Scheduling and Retries

Calyptia Fluent Bit has an Engine that helps to coordinate the data ingestion from input plugins and calls the Scheduler to decide when it is time to flush the data through one or multiple output plugins. The Scheduler flushes new data at a fixed time of seconds and the Scheduler retries when asked.

Once an output plugin gets called to flush some data, after processing that data it can notify the Engine three possible return statuses:

• OK

• Retry

• Error

If the return status was OK, it means it was successfully able to process and flush the data. If it returned an Error status, it means that an unrecoverable error happened and the engine should not try to flush that data again. If a Retry was requested, the Engine will ask the Scheduler to retry to flush that data, the Scheduler will decide how many seconds to wait before that happens.

Configuring Wait Time for Retry

The Scheduler provides two configuration options called scheduler.cap and scheduler.base which can be set in the Service section.

Key	Description	Default Value
scheduler.cap	Set a maximum retry time in seconds. The property is supported from v1.8.7.	2000
scheduler.base	Set a base of exponential backoff. The property is supported from v1.8.7.	5

These two configuration options determine the waiting time before a retry will happen.

Calyptia Fluent Bit uses an exponential backoff and jitter algorithm to determine the waiting time before a retry.

The waiting time is a random number between a configurable upper and lower bound.

For the Nth retry, the lower bound of the random number will be:

base

The upper bound will be:

min(base * (Nth power of 2), cap)

Given an example where base is set to 3 and cap is set to 30.

1st retry: The lower bound will be 3, the upper bound will be 3 * 2 = 6. So the waiting time will be a random number between (3, 6).

2nd retry: the lower bound will be 3, the upper bound will be 3 * (2 * 2) = 12. So the waiting time will be a random number between (3, 12).

3rd retry: the lower bound will be 3, the upper bound will be 3 * (2 * 2 * 2) = 24. So the waiting time will be a random number between (3, 24).

4th retry: the lower bound will be 3, since 3 * (2 * 2 * 2 * 2) = 48 > 30, the upper bound will be 30. So the waiting time will be a random number between (3, 30).

Basically, the scheduler.base determines the lower bound of time between each retry and the scheduler.cap determines the upper bound.

For a detailed explanation of the exponential backoff and jitter algorithm, please check this blog.

Example

The following example configures the scheduler.base as 3 seconds and scheduler.cap as 30 seconds.

[SERVICE]
    Flush            5
    Daemon           off
    Log_Level        debug
    scheduler.base   3
    scheduler.cap    30

The waiting time will be:

Nth retry	waiting time range (seconds)
1	(3, 6)
2	(3, 12)
3	(3, 24)
4	(3, 30)

Configuring Retries

The Scheduler provides a simple configuration option called Retry_Limit, which can be set independently on each output section. This option allows us to disable retries or impose a limit to try N times and then discard the data after reaching that limit:

	Value	Description
Retry_Limit	N	Integer value to set the maximum number of retries allowed. N must be >= 1 (default: 1)
Retry_Limit	no_limits or False	When Retry_Limit is set to no_limits orFalse, means that there is not limit for the number of retries that the Scheduler can do.
Retry_Limit	no_retries	When Retry_Limit is set to no_retries, means that retries are disabled and Scheduler would not try to send data to the destination if it failed the first time.

Example

The following example configures two outputs where the HTTP plugin has an unlimited number of while the Elasticsearch plugin have a limit of 5 retries:

[OUTPUT]
    Name        http
    Host        192.168.5.6
    Port        8080
    Retry_Limit False

[OUTPUT]
    Name            es
    Host            192.168.5.20
    Port            9200
    Logstash_Format On
    Retry_Limit     5