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1 | 1 | --- |
2 | 2 | title: Monitoring sentiment with Elasticsearch and Kibana |
3 | | -weight: 4 |
| 3 | +weight: 3 |
4 | 4 |
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5 | 5 | ### FIXED, DO NOT MODIFY |
6 | 6 | layout: learningpathall |
7 | 7 | --- |
8 | 8 |
|
9 | | -## Deploy Elasticsearch and Kibana on Arm-based EC2 instance |
| 9 | +### Elasticsearch |
10 | 10 |
|
11 | | -Elasticsearch is a NoSQL database, search, and analytics engine. It's designed to store, search and analyze large amounts of data. It has real-time indexing capability which is crucial for handling high-velocity data streams like Tweets. |
| 11 | +Elasticsearch is a NoSQL database, search, and analytics engine. It is designed to store, search, and analyze large amounts of data. It has a real-time indexing capability which is crucial for handling high-velocity data streams such as X posts. |
12 | 12 |
|
13 | | -Kibana is a dashboard and visualization tool that integrates seamlessly with Elasticsearch. It provides an interface to interact with twitter data, apply filters, and receive alerts. There are multiple ways to install Elasticsearch and Kibana, one method is shown below. |
| 13 | +### Kibana |
| 14 | + |
| 15 | +Kibana is a customizable dashboard and visualization tool which integrates seamlessly with Elasticsearch. It provides valuable insights and opportunities to explore collected data by presenting it in multiple differing views. |
| 16 | + |
| 17 | +In this Learning Path, you will use a Kibana dashboard as an interface to interact with X data, apply filters, and receive alerts. |
| 18 | + |
| 19 | +### How do I install Elasticsearch and Kibana? |
| 20 | + |
| 21 | +There are multiple ways to install Elasticsearch and Kibana. One of these methods is described here. |
14 | 22 |
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15 | 23 | Before you begin, ensure that Docker and Docker Compose have been installed on your computer. |
16 | 24 |
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17 | | -Use a text editor to create a `docker-compose.yml` file with the contents below: |
| 25 | +Use a text editor to create a `docker-compose.yml` file, and copy-and-paste in the contents below: |
18 | 26 |
|
19 | 27 | ```yml |
20 | 28 | version: '2.18.1' |
@@ -50,40 +58,42 @@ networks: |
50 | 58 | driver: bridge |
51 | 59 | ``` |
52 | 60 |
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53 | | -Use the following command to deploy Elasticsearch and Kibana Dashboard. |
| 61 | +Use the following command to deploy Elasticsearch and the Kibana Dashboard: |
54 | 62 |
|
55 | 63 | ```console |
56 | 64 | docker compose up |
57 | 65 | ``` |
| 66 | +If you do not have the `docker compose` plugin already installed, you can install it through the following commands: |
58 | 67 |
|
59 | | -```Note |
60 | | -If you don't have the `docker compose` plugin already installed, you can install it via the following commands |
| 68 | +{{% notice Note %}} |
61 | 69 | sudo apt-get update |
62 | 70 | sudo apt-get install docker-compose-plugin |
63 | | -``` |
| 71 | +{{% /notice %}} |
64 | 72 |
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65 | | -After the dashboard is up, use the the public IP of your server on the port 5601 to access the Kibana dashboard. |
| 73 | +After the dashboard is set up, use the public IP of your server on port `5601` to access the Kibana dashboard. See Figure 2. |
66 | 74 |
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67 | | - |
| 75 | + |
68 | 76 |
|
69 | | -Switch to the stack management using the menu on the left side as shown in below image. |
| 77 | +Switch to *Stack Management* using the menu on the left side as Figure 3 shows. |
70 | 78 |
|
71 | | - |
| 79 | + |
72 | 80 |
|
73 | | -To make sure that you are receiving the data from sentiment analysis application through Elasticsearch, check whether you have Data View in Stack Management. |
| 81 | +To make sure that you are receiving the data from the sentiment analysis application through Elasticsearch, check whether you have the Data View enabled in Stack Management. |
74 | 82 |
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75 | | - |
| 83 | + |
76 | 84 |
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77 | 85 | You can also check the types of attributes that are received as the Data Views. Now, you can switch to the dashboards on the left menu and start creating the visualizations to analyze the data. |
78 | 86 |
|
79 | | - |
| 87 | + |
| 88 | + |
| 89 | +Figure 6 shows a sample dashboard structure, displaying the records of different sentiments. |
80 | 90 |
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81 | | -One of the sample dashboard structures looks as below, showing the records of different sentiments. |
| 91 | + |
82 | 92 |
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83 | | - |
| 93 | +Similarly, you can design and create dashboards to analyze a particular set of data. The screenshot in Figure 7 shows the dashboard designed for this Learning Path. |
84 | 94 |
|
85 | | -Similarly, you can design and create dashboards to analyze a particular set of data. The screenshot below shows the dashboard designed for this learning path |
| 95 | + |
86 | 96 |
|
87 | | - |
| 97 | +Navigate to the `dashboards` directory in the cloned GitHub repository and locate the `sentiment_dashboard.ndjson` file. |
88 | 98 |
|
89 | | -Navigate to the `dashboards` directory in the cloned github repository and locate `sentiment_dashboard.ndjson` file. Import this file into Kibana dashboard and you should see a dashboard shown in previous step. |
| 99 | +Import this file into the Kibana dashboard and you should see a dashboard as shown in the previous step. |
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