Concepts
Metric filters in AWS CloudWatch provide a way to transform log data into numerical CloudWatch metrics that you can graph or set alarms on. When preparing for the AWS Certified SysOps Administrator – Associate (SOA-C02) exam, it’s important to understand how to create and use metric filters to monitor application and infrastructure performance.
A metric filter scans through your CloudWatch Logs for patterns and expressions that you define, and then it updates a CloudWatch metric in real-time based on what it finds. This can be anything from counting occurrences of specific statuses in log messages to extracting values to be used as the data points for metrics.
Step-by-Step Guide to Create Metric Filters
Step 1: Log into AWS Management Console
- Navigate to the CloudWatch service.
- From the left navigation pane, select “Logs”.
Step 2: Choose Log Group
- Select the log group that you want to associate the metric filter with.
- On the Log group page, choose “Create Metric Filter”.
Step 3: Define Pattern
- In the “Filter Pattern” box, enter a filter pattern to match the log events you want to catch.
- For example, to track HTTP 404 errors in your application logs:
"[ip, user, user_id, timestamp, request, status_code=404, size]".
- For example, to track HTTP 404 errors in your application logs:
- Select “Assign Metric”.
Step 4: Set Metric Details
- For “Filter Name”, enter a name for your metric filter.
- For “Metric Namespace”, enter a custom namespace or choose an existing one.
- For “Metric Name”, choose a descriptive name for your data collection.
- Optionally, you can add metric dimensions for additional granularity.
- Decide whether the metric is a Counter or represents another kind of value.
- For counting occurrences, such as the number of 404 errors, you will likely use a Counter.
- Define the metric value that will be incremented each time the pattern matches. For instance, “1” to increment a counter by one for each match.
Step 5: Review and Create
- Review your settings and select “Create Filter”.
- Your metric filter is now set up and will begin to report data to the specified CloudWatch metric.
Example Scenario
Suppose you have an application log that outputs lines such as:
[ERROR] – 2023-04-10T14:32:00.000Z – Login failure for user xyz
[INFO] – 2023-04-10T14:32:05.000Z – User xyz accessed the system
You want to track the number of login failures.
- Filter Pattern:
"[timestamp=*Z, level=ERROR, message, user=*]". - Metric Details:
- Filter Name:
LoginFailures - Metric Namespace:
MyAppMetrics - Metric Name:
LoginFailureCount - Metric Value:
1
- Filter Name:
Every time a log message starts with [ERROR] and contains Login failure for user, CloudWatch will increment the LoginFailureCount metric by 1.
Best Practices and Tips
- Filter patterns are case-sensitive by default.
- Each log event can only contribute once to a metric, regardless of how many times the pattern matches within the event.
- Test your filter patterns to ensure they match the desired log events before creating the metric filter.
- Remember that more complex filters might have a higher cost associated with them due to increased data processing.
Conclusion
Creating metric filters is a powerful way to gain insight into your system’s operations, obtain necessary metrics to evaluate performance, detect issues proactively, and automate actions based on those metrics. By mastering the process of creating metric filters, you will be better equipped to take on the operational challenges that the AWS Certified SysOps Administrator – Associate exam will present.
Answer the Questions in Comment Section
(True/False) Metric filters in AWS CloudWatch can only be created for log groups that are less than 24 hours old.
- Answer: False
Explanation: Metric filters can be created for any log group in AWS CloudWatch regardless of the age of the log group.
(Single Select) Which AWS service allows you to create metric filters for logs?
- A) AWS Lambda
- B) Amazon EC2
- C) AWS CloudTrail
- D) Amazon CloudWatch
Answer: D) Amazon CloudWatch
Explanation: Amazon CloudWatch is the service that provides log data and allows you to create metric filters on the logs.
(True/False) Metric filters can be used to transform log data into numerical CloudWatch metrics that you can graph or set alarms on.
- Answer: True
Explanation: Metric filters can be used to turn text-based log data into numerical metrics that can be graphed or used to create alarms in CloudWatch.
(Multiple Select) Which of the following metric filter components are used when creating a metric filter in Amazon CloudWatch?
- A) Filter pattern
- B) Metric Name
- C) Log group
- D) S3 bucket destination
Answer: A) Filter pattern, B) Metric Name, C) Log group
Explanation: When creating a metric filter, you define a filter pattern to match log event messages, a metric name for the CloudWatch metric, and select the log group where the metric filter will be applied. S3 bucket destination is not a component of a metric filter.
(True/False) Multiple metric filters can be applied to a single log event.
- Answer: True
Explanation: You can have multiple metric filters that match different data in a single log event, each creating its own metric.
(Single Select) How often are metrics from metric filters updated in Amazon CloudWatch?
- A) Instantly
- B) Every 1 minute
- C) Every 5 minutes
- D) Every 60 minutes
Answer: B) Every 1 minute
Explanation: Once a metric filter is matched to a log event, the metric data points are created and then updated in CloudWatch metrics approximately every 1 minute.
(True/False) When creating a metric filter, you can use test patterns against existing log data to validate the pattern.
- Answer: True
Explanation: AWS CloudWatch supports testing the filter pattern against existing log data to ensure it works as expected.
(Single Select) Which of the following characters can be used to separate the terms in a metric filter pattern?
- A) Commas (,)
- B) Spaces
- C) Semi-colons (;)
- D) Colons (:)
Answer: B) Spaces
Explanation: In a metric filter pattern, spaces are used to separate terms.
(Multiple Select) What can you set up once you have created a metric filter and associated it with a CloudWatch metric?
- A) Alarms
- B) EC2 Auto Scaling actions
- C) AWS Lambda functions
- D) CloudWatch Dashboards
Answer: A) Alarms, B) EC2 Auto Scaling actions, D) CloudWatch Dashboards
Explanation: Once you have a CloudWatch metric from a metric filter, you can set up alarms, EC2 Auto Scaling actions based on those alarms, and view the metrics in CloudWatch Dashboards. Lambda functions are not set up directly through metric filters.
(True/False) It is possible to delete a metric filter after it has been created in Amazon CloudWatch.
- Answer: True
Explanation: You can delete metric filters that you no longer need from the Amazon CloudWatch console.
(Single Select) What is the maximum number of metric filters that can be applied to a single log group in AWS CloudWatch?
- A) 100
- B) 500
- C) 1,000
- D) No limit
Answer: D) No limit
Explanation: Currently, AWS does not specify a limit on the number of metric filters you can apply to a single log group, but there are other service limits within AWS.
(True/False) For each matched event that a metric filter finds, a metric dimension will be automatically created.
- Answer: False
Explanation: Metric dimensions are not created automatically; rather, you can optionally specify one or more dimensions to further refine the metric created by a metric filter.
Great post! This really helped me understand metric filters for the AWS Certified SysOps Administrator exam.
Can anyone explain how to create a custom metric filter?
Thanks for the detailed post! It clarified many of my doubts about metric filters.
Very helpful post, appreciate it!
Do you need to reference the metric filter in your CloudFormation template?
Excellent blog post, just what I needed!
I found that Lambda can also generate custom metrics. Is it better to use that instead?
Thanks for this post. Helped me get through a tricky exam question!