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Previously, public referred to gRPC services that are both exposed on the dedicated gRPC port and have their definitions in the proto-public directory (so were considered usable by 3rd parties). Whereas private referred to services on the multiplexed server port that are only usable by agents and other servers. Now, we're splitting these definitions, such that external/internal refers to the port and public/private refers to whether they can be used by 3rd parties. This is necessary because the peering replication API needs to be exposed on the dedicated port, but is not (yet) suitable for use by 3rd parties. |
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README.md | ||
adding-a-topic.md | ||
event-filtering.mmd | ||
event-filtering.svg | ||
event-publisher-layout.mmd | ||
event-publisher-layout.svg | ||
framing-events.mmd | ||
framing-events.svg | ||
overview.mmd | ||
overview.svg |
README.md
Event Streaming
Event streaming is a new asynchronous RPC mechanism that is being added to Consul. Instead of synchronous blocking RPC calls (long polling) to fetch data when it changes, streaming sends events as they occur, and the client maintains a materialized view of the events.
At the time of writing only the service health endpoint uses streaming, but more endpoints will be added in the future.
See adding a topic for a guide on adding new topics to streaming.
Overview
The diagram below shows the components that are used in streaming, and how they fit into the rest of Consul.
Read requests are received either from the HTTP API or from a DNS request. They use rpcclient/health.Health to query the cache. The StreamingHealthServices cache-type uses a materialized view to manage subscriptions and store the aggregated events. On the server, the SubscribeEndpoint subscribes and receives events from EventPublisher.
Writes will likely enter the system through the client as well, but to make the diagram less complicated the write flow starts when it is received by the RPC endpoint. The endpoint calls raft.Apply, which if successful will save the new data in the state.Store. When the state.Store commits it produces an event which is managed by the EventPublisher and sent to any active subscriptions.
Event Publisher
The EventPublisher is at the core of streaming. It receives published events, and subscription requests, and forwards events to the appropriate subscriptions. The diagram below illustrates how events are stored by the EventPublisher.
When a new subscription is created it will create a snapshot of the events required to reflect the current state. This snapshot is cached by the EventPublisher so that other subscriptions can re-use the snapshot without having to recreate it.
The snapshot always points at the first item in the linked list of events. A subscription
will initially point at the first item, but the pointer advances each time
Subscribe.Next
is called. The topic buffers in the EventPublisher always point at the
latest item in the linked list, so that new events can be appended to the buffer.
When a snapshot cache TTL expires, the snapshot is removed. If there are no other subscriptions holding a reference to those items, the items will be garbage collected by the Go runtime. This setup allows EventPublisher to keep some events around for a short period of time, without any hard coded limit on the number of events to cache.
Subscription events
A subscription provides a stream of events on a single topic. Most of the events contain
data for a change in state, but there are a few special "framing" events that are used to
communicate something to the client. The diagram below helps illustrate the logic in
EventPublisher.Subscribe
and the materialized view.
Events in the Snapshot
contain the same data as those in the EventStream
, the only
difference is that events in the Snapshot
indicate the current state not a change in
state.
NewSnapshotToFollow
is a framing event that indicates to the client that their existing
view is out of date. They must reset their view and prepare to receive a new snapshot.
EndOfSnapshot
indicates to the client that the snapshot is complete. Any future events
will be changes in state.
Event filtering
As events pass through the system from the state.Store
to the client they are grouped
and filtered along the way. The diagram below helps illustrate where each of the grouping
and filtering happens.