diff --git a/ROADMAP.md b/ROADMAP.md
index 8c1eee221d4..911c9293a7d 100644
--- a/ROADMAP.md
+++ b/ROADMAP.md
@@ -1,25 +1,62 @@
-# KServe Roadmap
-## 2021 Q4/2022 Q1
-
-### Kubernetes Deployment
-Objective: "Enable raw kubernetes deployment as alternative mode"
-* Support existing ML frameworks, transformer/explainer, logger and batching
-* Make Istio/KNative optional and unlock KNative limitations
-  * Allow multiple volumes mounted
-  * Allow TCP/UDP
-
-### Inference Graph
-Objective: "Enable model serving pipelines with flexible routing graph"
-* Inference Router
-    * Model Experimentation.
-    * Ensembling.
-    * Multi Arm Bandit.
-    * Pipeline
-Proposal: https://docs.google.com/document/d/1rV8kI_40oiv8jMhY_LwkkyKLdOwSI1Qda-Dc6Dgjz1g
-
-### ModelMesh
-Objective: "Unifying interface for SingleModel and ModelMesh deployment"
-* Ability to perform inference using Predict v2 API with REST/gRPC
-* Unify the storage support for single and ModelMesh
-* InferenceService controller to utilize ServingRuntime
-* Single install for KServe which includes SingleModel and ModelMesh Serving
+# KServe 2023 Roadmap
+
+## Objective: "Graduate core inference capability to stable/GA"
+- Promote `InferenceService` and `ClusterServingRuntime`/`ServingRuntime` CRD from v1beta1 to v1 
+  * Improve `InferenceService` CRD for REST/gRPC protocol interface
+  * Unify model storage spec and implementation between KServe and ModelMesh
+  * Add Status to `ServingRuntime` for both ModelMesh and KServe, surface `ServingRuntime` validation errors and deployment status
+  * Deprecate `TrainedModel` CRD and use `InferenceService` annotation to allow dynamic model updates as alternative option to storage initializer
+  * Collocate transformer and predictor in the pod to reduce sidecar resources and networking latency
+  * Stablize `RawDeployment` mode with comprehensive testing for supported features
+
+- All model formats to support v2 inference protocol including custom serving runtime
+  * TorchServe to support v2 gRPC inference protocol
+  * Support batching for v2 inference protocol
+  * Transformer and Explainer v2 inference protocol interoperability
+  * Improve codec for v2 inference protocol
+
+Reference: [Control plane issues](https://github.com/kserve/kserve/issues?q=is%3Aissue+is%3Aopen+label%3Akserve%2Fcontrol-plane), [Data plane issues](https://github.com/kserve/kserve/issues?q=is%3Aissue+is%3Aopen+label%3Akfserving%2Fdata-plane)，[Serving Runtime issues](https://github.com/kserve/kserve/issues?q=is%3Aissue+is%3Aopen+label%3Akserve%2Fservingruntime).
+
+## Objective: "Graduate KServe Python SDK to 1.0“
+
+- Improve KServe Python SDK dependency management with Poetry
+- Create standarized model packaging API
+- Improve KServe model server observability with metrics and distruted tracing
+- Support batch inference
+
+Reference：[Python SDK issues](https://github.com/kserve/kserve/issues?q=is%3Aissue+is%3Aopen+label%3Akserve%2Fsdk), [Storage issues](https://github.com/kserve/kserve/issues?q=is%3Aissue+is%3Aopen+label%3Akfserving%2Fstorage)
+
+## Objective: "Graduate ModelMesh to beta"
+- Support TorchServe ServingRuntime
+- Add PVC support and unify storage implementation with KServe
+- Add optional ingress for ModelMesh deployments
+- Etcd secret security for multi-namespace mode
+- Add estimated model size field
+
+Reference: [ModelMesh issues](https://github.com/kserve/modelmesh-serving/issues?page=1&q=is%3Aissue+is%3Aopen)
+
+## Objective: "Graduate InferenceGraph to beta"
+- Improve `InferenceGraph` spec for replica and concurrency control
+- Allow setting resource limits per `InferenceGraph`
+- Support distributed tracing
+- Support gRPC for `InferenceGraph`
+- Standalone `Transformer` support for `InferenceGraph`
+- Support traffic mirroring node
+- Support `RawDeployment` mode for `InferenceGraph`
+
+Reference: [InferenceGraph issues](https://github.com/kserve/kserve/issues?q=is%3Aissue+is%3Aopen+label%3Akserve%2Finference_graph)
+
+## Objective: "Secure InferenceService"
+- Document KServe ServiceMesh setup with mTLS
+- Support programmatic authentication token
+- Implement per service level auth
+- Add support for SPIFFE/SPIRE identity integration with `InferenceService`
+
+Reference: [Auth related issues](https://github.com/kserve/kserve/issues?q=is%3Aissue+is%3Aopen+label%3Akserve%2Fauth)
+
+## Objective: "KServe 1.0 documentation"
+- Add ModelMesh docs and explain the use cases for classic KServe and ModelMesh
+- Unify the data plane v1 and v2 page formats
+- Improve v2 data plane docs to tell the story why and what changed
+- Clean up the examples in kserve repo and unify them with the website's by creating one source of truth for example documentation
+- Update any out-of-date documentation and make sure the website as a whole is consistent and cohesive