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updates from Cassie/Mark 

Signed-off-by: Hannah Hunter <hannahhunter@microsoft.com>
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Hannah Hunter 2024-12-12 15:14:12 -05:00
parent dde0fdc78f
commit c653973450
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daprdocs/content/en/concepts/dapr-services/scheduler.md
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@ -19,7 +19,9 @@ The Scheduler service Docker container is started automatically as part of `dapr
## Kubernetes mode
The Scheduler service is deployed as part of `dapr init -k`, or via the Dapr Helm charts. For more information on running Dapr on Kubernetes, visit the [Kubernetes hosting page]({{< ref kubernetes >}}).
The Scheduler service is deployed as part of `dapr init -k`, or via the Dapr Helm charts. You can run Scheduler in high availability (HA) mode. [Learn more about setting HA mode in your Kubernetes service.]({{< ref "kubernetes-production.md#high-availability-mode" >}})
For more information on running Dapr on Kubernetes, visit the [Kubernetes hosting page]({{< ref kubernetes >}}).
## Related links

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daprdocs/content/en/developing-applications/building-blocks/actors/actors-timers-reminders.md
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@ -148,7 +148,9 @@ If an invocation of the method fails, the timer is not removed. Timers are only
## Reminder data serialization format
Actor reminder data is serialized to JSON by default. Dapr v1.13 onwards supports a protobuf serialization format for reminders data which, depending on throughput and size of the payload, can result in significant performance improvements, giving developers a higher throughput and lower latency. Another benefit is storing smaller data in the actor underlying database, which can result in cost optimizations when using some cloud databases. A restriction with using protobuf serialization is that the reminder data can no longer be queried.
Actor reminder data is serialized to JSON by default. Dapr v1.13 onwards supports a protobuf serialization format for internal reminders data for workflow via both the Placement and Scheduler services. Depending on throughput and size of the payload, this can result in significant performance improvements, giving developers a higher throughput and lower latency.
Another benefit is storing smaller data in the actor underlying database, which can result in cost optimizations when using some cloud databases. A restriction with using protobuf serialization is that the reminder data can no longer be queried.
{{% alert title="Note" color="primary" %}}
Protobuf serialization will become the default format in Dapr 1.14

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daprdocs/content/en/operations/hosting/kubernetes/kubernetes-production.md
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@ -95,6 +95,16 @@ For a new Dapr deployment, HA mode can be set with both:
For an existing Dapr deployment, [you can enable HA mode in a few extra steps]({{< ref "#enabling-high-availability-in-an-existing-dapr-deployment" >}}).
### Scheduler service HA configuration
As of Dapr 1.15, the scheduler `dapr_scheduler.ha` flag scales schedulers to three instances independently of the `global.ha.enabled` flag. Default is one instance, meaning HA for schedulers is not default.
`global.ha.enabled` set to `true` is fully respected and cannot be overridden by setting the local HA flag to `false`.
To scale the schedulers to three instancers, set `global.ha.enabled` to false and `dapr_scheduler.ha` to true.
This flag can be set via Helm with `--set dapr_scheduler.ha=true`.
## Setting cluster critical priority class name for control plane services
In some scenarios, nodes may have memory and/or cpu pressure and the Dapr control plane pods might get selected