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Network performance can have a big impact on the health of your services. With Pixie, you can easily monitor your network alongside your application and infrastructure layers.
This tutorial will demonstrate how to use Pixie to see:
A global view of the network traffic flowing within a cluster can be used to:
Let’s use the px/net_flow_graph
script to see a graph of all of the network traffic passing through the cluster:
px/net_flow_graph
from the script
drop-down menu at the top.When the script opens, you’ll get an error indicating a value is missing for the
namespace
required argument. The UI denotes required script arguments with an asterisk after the argument name.
pl
for the required namespace
argument.Select the drop down arrow next to the
namespace
argument, typepl
, and hit Enter.pl
is the namespace that Pixie deploys to.
This script shows a mapping of all the outgoing connections for the pods in the specified namespace.
Let's filter the graph to only show communication to the
pl-nats
pod.
to_entity_filter
argument, type pl-nats
, and press Enter to re-run the script.The graph should update to only show network traffic sent to the
pl-nats
pod. Pixie uses NATS as our messaging system.
Clear the to_entity_filter
value by selecting the drop-down arrow and pressing Enter.
Scroll down to the table below the graph. This table contains the same data that is used to construct the graph above.
Another capability Pixie provides is the ability to inspect and analyze DNS traffic. This information can be used to:
Let’s use the px/dns_flow_graph script to see a graph of DNS requests in the cluster:
px/dns_flow_graph
from the script
drop-down menu.This script shows all of the DNS requests made in the cluster, with latency and throughput stats.
This cluster doesn't have anything deployed except Pixie, so all we see are the kube-dns pods communicating with the metadata server.
LATENCY_AVG
column title to sort the table data by average latency.TCP drops and retransmits can indicate network connectivity issues that may affect application performance.
Let's use the bpftrace/tcp_drops
script to see a global view of TCP drops across the cluster.
bpftrace/tcp_drops
from the script drop-down menu.Hover over an edge to see the number of drops between pod pairs. The color and thickness of the edges indicate an increase in the number of TCP drops.
After a few seconds have passed, press the "RUN" button once again. Since more time has elapsed since the tracepoint was deployed, you should see more data in the graph.
This tutorial demonstrated three of Pixie's community scripts. For more insight into your network, check out the following scripts: