Total Service Connections
The (Number of) Total Service Connections table
displays details about your service connections, such as the remote
IP addresses and how many tunnels are associated with it.
The Prisma Access
Insights user interface displays up to 10,000 records in a table. If you have more
than 10,000 records, you can view them by exporting the table into a CSV format
by clicking Export CSV. Any filters that you might have
applied to the data in the table are also applied to the data that is being
exported to the CSV format. The columns that do not have data in them do not get
exported and are omitted in the exported CSV file.
If you want to view in-depth data about a specific service connection,
select a Service Connection name to go the
site’s details page. You’ll see data about that service connection’s Tunnel
Bandwidth Over Time, Round Trip Time, Bandwidth Consumption
Over Time, Health, Connectivity,
and Consumption during the Time
Range specified.
The Round Trip Time graph indicates the trend of the average round-trip
time (RTT) over the IPSec tunnel originating from your headquarters or data
center to your Prisma Access service connection site. RTT, expressed in
milliseconds, measures the time taken to initiate a network request from an
originating source and receive the corresponding network response from the
target destination. RTT values can range from tens of milliseconds to hundreds
of milliseconds, with higher RTT values being indicative of link degradation
conditions resulting in degraded experience for accessing applications hosted in
headquarters or the data center. The RTT metric depends on factors such as
propagation delay, queuing delay, encoding delay, processing delay, and so on,
of which the propagation delay is generally considered the most significant.
Within headquarters or the data center, application server issues are likely to
be reflected in higher RTT values, as well.
Use this graph to learn about the service connection tunnel connectivity
performance and the variability of the RTT metric over time. When
you view this data over a period of time, you may notice established
patterns that can be flagged as normal or anomalous, therefore requiring
further investigation and possible remediation.