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Tutorials > Microservices > Monitoring and Logging

Monitoring and Logging

To monitor and log microservices using tools like Prometheus, Grafana, or ELK stack, follow these steps:

  • Prometheus:

Prometheus is a monitoring system that collects metrics from monitored targets by scraping metrics HTTP endpoints. To monitor microservices with Prometheus, you need to instrument your code with a Prometheus client library and expose metrics HTTP endpoints. Then, you can configure Prometheus to scrape the endpoints and collect metrics.

a. Instrument your code with a Prometheus client library. For example, in a Python application, you could use the prometheus_client library to create a counter:

python
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from prometheus_client import Counter

requests_total = Counter('requests_total', 'Total number of requests')

b. Expose metrics HTTP endpoints in your microservices. For example, in a Flask application, you could use the prometheus_flask_exporter library to expose metrics:

python
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from prometheus_flask_exporter import PrometheusMetrics

metrics = PrometheusMetrics(app)

@app.route('/hello')
def hello():
    requests_total.inc()
    return 'Hello, World!'

c. Configure Prometheus to scrape the metrics endpoints. For example, in a Prometheus configuration file, you could add the following job to scrape the Flask application:

yaml
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scrape_configs:
  - job_name: 'flask_app'
    scrape_interval: 5s
    static_configs:
      - targets: ['flask_app:5000']
  • Grafana:

Grafana is a platform for data visualization and analytics. To visualize metrics collected by Prometheus in Grafana, you need to configure Grafana to connect to Prometheus as a data source and create a dashboard.

a. Configure Grafana to connect to Prometheus as a data source. For example, in the Grafana UI, you could add a new data source and enter the following information:

diff
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- Name: Prometheus
- Type: Prometheus
- URL: http://prometheus:9090

b. Create a dashboard in Grafana. For example, you could add a new panel to display the requests_total metric:

vbnet
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- Click on the '+' icon in the top menu and select 'Add panel'
- Select the Prometheus data source
- Set the query to 'requests_total'

3. ELK stack:

ELK stack is a collection of open-source tools for log management and analysis, including Elasticsearch, Logstash, and Kibana. To log microservices with ELK stack, you need to send logs from your microservices to a centralized logging system using Logstash or Filebeat. Then, you can use Kibana to search, visualize, and analyze logs.

a. Send logs from your microservices to a centralized logging system. For example, in a Python application, you could use the logstash_formatter library to format logs in Logstash JSON format and send them to a Logstash server:

python
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import logging
from logstash_formatter import LogstashFormatter

logstash_handler = logging.handlers.SocketHandler('logstash', 5000)
logstash_handler.setFormatter(LogstashFormatter())

logger = logging.getLogger('myapp')
logger.addHandler(logstash_handler)
logger.setLevel(logging.INFO)

logger.info('Hello, World!')

b. Configure Logstash or Filebeat to receive and process logs. For example, you could create a Logstash configuration file to receive logs over a TCP input and output them to Elasticsearch:

yaml
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input {
  tcp {
    port => 5000
    codec => json_lines
  }
}

output {
  elasticsearch {
    hosts => ['elasticsearch:9200']
  }
}

c. Use Kibana to search, visualize, and analyze logs. For example, you could create a Kibana index pattern to match the index name in Elasticsearch, and create a visualization to display log messages:

sql
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- Click on the 'Discover' tab in the Kibana UI
- Create an index pattern to match the Elasticsearch index
- Search for log messages
- Click on the 'Visualize' tab
- Create a new visualization with the following settings:
    - Type: 'Data table'
    - Aggregation: 'Terms'
    - Field: 'message'
    - Size: 10
    - Sort: 'Descending'
    - Save the visualization and add it to a dashboard

Overall, monitoring and logging microservices is an important part of managing a distributed system, and using tools like Prometheus, Grafana, or ELK stack can help you collect, visualize, and analyze metrics and logs.



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