Fix CI issues

The CI configuration had multilple issues around the Rust related
tooling. This commit addresses those and corrects a few typos.

Extra:

Delete Makefile as it is has been replaced with a justfile.

.github/workflows/action.yaml

@@ -1,12 +1,8 @@
 on: push
 
-env:
-  IMG: ame-controller:local
-  SERVER_IMG: ame-server:local
-
 jobs:
   validate:
-    runs-on: ubuntu-20.04
+    runs-on: ubuntu-22.04
     steps:
       - uses: actions/checkout@v2
       - uses: extractions/setup-just@v1
@@ -15,21 +11,23 @@ jobs:
           profile: minimal
           toolchain: stable
       - uses: Swatinem/rust-cache@v2
+        with:
+          shared-key: ame-ci-cache
+      - uses: rinx/[email protected]
+        with:
+          skipClusterCreation: true
       - uses: arduino/setup-protoc@v1
         with:
           version: '3.19.4'
-      - name: Rust validation
+      - name: Prep test environment
         run: |
+          sudo apt-get install -y build-essential openssl libssl-dev libc6-dev clang libclang-dev ca-certificates
           just setup_toolchains
           just tools
-          just check
+          just add_helm_repos
           just setup_cluster
-          just install_ame
-          just test
-      - name: Prep test environment
-        run: |
-          make tools
-          make deploy_local_cluster
+          just deploy_ame_to_cluster
       - name: Validate commit
         run: |
-          make test
+          just check
+          just test

README.md

@@ -94,7 +94,7 @@ TODO: show an example of this.
 
 ### Pipelines
 
-You might have multiple Tasks meant to be executed together, for example downloading data, preparing data, model training, model upload. Each of these Tasks will have different requirements. This can be expressed using a pipeline. Each Task in a pipeline is executed in a separate container potentially on different machines if their compute requirements are different. To ensure that your code will work without modification, all of the state is transferred between steps transparently so it appears as if all of the steps are executed on the same machine. For example data is downloaed in step 1, prepared in step 2 and trained on in step 3 AME will make sure to transfer these files automaticlly between steps so no adjustments are reqired to the project's code.
+You might have multiple Tasks meant to be executed together, for example downloading data, preparing data, model training, model upload. Each of these Tasks will have different requirements. This can be expressed using a pipeline. Each Task in a pipeline is executed in a separate container potentially on different machines if their compute requirements are different. To ensure that your code will work without modification, all of the state is transferred between steps transparently so it appears as if all of the steps are executed on the same machine. For example data is downloaed in step 1, prepared in step 2 and trained on in step 3 AME will make sure to transfer these files automatically between steps so no adjustments are reqired to the project's code.
 
 ```yaml
 #ame.yaml
@@ -141,7 +141,7 @@ RecurringTasks, concists of a Task, a cron schedule and a reference to a git rep
 
 ## Deployment and administration
 
-AME is Kubernetes native, it will play nicely with any existing Kubenertes setup you may have and is very gitops friendly.
+AME is Kubernetes native, it will play nicely with any existing Kubernetes setup you may have and is very gitops friendly.
 
 TODO: Fill in details
 

WALKTHROUGH.md

@@ -28,7 +28,7 @@ TODO: gif
 
 #### Creating a pipeline
 
-Inorder to conserve compute resources and allow for cacheing you might want to split up your task into multiple sub tasks. AME supports pipelines of Tasks with individual requirenments. All of the project context is carried over between steps in the pipeline so if your first task saves files to the project directory, they will be available in the next step.
+Inorder to conserve compute resources and allow for caching you might want to split up your task into multiple sub tasks. AME supports pipelines of Tasks with individual requirenments. All of the project context is carried over between steps in the pipeline so if your first task saves files to the project directory, they will be available in the next step.
 
 TODO: gif
 

ame-cli/src/lib.rs

@@ -25,7 +25,7 @@ pub enum Error {
     EmptyProjectField(String),
 
     #[error("The project file is in a bad state: {0}")]
-    MisConfiguredProject(String),
+    MissConfiguredProject(String),
 
     #[error("Could not find a task with the given name: {0} in the project file")]
     MissingTaskTemplate(String),

ame-cli/src/project.rs

@@ -67,7 +67,7 @@ impl Project {
             task_templates.iter().filter(|t| t.name == name).collect();
 
         if valid_task_templates.len() > 1 {
-            return Err(Error::MisConfiguredProject(
+            return Err(Error::MissConfiguredProject(
                 "found multiple tasks templates with the same name".to_string(),
             ));
         }

client/src/lib.rs

@@ -28,7 +28,7 @@ impl CreateTaskRequest {
     pub fn new(task_name: &str, task_template: TaskTemplate) -> Self {
         Self {
             id: Some(TaskIdentifier::from(task_name)),
-            templat: Some(task_template),
+            template: Some(task_template),
         }
     }
 }