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@@ -30,18 +30,18 @@ Then from pubsubly/docker run:
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Once everything is up and running you can navigate to http://localhost:3001 and see the Pubsubly UI interface.
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## Quickstart - Local
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First follow the build instructions for building pubsubly-api and pubsubly-service below ([How to build](#how-to-build)).
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Once you clone the repo, if you don't already have access to Kafka brokers you can start Kafka with the docker-compose.yml file in pubsubly/docker:
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Once you clone the repo, if you don't already have access to Kafka brokers you can start Kafka with the docker-compose-kafka.yml file in pubsubly/docker.
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First you need to create a network that is used by Kafka and Pubsubly, then you need to start the services:
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docker-compose up
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docker network create pubsubly-network
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docker-compose -f docker-compose-kafka.yml -f docker-compose.yml up
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If you aren't running Kafka locally, then you'll have update the application.yml with the broker URLs. In the application.yml in the pubsubly-service resources, update:
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If you aren't running Kafka locally, then you'll have update the application.yml with the broker URLs. In the application.yml in the pubsubly/docker/ folder resources, update:
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spring:
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kafka:
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bootstrap-servers: localhost:9092
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bootstrap-servers: <IP or hostname of Kafka broker>:9092
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Also update the topics you want to listen to either with a pattern OR topic names:
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@@ -51,14 +51,9 @@ or
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kafka.topic.names:
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Then you can start the server either through you Spring-Boot supported IDE or from the pubsubly-service root:
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mvn spring-boot:run
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To run the pubsubly-ui go to the pubsubly-ui root and do:
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Then you can start the server through docker-compose:
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npm install
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npm run dev
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docker-compsose -f docker-compose.yml up
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Then navigate to localhost:3001 in your browser.
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@@ -108,6 +103,10 @@ This demo demonstrates the use of 3 different messaging platforms and the abilit
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The demo runs a basic simulator that produces events. The event chains are triggered every 60 seconds and they simulate the creation of a user, the user getting a session stored in Redis and the sending of user data to a legacy system using ActiveMQ.
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The simulation also shows a series of bids and asks on a product, eventually resulting in a match which creates an order.
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To run the demo execute the following from pubsubly/docker:
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docker-compose -f docker-compose-demo.yml up
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This image shows the home page. The home page consists of a bar graph that shows the topics and the amount of messages from each topic. It also has a bubble chart that depicts the amount of messages processed per day per hour. This is to bring any attention to times of the day where message flow is high.
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The "Latest messages" section is a live display of the last 50 messages processed. The charts do not automatically update, so the page needs to be refreshed to reflect the latest numbers.
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The search page allows you to search by specific tag values, header keys and values, or text within the payload. In this example we performed a search for messages that contained the text "Yeezy".
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The listeners page allows you to add and remove additional Kafka topic names or topic patterns.
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Messages will automatically start being consumed from topics matching the new names or patterns.
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## How to build
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- id: eventName
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value: eventName
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description: This is the event name
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patternValueMonitors:
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- regexPattern: The regex pattern you want to match for this value, example '.*ERROR.*'
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priority: Possible values - NORMAL, LOW, MEDIUM, HIGH
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