diff --git a/rsts/deployment/ideal_flow.rst b/rsts/deployment/ideal_flow.rst
new file mode 100644
index 0000000000..a30d04914b
--- /dev/null
+++ b/rsts/deployment/ideal_flow.rst
@@ -0,0 +1,43 @@
+.. _ideal-flow:
+
+How to Streamline Your Flyte Workflows
+--------------------------------------
+
+Flyte could be useful for many use cases, be it model training, data processing, ELT/ETL, or bioinformatics.
+When workflows are built and deployed, be it in any domain, we may need automation to reduce human-in-the-loop to some extent;
+essentially, to automate serializing and registering workflows, creating docker containers, etc.
+
+Before diving into an example use case that explains how DevOps could power Flyte pipelines, let's look at some DevOps-style features Flyte ships with.
+
+- Every DAG can be versioned with Git commit's SHA or the hash of the code artifact; to know more about versioning, see :ref:`divedeep-versioning`
+- Tasks and workflows are immutable, i.e., a version is immutable; any mutation results in a new version
+- In the case of rapid iteration of code with no dependency modification, :ref:`deployment-fast-registration` can be used
+- Multi-tenancy support through projects and domains
+- Executions can be monitored using logs on :ref:`Flyte UI <ui>`
+
+Case Study: MLOps at Lyft
+=========================
+
+Flyte powers more than 1 million model training and data processing executions per month at Lyft.
+DevOps automation has been made part of Flyte pipelines to handle such a massive number of executions.
+
+- Every time a new PR is created:
+
+  - A Docker container is built from the PR
+  - Tasks and workflows are registered with Flyte
+- If dependencies are modified, PR securely builds the container again
+- For just code changes, fast registration is used
+
+  - Code can be pushed from a local machine where users are not permitted to push Docker containers
+- Once a PR is merged, the user simulates a deployment through a deployment pipeline
+- At each stage of the deployment, tasks and workflows are registered with a specific domain in Flyte,
+  where each domain may change the data directory, associated roles, or some meta attributes like labels and annotations
+- For production deployments, logs and metrics are automatically tracked, and models are promoted to serving infrastructure
+- Users can use interactive notebooks to retrieve intermediate or final outputs, analyze data and automate various monitoring tasks
+
+Thus, everything is automatically tracked. In fact, multiple users can create isolated PRs and test independently.
+
+Implementing DevOps when running Flyte pipelines could be essential when Flyte is deployed to production.
+You could have a team of engineers working on various pipelines with continuous code iteration and deployment.
+In such a case, we highly encourage you to incorporate automation to build Flyte pipelines.
+This could help speed up your development, iteration, and deployment time!
\ No newline at end of file
diff --git a/rsts/deployment/index.rst b/rsts/deployment/index.rst
index 194548db4b..996ace485a 100644
--- a/rsts/deployment/index.rst
+++ b/rsts/deployment/index.rst
@@ -66,6 +66,14 @@ solution). The following pages will help you effectively deploy and manage an en
     ^^^^^^^^^^^^
     Flyte comes with a lot of things you can configure. These pages will walk you through the various components.
 
+    ---
+    .. link-button:: ideal-flow
+       :type: ref
+       :text: How to Streamline Your Flyte Workflows
+       :classes: btn-block stretched-link
+    ^^^^^^^^^^^^
+    An example use case leveraging DevOps practices to run Flyte pipelines.
+
 
 .. toctree::
     :maxdepth: 1
@@ -79,3 +87,4 @@ solution). The following pages will help you effectively deploy and manage an en
     sandbox
     plugin_setup/index
     security/security
+    ideal_flow