Redis slow log from your Amazon ElastiCache for Redis clusters to Amazon CloudWatch Logs and Amazon Kinesis Data Firehose. The Redis slow log provides visibility into the execution time of commands in your Redis cluster, enabling you to continuously monitor the performance of these operations. You can choose to send these logs in either JSON or text format to Amazon CloudWatch Logs and Amazon Kinesis Data Firehose. View the full article
  6. Amazon Web Services
    Amazon Kinesis Data Analytics now allows you to Force Stop a running application and reset its status to Ready, giving you more control over your applications. In addition, you can check if your application is scaling up or down through the new ‘Autoscaling' application status. View the full article
  7. Amazon Web Services
    Apache Flink Kinesis Consumer now supports Enhanced Fan Out (EFO) and the HTTP/2 data retrieval API for Amazon Kinesis Data Streams. EFO allows Amazon Kinesis Data Streams consumers to scale by offering each consumer a dedicated read throughput up to 2MB/second. The HTTP/2 data retrieval API reduces latency of data delivery from producers to consumers to 70 milliseconds or better. In combination, these two features allow you to build low latency Apache Flink applications that utilize dedicated throughput from Amazon Kinesis Data Streams. View the full article
  8. Amazon Web Services
    With Amazon Kinesis Data Streams for Amazon DynamoDB, you can capture item-level changes in your DynamoDB tables as a Kinesis data stream. You can enable streaming to a Kinesis data stream on your table with a single click in the DynamoDB console, or via the AWS API or AWS CLI. View the full article
  9. Amazon Web Services
    Amazon Kinesis Data Analytics for Apache Flink now provides access to the Apache Flink Dashboard, giving you greater visibility into your applications and advanced monitoring capabilities. You can now view your Apache Flink application’s environment variables, over 120 metrics, logs, and the directed acyclic graph (DAG) of the Apache Flink application in a simple, contextualized user interface. View the full article
  10. Amazon Web Services
    You can now build and run streaming applications using Apache Flink version 1.11 in Amazon Kinesis Data Analytics for Apache Flink. Apache Flink v1.11 provides improvements to the Table and SQL API, which is a unified, relational API for stream and batch processing and acts as a superset of the SQL language specially designed for working with Apache Flink. Apache Flink v1.11 capabilities also include an improved memory model and RocksDB optimizations for increased application stability, and support for task manager stack traces in the Apache Flink Dashboard. View the full article
  11. Amazon Web Services
    Amazon Kinesis Video Streams adds client metrics support to its WebRTC SDK in C. Kinesis Video Streams with WebRTC enables developers to build web, mobile, and IoT devices application for real-time media and data streaming. Developers can use this capability to build applications for use cases such as home security and monitoring, camera-enabled doorbells, baby and pet monitoring, smart appliances, and more. Kinesis Video Streams WebRTC SDK in C enables IoT devices to securely connect with Kinesis Video Streams for peer discovery and media streaming. The client metrics allows developers to monitor and track performance of the applications built using the WebRTC SDK in C. View the full article
  12. Amazon Web Services
    You can now store streaming data for up to one year in Amazon Kinesis Data Streams. Long term retention of streaming data enables you to use the same platform for both real-time and older data retained in Amazon Kinesis Data Streams. For example, you can train machine learning algorithms for financial trading, marketing personalization, and recommendation models without moving the data into a different data store or writing a new application. You can also satisfy certain data retention regulations, including under HIPAA and FedRAMP, using long term retention. You only pay for data stored and retrieved without provisioning additional storage or compute resources. View the full article
  13. Amazon Web Services
    Amazon Kinesis Data Analytics is now available in the US West (California) AWS region. View the full article
  14. Amazon Web Services
    You can now process multiple Amazon Kinesis data streams with a single Kinesis Client Library (KCL) based consumer application. Previously, each KCL based application processes a single Kinesis data stream. With this new capability, you can update the list of streams at runtime for multi-stream processing in a scalable KCL application without redeploying the application. This reduces operational overhead of maintaining multiple KCL applications. View the full article

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