Loki with BoltDB Shipper

OperationsStorageBoltDB Shipper

:warning: BoltDB Shipper is still an experimental feature. It is not recommended to be used in production environments.

BoltDB Shipper lets you run Loki without any dependency on NoSQL stores for storing index. It locally stores the index in BoltDB files instead and keeps shipping those files to a shared object store i.e the same object store which is being used for storing chunks. It also keeps syncing BoltDB files from shared object store to a configured local directory for getting index entries created by other services of same Loki cluster. This helps run Loki with one less dependency and also saves costs in storage since object stores are likely to be much cheaper compared to cost of a hosted NoSQL store or running a self hosted instance of Cassandra.

Note: BoltDB shipper works best with 24h periodic index files. It is a requirement to have index period set to 24h for either active or upcoming usage of boltdb-shipper. If boltdb-shipper already has created index files with 7 days period, and you want to retain previous data then just add a new schema config using boltdb-shipper with a future date and index files period set to 24h.

Example Configuration

Example configuration with GCS:

    - from: 2018-04-15
      store: boltdb-shipper
      object_store: gcs
      schema: v11
        prefix: loki_index_
        period: 24h

    bucket_name: GCS_BUCKET_NAME

    active_index_directory: /loki/index
    shared_store: gcs
    cache_location: /loki/boltdb-cache

This would run Loki with BoltDB Shipper storing BoltDB files locally at /loki/index and chunks at configured GCS_BUCKET_NAME. It would also keep shipping BoltDB files periodically to same configured bucket. It would also keep downloading BoltDB files from shared bucket uploaded by other ingesters to /loki/boltdb-cache folder locally.

Operational Details

Loki can be configured to run as just a single vertically scaled instance or as a cluster of horizontally scaled single binary(running all Loki services) instances or in micro-services mode running just one of the services in each instance. When it comes to reads and writes, Ingesters are the ones which writes the index and chunks to stores and Queriers are the ones which reads index and chunks from the store for serving requests.

Before we get into more details, it is important to understand how Loki manages index in stores. Loki shards index as per configured period which defaults to seven days i.e when it comes to table based stores like Bigtable/Cassandra/DynamoDB there would be separate table per week containing index for that week. In the case of BolDB Shipper, a table is defined by a collection of many smaller BoltDB files, each file storing just 15 mins worth of index. Tables created per day are identified by a configured prefix_ + <period-number-since-epoch>. Here <period-number-since-epoch> in case of boltdb-shipper would be day number since epoch. For example, if you have a prefix set to loki_index_ and a write request comes in on 20th April 2020, it would be stored in a table named loki_index_18372 because it has been 18371 days since the epoch, and we are in 18372th day. Since sharding of index creates multiple files when using BoltDB, BoltDB Shipper would create a folder per day and add files for that day in that folder and names those files after ingesters which created them.

To reduce the size of files which help with faster transfer speeds and reduced storage costs, they are stored after compressing them with gzip.

To show how BoltDB files in shared object store would look like, let us consider 2 ingesters named ingester-0 and ingester-1 running in a Loki cluster, and they both having shipped files for day 18371 and 18372 with prefix loki_index_, here is how the files would look like:

└── index
    ├── loki_index_18371
    │   ├── ingester-0-1587254400.gz
    │   └── ingester-1-1587255300.gz
    |   ...
    └── loki_index_18372
        ├── ingester-0-1587254400.gz
        └── ingester-1-1587254400.gz

Note: We also add a timestamp to names of the files to randomize the names to avoid overwriting files when running Ingesters with same name and not have a persistent storage. Timestamps not shown here for simplification.

Let us talk about more in depth about how both Ingesters and Queriers work when running them with BoltDB Shipper.


Ingesters keep writing the index to BoltDB files in active_index_directory and BoltDB Shipper keeps looking for new and updated files in that directory every 15 Minutes to upload them to the shared object store. When running Loki in clustered mode there could be multiple ingesters serving write requests hence each of them generating BoltDB files locally.

Note: To avoid any loss of index when Ingester crashes it is recommended to run Ingesters as statefulset(when using k8s) with a persistent storage for storing index files.

Another important detail to note is when chunks are flushed they are available for reads in object store instantly while index is not since we only upload them every 15 Minutes with BoltDB shipper. Ingesters expose a new RPC for letting Queriers query the Ingester’s local index for chunks which were recently flushed but its index might not be available yet with Queriers. For all the queries which require chunks to be read from the store, Queriers also query Ingesters over RPC for IDs of chunks which were recently flushed which is to avoid missing any logs from queries.


Queriers lazily loads BoltDB files from shared object store to configured cache_location. When a querier receives a read request, the query range from the request is resolved to period numbers and all the files for those period numbers are downloaded to cache_location, if not already. Once we have downloaded files for a period we keep looking for updates in shared object store and download them every 15 Minutes by default. Frequency for checking updates can be configured with resync_interval config.

To avoid keeping downloaded index files forever there is a ttl for them which defaults to 24 hours, which means if index files for a period are not used for 24 hours they would be removed from cache location. ttl can be configured using cache_ttl config.

Note: For better read performance and to avoid using node disk it is recommended to run Queriers as statefulset(when using k8s) with persistent storage for downloading and querying index files.

Write Deduplication disabled

Loki does write deduplication of chunks and index using Chunks and WriteDedupe cache respectively, configured with ChunkStoreConfig. The problem with write deduplication when using boltdb-shipper though is ingesters only keep uploading boltdb files periodically to make them available to all the other services which means there would be a brief period where some of the services would not have received updated index yet. The problem due to that is if an ingester which first wrote the chunks and index goes down and all the other ingesters which were part of replication scheme skipped writing those chunks and index due to deduplication, we would end up missing those logs from query responses since only the ingester which had the index went down. This problem would be faced even during rollouts which is quite common.

To avoid this, Loki disables deduplication of index when the replication factor is greater than 1 and boltdb-shipper is an active or upcoming index type. While using boltdb-shipper please avoid configuring WriteDedupe cache since it is used purely for the index deduplication, so it would not be used anyways.


Compactor is a BoltDB Shipper specific service that reduces the index size by deduping the index and merging all the files to a single file per table. We recommend running a Compactor since a single Ingester creates 96 files per day which include a lot of duplicate index entries and querying multiple files per table adds up the overall query latency.

Note: There should be only 1 compactor instance running at a time that otherwise could create problems and may lead to data loss.

Example compactor configuration with GCS:

  working_directory: /loki/compactor
  shared_store: gcs

    bucket_name: GCS_BUCKET_NAME