S3 Archiving for LogScale Cloud

Permission Requirements

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.

Archiving works 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 admin user needs to set up archiving per repository. After selecting a repository on the LogScale front page, the configuration page is available under Settings.


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.


S3 archiving is not supported for S3 buckets where object locking is enabled.

For more information on segments files and datasources, see Ingest Flow and Data Sources

S3 Layout (LogScale Cloud)

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 browseable through the S3 management console.

LogScale uses the following pattern:


Read more about Event Tags.

LogScale Cloud Setup

Enabling LogScale Cloud to write to your S3 bucket means setting up AWS cross-account access.

  • In AWS:

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

    2. Click the name of the bucket where archived logs should be written.


      Please 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. Click Permissions

    4. Scroll down to the Access Contol Lists and click Edit

    5. Scroll down and click the Add Grantee button

    6. Enter the canonical ID for LogScale:

    7. Give the Grantee Read and Write access on the Bucket ACL.

    8. Additionally give it Write on the objects.

  • In LogScale:

    1. Go to the repository you want to archive and select SettingsS3 Archiving.

    2. Configure by giving the bucket name, region, and then Save.

S3 Archived Log Re-ingestion

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

This process has the following requirements:

  • The files will need to be downloaded from the S3 bucket to the machine running the LogScale 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 reingest logs this way:

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

  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 configration similar to this:

      token: b2XXXXXX-fd23-XXXX-98e9-1890e6XXXXXX
      ## Change the URL if needed to reflect your LogScale URL.
      url: https://cloud.us.humio.com
    #dataDirectory is only required in the case of local configurations and must not be used for remote configurations files.
    dataDirectory: data
        type: file
        # Glob patterns
        - /bucketdata/*.gz
        sink: my_humio_instance
        parser: json

    For more information, see Sources and Examples.

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

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


The default archiving format is NDJSON and optionally raw log lines. When using NDJSON, the parsed fields will be available along with the raw log line. This incurs some extra storage cost compared to using raw log lines but gives the benefit of ease of use when processing the logs in an external system.

Tag Grouping

If tag grouping is defined for a repository, the segment files will be split by each unique combination of tags present in a file. This results in a file in S3 per each unique combination of tags. The same layout pattern is used as in the normal case. The reason for doing this is to make it easier for a human operator to determine whether a log file is relevant.