Apache NiFi: Monitoring metrics and provenance events using Azure Log Analytics

There are several cases where you might want to use Azure Log Analytics to monitor your NiFi instances. An obvious one is when NiFi is running in Azure. Azure Log Analytics can also be used as single monitoring/alerting solution for multiple applications making operations easier by providing a single interface for this. You might want this if you want to monitor business processes which span multiple applications and you want to monitor the entire process to for example identify bottlenecks.

In this blog post I'll show you how easy it is to achieve this using the AzureLogAnalyticsReportingTask and the AzureLogAnalyticsProvenanceReportingTask from NiFi and what you need to configure in Azure Log Analytics to make this work.

Filesystem events to Elasticsearch / Kibana through Kafka Connect / Kafka

Filesystem events are useful to monitor. They can indicate a security breach. They can also help  understanding how a complex system works by looking at the files it reads and writes.

When monitoring events, you can expect a lot of data to be generated quickly. The events might be interesting to process for different systems and at a different pace. Also it would be nice if you could replay events from the start or a specific moment. Enter Kafka. In order to put the filesystem events in Kafka (from an output file), the Kafka Connect FileSourceConnector is used. In order to get the data from Kafka to Elasticsearch, the Kafka Connect ElasticsearchSinkConnector is used. Both connectors can be used without Enterprise license.