6.1 KiB
id | title |
---|---|
edge | Edges |
Edge
represents an edge between nodes.
Basic
Edge
is an object representing a connection between nodes with some additional properties.
An edge object contains three attributes: label, color, and style. They mirror the corresponding Graphviz edge attributes.
from diagrams import Cluster, Diagram, Edge
from diagrams.onprem.analytics import Spark
from diagrams.onprem.compute import Server
from diagrams.onprem.database import PostgreSQL
from diagrams.onprem.inmemory import Redis
from diagrams.onprem.aggregator import Fluentd
from diagrams.onprem.monitoring import Grafana, Prometheus
from diagrams.onprem.network import Nginx
from diagrams.onprem.queue import Kafka
with Diagram(name="Advanced Web Service with On-Premises (colored)", show=False):
ingress = Nginx("ingress")
metrics = Prometheus("metric")
metrics << Edge(color="firebrick", style="dashed") << Grafana("monitoring")
with Cluster("Service Cluster"):
grpcsvc = [
Server("grpc1"),
Server("grpc2"),
Server("grpc3")]
with Cluster("Sessions HA"):
primary = Redis("session")
primary \
- Edge(color="brown", style="dashed") \
- Redis("replica") \
<< Edge(label="collect") \
<< metrics
grpcsvc >> Edge(color="brown") >> primary
with Cluster("Database HA"):
primary = PostgreSQL("users")
primary \
- Edge(color="brown", style="dotted") \
- PostgreSQL("replica") \
<< Edge(label="collect") \
<< metrics
grpcsvc >> Edge(color="black") >> primary
aggregator = Fluentd("logging")
aggregator \
>> Edge(label="parse") \
>> Kafka("stream") \
>> Edge(color="black", style="bold") \
>> Spark("analytics")
ingress \
>> Edge(color="darkgreen") \
<< grpcsvc \
>> Edge(color="darkorange") \
>> aggregator
Less Edges
As you can see on the previous graph the edges can quickly become noisy. Below are two examples to solve this problem.
One approach is to get creative with the Node class to create blank placeholders, together with named nodes within Clusters, and then only pointing to single named elements within those Clusters.
Compare the output below to the example output above .
from diagrams import Cluster, Diagram, Node
from diagrams.onprem.analytics import Spark
from diagrams.onprem.compute import Server
from diagrams.onprem.database import PostgreSQL
from diagrams.onprem.inmemory import Redis
from diagrams.onprem.aggregator import Fluentd
from diagrams.onprem.monitoring import Grafana, Prometheus
from diagrams.onprem.network import Nginx
from diagrams.onprem.queue import Kafka
with Diagram("\nAdvanced Web Service with On-Premise Less edges", show=False) as diag:
ingress = Nginx("ingress")
with Cluster("Service Cluster"):
serv1 = Server("grpc1")
serv2 = Server("grpc2")
serv3 = Server("grpc3")
with Cluster(""):
blankHA = Node("", shape="plaintext", width="0", height="0")
metrics = Prometheus("metric")
metrics << Grafana("monitoring")
aggregator = Fluentd("logging")
blankHA >> aggregator >> Kafka("stream") >> Spark("analytics")
with Cluster("Database HA"):
db = PostgreSQL("users")
db - PostgreSQL("replica") << metrics
blankHA >> db
with Cluster("Sessions HA"):
sess = Redis("session")
sess - Redis("replica") << metrics
blankHA >> sess
ingress >> serv2 >> blankHA
diag
Merged Edges
Yet another option is to set the graph_attr dictionary key "concentrate" to "true".
Note the following restrictions:
- the Edge must end at the same headport
- This only works when the "splines" graph_attr key is set to the value "spline". It has no effect when the value was set to "ortho", which is the default for the diagrams library.
- this will only work with the "dot" layout engine, which is the default for the diagrams library.
For more information see:
https://graphviz.gitlab.io/doc/info/attrs.html#d:concentrate
https://www.graphviz.org/pdf/dotguide.pdf Section 3.3 Concentrators
from diagrams import Cluster, Diagram, Edge, Node
from diagrams.onprem.analytics import Spark
from diagrams.onprem.compute import Server
from diagrams.onprem.database import PostgreSQL
from diagrams.onprem.inmemory import Redis
from diagrams.onprem.aggregator import Fluentd
from diagrams.onprem.monitoring import Grafana, Prometheus
from diagrams.onprem.network import Nginx
from diagrams.onprem.queue import Kafka
graph_attr = {
"concentrate": "true",
"splines": "spline",
}
edge_attr = {
"minlen":"3",
}
with Diagram("\n\nAdvanced Web Service with On-Premise Merged edges", show=False,
graph_attr=graph_attr,
edge_attr=edge_attr) as diag:
ingress = Nginx("ingress")
metrics = Prometheus("metric")
metrics << Edge(minlen="0") << Grafana("monitoring")
with Cluster("Service Cluster"):
grpsrv = [
Server("grpc1"),
Server("grpc2"),
Server("grpc3")]
blank = Node("", shape="plaintext", height="0.0", width="0.0")
with Cluster("Sessions HA"):
sess = Redis("session")
sess - Redis("replica") << metrics
with Cluster("Database HA"):
db = PostgreSQL("users")
db - PostgreSQL("replica") << metrics
aggregator = Fluentd("logging")
aggregator >> Kafka("stream") >> Spark("analytics")
ingress >> [grpsrv[0], grpsrv[1], grpsrv[2],]
[grpsrv[0], grpsrv[1], grpsrv[2],] - Edge(headport="w", minlen="1") - blank
blank >> Edge(headport="w", minlen="2") >> [sess, db, aggregator]
diag