That is alright. I wanted to float the idea and get an agreement. I'll be
happy to implement it, if we see value in it.

On Sat, Jan 24, 2015 at 3:16 AM, Rainer Gerhards <[email protected]>
wrote:

> Sorry to be that blunt, but I simply have no time to participate in
> developing this. But I would be very open to merge any results.
>
> Rainer
>
> Sent from phone, thus brief.
> Am 23.01.2015 22:17 schrieb "singh.janmejay" <[email protected]>:
>
> > On Sat, Jan 24, 2015 at 2:19 AM, David Lang <[email protected]> wrote:
> >
> > > RELP is the network protocol you need for this sort of reliability.
> > > However, you would also need to not allow any message to be stored in
> > > memory (because it would be lost if rsyslog crashes or the system
> reboots
> > > unexpectedly). You would have to use disk queues (not disk assisted
> > queues)
> > > everywhere and do some other settings (checkpoint interval of 1 for
> > example)
> > >
> > > This would absolutly cripple your performance due to the disk I/O
> > > limitations. I did some testing of this a few years ago. I was using a
> > > high-end PCI SSD (a 160G card cost >$5K at the time) and depending on
> the
> > > filesystem I used, I could get rsyslog to receive between 2K and 8K
> > > messages/sec. The same hardware writing to a 7200rpm SATA drive with
> > memory
> > > buffering allowed could handle 380K messages/sec (the limiting factor
> was
> > > the Gig-E network)
> > >
> > > Doing this sort of reliability on a 15Krpm SAS drive would limit you to
> > > ~50 logs/sec. Modern SSDs would be able to do better, I would guess a
> few
> > > hundred logs/sec from a good drive, but you would be chewing through
> the
> > > drive lifetime several thousand times faster than if you were allowing
> > > memory buffering.
> > >
> > > Very few people have logs that are critical enough to warrent this sort
> > of
> > > performance degredation.
> > >
> >
> > I didn't particularly have disk-based queues in mind for reliability
> > reasons. However, messages may need to overflow to disk to manage bursts
> > (but only for burstability reasons). For a large-architecture for this
> > nature, its generally useful to classify failures in a broad way (rather
> > than very granular failure modes, that we identify for transactional
> > databases etc). The reason for this ties back to self-healing. Its easier
> > to build self-healing mechanisms assuming only one kind of failure, node
> > loss. It could happen for multiple reasons, but if we treat it that way,
> > all we have to do is build room for managing the cluster when 1 (or k)
> > nodes are lost.
> >
> > So thinking of it that way, a rsyslog crash, or a machine-crash or a disk
> > failure are all the same to me. They are just node loss (we may be able
> to
> > bring the node back with some offline procedure), but it'll come back as
> a
> > fresh machine with no state.
> >
> > Which is why I treat K-safety as a basic design parameter. If K nodes
> > disappear, data will be lost.
> >
> > With this kind of coarse-grained failure-mode, messages can easily be
> kept
> > in memory.
> >
> >
> > >
> > > In addition, this sort of reliability is saying that you would rather
> > have
> > > your applications freeze than have them do something and not have it
> > > logged. And that you are willing to have your application slow down to
> > the
> > > speed of the logging. Very few people are willing to do this.
> > >
> > >
> > >
> > > You are proposing doing the application ack across multiple hops
> instead
> > > of doing it hop-by-hop. This would avoid the problem that can happen
> with
> > > hop-by-hop acks where a machine that has acked a message then dies and
> > > needs to be recovered before the message can get delivered (assuming
> you
> > > have redundant storage and enough of the storage survives to be able to
> > be
> > > read, the message would eventually get through).
> > >
> > > But you now have the problem that the sender needs to know how many
> > > destinations the logs are going to. If you have any filters to decide
> > what
> > > to do with the logs, the sender needs to know if the log got lost, or
> if
> > a
> > > filter decided to not write the log. If the rules would deliver the
> logs
> > to
> > > multiple places, the sender will need to know how many places it's
> going
> > to
> > > be delivered to so that it can know how many different acks it's
> supposed
> > > to get back.
> > >
> >
> > So the design expects clusters to be broken in multiple tiers. Let us
> take
> > a 3 tier example.
> >
> > Say we have 100 machines, we break them into 3 tiers of 34, 33 and 33
> > machines.
> >
> > Assuming every producer wants at the most 2-safety, I can use 3 tiers to
> > build this design.
> >
> > So first producer discovers Tier-1 nodes, and hashes its session_id to
> pick
> > one of the 34 nodes, if it is not able to connect, it discards that node
> > from the collection(now we end up with 33 nodes in Tier-1) and hashes to
> a
> > different node (again a Tier-1 node, of-course).
> >
> > One it finds a node that it can connect to, it sends its session_id and
> > message-batch to it.
> >
> > The selected Tier-1 node now hashes the session_id and finds a Tier-2
> node
> > (it again discovers all Tier-2 nodes via external discovery mechanism).
> If
> > it fails to connect, it discards that node and hashes again to one of the
> > remaining 32 nodes, and so on.
> >
> > Eventually it reaches Tier-3, which is where ruleset has a clause which
> > checks for replica_number == 1, and handles the message differently. It
> is
> > handed over to an action which delivers it to the downstream system
> (which
> > may in-turn again be a syslog-cluster, or a datastore etc).
> >
> > So each node only has to worry about the next hop that it needs to
> deliver
> > to.
> >
> >
> > >
> > > These problems make it so that I don't see how you would reasonably
> > manage
> > > this sort of environment.
> > >
> > >
> > >
> > > I would suggest that you think hard about what your requirements really
> > > are.
> > >
> > > It may be that you are only sending to one place, in which case, you
> > > really want to just be inserting your messages into an ACID complient
> > > database.
> > >
> > > It may be that your requirements for absolute reliability are not quite
> > as
> > > severe as you are initially thinking that they are, and that you can
> then
> > > use the existing hop-by-hop reliability. Or they are even less severe
> and
> > > you can accept some amount of memory buffering to get a few orders of
> > > magnatude better performance from your logging. Remember that we are
> > > talking about performance differences of 10,000x on normal hardware. A
> > bit
> > > less, but still 100x or so on esoteric, high-end hardware.
> > >
> > >
> > Yep, I completely agree. In most cases extreme reliability such as this
> is
> > not required, and is best avoided for cost reasons.
> >
> > But for select applications it is lifesaver.
> >
> >
> > >
> > > I will also say that there are messaging systems that claim to have the
> > > properties that you are looking for (Flume for example), but almost
> > nobody
> > > operates them in their full reliability mode because of the performance
> > > issues. And they do not have the filtering and multiple destination
> > > capabilities that *syslog provides.
> > >
> >
> > Yes, Flume is one of the best options. But it comes with some unique
> > problems too (its not light-weight enough for running producer side +
> > managed-environment overhead (GC etc) cause their own set of problems).
> > There is also value in offering the same interface to producers for
> > ingestion into un-acked and reliable pipeline (because a lot of other
> > things, like integration with other systems can be reused). It also keeps
> > things simple because producers do all operations in one way, with one
> > tool, regardless of its ingestion mechanism being acked/replicated etc.
> >
> > Reliability in this case is built end-to-end, so building stronger
> > guarantees over-the-wire parts of the pipeline doesn't seem very valuable
> > to me. Why do you feel RELP will be necessary?
> >
> >
> > >
> > > David Lang
> > >
> > >
> > >
> > > On Sat, 24 Jan 2015, singh.janmejay wrote:
> > >
> > >  Date: Sat, 24 Jan 2015 01:48:18 +0530
> > >> From: singh.janmejay <[email protected]>
> > >> Reply-To: rsyslog-users <[email protected]>
> > >> To: rsyslog-users <[email protected]>
> > >> Subject: [rsyslog] [RFC: Ingestion Relay] End-to-end reliable
> > >> 'at-least-once'
> > >>     message delivery at large scale
> > >>
> > >>
> > >> Greetings,
> > >>
> > >> This is a proposal for new-feature, and im inviting thoughts.
> > >>
> > >> The aim is to use a set of rsyslog nodes(let us call it a cluster) to
> be
> > >> able to move messages reliably from source to destination.
> > >>
> > >> Let us make a few assumptions so we can define the expected properties
> > >> clearly.
> > >>
> > >>
> > >> Assumptions:
> > >>
> > >> - Data once successfully delivered to the Destination (typically a
> > >> datastore) is considered safe.
> > >> - Source-crashing with incomplete message hand-off to the cluster is
> > >> outside the scope of this. In such a case, source must retry.
> > >> - The cluster must be designed to support a maximum of K node failures
> > >> without any message loss
> > >>
> > >>
> > >> Here are the properties that may be desirable in such a service(the
> > >> cluster
> > >> is implementation of this service):
> > >>
> > >> - No message should ever be lost once handed over to the
> > delivery-network
> > >> except in a disaster scenario
> > >> - Disaster scenario is a condition where more than k nodes in the
> > cluster
> > >> fail
> > >> - Each source may pick a desirable value of k, where (k <= K)
> > >> - Any cluster nodes must re-transmit messages at a timeout T, if
> > >> downstream
> > >> fails to ACK it before the timeout.
> > >> - Such a cluster should ideally be composable, in the sense, user
> should
> > >> be
> > >> able to chain multiple such clusters.
> > >>
> > >>
> > >> This requires the cluster to support k-way replication of messages in
> > the
> > >> cluster.
> > >>
> > >> Implementation:
> > >>
> > >> High level:
> > >> - The cluster is divided in multiple tiers (let us call them
> > >> replication-tiers (or rep-tiers).
> > >> - The cluster can handle multiple sessions at a time.
> > >> - Session_ids are unique and are generated by producer system when
> they
> > >> start producing messages
> > >> - Within a session, we have a notion of sequence-number (or seq_no),
> > which
> > >> is a monotonically increasing number(incremented by 1 per message).
> This
> > >> requirement can possibly be relaxed for performance reasons, and gaps
> in
> > >> seq-id may be acceptable.
> > >> - Replication is basically managed by lower tiers sending data over to
> > >> higher tiers within the cluster, until replica-number (an attribute
> each
> > >> message carries, falls to 1)
> > >> - When replica-number falls to zero, we transmit message to desired
> > >> destination. (This can alternatively be done at the earliest
> > opportunity,
> > >> i.e. in Tier-1, under special-circumstances, but let us discuss that
> > later
> > >> if we find enough interest in doing so).
> > >> - There must be several nodes in each Tier, allocated to minimize
> > >> possibility of all of them going down at once (across availability
> > zones,
> > >> different chassis etc).
> > >> - There must be a mechanism which allows nodes from upstream system to
> > >> discover nodes of Tier-1 of the cluster, and Tier-1 nodes to discover
> > >> nodes
> > >> in Tier-2 of the cluster and so on. Hence nodes in Tier-K of the
> cluster
> > >> should be able to discover downstream nodes.
> > >> - Each session (or multiple sessions bundled according to arbitrary
> > logic,
> > >> such as hashing), must pick one node from each tier as
> > >> downstream-tier-node.
> > >> - Each node must maintain 2 watermarks:
> > >>    * Replicated till seq_no : till what sequence number have messages
> > been
> > >> k-way replicated in the cluster
> > >>    * Delivered till seq_no: till what sequence number have messages
> been
> > >> delivered to downstream system
> > >> - Each send-operation (i.e. transmission of messages) from upstream to
> > >> cluster's Tier-1 or from lower tier in cluster to higher tier in
> cluster
> > >> will pass messages such that highest seq_no of any message(per
> session)
> > in
> > >> transmitted batch is known
> > >> - Each receive-operation in cluster's Tier-1 or in upper-tiers within
> > >> cluster must respond/reply to transmitter with the two water-mark
> values
> > >> (i.e Replicated seq_no and Delivered seq_no) per session.
> > >> - Lower tiers (within the cluster) are free to discard messages all
> > >> message
> > >> with seq_no <= Delivered till seq_no
> > >> - Upstream system is free to discard all messages with seq_no <=
> > >> Replicated
> > >> till seq_no of cluster
> > >> - Upstream and downstream systems can be chained as instances of such
> > >> clusters if need be
> > >> - Maximum replication factor 'K' is dictated by cluster design (number
> > of
> > >> tiers)
> > >> - Desired replication factor 'k' is a per-message controllable
> attribute
> > >> (decided by the upstream)
> > >>
> > >> The sequence-diagrams below explain this visually:
> > >>
> > >> Here is a case with an upstream sending messages with k = K :​
> > >> ingestion_relay_1_max_replication.png
> > >> <https://docs.google.com/file/d/0B_XhUZLNFT4dN21TLTZBQjZMdUk/
> > >> edit?usp=drive_web>
> > >>
> > >> This is a case with k < K :​
> > >> ingestion_relay_2_low_replication.png
> > >> <https://docs.google.com/file/d/0B_XhUZLNFT4da1lKMnRKdU9JUkU/
> > >> edit?usp=drive_web>
> > >> ​
> > >> The above 2 cases show only one transmission going from upstream
> system
> > to
> > >> downstream system serially, this shows it pipelined :​
> > >> ingestion_relay_3_pipelining.png
> > >> <https://docs.google.com/file/d/0B_XhUZLNFT4dQUpTZGRDdVVXLVU/
> > >> edit?usp=drive_web>
> > >> ​
> > >> This demonstrates failure of a node in the cluster, and how it
> recovers
> > in
> > >> absence of continued transmission (it is recovered by timeout and
> > >> retransmission) :​
> > >> ingestion_relay_4_timeout_based_recovery.png
> > >> <https://docs.google.com/file/d/0B_XhUZLNFT4dMm5kUWtaTlVfV1U/
> > >> edit?usp=drive_web>
> > >> ​
> > >> This demonstrates failure of a node in the cluster, and how it
> recovers
> > >> due
> > >> to continued transmission :​
> > >> ingestion_relay_5_broken_transmission_based_recovery.png
> > >> <https://docs.google.com/file/d/0B_XhUZLNFT4dd3M0SXpUYjFXdlk/
> > >> edit?usp=drive_web>
> > >>
> > >> ​
> > >>
> > >> Rsyslog level implementation sketch:
> > >>
> > >> - Let us assume there is a way to identify the set of inputs, queues,
> > >> rulesets and actions that need to participate as reliable pipeline
> > >> components in a cluster node
> > >> - Each participating queue, will expect messages to contain a
> session-id
> > >> - Consumer bound to a queue will be expected to provide values for
> both
> > >> watermarks to per-session to dequeue more messages.
> > >> - Producer bound to a queue will be provided values for both
> watermarks
> > >> per-session as return value when en-queueing more messages.
> > >> - The inputs will transmit (either broadcast or unicast) both
> watermark
> > >> values to upstream actions (unicast is sent over relevant connections,
> > >> broadcast is sent across all connections) (please note this has
> nothing
> > to
> > >> do with network broadcast domains, as everything is over TCP).
> > >> - Actions will receive the two watermarks and push it back to the
> queue
> > >> action is bound to, in order to dequeue more messages
> > >> - Rulesets will need to pick the relevant actions value across
> multiple
> > >> action-queues according to user-provided configuration, and propagate
> it
> > >> backwards
> > >> - Action must have ability to set arbitrarily value for replica-number
> > >> when
> > >> passing it to downstream-system (so that chaining is possible).
> > >> - Inputs may produce the new value for replicated till seq_no when
> > >> receiving a message with replica_number == 1
> > >> - Action may produce the new value for delivered till seq_no after
> > having
> > >> successfully delivered a message with replica_number == 1
> > >>
> > >> Rsyslog configuration required(from user):
> > >>
> > >> - User will need to identify machines that are a part of cluster
> > >> - These machines will have to be divided in multiple replication tiers
> > (as
> > >> replication will happen only across machines in different tiers)
> > >> - User can pass message to the next cluster by setting replica_number
> > back
> > >> to a desired number and passing it to an action which writes it to one
> > of
> > >> the nodes in a downstream cluster
> > >> - User needs to check replica_number in the ruleset and take special
> > >> action
> > >> (to write it to downstream system) when replica_number == 1
> > >>
> > >>
> > >> Does this have any overlap with RELP?
> > >>
> > >> I haven't studied RELP in depth yet, but as far as I understand it, it
> > >> tries to solve the problem of delivering messages reliably between a
> > >> single-producer and a single-consumer losslessly (it targets different
> > >> kind
> > >> of loss scenarios specifically). In addition to this, its scope is
> > limited
> > >> to ensuring no messages are lost during transportation. In event of a
> > >> crash
> > >> of the receiver node before it can handle received message reliably,
> > some
> > >> messages may be lost. Someone with deeper knowledge of RELP should
> chime
> > >> in.
> > >>
> > >>
> > >>
> > >> Thoughts?
> > >>
> > >>
> > >>
> > >> --
> > >> Regards,
> > >> Janmejay
> > >> http://codehunk.wordpress.com
> > >> _______________________________________________
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> > >
> > >
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> >
> >
> >
> > --
> > Regards,
> > Janmejay
> > http://codehunk.wordpress.com
> > _______________________________________________
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-- 
Regards,
Janmejay
http://codehunk.wordpress.com
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