From 43c1e15314298d946a5cfa2974082632d256a9a2 Mon Sep 17 00:00:00 2001 From: Romil Bhardwaj Date: Tue, 16 Jul 2024 15:12:45 -0700 Subject: [PATCH 01/11] Add comparison page --- docs/source/docs/index.rst | 1 + docs/source/reference/comparison.rst | 172 +++++++++++++++++++++++++++ 2 files changed, 173 insertions(+) create mode 100644 docs/source/reference/comparison.rst diff --git a/docs/source/docs/index.rst b/docs/source/docs/index.rst index 5a648dbcda4..2384e4a3e9b 100644 --- a/docs/source/docs/index.rst +++ b/docs/source/docs/index.rst @@ -161,6 +161,7 @@ Contents ../reference/tpu ../reference/logging ../reference/faq + Comparing SkyPilot <../reference/comparison> .. toctree:: diff --git a/docs/source/reference/comparison.rst b/docs/source/reference/comparison.rst new file mode 100644 index 00000000000..83814288cf7 --- /dev/null +++ b/docs/source/reference/comparison.rst @@ -0,0 +1,172 @@ +.. _sky-compare: + +Comparing SkyPilot with other systems +===================================== + +We are often asked "How does SkyPilot compare against XYZ?". Providing an unbiased and up-to date answer for such questions is not easy, especially when the differences may be qualitative. + +This page tries to provide a comparison of SkyPilot with other systems, focusing on the unique features of SkyPilot. We welcome feedback and contributions to this page. + + +SkyPilot vs Vanilla Kubernetes +------------------------------ + +Kubernetes is a powerful system for managing containerized applications. SkyPilot builds on top of Kubernetes to provide a more powerful and easier-to-use framework for running AI workloads. + +Faster iteration with interactive development +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +.. figure:: https://blog.skypilot.co/ai-on-kubernetes/images/k8s_vs_skypilot_iterative_v2.png + :align: center + :width: 80% + :alt: Iterative Development with Kubernetes vs SkyPilot + + Iterative Development with Kubernetes requires tedious updates to docker images and multiple steps to update the training run. With SkyPilot, all you need is sky launch. + +Interactive workflows benefit from faster iteration with SkyPilot. For example, a common workflow for AI engineers is to iteratively develop and train models by tweaking code and hyperparameters by observing the training runs. + +* **With Kubernetes, a single iteration is a multi-step process** involving building a Docker image, pushing it to a registry, updating the Kubernetes YAML and then deploying it. + +* **With SkyPilot, a single sky launch takes care of everything.** Behind the scenes, SkyPilot provisions pods, installs all required dependencies, executes the job, returns logs and provides SSH and VSCode access to debug. + + +Simpler YAMLs +^^^^^^^^^^^^^ + +Consider serving `Gemma `_ with `vLLM `_ on Kubernetes: + +* **With vanilla Kubernetes**, you need over `65 lines of Kubernetes YAML `_ to launch a Gemma model served with vLLM. +* **With SkyPilot**, an easy-to-understand `19-line YAML `_ launches a pod serving Gemma with vLLM. + +Here is a side-by-side comparison of the YAMLs for serving Gemma with vLLM on SkyPilot vs Kubernetes: + +.. raw:: html + +
+
+

SkyPilot

+
+           
+   envs:
+     MODEL_NAME: google/gemma-2b-it
+     HF_TOKEN: myhftoken
+
+   resources:
+     image_id: docker:vllm/vllm-openai:latest
+     accelerators: L4:1
+     ports: 8000
+
+   setup: |
+     conda deactivate
+     python3 -c "import huggingface_hub; huggingface_hub.login('${HF_TOKEN}')"
+
+   run: |
+     conda deactivate
+     echo 'Starting vllm openai api server...'
+     python -m vllm.entrypoints.openai.api_server \
+     --model $MODEL_NAME \
+     --tokenizer hf-internal-testing/llama-tokenizer \
+     --host 0.0.0.0
+           
+           
+
+
+

Kubernetes

+
+           
+   apiVersion: apps/v1
+   kind: Deployment
+   metadata:
+   name: vllm-gemma-deployment
+   spec:
+   replicas: 1
+   selector:
+     matchLabels:
+       app: gemma-server
+   template:
+     metadata:
+       labels:
+         app: gemma-server
+         ai.gke.io/model: gemma-1.1-2b-it
+         ai.gke.io/inference-server: vllm
+         examples.ai.gke.io/source: user-guide
+     spec:
+       containers:
+       - name: inference-server
+         image: us-docker.pkg.dev/vertex-ai/ vertex-vision-model-garden-dockers/pytorch-vllm-serve:20240527_0916_RC00
+         resources:
+           requests:
+             cpu: "2"
+             memory: "10Gi"
+             ephemeral-storage: "10Gi"
+             nvidia.com/gpu: 1
+           limits:
+             cpu: "2"
+             memory: "10Gi"
+             ephemeral-storage: "10Gi"
+             nvidia.com/gpu: 1
+         args:
+         - --model=$(MODEL_ID)
+         - --tensor-parallel-size=1
+         env:
+         - name: MODEL_ID
+           value: google/gemma-1.1-2b-it
+         - name: HUGGING_FACE_HUB_TOKEN
+           valueFrom:
+             secretKeyRef:
+               name: hf-secret
+               key: hf_api_token
+         volumeMounts:
+         - mountPath: /dev/shm
+           name: dshm
+       volumes:
+       - name: dshm
+         emptyDir:
+             medium: Memory
+       nodeSelector:
+         cloud.google.com/gke-accelerator: nvidia-l4
+   ---
+   apiVersion: v1
+   kind: Service
+   metadata:
+   name: llm-service
+   spec:
+   selector:
+     app: gemma-server
+   type: ClusterIP
+   ports:
+     - protocol: TCP
+       port: 8000
+       targetPort: 8000
+           
+           
+
+
+ + +Scale beyond single region/cluster +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +.. figure:: https://blog.skypilot.co/ai-on-kubernetes/images/failover.png + :align: center + :width: 80% + :alt: Scaling beyond a single region Kubernetes cluster with SkyPilot + + If the Kubernetes cluster is full, SkyPilot can get GPUs from other regions and clouds to run your tasks at the lowest cost. + +Kubernetes deployments are typically contained to a single region in a single cluster. +This is because longer latencies across regions causes etcd, the store for Kubernetes state, to timeout and fail [1]_ [2]_ [3]_. + +Being restricted to a single region/cloud with Vanilla Kubernetes has two drawbacks: + +1. `Availability is reduced by up to 29% `_ because you cannot utilize +available capacity elsewhere. + +2. `Costs increase by 2.4x `_ as you are unable to +take advantage of cheaper resources in other regions. + +SkyPilot was designed to scale across clouds and regions - it allows you to run your tasks on your Kubernetes cluster, and burst to more regions and clouds if needed. In doing so, SkyPilot ensures that your tasks are always running in the most cost-effective region, while maintaining high availability. + +.. [1] `etcd FAQ `_ +.. [2] `"Multi-region etcd cluster performance issue" on GitHub `_ +.. [3] `DevOps StackExchange answer `_ From 47a2e053a3acc0c116e6b2963cad584ac09f3f1c Mon Sep 17 00:00:00 2001 From: Romil Bhardwaj Date: Mon, 29 Jul 2024 18:32:49 -0700 Subject: [PATCH 02/11] comments --- docs/source/docs/index.rst | 2 +- docs/source/reference/comparison.rst | 46 ++++++++++++---------------- 2 files changed, 21 insertions(+), 27 deletions(-) diff --git a/docs/source/docs/index.rst b/docs/source/docs/index.rst index 2384e4a3e9b..d5d73197074 100644 --- a/docs/source/docs/index.rst +++ b/docs/source/docs/index.rst @@ -161,7 +161,7 @@ Contents ../reference/tpu ../reference/logging ../reference/faq - Comparing SkyPilot <../reference/comparison> + SkyPilot vs. Other Systems <../reference/comparison> .. toctree:: diff --git a/docs/source/reference/comparison.rst b/docs/source/reference/comparison.rst index 83814288cf7..bad05cc0780 100644 --- a/docs/source/reference/comparison.rst +++ b/docs/source/reference/comparison.rst @@ -3,7 +3,7 @@ Comparing SkyPilot with other systems ===================================== -We are often asked "How does SkyPilot compare against XYZ?". Providing an unbiased and up-to date answer for such questions is not easy, especially when the differences may be qualitative. +We are often asked "How does SkyPilot compare with XYZ?". Providing an unbiased and up-to date answer for such questions is not easy, especially when the differences may be qualitative. This page tries to provide a comparison of SkyPilot with other systems, focusing on the unique features of SkyPilot. We welcome feedback and contributions to this page. @@ -11,23 +11,23 @@ This page tries to provide a comparison of SkyPilot with other systems, focusing SkyPilot vs Vanilla Kubernetes ------------------------------ -Kubernetes is a powerful system for managing containerized applications. SkyPilot builds on top of Kubernetes to provide a more powerful and easier-to-use framework for running AI workloads. +Kubernetes is a powerful system for managing containerized applications. :ref:`Using SkyPilot to access your Kubernetes cluster ` boosts developer productivity and allows you to scale your infra beyond a single Kubernetes cluster. -Faster iteration with interactive development -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +Faster iteration speed +^^^^^^^^^^^^^^^^^^^^^^ .. figure:: https://blog.skypilot.co/ai-on-kubernetes/images/k8s_vs_skypilot_iterative_v2.png :align: center - :width: 80% + :width: 95% :alt: Iterative Development with Kubernetes vs SkyPilot - Iterative Development with Kubernetes requires tedious updates to docker images and multiple steps to update the training run. With SkyPilot, all you need is sky launch. + Iterative Development with Kubernetes requires tedious updates to Docker images and multiple steps to update the training run. With SkyPilot, all you need is one CLI (``sky launch``). -Interactive workflows benefit from faster iteration with SkyPilot. For example, a common workflow for AI engineers is to iteratively develop and train models by tweaking code and hyperparameters by observing the training runs. +SkyPilot provides faster iteration for interactive development. For example, a common workflow for AI engineers is to iteratively develop and train models by tweaking code and hyperparameters by observing the training runs. * **With Kubernetes, a single iteration is a multi-step process** involving building a Docker image, pushing it to a registry, updating the Kubernetes YAML and then deploying it. -* **With SkyPilot, a single sky launch takes care of everything.** Behind the scenes, SkyPilot provisions pods, installs all required dependencies, executes the job, returns logs and provides SSH and VSCode access to debug. +* **With SkyPilot, a single command (``sky launch``) takes care of everything.** Behind the scenes, SkyPilot provisions pods, installs all required dependencies, executes the job, returns logs and provides SSH and VSCode access to debug. Simpler YAMLs @@ -45,9 +45,8 @@ Here is a side-by-side comparison of the YAMLs for serving Gemma with vLLM on Sk

SkyPilot

-
-           
-   envs:
+           
+   envs:
      MODEL_NAME: google/gemma-2b-it
      HF_TOKEN: myhftoken
 
@@ -66,15 +65,12 @@ Here is a side-by-side comparison of the YAMLs for serving Gemma with vLLM on Sk
      python -m vllm.entrypoints.openai.api_server \
      --model $MODEL_NAME \
      --tokenizer hf-internal-testing/llama-tokenizer \
-     --host 0.0.0.0
-           
-           
+ --host 0.0.0.0

Kubernetes

-
-           
-   apiVersion: apps/v1
+           
+   apiVersion: apps/v1
    kind: Deployment
    metadata:
    name: vllm-gemma-deployment
@@ -137,9 +133,7 @@ Here is a side-by-side comparison of the YAMLs for serving Gemma with vLLM on Sk
    ports:
      - protocol: TCP
        port: 8000
-       targetPort: 8000
-           
-           
+ targetPort: 8000
@@ -149,23 +143,23 @@ Scale beyond single region/cluster .. figure:: https://blog.skypilot.co/ai-on-kubernetes/images/failover.png :align: center - :width: 80% + :width: 95% :alt: Scaling beyond a single region Kubernetes cluster with SkyPilot If the Kubernetes cluster is full, SkyPilot can get GPUs from other regions and clouds to run your tasks at the lowest cost. -Kubernetes deployments are typically contained to a single region in a single cluster. -This is because longer latencies across regions causes etcd, the store for Kubernetes state, to timeout and fail [1]_ [2]_ [3]_. +A Kubernetes cluster is typically constrained to a single region in a single cloud. +This is because etcd, the control store for Kubernetes state, can timeout and fail when it faces highers latencies across regions [1]_ [2]_ [3]_. Being restricted to a single region/cloud with Vanilla Kubernetes has two drawbacks: -1. `Availability is reduced by up to 29% `_ because you cannot utilize +1. `GPU availability gets reduced `_ because you cannot utilize available capacity elsewhere. -2. `Costs increase by 2.4x `_ as you are unable to +2. `Costs increase `_ as you are unable to take advantage of cheaper resources in other regions. -SkyPilot was designed to scale across clouds and regions - it allows you to run your tasks on your Kubernetes cluster, and burst to more regions and clouds if needed. In doing so, SkyPilot ensures that your tasks are always running in the most cost-effective region, while maintaining high availability. +SkyPilot is designed to scale across clouds and regions: it allows you to run your tasks on your Kubernetes cluster, and burst to more regions and clouds if needed. In doing so, SkyPilot ensures that your tasks are always running in the most cost-effective region, while maintaining high availability. .. [1] `etcd FAQ `_ .. [2] `"Multi-region etcd cluster performance issue" on GitHub `_ From 5eac4fa637965f5bf5c77a9bf1f1650b1ad509a1 Mon Sep 17 00:00:00 2001 From: Romil Bhardwaj Date: Mon, 29 Jul 2024 18:33:30 -0700 Subject: [PATCH 03/11] margin --- docs/source/reference/comparison.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/reference/comparison.rst b/docs/source/reference/comparison.rst index bad05cc0780..f6d43578c48 100644 --- a/docs/source/reference/comparison.rst +++ b/docs/source/reference/comparison.rst @@ -45,7 +45,7 @@ Here is a side-by-side comparison of the YAMLs for serving Gemma with vLLM on Sk

SkyPilot

-
+           
    envs:
      MODEL_NAME: google/gemma-2b-it
      HF_TOKEN: myhftoken

From 6a12a14f83e7117b24d4c5dc8cdfe233ae1ee486 Mon Sep 17 00:00:00 2001
From: Romil Bhardwaj 
Date: Mon, 29 Jul 2024 18:43:36 -0700
Subject: [PATCH 04/11] Add line numbers

---
 docs/source/reference/comparison.rst | 132 +++++++++++++++------------
 1 file changed, 72 insertions(+), 60 deletions(-)

diff --git a/docs/source/reference/comparison.rst b/docs/source/reference/comparison.rst
index f6d43578c48..62697e08898 100644
--- a/docs/source/reference/comparison.rst
+++ b/docs/source/reference/comparison.rst
@@ -45,8 +45,11 @@ Here is a side-by-side comparison of the YAMLs for serving Gemma with vLLM on Sk
    

SkyPilot

-
-   envs:
+
+.. code-block:: yaml
+   :linenos:
+
+   envs:
      MODEL_NAME: google/gemma-2b-it
      HF_TOKEN: myhftoken
 
@@ -63,77 +66,86 @@ Here is a side-by-side comparison of the YAMLs for serving Gemma with vLLM on Sk
      conda deactivate
      echo 'Starting vllm openai api server...'
      python -m vllm.entrypoints.openai.api_server \
-     --model $MODEL_NAME \
-     --tokenizer hf-internal-testing/llama-tokenizer \
-     --host 0.0.0.0
+ --model $MODEL_NAME --tokenizer hf-internal-testing/llama-tokenizer \ + --host 0.0.0.0 + +.. raw:: html +

Kubernetes

-
-   apiVersion: apps/v1
+
+.. code-block:: yaml
+   :linenos:
+
+   apiVersion: apps/v1
    kind: Deployment
    metadata:
-   name: vllm-gemma-deployment
+     name: vllm-gemma-deployment
    spec:
-   replicas: 1
-   selector:
-     matchLabels:
-       app: gemma-server
-   template:
-     metadata:
-       labels:
+     replicas: 1
+     selector:
+       matchLabels:
          app: gemma-server
-         ai.gke.io/model: gemma-1.1-2b-it
-         ai.gke.io/inference-server: vllm
-         examples.ai.gke.io/source: user-guide
-     spec:
-       containers:
-       - name: inference-server
-         image: us-docker.pkg.dev/vertex-ai/ vertex-vision-model-garden-dockers/pytorch-vllm-serve:20240527_0916_RC00
-         resources:
-           requests:
-             cpu: "2"
-             memory: "10Gi"
-             ephemeral-storage: "10Gi"
-             nvidia.com/gpu: 1
-           limits:
-             cpu: "2"
-             memory: "10Gi"
-             ephemeral-storage: "10Gi"
-             nvidia.com/gpu: 1
-         args:
-         - --model=$(MODEL_ID)
-         - --tensor-parallel-size=1
-         env:
-         - name: MODEL_ID
-           value: google/gemma-1.1-2b-it
-         - name: HUGGING_FACE_HUB_TOKEN
-           valueFrom:
-             secretKeyRef:
-               name: hf-secret
-               key: hf_api_token
-         volumeMounts:
-         - mountPath: /dev/shm
-           name: dshm
-       volumes:
-       - name: dshm
-         emptyDir:
+     template:
+       metadata:
+         labels:
+           app: gemma-server
+           ai.gke.io/model: gemma-1.1-2b-it
+           ai.gke.io/inference-server: vllm
+           examples.ai.gke.io/source: user-guide
+       spec:
+         containers:
+         - name: inference-server
+           image: us-docker.pkg.dev/vertex-ai/ vertex-vision-model-garden-dockers/pytorch-vllm-serve:20240527_0916_RC00
+           resources:
+             requests:
+               cpu: "2"
+               memory: "10Gi"
+               ephemeral-storage: "10Gi"
+               nvidia.com/gpu: 1
+             limits:
+               cpu: "2"
+               memory: "10Gi"
+               ephemeral-storage: "10Gi"
+               nvidia.com/gpu: 1
+           command: ["python3", "-m", "vllm.entrypoints.api_server"]
+           args:
+           - --model=$(MODEL_ID)
+           - --tensor-parallel-size=1
+           env:
+           - name: MODEL_ID
+             value: google/gemma-1.1-2b-it
+           - name: HUGGING_FACE_HUB_TOKEN
+             valueFrom:
+               secretKeyRef:
+                 name: hf-secret
+                 key: hf_api_token
+           volumeMounts:
+           - mountPath: /dev/shm
+             name: dshm
+         volumes:
+         - name: dshm
+           emptyDir:
              medium: Memory
-       nodeSelector:
-         cloud.google.com/gke-accelerator: nvidia-l4
+         nodeSelector:
+           cloud.google.com/gke-accelerator: nvidia-l4
    ---
    apiVersion: v1
    kind: Service
    metadata:
-   name: llm-service
+     name: llm-service
    spec:
-   selector:
-     app: gemma-server
-   type: ClusterIP
-   ports:
-     - protocol: TCP
-       port: 8000
-       targetPort: 8000
+ selector: + app: gemma-server + type: ClusterIP + ports: + - protocol: TCP + port: 8000 + targetPort: 8000 + +.. raw:: html +
From 87e6c3aef57e22b6a3c49a5a9256c10562db7ebd Mon Sep 17 00:00:00 2001 From: Romil Bhardwaj Date: Mon, 29 Jul 2024 18:46:38 -0700 Subject: [PATCH 05/11] fix --- docs/source/reference/comparison.rst | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/reference/comparison.rst b/docs/source/reference/comparison.rst index 62697e08898..1edab63b64a 100644 --- a/docs/source/reference/comparison.rst +++ b/docs/source/reference/comparison.rst @@ -13,7 +13,7 @@ SkyPilot vs Vanilla Kubernetes Kubernetes is a powerful system for managing containerized applications. :ref:`Using SkyPilot to access your Kubernetes cluster ` boosts developer productivity and allows you to scale your infra beyond a single Kubernetes cluster. -Faster iteration speed +Faster developer velocity ^^^^^^^^^^^^^^^^^^^^^^ .. figure:: https://blog.skypilot.co/ai-on-kubernetes/images/k8s_vs_skypilot_iterative_v2.png From f333873eec6a6b85928d17a67d8ab2048c28c039 Mon Sep 17 00:00:00 2001 From: Romil Bhardwaj Date: Tue, 30 Jul 2024 08:59:04 -0700 Subject: [PATCH 06/11] fixes --- docs/source/reference/comparison.rst | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/docs/source/reference/comparison.rst b/docs/source/reference/comparison.rst index 1edab63b64a..c57c2d3ad34 100644 --- a/docs/source/reference/comparison.rst +++ b/docs/source/reference/comparison.rst @@ -14,7 +14,7 @@ SkyPilot vs Vanilla Kubernetes Kubernetes is a powerful system for managing containerized applications. :ref:`Using SkyPilot to access your Kubernetes cluster ` boosts developer productivity and allows you to scale your infra beyond a single Kubernetes cluster. Faster developer velocity -^^^^^^^^^^^^^^^^^^^^^^ +^^^^^^^^^^^^^^^^^^^^^^^^^ .. figure:: https://blog.skypilot.co/ai-on-kubernetes/images/k8s_vs_skypilot_iterative_v2.png :align: center @@ -23,11 +23,12 @@ Faster developer velocity Iterative Development with Kubernetes requires tedious updates to Docker images and multiple steps to update the training run. With SkyPilot, all you need is one CLI (``sky launch``). -SkyPilot provides faster iteration for interactive development. For example, a common workflow for AI engineers is to iteratively develop and train models by tweaking code and hyperparameters by observing the training runs. +SkyPilot provides faster iteration for interactive development. For example, a common workflow for AI engineers is to iteratively develop and train models by tweaking code and hyperparameters while observing the training runs. * **With Kubernetes, a single iteration is a multi-step process** involving building a Docker image, pushing it to a registry, updating the Kubernetes YAML and then deploying it. -* **With SkyPilot, a single command (``sky launch``) takes care of everything.** Behind the scenes, SkyPilot provisions pods, installs all required dependencies, executes the job, returns logs and provides SSH and VSCode access to debug. +* :strong:`With SkyPilot, a single command (`:literal:`sky launch`:strong:`) takes care of everything.` Behind the scenes, SkyPilot provisions pods, installs all required dependencies, executes the job, returns logs, and provides SSH and VSCode access to debug. + Behind the scenes, SkyPilot provisions pods, installs all required dependencies, executes the job, returns logs and provides SSH and VSCode access to debug. Simpler YAMLs @@ -44,7 +45,7 @@ Here is a side-by-side comparison of the YAMLs for serving Gemma with vLLM on Sk
-

SkyPilot

+

SkyPilot (19 lines)

.. code-block:: yaml :linenos: @@ -73,7 +74,7 @@ Here is a side-by-side comparison of the YAMLs for serving Gemma with vLLM on Sk
-

Kubernetes

+

Kubernetes (65 lines)

.. code-block:: yaml :linenos: @@ -165,7 +166,7 @@ This is because etcd, the control store for Kubernetes state, can timeout and fa Being restricted to a single region/cloud with Vanilla Kubernetes has two drawbacks: -1. `GPU availability gets reduced `_ because you cannot utilize +1. `GPU availability is reduced `_ because you cannot utilize available capacity elsewhere. 2. `Costs increase `_ as you are unable to From 026a0ef7c2e56e7d426613bf937ac5b0788554aa Mon Sep 17 00:00:00 2001 From: Romil Bhardwaj Date: Tue, 30 Jul 2024 09:15:50 -0700 Subject: [PATCH 07/11] fixes --- docs/source/reference/comparison.rst | 1 - 1 file changed, 1 deletion(-) diff --git a/docs/source/reference/comparison.rst b/docs/source/reference/comparison.rst index c57c2d3ad34..0899f073fed 100644 --- a/docs/source/reference/comparison.rst +++ b/docs/source/reference/comparison.rst @@ -28,7 +28,6 @@ SkyPilot provides faster iteration for interactive development. For example, a c * **With Kubernetes, a single iteration is a multi-step process** involving building a Docker image, pushing it to a registry, updating the Kubernetes YAML and then deploying it. * :strong:`With SkyPilot, a single command (`:literal:`sky launch`:strong:`) takes care of everything.` Behind the scenes, SkyPilot provisions pods, installs all required dependencies, executes the job, returns logs, and provides SSH and VSCode access to debug. - Behind the scenes, SkyPilot provisions pods, installs all required dependencies, executes the job, returns logs and provides SSH and VSCode access to debug. Simpler YAMLs From 19ca2b9257c15570571a12cbacf87799c5b19e46 Mon Sep 17 00:00:00 2001 From: Romil Bhardwaj Date: Wed, 31 Jul 2024 11:44:10 -0700 Subject: [PATCH 08/11] fixes --- docs/source/reference/comparison.rst | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/source/reference/comparison.rst b/docs/source/reference/comparison.rst index 0899f073fed..8b628e8c99d 100644 --- a/docs/source/reference/comparison.rst +++ b/docs/source/reference/comparison.rst @@ -3,9 +3,9 @@ Comparing SkyPilot with other systems ===================================== -We are often asked "How does SkyPilot compare with XYZ?". Providing an unbiased and up-to date answer for such questions is not easy, especially when the differences may be qualitative. +SkyPilot provides a framework for running AI and batch workloads on any infrastructure. Due to it's flexible design, its capabilities overlap with other systems and it can be used in conjunction with them to provide additional benefits. -This page tries to provide a comparison of SkyPilot with other systems, focusing on the unique features of SkyPilot. We welcome feedback and contributions to this page. +This page provides a comparison of SkyPilot with other systems, focusing on the unique benefits provided by SkyPilot. We welcome feedback and contributions to this page. SkyPilot vs Vanilla Kubernetes From bfdfbf07169289a72f5492b0b6c43162be4347d5 Mon Sep 17 00:00:00 2001 From: Romil Bhardwaj Date: Wed, 31 Jul 2024 11:46:06 -0700 Subject: [PATCH 09/11] fixes --- docs/source/reference/comparison.rst | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/docs/source/reference/comparison.rst b/docs/source/reference/comparison.rst index 8b628e8c99d..f0b36b8d5af 100644 --- a/docs/source/reference/comparison.rst +++ b/docs/source/reference/comparison.rst @@ -44,7 +44,7 @@ Here is a side-by-side comparison of the YAMLs for serving Gemma with vLLM on Sk
-

SkyPilot (19 lines)

+

SkyPilot (19 lines)

.. code-block:: yaml :linenos: @@ -73,7 +73,7 @@ Here is a side-by-side comparison of the YAMLs for serving Gemma with vLLM on Sk
-

Kubernetes (65 lines)

+

Kubernetes (65 lines)

.. code-block:: yaml :linenos: From ff8fa7186f4a8f076cd123523718889d9d1cdd14 Mon Sep 17 00:00:00 2001 From: Romil Bhardwaj Date: Wed, 31 Jul 2024 13:55:27 -0700 Subject: [PATCH 10/11] Add architecture figure --- .../images/k8s-skypilot-architecture-dark.png | Bin 0 -> 184816 bytes .../k8s-skypilot-architecture-light.png | Bin 0 -> 254050 bytes docs/source/reference/comparison.rst | 36 +++++++++++++++--- 3 files changed, 30 insertions(+), 6 deletions(-) create mode 100644 docs/source/images/k8s-skypilot-architecture-dark.png create mode 100644 docs/source/images/k8s-skypilot-architecture-light.png diff --git a/docs/source/images/k8s-skypilot-architecture-dark.png b/docs/source/images/k8s-skypilot-architecture-dark.png new file mode 100644 index 0000000000000000000000000000000000000000..bf21a1fd30393d6ee1293c206bf291ff2d9b0c7a GIT binary patch literal 184816 zcmeEudpy(o|M*I!K84P4ijwG5Bw^*2%dD&1m5kh#Q(71@WDMP;Lgap%F1s+dWNwp7 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-Scale beyond single region/cluster -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ +Scale beyond a single region/cluster +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ .. figure:: https://blog.skypilot.co/ai-on-kubernetes/images/failover.png :align: center