Redis integration

Redis is core to Skyline, it is used to store and query time series data and to store and its own internal data.

Skyline stores time series data for traditional metrics in msgpack in Redis keys. labelled metrics - Skyline utilises the RedisTimeseries module to store time series for key/value style labelled metrics.

If you wish to process labelled metrics, there is a minimum requirement of Redis server 6.2.x if you wish to load the module, or a requirement of redis-stack-server 6.2.x with loaded.

Redis Security

First please take the time to read and understand Redis security as described at

It is important that you understand factors relating to the default Redis security model. UPDATE the default security model in Redis has changed quite significantly and it is no longer insecure by default but rather the opposite.


With the introduction of rebrow and Luminosity it is very important that Redis and your environment are configured correctly in terms of securing Redis and access to Redis. Please ensure that you implement the recommendations described on security page and the Redis related Skyline recommendations described on the installations page in this documentation and

Types of Skyline and Redis implementations

There are two different types of Skyline implementations:

  • A single Skyline instance, Redis only needs to bind to

  • Multiple Skyline instances running in a distributed fashion Redis still only need to bind to and each Skyline node in the cluster accesses the required shared Redis data via specific API calls through webapp. See `Running multiple Skyline instances<running-multiple-skylines.html>`__

How are time series stored in Redis?

Part of the Horizon service’s job is to input data into Redis. Skyline uses MessagePack to store data in Redis. When a data point comes in, a Horizon worker will pack the data point with the schema [timestamp, value] into a MessagePack-encoded binary string and make a redis.append() call to append this string to the appropriate metric key. This way, Horizon can very easily make many updates to Redis at once, and this is how Skyline is able to support a very large firehose of metrics.

One downside to this scheme is that once time series in Redis start to get very long, Redis’ performance suffers. Redis was not designed to contain very large strings. We may one day switch to an alternative storage design as proposed by Antirez - see - but for now, this is how it is. And given that the last update to that repo was in 10 Oct 2012, it is highly probable that normal Redis will be used for the forseenable future. UPDATE the future is here.

Using the default settings.FULL_DURATION of 86400 (24 hours) ensures that Redis does not hit performance issues in most cases. Now where Skyline needs greater than settings.FULL_DURATION data to analyse in Mirage and Ionosphere, Skyline fetches that data from Graphite or VictoriaMetrics directly when required. This overcomes any Redis performance issues and the use of Graphite data removes the limitation of Skyline only being able to analyse data and be useful in the 24 hour time window.

What other data are stored in Redis?

In addition to all the metrics, there are a number of specialized Redis sets and keys which Skyline uses for metric management and fast querying, e.g. what is the id of this metrics? Skyline periodically calculates:

  • metrics.unique_metrics and mini.unique_metrics These contain every key that exists in Redis, and they are used by the Analyzer to make it easier for the Analyzer to know what to mget from Redis (as opposed to doing a very expensive keys * query)

  • analyzer.boring - a set of all metrics deemed Boring by Analyzer

  • analyzer.stale - a set of all metrics deemed Stale by Analyzer

  • analyzer.too_short - a set of all metrics deemed TooShort by Analyzer

  • derivative_metrics - a set of all metrics that have been defined as metrics to analyse as derivatives by Analyzer.

  • non_derivative_metrics - a set of all metrics that have been defined as to opposite of derivative_metrics by Analyzer.

  • - a set of metric anomalies with details that require learning.

  • ionosphere.training_data.* keys containing anomalies that need to be learnt e.g. [['metric_timestamp', 1526755861], ['base_name', 'carbon.relays.graphite-a.metricsReceived'], ['timeseries_dir', 'carbon/relays/graphite-a/metricsReceived'], ['added_by', 'analyzer']]

  • ionosphere.unique_metrics set

  • <skyline_app>.last_alert.<alerter>.<metric> keys

  • panorama.mysql_ids.* keys

  • rebrow.client.key.* keys - expiring rebrow Redis password JWT encoded tokens

  • etc, etc, feel free to browse Redis with rebrow and take a look.

What’s with the ‘mini’ and ‘metrics’ namespaces?

The ‘mini’ namespace is used by the Webapp to display a settings.MINI_DURATION seconds long view.