Logs are critical for many scenarios in the modern digital world. They are used in tandem with metrics for observability, monitoring, troubleshooting, usage and service level analytics, auditing, security, and much more. Any plan to build an application or IT environment should include a plan for logs.
As a high-availability service, Azure HDInsight ensures that you can spend time focused on your workloads, not worrying about the availability of your cluster.
Azure Monitor for virtual machines (VMs) collects network connection data that you can use to analyze the dependencies and network traffic of your VMs.
Azure HDInsight offers several ways to monitor your Hadoop, Spark or Kafka clusters. They can be broken down into three main categories: cluster health and availability, resource utilization and performance, and job status and logs.
Azure Monitor provides sophisticated tools for collecting and analyzing telemetry that allow you to maximize the performance and availability of your cloud while also maximizing on-premises resources and applications.
We’re happy to introduce the new Grafana integration with Azure Monitor logs. This integration is achieved through the new Log Analytics plugin, now available as part of the Azure Monitor data source.
Queries can start with either a table name like search or union operators. These commands are useful during data exploration and for searching terms over the entire data model. However, these operators are not efficient for productization in alerts.
In this blog, we introduce how to post Azure Storage analytics logs to Azure Log Analytics workspace, thus you can use these great features to operate Azure Storage resources better.
We’re happy to provide a new, unified log search and analytics experience for Azure Monitor logs, as announced earlier this week. Azure Monitor logs is the central analytics platform for monitoring, management, security, application, and all other log types in Azure.
Your customers expect your applications to always be up and running. When that isn’t the case, it is critical that you quickly understand where the issues are - in the infrastructure or in code - and address them.