Image migration to static resources (#294)

* Updates to grammar and image link. Signed-off-by: Alekhya Sai Punnamaraju <[email protected]> * Updated image link in readme. Signed-off-by: Alekhya Sai Punnamaraju <[email protected]> * Updates from review suggestions. Signed-off-by: Alekhya Sai Punnamaraju <[email protected]>
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diff --git a/flytectl/README.md b/flytectl/README.md
@@ -1,6 +1,6 @@
 <html>
     <p align="center"> 
-        <img src="https://github.com/flyteorg/flyte/blob/master/rsts/images/flyte_circle_gradient_1_4x4.png" alt="Flyte Logo" width="100">
+        <img src="https://raw.githubusercontent.com/flyteorg/static-resources/main/common/flyte_circle_gradient_1_4x4.png" alt="Flyte Logo" width="100">
     </p>
     <h1 align="center">
         FlyteCTL

diff --git a/flytectl/proposal/README.md b/flytectl/proposal/README.md
@@ -1,21 +1,18 @@
 # Introduction
 
-This document proposes, **Flytectl** as a single CLI that interacts with FlyteAdmin service. It is proposed to write the CLI in **Golang** and would support both gRPC and REST endpoints of
-FlyteAdmin. We will start with gRPC endpoint since the client can be easily generated. In the future, we will work on generating a Swagger-based REST client from the gRPC specification. As we build
-more SDKs in different languages we will support a common way of interacting with the API. This doesn't mean that some SDKs may provide native ways of interacting with the Admin API (for e.g.
-Flytekit), but the intention is to eventually replace **Flytekit/Flytecli** with Flytectl exclusively.
+This document proposes, **Flytectl** as a single CLI that interacts with the FlyteAdmin service. It is proposed to write the CLI in **Golang** and would support both gRPC and REST endpoints of the FlyteAdmin. We will start with gRPC endpoint since the client can be easily generated. In the future, we will work on generating a Swagger-based REST client from the gRPC specification. As we buildmore SDKs in different languages we will support a common way of interacting with the API. This doesn't mean that some SDKs may provide native ways of interacting with the Admin API (e.g. Flytekit), but the intention is to eventually replace **Flytekit/Flytecli** with Flytectl exclusively.
 
-Flytectl has been designed to deliver user features without having to rely on the UI. Flytectl will follow the standard oauth2 for
-authentication, supported by FlyteAdmin. Moreover, Flytectl should be readily available on almost any platform - OSX, Linux and Windows. We will strive to keep it relatively lean and fast.
+Flytectl has been designed to deliver user features without having to rely on the UI. Flytectl will follow the standard oauth2 for authentication, supported by FlyteAdmin. Moreover, Flytectl should be readily available on almost any platform - OSX, Linux and Windows. We will strive to keep it relatively lean and fast.
 
 # Why One CLI?
 
 As we build multiple SDKs, we need a native way of interacting with the API. Having multiple CLIs makes it hard to keep all of them in sync as we rapidly evolve the API and add more features.
 
-*Diagram here*
 
+<!-- *Diagram here* -->
 
 # Why Golang?
+
 - Most of Flyte backend is written in Golang.
 - Golang offers great CLI tooling support with viper and cobra.
 - Golang toolchain helps create cross-compiled small, light weight binary, which is efficient and easy to use.
@@ -24,6 +21,7 @@ As we build multiple SDKs, we need a native way of interacting with the API. Hav
 - Kubectl is a stellar example of a CLI done well.
 
 ## Generating Swagger code
+
 We started exploring this (Flytetools)[https://github.com/lyft/flytetools#tools] has some work. The Swagger code-gen maintainer also approached us to see if they could help.
 
 # API
@@ -41,19 +39,23 @@ $ flytectl [options]
 ```
 
 ### base options
+
 - *endpoint* endpoint where Flyteadmin is available
 - *insecure* use if Oauth is not available
 - optional *project* project for which we need to retrieve details
 - optional *domain* domain for which we need to retrieve details
 - TBD
 
 ### version
-returns the version of the CLI, version of Admin service and version of the Platform that is deployed
+
+returns the version of the CLI, version of Admin service, and version of the Platform that is deployed.
 
 ### configure
+
 Allows configuring Flytectl for your own usage (low pri). Needed for especially storing Auth tokens.
 
 ### get/delete
+
 Get retrieves a list of resources that is qualified by a further sub-command. for example
 ```bash
 $ flytectl --endpoint "example.flyte.net" get projects
@@ -68,25 +70,25 @@ $ flytectl --endpoint "example.flyte.net" --project "p" --domain "d" delete work
 ```
 
 ### Create is special
-Create may need more information than can be easily passed in command line and we recommend using files to create an entity. The file could be in protobuf, jsonpb (json) or jsonpb (yaml) form.
-Eventually we may want to simplify the json and yaml representations but that is not required in first pass. We may also want to create just a separate option for that.
-
-The create for Task and Workflow is essential what is encompassed in the pyflyte as the registration process. We will decouple the registration process such that pyflyte, jflyte (other native cli's or
-code methods) can dump a serialized representations of the workflows and tasks that are directly consumed by **Flytectl**. Thus Flytectl is essential in every flow for the user.
 
+Create may need more information that can be easily passed in the command line. We recommend using files to create an entity. The file could be in protobuf, jsonpb (json) or jsonpb (yaml) form.
+ Eventually, we may want to simplify the json and yaml representations, but that is not required in the first pass. We may also want to create just a separate option for that.
 
+The create for Task and Workflow is essential to what is encompassed in the pyflyte as the registration process. We will decouple the registration process such that the pyflyte, jflyte (other native cli's or
+code methods) can dump a serialized representations of the workflows and tasks that are directly consumed by **flytectl**. Thus flytectl is essential in every flow for the user.
 #### Create Templatization
-User-facing SDKs can serialize workflow code to protobuf representations but these will be incomplete. Specifically, the _project_, _domain_, and _version_ parameters must be supplied at create time since these are attributes of the registerable, rather than serialized object. Placeholder template variables including:
+
+User-facing SDKs can serialize workflow code to protobuf representations, but these will be incomplete. Specifically, the _project_, _domain_, and _version_ parameters must be supplied at create time since these are attributes of the registerable rather than serialized object. Placeholder template variables include:
 
 * `{{ .project }}`
 * `{{ .domain }}`
 * `{{ .version }}`
 * [auth](https://github.com/flyteorg/flyteidl/blob/c3baba8983019680ef57b6244cea36ba951233ed/protos/flyteidl/admin/common.proto#L241): including the assumable_iam_role and/or kubernetes_service_account
 * the [output_location_prefix](https://github.com/flyteorg/flyteidl/blob/c3baba8983019680ef57b6244cea36ba951233ed/protos/flyteidl/admin/common.proto#L250)
 
-will be included in the serialized protobuf that must be substituted at **create** time.  Eventually the hope is that substitution will be done server-side.
+will be included in the serialized protobuf that must be substituted at **create** time.  Eventually, the hope is that substitution will be done server-side.
 
-Furthermore, to reproduce the equivalent **fast-register** code path for the flyte-cli defined in flytekit an equivalent _fast-create_ command must fill in additional template variables in the [task container args](https://github.com/flyteorg/flyteidl/blob/master/protos/flyteidl/core/tasks.proto#L142). These serialized, templatized args will appear like so:
+Furthermore, to reproduce the equivalent **fast-register** code path for the flyte-cli defined in flytekit, an equivalent _fast-create_ command must fill in additional template variables in the [task container args](https://github.com/flyteorg/flyteidl/blob/master/protos/flyteidl/core/tasks.proto#L142). These serialized, templatized args will appear like so:
 
 ```
 "pyflyte-fast-execute",
@@ -99,21 +101,22 @@ Furthermore, to reproduce the equivalent **fast-register** code path for the fly
 ...
 ```
 
-The `remote package path` is determined by uploading the compressed user code (produced in the serialize step) to a user-specified remote directory (called `additional-distribution-dir` in flytekit). In the case of fast-create the code _version_ arg can be deterministcally assigned when serializing the code. Compressed code archives uploaded as individual files to the remote directory can assume the version name to guarantee uniqueness.
+The `remote package path` is determined by uploading the compressed user code (produced in the serialize step) to a user-specified remote directory (called `additional-distribution-dir` in flytekit). In the case of fast-create the code _version_ arg can be deterministically assigned when serializing the code. Compressed code archives uploaded as individual files to the remote directory can assume the version name to guarantee uniqueness.
 
 The `dest dir` is an optional argument specified by the user to designate where code is downloaded at execution time.
 
-![Registration process](flytectl_interaction.png)
+![Registration process](https://raw.githubusercontent.com/flyteorg/static-resources/main/flytectl/readme/flytectl_interaction.png)
 
 ### update
-This is a lower priority option as most entities in flyte are immutable and do not support updates. For the ones where update is supported, we should look into retrieving the existing and allow editing in an editor, like kubectl edit does.
 
-**To be specified**
+This is a lower priority option as most entities in flyte are immutable and do not support updates. For the ones where updates are supported, we should look into retrieving the existing and allowing editing in an editor, as kubectl edit does.
 
+<!-- **To be specified** -->
 
-# Details of each resource
 
+# Details of each resource
 ## Projects
+
 Projects are top level entity in Flyte. You can fetch multiple projects or one project using the CLI. Think about projects like namespaces.
 
  - create
@@ -144,23 +147,25 @@ $ flytectl update projects --id project-x ...
 ```
 
 ## Tasks
- - get
+
+- get
 ```bash
 $ flytectl get tasks [task-name] [-o yaml | -o json | default -o table] [--filters...] [--sort-by...] [--selectors...]
 ```
- - get specific version and get a template to launch
-   Create an execution is complicated as the user needs to know all the input types and  way to simplify this could be to create a YAML template locally from the launchplan (the interface, etc)
+ - get a specific version and get a template to launch
+   Create an execution is complicated as the user needs to know all the input types, and a way to simplify this could be to create a YAML template locally from the launchplan (the interface, etc.)
 ```bash
 $ flytectl get task task-name --execution-template -o YAML
 yaml.template (TBD)
-This is a special version of get launch-plan which can be executed by passing it to create execution.
+This is a special version of the get launch-plan which can be executed by passing it to create execution.
 
 ```
  - create
  - create
  - update
 
 ## Workflows
+
 Support
  - get
 ```bash
@@ -170,30 +175,32 @@ $ flytectl get workflows [workflow-name] [-o yaml | -o json | default -o table]
  - update
 
 ## Launch Plans
+
 Support
  - get
 ```bash
 $ flytectl get launch-plans [launchplan-name] [-o yaml | -o json | default -o table] [--filters...] [--sort-by...] [--selectors...]
 ```
- - get specific version and get a template to launch
-   Create an execution is complicated as the user needs to know all the input types and  way to simplify this could be to create a YAML template locally from the launchplan (the interface, etc)
+ - get a specific version and get a template to launch
+   Create an execution is complicated as the user needs to know all the input types, and a way to simplify this could be to create a YAML template locally from the launchplan (the interface, etc.)
 ```bash
 $ flytectl get launch-plans launch-plan-name --execution-template -o YAML
 yaml.template (TBD)
-This is a special version of get launch-plan which can be executed by passing it to create execution.
+This is a special version of the get launch-plan which can be executed by passing it to create execution.
 
 ```
  - create
  - update
 
 ## Execution
+
 Create or retrieve an execution. 
  - get
 Get all executions or get a single execution.
 ```bash
 $ flytectl get execution [exec-name] [-o yaml | -o json | default -o table] [--filters...] [--sort-by...] [--selectors...]
 ```
-An interesting feature in get-execution might be to filter within the execution only the execution of a node, or quickly find the ones that have failed. 
+An interesting feature in get-execution might be to filter the execution of a node within the execution only or quickly find the ones that have failed. 
 Visualizing the execution is also challenging. We may want to visualize
 We could use https://graphviz.org/ to visualize the DAG.
 Within the DAG, NodeExecutions and corresponding task executions need to be fetched.
@@ -207,12 +214,14 @@ $ flytectl create execution --launch-plan "name" --inputs "key=value"
  - delete - here refers to terminate
 
 ## MatchableEntity
-Ability to retrieve matchable entity and edit its details
+
+Ability to retrieve the matchable entity and edit its details
  - get
  - create
  - update
 
 ## Outputs
+
 Support
  - get
  - create
@@ -221,19 +230,21 @@ Support
 # No resource interactions
 
 ## Install all examples
-Today Flytesnacks houses a few examples for Flyte usage in python. When a user wants to get started with Flyte quickly it would be preferable that all Flytesnacks examples are serialized and stored as artifacts in flytesnacks for every checkin. This can be done for python flytekit using `pyflyte serialize` command. Once they are posted as serialized blobs, flytectl could easily retrieve them and register them in a specific project as desired by the user.
+
+Today Flytesnacks houses a few examples for Flyte usage in python. When a user wants to get started with Flyte quickly, it would be preferable that all Flytesnacks examples are serialized and stored as artifacts in flytesnacks for every checkin. This can be done for python flytekit using `pyflyte serialize` command. Once they are posted as serialized blobs, flytectl could easily retrieve them and register them in a specific project as desired by the user.
 
 ```bash
 $ flytectl examples register-all [cookbook|plugins|--custom-path=remote-path] [--semver semantic-version-of-flytesnacks-examples] --target-project --target-domain
 ```
-The remote has to follow a protocol. It should be an archive - `tar.gz` with two folders `example-set/ -tasks/*.pb -workflows/*.pb` All the workflows in this path will be installed to the target project / domain
+The remote has to follow a protocol. It should be an archive - `tar.gz` with two folders `example-set/ -tasks/*.pb -workflows/*.pb` All the workflows in this path will be installed to the target project/domain.
 
 ## Setup a repository with dockerfile for writing code for Flyte
+
 Maybe we should look at `boilr` or some other existing framework to do this
 ```bash
 $ flytectl init project --archetype tensorflow-2.0
 $ flytectl init project --archetype spark-3.0
 $ flytectl init project --archetype xgboost
 ...
 ```
-For this to work, all these archetypes should be available in a separate repository. An archetype is essentially a template with dockerfile and folder setup with flytekit.config
+All these archetypes should be available in a separate repository for this to work. An archetype is a template with dockerfile and folder setup with flytekit.config.