Warning! This page documents an old version of InfluxDB, which is no longer actively developed. InfluxDB v1.3 is the most recent stable version of InfluxDB.
Here’s a sample configuration file. Comments in the file explain the options.
# Welcome to the InfluxDB configuration file. # If hostname (on the OS) doesn't return a name that can be resolved by the other # systems in the cluster, you'll have to set the hostname to an IP or something # that can be resolved here. # hostname = "" bind-address = "0.0.0.0" # Once every 24 hours InfluxDB will report usage data to m.influxdb.com # The data includes raft name (random 8 bytes), os, arch and version # This is only used to track the number of instances running and # the versions which is very helpful for us. # Change this option to true to disable reporting. reporting-disabled = false [logging] # logging level can be one of "debug", "info", "warn" or "error" level = "info" file = "influxdb.log" # stdout to log to standard out # Configure the admin server [admin] port = 8083 # binding is disabled if the port isn't set assets = "./admin" # Configure the http api [api] port = 8086 # binding is disabled if the port isn't set # ssl-port = 8084 # SSL support is enabled if you set a port and cert # ssl-cert = "/path/to/cert.pem" # connections will timeout after this amount of time. Ensures that clients that misbehave # and keep alive connections they don't use won't end up connection a million times. # However, if a request is taking longer than this to complete, could be a problem. read-timeout = "5s" [input_plugins] # Configure the graphite api [input_plugins.graphite] enabled = false # port = 2003 # database = "" # store graphite data in this database # Raft configuration [raft] # The raft port should be open between all servers in a cluster. # However, this port shouldn't be accessible from the internet. port = 8090 # Where the raft logs are stored. The user running InfluxDB will need read/write access. dir = "/tmp/influxdb/development/raft" # election-timeout = "1s" [storage] dir = "/tmp/influxdb/development/db" # How many requests to potentially buffer in memory. If the buffer gets filled then writes # will still be logged and once the local storage has caught up (or compacted) the writes # will be replayed from the WAL write-buffer-size = 10000 [cluster] # A comma separated list of servers to seed # this server. this is only relevant when the # server is joining a new cluster. Otherwise # the server will use the list of known servers # prior to shutting down. Any server can be pointed to # as a seed. It will find the Raft leader automatically. # Here's an example. Note that the port on the host is the same as the raft port. # seed-servers = ["hosta:8090","hostb:8090"] # Replication happens over a TCP connection with a Protobuf protocol. # This port should be reachable between all servers in a cluster. # However, this port shouldn't be accessible from the internet. protobuf_port = 8099 protobuf_timeout = "2s" # the write timeout on the protobuf conn any duration parseable by time.ParseDuration protobuf_heartbeat = "200ms" # the heartbeat interval between the servers. must be parseable by time.ParseDuration protobuf_min_backoff = "1s" # the minimum backoff after a failed heartbeat attempt protobuf_max_backoff = "10s" # the maximum backoff after a failed heartbeat attempt # How many write requests to potentially buffer in memory per server. If the buffer gets filled then writes # will still be logged and once the server has caught up (or come back online) the writes # will be replayed from the WAL write-buffer-size = 10000 # the maximum number of responses to buffer from remote nodes, if the # expected number of responses exceed this number then querying will # happen sequentially and the buffer size will be limited to this # number max-response-buffer-size = 100000 # When queries get distributed out to shards, they go in parallel. This means that results can get buffered # in memory since results will come in any order, but have to be processed in the correct time order. # Setting this higher will give better performance, but you'll need more memory. Setting this to 1 will ensure # that you don't need to buffer in memory, but you won't get the best performance. concurrent-shard-query-limit = 10 [leveldb] # Maximum mmap open files, this will affect the virtual memory used by # the process max-open-files = 40 # LRU cache size, LRU is used by leveldb to store contents of the # uncompressed sstables. You can use `m` or `g` prefix for megabytes # and gigabytes, respectively. lru-cache-size = "200m" # The default setting on this is 0, which means unlimited. Set this to something if you want to # limit the max number of open files. max-open-files is per shard so this * that will be max. max-open-shards = 0 # The default setting is 100. This option tells how many points will be fetched from LevelDb before # they get flushed into backend. point-batch-size = 100 # These options specify how data is sharded across the cluster. There are two # shard configurations that have the same knobs: short term and long term. # Any series that begins with a capital letter like Exceptions will be written # into the long term storage. Any series beginning with a lower case letter # like exceptions will be written into short term. The idea being that you # can write high precision data into short term and drop it after a couple # of days. Meanwhile, continuous queries can run downsampling on the short term # data and write into the long term area. [sharding] # how many servers in the cluster should have a copy of each shard. # this will give you high availability and scalability on queries replication-factor = 1 [sharding.short-term] # each shard will have this period of time. Note that it's best to have # group by time() intervals on all queries be < than this setting. If they are # then the aggregate is calculated locally. Otherwise, all that data gets sent # over the network when doing a query. duration = "7d" # split will determine how many shards to split each duration into. For example, # if we created a shard for 2014-02-10 and split was set to 2. Then two shards # would be created that have the data for 2014-02-10. By default, data will # be split into those two shards deterministically by hashing the (database, series) # tuple. That means that data for a given series will be written to a single shard # making querying efficient. That can be overridden with the next option. split = 1 # You can override the split behavior to have the data for series that match a # given regex be randomly distributed across the shards for a given interval. # You can use this if you have a hot spot for a given time series writing more # data than a single server can handle. Most people won't have to resort to this # option. Also note that using this option means that queries will have to send # all data over the network so they won't be as efficient. # split-random = "/^hf.*/" [sharding.long-term] duration = "30d" split = 1 # split-random = "/^Hf.*/" [wal] dir = "/tmp/influxdb/development/wal" flush-after = 1000 # the number of writes after which wal will be flushed, 0 for flushing on every write bookmark-after = 1000 # the number of writes after which a bookmark will be created # the number of writes after which an index entry is created pointing # to the offset of the first request, default to 1k index-after = 1000 # the number of requests per one log file, if new requests came in a # new log file will be created requests-per-logfile = 10000