Re: Tolerance Data 2012 Torent
Theodora Glime
I am downloading from several torrents where there is only one good seed, and occasionally I see in the logs "Banning peer: too many pex messages. 5 since ___" banning the only seed giving me downloads. The seeds are also running uTorrent (the exact same version in fact) so there is no reason to be banning other uTorrent peers that are sending good data. I don't understand why this banning is necessary, and when I unban them manually they are not rebanned immediately so clearly the clients aren't misbehaving. How do I prevent uTorrent from banning peers for pex messages permanently?
Agreed. 90% of the torrents I connect to are unhealthy ones where the banning only causes more distress. From previous discussions, it is not going to be changed. I would love to see an advanced parameter to change the threshold for this behavior, though.
All that thread does is explain that the self-banning of your own IP or router address is not anything to worry about. OK, that is good to know. But the banning of other IP addresses due to an algorithm that examines a time period of too short an interval to take into account benign and intermittent network delays is not addressed. Keep the default for the average user of popular torrents to keep overhead down. I just want the option of more tolerance. This problem affects almost all the torrents I connect to so since I am constantly unbanning anyway why not just give me the option to not ban in the first place? Doesn't whether I ban or not only affect my system? I would rather have the overhead. Banning kills unhealthy struggling torrents.
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In a nutshell, fault tolerance is an upgraded version of high availability. High availability accepts that failure will occur and provides a way for the system to recover automatically, while systems with fault tolerance avoid system crashes, loss of performance, and loss of data altogether.
High availability achieves resiliency by removing single points of failure in the system. In contrast, fault-tolerant systems achieve resiliency by having full copies of the system operating in parallel. They are similar in the sense that they both have near-zero downtimes, but they differ in many other respects.
In this example, we need to design a license plate tracking system for use on a toll road. The county wants to capture images of the license plates of passing cars on a road installed with cameras. These images will be used to figure out where to send the bill for using the toll highway. We have a minimal budget, and the county is okay if the system goes down occasionally. The basic system might look like this:
The figure below shows one way we can design such a system to be Highly Available: we can see from the graphic that there are no single points of failure. A load-balancing service is being used with auto-scaling groups instead of an individual server. This means there are multiple image processing servers, with the possibility of more being spun up during traffic spikes. There is also more than one database server: the primary node constantly replicating to a read-only secondary node, both hidden behind a database alias. We also have more than one availability zone in use in case of a power loss that causes the data center AZ1 to go down. There may be some delays to images getting processed when only AZ2 is available because new servers can take time to spin up, and database switchover can take some time. However, despite some performance degradation, the system will stay operational.
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High availability and fault-tolerant systems both leverage scalability. In the examples above, we used auto-scaling groups to ensure that traffic spikes can be handled. During times of low traffic, since high availability allows for some degraded performance, Case 2 allows for scaling down the number of image processing instances or containers to reduce cost. Case 3 is a little more constrained when scaling down because a fault tolerant system has to maintain two active regions at all times, but for that use case, we always maintained cost was never an issue!
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Fault tolerance dictates zero performance degradation without caring how much the system costs. When load balancing is in use for Case 3, traffic gets routed to both regions during normal times, each of which has enough instances to handle the highest recorded traffic. In the event that an entire region fails, the remaining region will comfortably handle the entire load. No new instances will need to be created in case of such a disaster, so there is no performance impact. Keeping all these instances available can be costly, but if it can help resolve an amber alert, it just might be worth it!
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