Monitoring parameters for Azure PaaS services
Here are some key
monitoring parameters for Azure services like Azure Databricks, Azure Data
Factory, Azure Data Lake and Azure Synapse that can be monitored using Site
24x7 tool.
Azure Databricks:
Cluster utilization:
monitor CPU, memory, and disk usage of the Databricks clusters to ensure that
the resources are being used optimally.
Job success rate:
monitor the success rate of jobs to ensure that they are completing
successfully and meeting SLAs.
Cluster restarts:
monitor cluster restarts to identify potential issues that may impact job
performance and user experience.
Azure Data Factory:
Pipeline success
rate: monitor the percentage of successful pipeline runs compared to total
pipeline runs to ensure that data is being processed successfully.
Data integration
rate: monitor the amount of data being integrated to ensure that it is meeting
business requirements.
Latency: monitor the
time it takes for data to be processed to ensure that it is meeting SLAs.
Azure Data Lake:
Data ingestion and
processing rates: monitor the amount of data being ingested and processed to
ensure that the data lake is performing optimally.
Query performance:
monitor the time it takes to execute queries to ensure that they are meeting
SLAs.
Storage usage:
monitor the amount of storage used to ensure that the data lake is not running
out of storage capacity.
Azure Synapse:
Query performance:
monitor the time it takes to execute queries to ensure that they are meeting
SLAs.
Data ingestion and
processing rates: monitor the amount of data being ingested and processed to
ensure that Synapse is performing optimally.
Failed jobs and
errors: monitor the number of failed jobs and errors encountered to ensure that
issues are identified and addressed proactively.