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Found 21 results

  1. Today, AWS IoT Core for LoRaWAN announces a new fleet monitoring application that enables developers capture and visualize critical operational and health parameters related to the functioning of LoRaWAN-based gateways and devices. AWS IoT Core for LoRaWAN is a fully managed LoRaWAN Network Server that supports cloud connectivity for LoRaWAN-based wireless devices. Using the new metrics feature, developers can now quickly capture system health data, such as connection signal strength, data rate, and gateway latency and analyze their fleet’s performance. View the full article
  2. AWS Step Functions announces open workflow metrics for Step Functions workflows in Amazon CloudWatch to track and monitor the number of open workflow executions in real-time through Amazon CloudWatch. AWS Step Functions is a visual workflow service capable of orchestrating over 12,000+ API actions from over 220 AWS services to build distributed applications and data processing workloads. View the full article
  3. Metrics are closely associated with cloud infrastructure monitoring or application performance monitoring – we monitor metrics like infrastructure CPU and request latency to understand how our services are responding to changes in the system, which is a good way to surface new production issues. As many teams transition to observability, collecting metric data isn’t enough. […]View the full article
  4. Starting today, we are introducing a new Amazon CloudWatch metric called Attached EBS Status Check to monitor if one or more Amazon EBS volumes attached to your EC2 instances are reachable and able to complete I/O operations. With this new metric, you can now quickly detect and respond to any EBS impairments that may potentially be impacting the performance of your applications running on Amazon EC2 instances. View the full article
  5. DORA metrics enable developers to understand their process’ weak points and identify areas for improvement internally. View the full article
  6. Hey there! Are you curious about CloudOps metrics? Do you want to know more about how to measure the performance of your cloud operations? Well, you have come to the right place. In this article, we will explore the major CloudOps metrics that can help you optimize your cloud infrastructure for better performance, efficiency, and cost-effectiveness. View the full article
  7. Amazon Connect Contact Lens now provides manager alerts on real-time metrics via email notifications, EventBridge events, or Amazon Connect Tasks. These new alerts enable businesses to notify their managers on unexpected changes in contact center operations that could impact the end-customer experience. With this launch, businesses can now configure alerts that include choosing a metric (e.g., service level), defining a metric threshold (e.g., service level of 90 seconds drops below 75% on a business critical queue), and sending an automated email notification or assigning a task to a manager for follow-up action. View the full article
  8. Amazon Lookout for Metrics uses machine learning (ML) to automatically monitor the metrics critical to your businesses with greater speed and accuracy than traditional methods used for anomaly detection. The service makes it easier to diagnose the root cause of anomalies such as unexpected dips in revenue, high rates of abandoned shopping carts, spikes in payment transaction failures, increases in new user sign-ups, and many more. View the full article
  9. BMC this week announced it has added support for DevOps Research and Assessment (DORA) metrics within its portfolio of DevOps tools for mainframe environments. John McKenny, senior vice president and general manager for intelligent Z optimization and transformation at BMC, said the latest edition of BMC Compuware zAdviser now includes a DORA KPI Dashboard that […] The post BMC Adds Support for DORA Metrics to Mainframe Tools Portfolio appeared first on DevOps.com. View the full article
  10. Most folks working in DevOps or SRE roles are familiar with metrics like mean-time-to-recovery (MTTR). Keeping track of the average time a team takes to respond to incidents is crucial to identifying bottlenecks in the support process. It’s also something executives like to show higher-ups when sharing a snapshot of overall platform performance. However, focusing […] The post 5 Mean-Time Reliability Metrics To Follow appeared first on DevOps.com. View the full article
  11. Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, update, search, and share machine learning (ML) features. The service provides feature management capabilities such as enabling easy feature reuse, low latency serving, time travel, and ensuring consistency between features used in training and inference. Until today, SageMaker Feature Store monitoring was limited to consumed read and write units, which gave a limited view of the operational efficiency of the feature store. View the full article
  12. Amazon QuickSight now supports monitoring of QuickSight assets by sending metrics to Amazon CloudWatch. QuickSight developers and administrators can use these metrics to observe and respond to the availability and performance of their QuickSight ecosystem in near real time. They can monitor dataset ingestions, dashboards, and visuals to provide their readers with a consistent, performant, and uninterrupted experience on QuickSight. For more information, visit here. View the full article
  13. We are excited to announce that you can now add filters to alerts and also edit existing alerts while using Amazon Lookout for Metrics. With this launch you can now add filters to your alerts configuration to only get notifications for anomalies that matter the most to you. You can also simply modify existing alerts as per your needs for notification as anomalies evolve. View the full article
  14. Amazon Lookout for Metrics announces the launch of backtesting when using Amazon CloudWatch as a data source connector. Backesting is a new anomaly detection mode you can now select when setting up your detector. You can seamlessly connect to your data in CloudWatch to set up a highly accurate anomaly detector across metrics, dimensions, and namespaces of your choice. Amazon Lookout for Metrics uses machine learning (ML) to automatically detect and diagnose anomalies (outliers from the norm) without requiring any prior ML experience. Amazon CloudWatch provides you with actionable insights to monitor your applications, respond to system-wide performance changes, optimize resource utilization, and get a unified view of operational health. View the full article
  15. AWS Lookout for Metrics announces the launch of the Athena connector, a new connector in Lookout for Metrics that allows you to query data from various data sources such as Data Lake on AWS, Amazon S3, Amazon Redshift to ingest into Amazon Lookout for Metrics for anomaly detection. The Athena connector reduces the need to setup complex ETL jobs and data preparation time for anomaly detection. You can query large datasets using standard SQL and analyze it before ingesting in an anomaly detector. The Athena connector supports data formatted in CSV, JSON, ORC (Optimized Row Columnar), Parquet, XML, plain text and AVRO. View the full article
  16. Today, we are announcing the availability of Amazon CloudWatch metrics for usage monitoring on AWS Config. AWS Config tracks changes made to supported resources and records them as configuration items (CIs), which are then delivered to an Amazon Simple Storage Service (Amazon S3) bucket. Amazon CloudWatch metrics is a monitoring service which provides data about the usage of your systems, including the ability to search, graph, and build alarms on metrics about AWS resources. With this release, you can now use Amazon CloudWatch metrics to verify your setup and understand your usage of AWS Config. View the full article
  17. OpenTelemetry is a Cloud Native Computing Foundation (CNCF) initiative that provides open, vendor-neutral standards and tools for instrumenting services and applications. Many organizations use OpenTelemetry’s collection of APIs, SDKs, and tools to collect and export observability data from their environment to their preferred backend. As part of our ongoing commitment to OpenTelemetry, we are proud […] The post Ingest OpenTelemetry Traces and Metrics with the Datadog Agent appeared first on DevOps.com. View the full article
  18. Amazon S3 Replication now provides detailed metrics and notifications to monitor the status of object replication between buckets. You can monitor replication progress by tracking bytes pending, operations pending, and replication latency between your source and destination buckets using the S3 management console or Amazon CloudWatch. You can also set up S3 Event Notifications to receive replication failure notifications to quickly diagnose and correct configuration issues. S3 Replication metrics and notifications help you closely monitor replication progress. Previously, S3 Replication metrics and notifications were available with S3 Replication Time Control (S3 RTC). Beginning now, they can be enabled for all replication rules. View the full article
  19. AWS Fargate for Amazon Elastic Container Service (Amazon ECS) announced features to improve configuration and metrics of containers: environment files, secret versions and JSON keys, granular network metrics, and more metadata. View the full article
  20. Amazon CloudWatch launches Metrics Explorer – a tag-based dashboard tool that enables customers to filter, aggregate, and visualize operational health and performance metrics by tags. Metrics Explorer provides customers with a flexible troubleshooting experience, allowing them to build their tag-based application health dashboards, identify correlations, and quickly analyse their operational data to pinpoint issues. These tag-based dashboards will stay up to date as resources come and go, and they will help customers to identify the root cause and quickly isolate the issues when an alarm occurs on an application or environment. View the full article
  21. Like The Hobbit’s dragon Smaug laying on his pile of gold, never spending and only hoarding, many of us often stockpile pretty, feel-good, but useless metrics that never make a difference. In fact, they could actually be clouding your ability to get the context and clarity you need from your metrics. In this blog post, we'll help you kick your fetish and move away from Smaug-ing up all your metrics. View the full article
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