What thresholds should be set in Service Fabric Placement / Load balancing config for Cluster with large number of guest executable applications?
I am having trouble with Service Fabric trying to place too many services onto a single node too fast.
To give an example of cluster size, there are 2-4 worker node types, there are 3-6 worker nodes per node type, each node type may run 200 guest executable applications, and each application will have at least 2 replicas. The nodes are more than capable of running the services while running, it is just startup time where CPU is too high.
The problem seems to be the thresholds or defaults for placement and load balancing rules set in the cluster config. As examples of what I have tried: I have turned on InBuildThrottlingEnabled
and set InBuildThrottlingGlobalMaxValue
to 100
, I have set the Global Movement Throttle settings to be various percentages of the total application count.
At this point there are two distinct scenarios I am trying to solve for. In both cases, the nodes go to 100% for an amount of time such that service fabric declares the node as down.
1st: Starting an entire cluster from all nodes being off without overwhelming nodes.
2nd: A single node being overwhelmed by too many services starting after a host comes back online
Here are my current parameters on the cluster:
"Name": "PlacementAndLoadBalancing", "Parameters": [ { "Name": "UseMoveCostReports", "Value": "true" }, { "Name": "PLBRefreshGap", "Value": "1" }, { "Name": "MinPlacementInterval", "Value": "30.0" }, { "Name": "MinLoadBalancingInterval", "Value": "30.0" }, { "Name": "MinConstraintCheckInterval", "Value": "30.0" }, { "Name": "GlobalMovementThrottleThresholdForPlacement", "Value": "25" }, { "Name": "GlobalMovementThrottleThresholdForBalancing", "Value": "25" }, { "Name": "GlobalMovementThrottleThreshold", "Value": "25" }, { "Name": "GlobalMovementThrottleCountingInterval", "Value": "450" }, { "Name": "InBuildThrottlingEnabled", "Value": "false" }, { "Name": "InBuildThrottlingGlobalMaxValue", "Value": "100" } ] },
Based on discussion in answer below, wanted to leave a graph-image: if a node goes down, the act of shuffling services on to the remaining nodes will cause a second node to go down, as noted here. Green node goes down, then purple goes down due to too many resources being shuffled onto it.
The minimum supported size for a Service Fabric cluster running production workloads is five nodes.
A single Service Fabric node type/scale set can not contain more than 100 nodes/VMs. To scale a cluster beyond 100 nodes, add additional node types.
Because the Service Fabric Cluster Resource Manager doesn't use a greedy approach, some load could also be distributed to Node2. "Balancing" handles two different strategies for managing load in your cluster. The default strategy that the Cluster Resource Manager uses is to distribute load across the nodes in the cluster.
Balancing your service fabric cluster. The Service Fabric Cluster Resource Manager supports dynamic load changes, reacting to additions or removals of nodes or services. It also automatically corrects constraint violations, and proactively rebalances the cluster.
Balancing Thresholds are defined on a per-metric basis as a part of the cluster definition. For more information on metrics, check out this article. via ClusterConfig.json for Standalone deployments or Template.json for Azure hosted clusters:
It can be useful to take a look at the Event Viewer on the Service Fabric nodes: There techniques, along with the debugging capabilities part of Visual Studio should help you to troubleshoot most of the errors you can encounter while deploying your Service Fabric service into your cluster.
From SF's perspective, 1 & 2 are the same problem. Also as a note, SF doesn't evict a node just because CPU consumption is high. So: "The nodes go to 100% for an amount of time such that service fabric declares the node as down." needs some more explanation. The machines might be failing for other reasons, or I guess could be so loaded that the kernel level failure detectors can't ping other machines, but that isn't very common.
For config changes: I would remove all of these to go with the defaults
{
"Name": "PLBRefreshGap",
"Value": "1"
},
{
"Name": "MinPlacementInterval",
"Value": "30.0"
},
{
"Name": "MinLoadBalancingInterval",
"Value": "30.0"
},
{
"Name": "MinConstraintCheckInterval",
"Value": "30.0"
},
For the inbuild throttle to work, this needs to flip to true:
{
"Name": "InBuildThrottlingEnabled",
"Value": "false"
},
Also, since these are likely constraint violations and placement (not proactive rebalancing) we need to explicitly instruct SF to throttle those operations as well. There is config for this in SF, although it is not documented or publicly supported at this time, you can see it in the settings. By default only balancing is throttled, but you should be able to turn on throttling for all phases and set appropriate limits via something like the below.
These first two settings are also within PlacementAndLoadBalancing, like the ones above.
{
"Name": "ThrottlePlacementPhase",
"Value": "true"
},
{
"Name": "ThrottleConstraintCheckPhase",
"Value": "true"
},
These next settings to set the limits are in their own sections, and are a map of the different node type names to the limit you want to throttle for that node type.
{
"name": "MaximumInBuildReplicasPerNodeConstraintCheckThrottle",
"parameters": [
{
"name": "YourNodeTypeNameHere",
"value": "100"
},
{
"name": "YourOtherNodeTypeNameHere",
"value": "100"
}
]
},
{
"name": "MaximumInBuildReplicasPerNodePlacementThrottle",
"parameters": [
{
"name": "YourNodeTypeNameHere",
"value": "100"
},
{
"name": "YourOtherNodeTypeNameHere",
"value": "100"
}
]
},
{
"name": "MaximumInBuildReplicasPerNodeBalancingThrottle",
"parameters": [
{
"name": "YourNodeTypeNameHere",
"value": "100"
},
{
"name": "YourOtherNodeTypeNameHere",
"value": "100"
}
]
},
{
"name": "MaximumInBuildReplicasPerNode",
"parameters": [
{
"name": "YourNodeTypeNameHere",
"value": "100"
},
{
"name": "YourOtherNodeTypeNameHere",
"value": "100"
}
]
}
I would make these changes and then try again. Additional information like what is actually causing the nodes to be down (confirmed via events and SF health info) would help identify the source of the problem. It would probably also be good to verify that starting 100 instances of the apps on the node actually works and whether that's an appropriate threshold.
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