How to log application data

Logging application data is a crucial aspect of making sure your applications running on AWS are monitored properly for both performance and security. When preparing for the AWS Certified Data Analytics – Specialty (DAS-C01) exam, understanding how to effectively log, store, and analyze application data using AWS services is important. Below, we will discuss some methods and best practices for logging application data on AWS.

AWS CloudWatch Logs

AWS CloudWatch Logs is a monitoring service for AWS cloud resources and the applications you run on AWS. To log application data, you can use CloudWatch Logs to collect and track log files, set alarms, and automatically react to changes in your AWS resources.

Setting up CloudWatch Logs

1. Install the CloudWatch Logs agent on your EC2 instance or on-premise servers to send log data to CloudWatch. You can use AWS Systems Manager or manually install the agent.

   sudo yum install -y awslogs
   sudo service aws-config start

2. Configure the CloudWatch agent to specify which log files to send to CloudWatch. This is done through the awslogs.conf file.
3. Manage log groups and streams, ensuring you set up the right retention policies to fit within your budget and compliance requirements.

Push Logs from Lambda Functions

If you’re using AWS Lambda, you can automatically monitor functions and capture logs without installing agents. Lambda logs are sent to CloudWatch Logs.

Within your Lambda function, use the standard logging methods provided by most programming languages:

import logging

logger = logging.getLogger()
logger.setLevel(logging.INFO)

def lambda_handler(event, context):
logger.info(‘Log message from my Lambda function’)
# … rest of the code

AWS CloudTrail

CloudTrail provides a history of AWS API calls for your account, which can be particularly useful for logging usage data and auditing changes to your environment.

Configuration

1. Turn on CloudTrail by creating a trail in the AWS Management Console. You can choose to apply the trail to all regions and have logs delivered to an Amazon S3 bucket.
2. Define event selectors to specify which actions, resources, or users you want to log.
3. Monitor CloudTrail logs by setting up log file integrity validation to detect unauthorized access, and by analyzing logs using Amazon Athena for querying and AWS Glue for data cataloging.

Amazon Kinesis Data Firehose

For real-time data logging needs, Kinesis Data Firehose is an invaluable tool. It allows you to capture, transform, and load data streams into AWS data stores for real-time analytics.

Integration

1. Set up a Kinesis Data Firehose delivery stream, configuring the source either as direct PUT or other AWS services such as CloudWatch Logs.
2. Define data transformation if necessary, using an AWS Lambda function to transform the format or content of incoming data before it’s loaded into the destination.
3. Choose a destination like Amazon S3, Amazon Redshift, or Amazon Elasticsearch Service, where your logs will be stored and analyzed.

Best Practices for Logging

• Retention policies: Set retention policies to control costs and comply with data governance standards. For example, some logs may be set to rotate after 90 days while others may need to be retained for several years.
• Encryption: Ensure that sensitive log data is encrypted using AWS Key Management Service (KMS) for secure transmission and storage.
• Access Control: Use AWS Identity and Access Management (IAM) to control who can access your log data.
• Monitoring and Alarming: Set up alarms and notifications for specific log patterns. For example, if you’re logging error messages, you can create alarms to notify you of increased error rates.
• Consistent Logging Format: Standardize log formats across applications and services to make it easier for parsing and analysis.

Comparison between Services:

To sum up, AWS offers several services to log application data effectively. Each service serves different use cases, from real-time monitoring to compliance auditing. Understanding these services and how to utilize them is important for anyone preparing for the AWS Certified Data Analytics – Specialty (DAS-C01) exam and for professionals managing AWS-based applications.