Efficient Log Management with 'awslogs' (with examples)

The awslogs tool allows for efficient querying of groups, streams, and events within Amazon CloudWatch logs. It provides a command-line interface that facilitates easy access to and analysis of log data, helping organizations streamline their log management processes. Whether you are monitoring applications, debugging errors, or analyzing system performance, awslogs is a powerful utility that provides a simple way to interact with CloudWatch logs.

Use case 1: List log groups

Code:

awslogs groups

Motivation:

Listing log groups is a foundational step in managing and navigating through your cloud infrastructure’s logging data. By retrieving a list of all log groups, users can quickly get an overview of the different logs available, ensuring they have a clear understanding of where to look when seeking specific data. This command is often used during setup or auditing to ensure all expected log groups are present and correctly configured.

Explanation:

• awslogs: The primary command that interfaces with CloudWatch logs.
• groups: This argument requests a list of all log groups within the user’s AWS environment. Log groups serve as containers for log streams, which are sequences of log events.

Example Output:

/aws/lambda/function1
/aws/elasticbeanstalk/application
/var/log/syslog

This output lists the current log groups, allowing users to identify and access specific logs of interest quickly.

Use case 2: List existing streams for the specified group

Code:

awslogs streams /var/log/syslog

Motivation:

Understanding the structure of log streams within a specific group is crucial for accessing and managing log data effectively. By listing these streams, users can pinpoint and focus on specific log sequences of interest, making it easier to track application or system events and perform in-depth analysis.

Explanation:

• awslogs: Initiates the command to interact with logs.
• streams: This argument requests the display of log streams within a specific group.
• /var/log/syslog: Specifies which log group to explore. This is a traditional Linux system log group, commonly used for system and application logs.

Example Output:

2023/10/10/[$LATEST]abcd1234abcd1234abcd1234abcd1234
2023/10/11/[$LATEST]defg5678defg5678defg5678defg5678

This output lists the individual streams, each corresponding to a specific time period, making it straightforward to select exactly what log data needs to be examined.

Use case 3: Get logs for any streams in the specified group between 1 and 2 hours ago

Code:

awslogs get /var/log/syslog --start='2h ago' --end='1h ago'

Motivation:

Fetching logs from a particular timeframe is a common requirement when troubleshooting recent issues or conducting performance monitoring. By specifying a time range, users can efficiently narrow down large volumes of log data to only the relevant entries, significantly speeding up diagnostic and analysis processes.

Explanation:

• awslogs: Commands interaction with logs.
• get: Retrieves log events based on specified parameters.
• /var/log/syslog: Identifies the target log group.
• --start='2h ago': Specifies the starting point for retrieving logs, here indicating logs from two hours in the past.
• --end='1h ago': Denotes the endpoint for log retrieval, concluding one hour ago.

Example Output:

2023-10-11 10:00:00 INFO Starting application process...
2023-10-11 10:30:15 ERROR Unexpected shutdown detected!
2023-10-11 10:45:00 INFO Restarting services...

This output shows logs for the specified period, helping users to investigate what transpired within that timeframe with precise details.

Use case 4: Get logs that match a specific CloudWatch Logs Filter pattern

Code:

awslogs get /aws/lambda/my_lambda_group --filter-pattern='ERROR'

Motivation:

When debugging or monitoring applications, particularly serverless functions like AWS Lambda, quickly filtering logs for specific keywords or patterns is invaluable. This command allows users to isolate only the logs that contain critical terms such as “ERROR,” facilitating faster error tracking and resolution.

Explanation:

• awslogs: Initiates command processing within the logging system.
• get: Requests retrieval of specific log data.
• /aws/lambda/my_lambda_group: Indicates the log group name related to a particular Lambda function.
• --filter-pattern='ERROR': Directs the tool to return only those logs that match the pattern described, here isolating logs with “ERROR.”

Example Output:

2023-10-11 11:00:00 ERROR Lambda execution failed due to timeout
2023-10-11 11:05:10 ERROR Error processing input data in function

This example presents filtered output with only error logs, making it easy for developers and administrators to address failures.

Use case 5: Watch logs for any streams in the specified group

Code:

awslogs get /var/log/syslog ALL --watch

Motivation:

Real-time log monitoring is crucial for dynamic environments where immediate response actions can be necessary. Watching logs allows system administrators to continuously view new log events as they happen, which is especially useful for live debugging or when monitoring critical systems and applications.

Explanation:

• awslogs: Activates the query system for logs.
• get: Instructs the retrieval of log entries.
• /var/log/syslog: Specifies the log group to be watched.
• ALL: Denotes that all streams under the given log group should be monitored.
• --watch: Enables real-time log streaming, continuously updating with new entries.

Example Output:

2023-10-11 12:00:00 INFO New user login detected
2023-10-11 12:05:15 ERROR Database connection lost
2023-10-11 12:06:00 INFO Database connection reestablished

This output represents logs updating in real-time, providing valuable insights into live system activity and enabling immediate response to critical events.

Conclusion

The awslogs command-line tool is a versatile and powerful resource for interacting with AWS CloudWatch log data. Through examples such as listing log groups, accessing specific log streams, fetching time-restricted logs, filtering for error patterns, and watching logs in real-time, this utility simplifies the management and analysis of logs, which is essential for effective cloud operation and maintenance.