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+# Auto-Scale the Scheduler service
+
+* Author(s): Cassie Coyle (@cicoyle)
+* State: Review
+* Updated: 2024-09-12
+
+## Overview
+
+This proposal outlines a design for auto-scaling the Schedulers, which is needed for the Scheduler service to be Stable.
+The Scheduler's internal cron scheduler library code will need to be refactored to be dynamic. Runtime will need to be
+updated to also account for dynamically connecting to Schedulers when they are scaled up or down. The Scheduler server
+code will need to be updated such that it optionally runs embedded etcd on different Scheduler instances.
+
+
+## Background
+
+In Dapr v1.14 we introduced the Scheduler control plane service to support the Jobs API along with scaling the Actor
+reminder system and the Workflow API (since it uses Actor reminders under the hood). The Scheduler encompasses running
+itself as a new process, an embedded etcd instance, and an internal cron scheduler. This proposal will be detailing how 
+to support the auto-scaling of Schedulers and secondly enhancing the Schedulers such that we optionally run etcd 
+instances in the Schedulers under certain circumstances that make sense. When scaling beyond 3 etcd instances, there is
+little performance improvement, so it makes sense for Schedulers to become stateless at this point. For example, we 
+could have 20 Schedulers, but only 3 of them would contain the embedded etcd.
+
+## Related Items
+
+### Related issues
+
+[Tracking Issue: Scheduler Stable](https://github.com/dapr/dapr/issues/7796) &&
+[Auto Scale Scheduler Issue](https://github.com/dapr/dapr/issues/7912).
+
+## Expectations and alternatives
+
+There will be 3 changes needed for this feature to be complete. 
+
+1. **New control loop** for the [go-etcd-cron library](https://github.com/diagridio/go-etcd-cron), such that the leadership table is able to be dynamic. This 
+means we need to watch the leadership table to observe a new Scheduler starting up or going down, stopping all Schedulers 
+job triggers for that moment until the leadership table is updated and synchronized. We will need to stop the job queue 
+and rebuild it again by reshuffling all the jobs to evenly split up the job ownership amongst Schedulers. Refactoring is
+needed here such that the queue logic can be stopped and restarted. The leadership table will be updated to additionally
+include the host address as the data such that the key in the table remains the id, but the value becomes the proposed
+protobuf below, including the observed total replicas, host address, and port.
+
+Leadership in this case refers to partition leadership, which is responsible for evenly dividing up the jobs amongst the 
+available Schedulers. It's unrelated to etcd clustering or consensus. The Schedulers share job triggering responsibilities 
+across the replicaset, based on the partition ID relative to the total number of total partitions. Partition leadership 
+ensures that no 2 Schedulers are working on the same nth partition, and that partitions are non-overlapping because they
+agree on the same observed total partition count.
+
+In a new `leadership.proto` file in the `go-etcd-cron` library we will have the following to dynamically track hosts 
+available for job ownership distribution.
+```protobuf
+// Leadership is the message written to the leadership table when the replica
+// gains ownership of the leader key.
+message Leadership {
+  // total is this replicas understanding of the total number of partition
+  // replicas.
+  uint32 total = 1;
+
+  // leader_data is custom data that is associated with this leader. All leader
+  // data will be sent to library consumer on leadership table updates.
+  optional google.protobuf.Any leader_data = 2;
+}
+```
+
+Initially we were storing the partition total as a string in etcd, but with this design we will store the above protobuf,
+in string form due to an etcd requirement. This approach will **not** break users since we are doing a string comparison
+in the library, we don't panic, and this data in particular is ephemeral anyways.
+
+By introducing this optional field, we make the library extensible and useful for other use cases beyond of the 
+Scheduler, while ensuring a non-breaking, backwards-compatible change. 
+
+On the Scheduler side, we’ll implement the following change in a new `dapr/proto/internals/scheduler.proto`:
+```protobuf
+// SchedulerPartitionOwner is the data which is written to the cron leadership
+// table.
+message SchedulerPartitionOwner {
+  // host is the host address of this partition owner.
+  string host = 1;
+
+  // port is the port of this partition owner.
+  uint32 port = 2;
+}
+```
+
+Upon startup, each Scheduler will retrieve its own host and port, and pass that into to the cron library via the cron
+library `Options` here: https://github.com/dapr/dapr/blob/master/pkg/scheduler/server/server.go#L193. This information  
+will feed into the new proposed control loop in the cron library ensuring that as Schedulers scale up or down, the 
+job triggering load is evenly distributed among them.
+
+- An optimization we can do after the initial work is done, is to keep all jobs in memory. Having a local cache 
+would optimize building the queue faster, since we are using etcd this should be feasible. 
+
+2. **A new WatchHosts RPC** is added to `scheduler.proto`, allowing the dapr sidecar to connect to any available Scheduler 
+instance via a ClusterIP service, rather than needing to manually track and connect to each instance as in the current 
+headless service model. This `WatchHosts` RPC dynamically provides the current set of active Scheduler instances to the 
+sidecar, keeping it updated as Schedulers scale up or down.
+
+- For **backward compatibility**, we will check to determine whether the `WatchHosts` RPC is available or not. If it 
+exists, Dapr will use it to manage Scheduler connections dynamically. If not, Dapr will continue using the existing 
+static connection logic, maintaining compatibility with earlier versions by sending the full list back of available 
+Schedulers.
+
+```protobuf
+service Scheduler {
+  ...
+  rpc WatchHosts(WatchHostsRequest) returns (stream WatchHostsResponse) {}
+}
+
+message HostPort {
+  string host = 1;
+  uint32 port = 2;
+}
+
+message WatchHostsResponse {
+  repeated HostPort hosts = 1;
+}
+
+message WatchHostsRequest {}
+
+```
+
+3. **1 or 3 Schedulers with respective embedded etcd instances, beyond 3 instances run Schedulers stateless**. We want to
+optionally run embedded etcd in Scheduler for cases where it makes sense. Cases to consider:
+- running 1 Scheduler means running it with embedded etcd
+- running 2 Schedulers means running the first with embedded etcd, the second Scheduler will be stateless and connect to
+the existing etcd
+- running 3 Schedulers means running all with embedded etcd
+- running 4 Schedulers means running 3 Schedulers with embedded etcd, and the last one will be stateless and connect to
+an existing etcd. Note, here there is no gain to round-robin-ing between the existing etcd instances due to the way 
+etcd works with raft under the hood.
+- running 5 Schedulers means running 3 Schedulers with embedded etcd, the last two Scheduler instances will be stateless.
+- running beyond 5 Schedulers means running 3 Schedulers with embedded etcd, and any Scheduler beyond 3 will be 
+stateless and connect to an existing etcd instance.
+
+![Stateless Schedulers Example](./resources/20240912-R-scheduler-auto-scale/statelessSchedulersExample.png)
+
+etcd must run with an odd number of replicas. In dapr, 3 will be our practical limit while running inside Schedulers. 
+With the cron scheduler library and embedded etcd already separate processes in Scheduler, we just need to optionally 
+run the embedded etcd.
+
+Regarding [etcd's cluster reconfiguration operations guide](https://etcd.io/docs/v3.3/op-guide/runtime-configuration/#cluster-reconfiguration-operations),
+for adding members, or etcd instances, we will need to set the `initial-cluster-state` to be existing for the new 
+instances. We do not need to update the configuration of existing members manually, as once the new members join the 
+cluster, it will automatically be integrated into the consensus and the cluster's state will include the new member. 
+
+As noted in their documentation, we _**should**_ set the `strict-reconfig-check` flag on etcd such that we reject
+reconfiguration requests if the number of started members will be less than a quorum. This flag will ensure we avoid
+quorum loss as we dynamically add or remove stateful Schedulers.
+
+## Completion Checklist
+
+- [ ] Write the new control loop for the go-etcd-cron library to make the leadership table & job queue dynamic
+- [ ] Add WatchHosts to scheduler.proto & update code to use it while ensuring backwards compatibility
+- [ ] 1 or 3 Scheduler etcd problem where Schedulers might be stateless
+- [ ] Tests
+- [ ] Document that some Schedulers might be stateless
\ No newline at end of file
diff --git a/resources/20240912-R-scheduler-auto-scale/statelessSchedulersExample.png b/resources/20240912-R-scheduler-auto-scale/statelessSchedulersExample.png
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diff --git a/templates/proposal.md b/templates/proposal.md
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--- a/templates/proposal.md
+++ b/templates/proposal.md
@@ -13,7 +13,7 @@ A brief description of the proposal; include information such as:
 
 ## Background
 
-This section is intented to provide the community with the reasoning behind this proposal -- why is this proposal being made? What problem is it solving for users / developers / operators and how does it solve that for them?
+This section is intended to provide the community with the reasoning behind this proposal -- why is this proposal being made? What problem is it solving for users / developers / operators and how does it solve that for them?
 
 ## Related Items