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90 lines
4.3 KiB
90 lines
4.3 KiB
2010/01/24 - Design of multi-criteria request rate shaping.
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We want to be able to rate-shape traffic on multiple cirteria. For instance, we
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may want to support shaping of per-host header requests, as well as per source.
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In order to achieve this, we will use checkpoints, one per criterion. Each of
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these checkpoints will consist in a test, a rate counter and a queue.
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A request reaches the checkpoint and checks the counter. If the counter is
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below the limit, it is updated and the request continues. If the limit is
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reached, the request attaches itself into the queue and sleeps. The sleep time
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is computed from the queue status, and updates the queue status.
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A task is dedicated to each queue. Its sole purpose is to be woken up when the
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next task may wake up, to check the frequency counter, wake as many requests as
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possible and update the counter. All the woken up requests are detached from
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the queue. Maybe the task dedicated to the queue can be avoided and replaced
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with all queued tasks's sleep counters, though this looks tricky. Or maybe it's
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just the first request in the queue that should be responsible for waking up
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other tasks, and not to forget to pass on this responsibility to next tasks if
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it leaves the queue.
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The woken up request then goes on evaluating other criteria and possibly sleeps
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again on another one. In the end, the task will have waited the amount of time
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required to pass all checkpoints, and all checkpoints will be able to maintain
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a permanent load of exactly their limit if enough streams flow through them.
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Since a request can only sleep in one queue at a time, it makes sense to use a
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linked list element in each session to attach it to any queue. It could very
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well be shared with the pendconn hooks which could then be part of the session.
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This mechanism could be used to rate-shape sessions and requests per backend
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and per server.
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When rate-shaping on dynamic criteria, such as the source IP address, we have
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to first extract the data pattern, then look it up in a table very similar to
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the stickiness tables, but with a frequency counter. At the checkpoint, the
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pattern is looked up, the entry created or refreshed, and the frequency counter
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updated and checked. Then the request either goes on or sleeps as described
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above, but if it sleeps, it's still in the checkpoint's queue, but with a date
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computed from the criterion's status.
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This means that we need 3 distinct features :
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- optional pattern extraction
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- per-pattern or per-queue frequency counter
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- time-ordered queue with a task
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Based on past experiences with frequency counters, it does not appear very easy
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to exactly compute sleep delays in advance for multiple requests. So most
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likely we'll have to run per-criterion queues too, with only the head of the
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queue holding a wake-up timeout.
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This finally leads us to the following :
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- optional pattern extraction
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- per-pattern or per-queue frequency counter
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- per-frequency counter queue
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- head of the queue serves as a global queue timer.
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This brings us to a very flexible architecture :
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- 1 list of rule-based checkpoints per frontend
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- 1 list of rule-based checkpoints per backend
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- 1 list of rule-based checkpoints per server
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Each of these lists have a lot of rules conditioned by ACLs, just like the
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use-backend rules, except that all rules are evaluated in turn.
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Since we might sometimes just want to enable that without setting any limit and
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just for enabling control in ACLs (or logging ?), we should probably try to
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find a flexible way of declaring just a counter without a queue.
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These checkpoints could be of two types :
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- rate-limit (described here)
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- concurrency-limit (very similar with the counter and no timer). This
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feature would require to keep track of all accounted criteria in a
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request so that they can be released upon request completion.
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It should be possible to define a max of requests in the queue, above which a
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503 is returned. The same applies for the max delay in the queue. We could have
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it per-task (currently it's the connection timeout) and abort tasks with a 503
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when the delay is exceeded.
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Per-server connection concurrency could be converted to use this mechanism
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which is very similar.
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The construct should be flexible enough so that the counters may be checked
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from ACLs. That would allow to reject connections or switch to an alternate
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backend when some limits are reached.
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