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Sumo Logic

Collect logs for the Amazon S3 Audit App

Amazon Simple Storage Service (S3) provides a simple web services interface that can be used to store and retrieve any amount of data from anywhere on the web.

This topic details how to collect logs for Amazon S3 Audit and ingest them into Sumo Logic.

Log Types

Amazon S3 Audit uses Server Access Logs (activity logs). For more information on the log format, see:

http://docs.aws.amazon.com/AmazonS3/latest/dev/LogFormat.html

Configure Logging in AWS

Before you can begin to collect logs from an S3 bucket, perform the following steps:

  1. Grant Access to an AWS S3 Bucket.
  2. Enable logging using the AWS Management Console.
  3. Confirm that logs are being delivered to the S3 bucket.

Configure a Collector

In Sumo Logic, configure a Hosted Collector.

Configure an S3 Audit Source

When you create an AWS Source, you associate it with a Hosted Collector. Before creating the Source, identify the Hosted Collector you want to use, or create a new Hosted Collector. For instructions, see Configure a Hosted Collector.

These configuration instructions apply to log collection from all AWS Source types. Select the correct Source type for your Source in Step 3.

  1. In Sumo Logic select Manage Data > Collection > Collection
  2. On the Collectors page, click Add Source next to a hosted collector, either an existing hosted collector, or one you have created for this purpose.
  3. Select your AWS Source type. 
  4. Enter a name to display for the new Source. Description is optional.
  5. For Bucket Name, enter the exact name of your organization's S3 bucket. 
    Be sure to double-check the name as it appears in AWS, for example:

    S3_Bucket_name.png
  1. For Path Expression, enter the string that matches the S3 objects you'd like to collect. You can use one wildcard (*) in this string. Recursive path expressions use a single wildcard and do NOT use a leading forward slash. See About Amazon Path Expressions for details.
  2. Collection should begin. Choose or enter how far back you'd like to begin collecting historical logs. You can either:
    • Choose a predefined value from dropdown list, ranging from "Now" to “72 hours ago” to “All Time”, or
    • Enter a relative value. To enter a relative value, click the Collection should begin field and press the delete key on your keyboard to clear the field. Then, enter a relative time expression, for example-1w. You can define when you want collection to begin in terms of months (M), weeks (w), days (d), hours (h) and minutes (m).
  1. For Source Category, enter any string to tag the output collected from this Source. (Category metadata is stored in a searchable field called _sourceCategory.)
  2. For Key ID, enter the AWS Access Key ID number granted to Sumo Logic. (See Granting access to an S3 bucket for more information.)
  3. For Secret Key, enter the AWS Secret Access Key Sumo Logic should use to access the S3 bucket. (See Granting access to an S3 bucket for more information.)
  4. For Scan Interval, use the default of 5 minutes. Alternately, enter the frequency Sumo Logic will scan your S3 bucket for new data. To learn more about Scan Interval considerations, see About setting the S3 Scan Interval.
  5. Set any of the following under Advanced:
  • Enable Timestamp Parsing. This option is selected by default. If it's deselected, no timestamp information is parsed at all.
    • Time Zone. There are two options for Time Zone. You can use the time zone present in your log files, and then choose an option in case time zone information is missing from a log message. Or, you can have Sumo Logic completely disregard any time zone information present in logs by forcing a time zone. It's very important to have the proper time zone set, no matter which option you choose. If the time zone of logs can't be determined, Sumo Logic assigns logs UTC; if the rest of your logs are from another time zone your search results will be affected.
    • Timestamp Format. By default, Sumo Logic will automatically detect the timestamp format of your logs. However, you can manually specify a timestamp format for a Source. See Timestamps, Time Zones, Time Ranges, and Date Formats for more information.
  • Enable Multiline Processing. See Collecting Multiline Logs for details on multiline processing and its options. This is enabled by default. Use this option if you're working with multiline messages (for example, log4J or exception stack traces). Deselect this option if you want to avoid unnecessary processing when collecting single-message-per-line files (for example, Linux system.log). Choose one of the following:  
    • Infer Boundaries. Enable when you want Sumo Logic to automatically attempt to determine which lines belong to the same message. If you deselect the Infer Boundaries option, you will need to enter a regular expression in the Boundary Regex field to use for detecting the entire first line of multiline messages.
    • Boundary Regex. You can specify the boundary between messages using a regular expression. Enter a regular expression that matches the entire first line of every multiline message in your log files.
  1. Create any Processing Rules you'd like for the AWS Source.
  2. When you are finished configuring the Source click Save.

Field Extraction Rules

Field Extraction Rules (FERs) tell Sumo Logic which fields to parse out automatically. For instructions, see Create a Field Extraction Rule.

Use the following Parse Expression:

parse "* * [*] * * * * * \"* HTTP/1.1\" * * * * * * * \"*\" *" as bucket_owner, bucket, time, remoteIP, requester, request_ID, operation, key, request_URI, status_code, error_code, bytes_sent, object_size, total_time, turn_time, referrer, user_agent, version_ID

Sample Log Messages

The server access log files consist of a sequence of new-line delimited log records. Each log record represents one request and consists of space delimited fields. The following is an example log consisting of six log records.

79a59df900b949e55d96a1e698fbacedfd6e09d98eacf8f8d5218e7cd47ef2be mybucket [06/Feb/2014:00:00:38 +0000] 192.0.2.3 79a59df900b949e55d96a1e698fbacedfd6e09d98eacf8f8d5218e7cd47ef2be 3E57427F3EXAMPLE REST.GET.VERSIONING - "GET /mybucket?versioning HTTP/1.1" 200 - 113 - 7 - "-" "S3Console/0.4" - 79a59df900b949e55d96a1e698fbacedfd6e09d98eacf8f8d5218e7cd47ef2be mybucket [06/Feb/2014:00:00:38 +0000] 192.0.2.3 79a59df900b949e55d96a1e698fbacedfd6e09d98eacf8f8d5218e7cd47ef2be 891CE47D2EXAMPLE REST.GET.LOGGING_STATUS - "GET /mybucket?logging HTTP/1.1" 200 - 242 - 11 - "-" "S3Console/0.4" - 79a59df900b949e55d96a1e698fbacedfd6e09d98eacf8f8d5218e7cd47ef2be mybucket [06/Feb/2014:00:00:38 +0000] 192.0.2.3 79a59df900b949e55d96a1e698fbacedfd6e09d98eacf8f8d5218e7cd47ef2be A1206F460EXAMPLE REST.GET.BUCKETPOLICY - "GET /mybucket?policy HTTP/1.1" 404 NoSuchBucketPolicy 297 - 38 - "-" "S3Console/0.4" - 79a59df900b949e55d96a1e698fbacedfd6e09d98eacf8f8d5218e7cd47ef2be mybucket [06/Feb/2014:00:01:00 +0000] 192.0.2.3 79a59df900b949e55d96a1e698fbacedfd6e09d98eacf8f8d5218e7cd47ef2be 7B4A0FABBEXAMPLE REST.GET.VERSIONING - "GET /mybucket?versioning HTTP/1.1" 200 - 113 - 33 - "-" "S3Console/0.4" - 79a59df900b949e55d96a1e698fbacedfd6e09d98eacf8f8d5218e7cd47ef2be mybucket [06/Feb/2014:00:01:57 +0000] 192.0.2.3 79a59df900b949e55d96a1e698fbacedfd6e09d98eacf8f8d5218e7cd47ef2be DD6CC733AEXAMPLE REST.PUT.OBJECT s3-dg.pdf "PUT /mybucket/s3-dg.pdf HTTP/1.1" 200 - - 4406583 41754 28 "-" "S3Console/0.4" - 79a59df900b949e55d96a1e698fbacedfd6e09d98eacf8f8d5218e7cd47ef2be mybucket [06/Feb/2014:00:03:21 +0000] 192.0.2.3 79a59df900b949e55d96a1e698fbacedfd6e09d98eacf8f8d5218e7cd47ef2be BC3C074D0EXAMPLE REST.GET.VERSIONING - "GET /mybucket?versioning HTTP/1.1" 200 - 113 - 28 - "-" "S3Console/0.4" -

Sample Query

| parse "* * [*] * * * * * \"* HTTP/1.1\" * * * * * * * \"*\" *" as bucket_owner, bucket, time, remoteIP, requester, request_ID, operation, key, request_URI, status_code, error_code, bytes_sent, object_size, total_time, turn_time, referrer, user_agent, version_ID
| parse regex field=operation "[A-Z]+\.(?<operation>[\w.]+)"
| count by operation