Merge pull request #454 from wrijeff/v0.8.x

Added release notes for v0.8.0.

deployment-template/eks/README.md

@@ -9,7 +9,8 @@ Other configuration options can be specified by editing the _ingress.yaml_ file;
 
 ## Steps
 1. Provision an Amazon EKS cluster: <https://docs.aws.amazon.com/eks/latest/userguide/create-cluster.html>
-2. Configure kubectl to connect with the cluster: <https://aws.amazon.com/premiumsupport/knowledge-center/eks-cluster-connection/>
-3. Install the AWS Load Balancer Controller: <https://docs.aws.amazon.com/eks/latest/userguide/aws-load-balancer-controller.html>
-4. Run `kubectl apply -f ingress.yaml` in this directory
-5. Confirm an ALB with Target Group was created in the Load Balancer AWS Console
+1. Configure kubectl to connect with the cluster: <https://aws.amazon.com/premiumsupport/knowledge-center/eks-cluster-connection/>
+1. Apply the Data Prepper Kubernetes config files located in the [/k8s](../k8s) directory to provision Data Prepper pods
+1. Install the AWS Load Balancer Controller: <https://docs.aws.amazon.com/eks/latest/userguide/aws-load-balancer-controller.html>
+1. Run `kubectl apply -f ingress.yaml` in this directory
+1. Confirm an ALB with Target Group was created in the Load Balancer AWS Console

release/release-notes/odfe-data-prepper.release-notes-0.7.0.md

@@ -1,4 +1,4 @@
-## 2020-12-10 Version 0.7.0 (Current)
+# 2020-12-10 Version 0.7.0 (alpha)
 
 This is the first official release of Data Prepper.
 
@@ -7,4 +7,4 @@ In the first release of Data Prepper, it only supports plugins that are required
 
 ### Documentation
 * [Overview](https://github.com/opendistro-for-elasticsearch/Data-Prepper/blob/e51238b2cea55bba138466f146fc19622331e59c/docs/readme/overview.md): Overview of Data Prepper
-* [Trace Overview](https://github.com/opendistro-for-elasticsearch/Data-Prepper/blob/e51238b2cea55bba138466f146fc19622331e59c/docs/readme/trace_overview.md): Trace overview
+* [Trace Overview](https://github.com/opendistro-for-elasticsearch/Data-Prepper/blob/e51238b2cea55bba138466f146fc19622331e59c/docs/readme/trace_overview.md): Trace overview

release/release-notes/odfe-data-prepper.release-notes-0.8.0.md

@@ -0,0 +1,26 @@
+# 2021-03-25 Version 0.8.0 (beta)
+
+## Highlights:
+* Horizontally-scaling clusters can now be deployed by using the new _Peer Forwarder_ plugin. 
+  * Refer to the [README file](https://github.com/opendistro-for-elasticsearch/data-prepper/blob/main/data-prepper-plugins/peer-forwarder/README.md) for usage instructions
+  * See the [deployment templates directory](https://github.com/opendistro-for-elasticsearch/data-prepper/tree/main/deployment-template) for new container-based deployment strategies.
+* [Prometheus](https://prometheus.io/)-friendly metrics can now be scraped via a new /metrics endpoint.
+  * See the [monitoring docs](../../docs/readme/monitoring.md) for more information
+
+---
+
+## Peer Forwarder Plugin
+To enable horizontal scaling, it is expected to run Data Prepper instances in a cluster with requests distributed by a load balancer. This complicates preppers which maintain state between requests, specifically those which require that only one instance process all spans for a given trace. Peer forwarding facilitates this usecase by ensuring all spans for a given trace arrive at a specific Data Prepper instance.
+
+The Peer Forwarding plugin enables instances in a Data Prepper cluster to forward requests to other specific instances within the cluster. Peer forwarding is accomplished by a consistent hashing algorithm to ensure that all requests for a given trace are routed to the same Data Prepper instance. The algorithm maps requests to addresses of known instances - these instances are provided via a peer discovery mechanism. As of version 0.8.0, peer discovery can be provided by either a static address list or by dynamic DNS lookups.
+
+Refer to the [README file](https://github.com/opendistro-for-elasticsearch/data-prepper/blob/main/data-prepper-plugins/peer-forwarder/README.md) for usage instructions.
+
+---
+
+## Metrics
+Version 0.8.0-beta offers APIs which provide JVM/system metrics and Plugin metrics.
+
+Users can use these endpoints to connect to their existing [Prometheus](https://prometheus.io/) instance to start aggregating metrics. Additional tools such as [Grafana](https://grafana.com/) can then be used to provide dashboards and alerting.
+
+See the [monitoring docs](../../docs/readme/monitoring.md) for a list of default metrics emitted by each component type (buffers, sinks, etc.)