Thanks Dominic for the details. It seems like an operator has to choose between “do I hurt performance(low timeout) or do I hurt the SLA” ?
If this is the trade off , isn’t this a hard choice to make ? So I’m wondering whether some alternative designs could be used for this problem. The key decision here is: should OW be given a cluster wide power to view and control the resources or not. IIUC the current proposal doesn’t support this? I’m not saying the proposed model is not good; I’d just feel more comfortable if OW would allow more options instead of one, in the same way the JVM allows multiple GC implementations. In the proposed model the GC would offload the decision to each container, while other implementations may do it differently. For instance, I’d implement something dynamic that adapts the timeout to the load, and maybe try some predictive ML algorithms to manage resources - if a model suggests that out of 3 actions that could be removed, 1 has a higher probability to be invoked again, wouldn’t it be more efficient to remove one of the other 2 ? Such a logic can only be achieved through an entity with a cluster wide view, as actions don’t know about each other, to negotiate a dynamic timeout. - dragos On Wed, Apr 10, 2019 at 3:46 AM Dominic Kim <style9...@gmail.com> wrote: > Dear Dascalita > > That depends on the timeout configuration. > For example, if you need something similar to the one in the current code > base, you can just configure the timeout to a small enough value, such as > 50ms. > > The idea behind the longer timeout is, it shows better performance when > there are highly likely subsequent requests. > For example, it takes about 100ms ~ 1s to create a new coldstart container. > If the action execution takes 10ms, it should wait 10 to 100 times more for > a new container. > In this case, it is reasonable to wait for the previous execution and reuse > the existing container rather than creating a new container. > So 100ms ~ 1s could be good options for the timeout value. > (Under heavy loads, I even observed it took 2s ~ 5s to create a coldstart > container.) > And this implies some changes in the notion of resources. > > In the cluster, there would be a different kind of requests. > There would be both batch and real-time invocation. > So I think this is a tradeoff. > Longer timeout will increase the reuse rate of containers but idle > containers will possess resources longer. > > And even in the current implementation, subsequent invocation should wait > for some time to remove existing(warmed containers) and create a new cold > start container. > As I said, it could take up to few seconds under heavy loads. > With reasonable timeout value, there would be no big performance difference > in the above situation. > (Actually, I expect new scheduler would outperform even with 5~10s timeout > value as it will evenly distribute docker operation. > In the current implementation, all execution is sent to the home invoker > first and it could make the situation worse in edge cases. > I hope I can share performance comparison results as I am doing > benchmarking.) > > Also, I think the above case is an edge case that someone is consuming most > of the cluster resources and executing two different batch invocation > alternatively. > Anyway, we can support such an edge case with some shutdown period. > This can be controversial, but I believe this is a viable option. > > > If you said that in the view of OpenWhisk operator, I think you meant there > are more than 1 heavy users. > Let's say, one user has 60 containers limit and the other has 80 containers > limit. > Then can we guarantee both users' execution without any issue in current > implementation? > If their invocation requests come together, one or both of their invocation > will be heavily delayed. > > So I think when we(operators) notice there are such heavy users, we should > scale out our clusters to guarantee their invocation or we should reduce > their resource limit. > This is also a tradeoff. If we must guarantee their invocation, we at least > need a bigger cluster than the sum of their throttling limit. > If we have weak SLA, we can support both users with smaller cluster though > their invocation can be delayed a bit. > > > In short, if you prefer the current behavior you can still have a similar > effect by configuring the timeout as 50ms. > (So containers will only wait for 50ms, though it may induce some > performance degradation in other cases.) > > Best regards > Dominic > > > 2019년 4월 10일 (수) 오전 1:36, Dascalita Dragos <ddrag...@gmail.com>님이 작성: > > > "...When there is no more activation message, ContainerProxy will be wait > > for the given time(configurable) and just stop...." > > > > How does the system allocate and de-allocate resources when it's > congested > > ? > > I'm thinking at the use case where the system receives a batch of > > activations that require 60% of all cluster resources. Once those > > activations finish, a different batch of activations are received, and > this > > time the new batch requires new actions to be cold-started; these new > > activations require a total of 80% of the overall cluster resources. > Unless > > the previous actions are removed, the cluster is over-allocated. In the > > current model would the cluster process 1/2 of the new activations b/c it > > needs to wait for the previous actions to stop by themselves ? > > > > On Sun, Apr 7, 2019 at 7:34 PM Dominic Kim <style9...@gmail.com> wrote: > > > > > Hi Mingyu > > > > > > Thank you for the good questions. > > > > > > Before answering to your question, I will share the Lease in ETCD > first. > > > ETCD has a data model which is disappear after given time if there is > no > > > relevant keepalive on it, the Lease. > > > > > > So once you grant a new lease, you can put it with data in each > operation > > > such as put, putTxn(transaction), etc. > > > If there is no keep-alive for the given(configurable) time, inserted > data > > > will be gone. > > > > > > In my proposal, most of data in ETCD rely on a lease. > > > For example, each scheduler stores their endpoint information(for queue > > > creation) with a lease. Each queue stores their information(for > > activation) > > > in ETCD with a lease. > > > (It is overhead to do keep-alive in each memory queue separately, I > > > introduced EtcdKeepAliveService to share one global lease among all > > queues > > > in a same scheduler.) > > > Each ContainerProxy store their information in ETCD with a lease so > that > > > when a queue tries to create a container, they can easily count the > > number > > > of existing containers with "Count" API. > > > Both data are stored with a lease, if one scheduler or invoker are > > failed, > > > keep-alive for the given lease is not continued, and finally those data > > > will be removed. > > > > > > Follower queues are watching on the leader queue information. If there > > are > > > any changes,(the data will be removed upon scheduler failure) they can > > > receive the notification and start new leader election. > > > When a scheduler is failed, ContainerProxys which were communicating > > with a > > > queue in that scheduler, will receive a connection error. > > > Then they are designed to access to the ETCD again to figure out the > > > endpoint of the leader queue. > > > As one of followers becomes a new leader, ContainerProxys can connect > to > > > the new leader. > > > > > > One thing to note here is, there is only one QueueManager in each > > > scheduler. > > > One QueueManager holds all queues and delegate requests to the proper > > queue > > > in respond to "fetch" requests. > > > > > > In short, all endpoints data are stored in ETCD and they are renewed > > based > > > on keep-alive and lease. > > > Each components are designed to access ETCD when the failure detected > and > > > connect to a new(failed-over) scheduler. > > > > > > I hope it is useful to you. > > > And I think when I and my colleagues open PRs, we need to add more > detail > > > design along with them. > > > > > > If you have any further questions, kindly let me know. > > > > > > Thanks > > > Best regards > > > Dominic > > > > > > > > > > > > 2019년 4월 6일 (토) 오전 11:28, Mingyu Zhou <zhoum...@gmail.com>님이 작성: > > > > > > > Dear Dominic, > > > > > > > > Thanks for your proposal. It is very inspirational and it looks > > > promising. > > > > > > > > I'd like to ask some questions about the fall over/failure recovery > > > > mechanism of the scheduler component. > > > > > > > > IIUC, a scheduler instance hosts multiple queue managers. If a > > scheduler > > > is > > > > down, we will lose multiple queue managers. Thus, there should be > some > > > form > > > > of failure recovery of queue managers and it raises the following > > > > questions: > > > > > > > > 1. In your proposal, how the failure of a scheduler is detected? > I.e., > > > > when a scheduler instance is down and some queue manager become > > > > unreachable, which component will be aware of this unavailability and > > > then > > > > trigger the recovery procedure? > > > > > > > > 2. How should the failure be recovered and lost queue managers be > > brought > > > > back to life? Specifically, in your proposal, you designed a hot > > > > standing-by pairing of queue managers (one leader/two followers). > Then > > > how > > > > should the new leader be selected in face of scheduler crash? And do > we > > > > need to allocate a new queue manager to maintain the > > > > one-leader-two-follower configuration? > > > > > > > > 3. How will the other components in the system learn the new > > > configuration > > > > after a fall over? For example, how will the pool balancer discover > the > > > new > > > > state of the scheduler it managers and change its policy to > distribute > > > > queue creation requests? > > > > > > > > Thanks > > > > Mingyu Zhou > > > > > > > > On Fri, Apr 5, 2019 at 2:56 PM Dominic Kim <style9...@gmail.com> > > wrote: > > > > > > > > > Dear David, Matt, and Dascalita. > > > > > Thank you for your interest in my proposal. > > > > > > > > > > Let me answer your questions one by one. > > > > > > > > > > @David > > > > > Yes, I will(and actually already did) implement all components > based > > on > > > > > SPI. > > > > > The reason why I said "breaking changes" is, my proposal will > affect > > > most > > > > > of components drastically. > > > > > For example, InvokerReactive will become a SPI and current > > > > InvokerReactive > > > > > will become one of its concrete implementation. > > > > > My load balancer and throttler are also based on the current SPI. > > > > > So though my implementation would be included in OpenWhisk, > > downstreams > > > > > still can take advantage of existing implementation such as > > > > > ShardingPoolBalancer. > > > > > > > > > > Regarding Leader/Follower, a fair point. > > > > > The reason why I introduced such a model is to prepare for the > future > > > > > enhancement. > > > > > Actually, I reached a conclusion that memory based activation > passing > > > > would > > > > > be enough for OpenWhisk in terms of message persistence. > > > > > But it is just my own opinion and community may want more rigid > level > > > of > > > > > persistence. > > > > > I naively thought we can add replication and HA logic in the queue > > > which > > > > > are similar to the one in Kafka. > > > > > And Leader/Follower would be a good base building block for this. > > > > > > > > > > Currently only a leader fetch activation messages from Kafka. > > Followers > > > > > will be idle while watching the leadership change. > > > > > Once the leadership is changed, one of followers will become a new > > > leader > > > > > and at that time, Kafka consumer for the new leader will be > created. > > > > > This is to minimize the failure handling time in the aspect of > > clients > > > as > > > > > you mentioned. It is also correct that this flow does not prevent > > > > > activation messages lost on scheduler failure. > > > > > But it's not that complex as activation messages are not replicated > > to > > > > > followers and the number of followers are configurable. > > > > > If we want, we can configure the number of required queue to 1, > there > > > > will > > > > > be only one leader queue. > > > > > (If we ok with the current level of persistence, I think we may not > > > need > > > > > more than 1 queue as you said.) > > > > > > > > > > Regarding pulling activation messages, each action will have its > own > > > > Kafka > > > > > topic. > > > > > It is same with what I proposed in my previous proposals. > > > > > When an action is created, a Kafka topic for the action will be > > > created. > > > > > So each leader queue(consumer) will fetch activation messages from > > its > > > > own > > > > > Kafka topic and there would be no intervention among actions. > > > > > > > > > > When I and my colleagues open PRs for each component, we will add > > > detail > > > > > component design. > > > > > It would help you guys understand the proposal more. > > > > > > > > > > @Matt > > > > > Thank you for the suggestion. > > > > > If I change the name of it now, it would break the link in this > > thread. > > > > > I would use the name you suggested when I open a PR. > > > > > > > > > > > > > > > @Dascalita > > > > > > > > > > Interesting idea. > > > > > Any GC patterns do you keep in your mind to apply in OpenWhisk? > > > > > > > > > > In my proposal, the container GC is similar to what OpenWhisk does > > > these > > > > > days. > > > > > Each container will autonomously fetch activations from the queue. > > > > > Whenever they finish invocation of one activation, they will fetch > > the > > > > next > > > > > request and invoke it. > > > > > In this sense, we can maximize the container reuse. > > > > > > > > > > When there is no more activation message, ContainerProxy will be > wait > > > for > > > > > the given time(configurable) and just stop. > > > > > One difference is containers are no more paused, they are just > > removed. > > > > > Instead of pausing them, containers are waiting for subsequent > > requests > > > > for > > > > > longer time(5~10s) than current implementation. > > > > > This is because pausing is also relatively expensive operation in > > > > > comparison to short-running invocation. > > > > > > > > > > Container lifecycle is managed in this way. > > > > > 1. When a container is created, it will add its information in > ETCD. > > > > > 2. A queue will count the existing number of containers using above > > > > > information. > > > > > 3. Under heavy loads, the queue will request more containers if the > > > > number > > > > > of existing containers is less than its resource limit. > > > > > 4. When the container is removed, it will delete its information in > > > ETCD. > > > > > > > > > > > > > > > Again, I really appreciate all your feedbacks and questions. > > > > > If you have any further questions, kindly let me know. > > > > > > > > > > Best regards > > > > > Dominic > > > > > > > > > > > > > > > > > > > > 2019년 4월 5일 (금) 오전 1:24, Dascalita Dragos <ddrag...@gmail.com>님이 > 작성: > > > > > > > > > > > Hi Dominic, > > > > > > Thanks for sharing your ideas. IIUC (and pls keep me honest), the > > > goal > > > > of > > > > > > the new design is to improve activation performance. I personally > > > love > > > > > > this; performance is a critical non-functional feature of any > FaaS > > > > > system. > > > > > > > > > > > > There’s something I’d like to call out: the management of > > containers > > > > in a > > > > > > FaaS system could be compared to a JVM. A JVM allocates objects > in > > > > > memory, > > > > > > and GC them. A FaaS system allocates containers to run actions, > and > > > it > > > > > GCs > > > > > > them when they become idle. If we could look at OW's scheduling > > from > > > > this > > > > > > perspective, we could reuse the proven patterns in the JVM vs > > > inventing > > > > > > something new. I’d be interested on any GC implications in the > new > > > > > design, > > > > > > meaning how idle actions get removed, and how is that > orchestrated. > > > > > > > > > > > > Thanks, > > > > > > dragos > > > > > > > > > > > > > > > > > > On Thu, Apr 4, 2019 at 8:40 AM Matt Sicker <boa...@gmail.com> > > wrote: > > > > > > > > > > > > > Would it make sense to define an OpenWhisk > > Improvement/Enhancement > > > > > > > Propoposal or similar that various other Apache projects do? We > > > could > > > > > > > call them WHIPs or something. :) > > > > > > > > > > > > > > On Thu, 4 Apr 2019 at 09:09, David P Grove <gro...@us.ibm.com> > > > > wrote: > > > > > > > > > > > > > > > > > > > > > > > > Dominic Kim <style9...@gmail.com> wrote on 04/04/2019 > 04:37:19 > > > AM: > > > > > > > > > > > > > > > > > > I have proposed a new architecture. > > > > > > > > > > > > > > > > > > https://cwiki.apache.org/confluence/display/OPENWHISK/New+architecture > > > > > > > > +proposal > > > > > > > > > > > > > > > > > > It includes many controversial agendas and breaking > changes. > > > > > > > > > So I would like to form a general consensus on them. > > > > > > > > > > > > > > > > > > > > > > > > > Hi Dominic, > > > > > > > > > > > > > > > > There's much to like about the proposal. Thank you > for > > > > > writing > > > > > > > it > > > > > > > > up. > > > > > > > > > > > > > > > > One meta-comment is that the work will have to be > done > > > in a > > > > > way > > > > > > > so > > > > > > > > there are no actual "breaking changes". It has to be > possible > > to > > > > > > > continue > > > > > > > > to configure the system using the existing architectures > while > > > this > > > > > > work > > > > > > > > proceeds. I would expect this could be done via a new > > > LoadBalancer > > > > > and > > > > > > > > some deployment options (similar to how Lean OpenWhisk was > > done). > > > > If > > > > > > > work > > > > > > > > needs to be done to generalize the LoadBalancer SPI, that > could > > > be > > > > > done > > > > > > > > early in the process. > > > > > > > > > > > > > > > > On the proposal itself, I wonder if the complexity of > > > > > > > Leader/Follower > > > > > > > > is actually needed? If a Scheduler crashes, it could be > > > restarted > > > > > and > > > > > > > then > > > > > > > > resume handling its assigned load. I think there should be > > > enough > > > > > > > > information in etcd for it to recover its current set of > > assigned > > > > > > > > ContainerProxys and carry on. Activations in its in memory > > > queues > > > > > > would > > > > > > > > be lost (bigger blast radius than the current architecture), > > but > > > I > > > > > > don't > > > > > > > > see that the Leader/Follower changes that (seems way too > > > expensive > > > > to > > > > > > be > > > > > > > > replicating every activation in the Follower Queues). The > > > > > > > Leader/Follower > > > > > > > > would allow for shorter downtime for those actions assigned > to > > > the > > > > > > downed > > > > > > > > Scheduler, but at the cost of significant complexity. Is it > > > worth > > > > > it? > > > > > > > > > > > > > > > > Perhaps related to the Leader/Follower, its not clear > > to > > > me > > > > > how > > > > > > > > activation messages are being pulled from the action topic in > > > Kafka > > > > > > > during > > > > > > > > the Queue creation window. I think they have to go somewhere > > > > (because > > > > > > the > > > > > > > > is a mix of actions on a single Kafka topic and we can't > stall > > > > other > > > > > > > > actions while waiting for a Queue to be created for a new > > > action), > > > > > but > > > > > > if > > > > > > > > you don't know yet which Scheduler is going to win the race > to > > > be a > > > > > > > Leader > > > > > > > > how do you know where to put them? > > > > > > > > > > > > > > > > --dave > > > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > > > > Matt Sicker <boa...@gmail.com> > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > 周明宇 > > > > > > > > > >
