def simple_main():
# graph_attr é a lista de parâmetros utilizados na construção do diagrama.
graph_attr = {"fontsize": "32", "fontcolor": "#1D3B52", "bgcolor": "white"}
# Cria o Diagrama base do nosso mapa
with Diagram('fboaventura.dev',
direction='LR',
filename='simple_fboaventura_dev',
outformat='png',
graph_attr=graph_attr,
show=False) as diag:
# Adiciona os nós no mapa
ingress = Haproxy('loadbalancer')
webserver = Nginx('django')
db = Postgresql('database')
memcached = Memcached('sessions')
# Criamos um cluster para os componentes do Celery, que trabalham em conjunto
with Cluster('Celery'):
beat = Celery('beat')
workers = [Celery('worker1'), Celery('worker2')]
flower = Celery('flower')
broker = Rabbitmq('broker')
logs = Redis('logs')
# Montamos o mapa de relacionamentos entre os nós
ingress >> webserver
webserver >> broker
beat >> broker
workers >> beat
webserver >> db
db >> broker
webserver >> memcached
broker >> logs
workers >> logs
flower >> beat
flower >> workers
beat >> logs
#
# (C) Copyright 2021 Pavel Tisnovsky
#
# All rights reserved. This program and the accompanying materials
# are made available under the terms of the Eclipse Public License v1.0
# which accompanies this distribution, and is available at
# http://www.eclipse.org/legal/epl-v10.html
#
# Contributors:
# Pavel Tisnovsky
#
from diagrams import Diagram
from diagrams.onprem.queue import Kafka, Rabbitmq
from diagrams.programming.language import Go
# novy graf s urcenim jeho zakladnich vlastnosti
with Diagram("OnPrem #1", show=True):
# definice uzlu - konzument
consumer = Kafka("input stream")
# definice uzlu - worker
worker = Go("worker")
# definice uzlu - producent
producer = Rabbitmq("output stream")
# propojeni uzlu grafu orientovanymi hranami
consumer >> worker >> producer
# Cria o Diagrama base do nosso mapa
with Diagram('fboaventura.dev', direction='LR', filename='simple_fboaventura_dev',
outformat='png', graph_attr=graph_attr) as diag:
# Adiciona os nós no mapa
ingress = Haproxy('loadbalancer')
webserver = Nginx('django')
db = Postgresql('database')
memcached = Memcached('sessions')
# Criamos um cluster para os componentes do Celery, que trabalham em conjunto
with Cluster('Celery'):
beat = Celery('beat')
workers = [Celery('worker1'), Celery('worker2')]
flower = Celery('flower')
broker = Rabbitmq('broker')
logs = Redis('logs')
# Montamos o mapa de relacionamentos entre os nós
ingress >> webserver
webserver >> broker
beat >> broker
workers >> beat
webserver >> db
db >> broker
webserver >> memcached
broker >> logs
workers >> logs
flower >> beat
flower >> workers
beat >> logs
from diagrams.onprem.database import Mongodb
from diagrams.onprem.queue import Rabbitmq
from diagrams.gcp.analytics import BigQuery, Dataflow, PubSub
from diagrams.programming.language import Nodejs
from diagrams.onprem.monitoring import Grafana, Prometheus
from diagrams.aws.database import RDS
from diagrams.aws.network import ELB
from diagrams.aws.storage import S3
from diagrams.onprem.network import Traefik
from diagrams.custom import Custom
from diagrams.onprem.tracing import Jaeger
from diagrams.onprem.database import Cassandra
with Diagram("OpenFlow Basic"):
with Cluster("Backend"):
b = [Mongodb("MongoDB"), Rabbitmq("RabbitMQ")]
with Cluster("Remote Clients"):
rc = [Custom("OpenRPA", "./my_resources/open_rpa128.png"), Custom("PowerShell",
"./my_resources/PowerShell_5.0_icon.png"), Custom("NodeRED", "./my_resources/node-red-icon.png")]
with Cluster("Frontend + API"):
api = EC2("WEB-API")
Custom("NodeRED", "./my_resources/node-red-icon.png")
b << api
api << rc
with Diagram("OpenFlow with Traefik"):
with Cluster("Backend"):
b = [Mongodb("MongoDB"), Rabbitmq("RabbitMQ")]
with Cluster("Remote Clients"):
from diagrams.azure.analytics import Hdinsightclusters
from diagrams.alibabacloud.analytics import ElaticMapReduce
from diagrams.aws.analytics import EMR
node_attr = {
"fontsize":"20"
}
graph_attr = {
"fontsize":"28"
}
with Diagram("", show=False, node_attr=node_attr):
with Cluster("Brokers", graph_attr=graph_attr):
kafka = Kafka("\nKafka")
activemq = Activemq("\nActiveMQ")
rabbitmq = Rabbitmq("\nRabbitMQ")
zeromq = Zeromq("\nZeroMQ")
kafka - activemq
rabbitmq - zeromq
with Cluster("Speed Layer", graph_attr=graph_attr):
kstream = Kafka("\nKafka\nStreams")
sparks = Spark("\nSpark Streaming")
flink = Flink("\nFlink")
#stream_group = [kstream, sparks, flink]
kstream - [sparks] - flink
with Cluster("Batch Layer", graph_attr=graph_attr):
hdfs = Hadoop("\nHDFS")
with Cluster("Serving Layer", graph_attr=graph_attr):