S3 Archiving

Security Requirements and Controls

LogScale supports archiving ingested logs to Amazon S3. The archived logs are then available for further processing in any external system that integrates with S3. The files written by LogScale in this format are not searchable by LogScale — this is an export meant for other systems to consume.

When S3 Archiving is enabled all the events in repository are backfilled into S3 and then it archives new events by running a periodic job inside all LogScale nodes, which looks for new, unarchived segment files. The segment files are read from disk, streamed to an S3 bucket, and marked as archived in LogScale.

An administrator must set up archiving per repository. After selecting a repository on LogScale, the configuration page is available under Settings.

Note

For slow-moving datasources it can take some time before segment files are completed on disk and then made available for the archiving job. In the worst case, before a segment file is completed, it must contain a gigabyte of uncompressed data or 30 minutes must have passed. The exact thresholds are those configured as the limits on mini segments.

Important

LogScale supports archiving to S3 buckets where object locking is enabled.

For more information on segments files and datasources, see segment files and Datasources.

S3 Archiving Storage Format and Layout

When uploading a segment file, LogScale creates the S3 object key based on the tags, start date, and repository name of the segment file. The resulting object key makes the archived data browsable through the S3 management console.

LogScale uses the following pattern:

Where:

An example of this layout can be seen in the file list below:

Read more about .

File Format

LogScale supports two formats for storage: native format and NDJSON.

Each record includes the full detail for each event, including parsed fields, the original raw event string, and tagged field entries.

How Data is Uploaded to S3

Data is uploaded to S3 as soon as a segment file has been created during ingest (for more information, see Ingestion: Digest Phase).

Each segment file is sent as as multipart upload, so the upload of a single file may require multiple S3 requests. The exact number of requests will depend on rate of ingest, but expect a rate of one request for each 8MB of ingested data.

Setup S3 archiving with IAM role

Note

From version 1.177 it is only possible to perform S3 archiving using roles in AWS. Any previous S3 archiving set up to a user will continue to work as expected, but you cannot create new S3 archiving from repositories in LogScale.

Configuring S3 archiving with the IAM role requires that the role has PutObject (write) permissions to the bucket. So in the diagram below, the AWS IAM User has the AWS IAM Role which has PutObject (write) permissions for the S3 bucket.

In LogScale:

  1. Create a repository for the archiving data. For information about how to create a repository, see Creating a Repository or View.

  2. Open the repository you created and click Settings. Click S3 archiving.

In AWS:

  1. Log in to the AWS console and navigate to your S3 service page.

  2. Create a new bucket. Follow the instructions on the AWS docs on naming conventions. In particular, using dashes not periods as a separator, and ensuring you do not repeat dashes and dots.

  3. Navigate to IAM and click Roles.

  4. Create a new role and select Custom trust policy. Copy and paste the trust policy below. You will customize it in the next steps.

    JSON
    {
  "Version": "2012-10-17",
  "Statement": [
      {
          "Sid": "AllowLogScaleS3Archiving",
          "Effect": "Allow",
          "Principal": {
              "AWS": "arn:aws:iam::123456789012:user/LogScaleS3Archiving"
          },
          "Action": "sts:AssumeRole",
          "Condition": {
              "StringEquals": {
                  "sts:ExternalId": "2ph55aGUve1rxxLv9B4CFnnb/ItCOD9MHBBsna9KBiFFPahzq"
              }
          }
      }
  ]
}

  5. Go to LogScale and in the S3 archiving page for your repository, copy the IAM identity. Switch to AWS and paste it into the AWS field in your trust policy. Do the same for the External ID. Then click Next in AWS.

  6. Click Next to skip creating a policy for now.

  7. Enter a name for the role. Click Create Role.

  8. Search for the role you created and open it. Click the Add Permission button and choose Create inline policy.

  9. Switch the policy editor in AWS to use JSON and copy and paste the below into the policy editor. You will customize it in the next steps.

    JSON
    {
  "Version": "2012-10-17",
  "Statement": [
      {
          "Sid": "AllowWriteToBucket",
          "Effect": "Allow",
          "Resource": "arn:aws:s3:::MyLogScaleS3ArchivingBucket/*",
          "Action": "s3:PutObject"
      }
  ]
}

  10. In the pasted text, change the bucket name MyLogScaleS3ArchivingBucket/* to match the name of the bucket you created in Create new bucket. Be sure that the /* is preserved.

  11. Enter a name for the policy and click Create Policy.

  12. Locate the ARN on the role in AWS and copy it.

  13. Go to LogScale and in the S3 archiving page for your repository, paste the ARN you copied into Role ARN. Enter the bucket name and region. Click Submit.

Troubleshoot S3 archiving configuration

If you encounter an access denied error message when configuring S3 archiving, check your configuration settings for missing information or typos.

Tag Grouping

From version 1.169, if tag grouping is applied for a repository, the archiving logic will upload one segment into one S3 file, even though the tag grouping makes each segment possibly contain multiple unique combinations of tags. The TAG_VALUE part of the S3 file name that corresponds to a tag with tag grouping will not contain any of the specific values for the tag in that segment, but will instead contain an internal value that denotes which tag group the segment belongs to. This is less human readable than splitting out a segment into a number of S3 files corresponding to each unique tag combination in the segment, but avoids the risk of a single segment being split into an unmanageable amount of S3 files.

S3 archived log re-ingestion

You can re-ingest log data that has been written to an S3 bucket through S3 archiving by using Log Collector and the native JSON parsing within LogScale.

This process has the following requirements:

  • The files need to be downloaded from the S3 bucket to the machine running the Log Collector. The S3 files cannot be accessed natively by the Log Collector.

  • The ingested events will be ingested into the repository that is created for the purpose of receiving the data.

To re-ingest logs:

  1. Create a repo in LogScale where the ingested data will be stored. See Creating a Repository or View.

  2. Create an ingest token, and choose the JSON parser. See Assigning Parsers to Ingest Tokens.

  3. Install the Falcon LogScale Collector to read from a file using the .gz extension as the file match. For example, using a configuration similar to this:

    yaml
    #dataDirectory is only required in the case of local configurations and must not be used for remote configurations files.
dataDirectory: data
sources:
bucketdata:
  type: file
  # Glob patterns
  include:
  - /bucketdata/*.gz
  sink: my_humio_instance
  parser: json
  ...

    For more information, see Sources & Examples.

  4. Copy the log file from the S3 bucket into the configured directory (/bucketdata) in the above example.

The Log Collector reads the file that has been copied, sends it to LogScale, where the JSON event data will be parsed and recreated.