Get Started
Guide to deploy and scale your applications and machine learning workloads on Outpost.
Services
tab.Create Service
and provide a name and description.outpost.yaml
file with all necessary dependencies.1# Task name (optional), used for display purposes.
2name: my-task
3# Working directory (optional)
4workdir: ~/my-task-code
5resources:
6 cloud: aws # The cloud to use (optional).
7 # The region to use (optional)
8 region: us-east-1
9 # The zone to use (optional)
10 zone: us-east-1a
11 # 1x A10/A10G GPU
12 accelerators: {A10G:1, A10:1}
13 # Open port 8000
14 ports: [8000]
15
16env:
17 # set the environment variable MY_ENV_VAR to my-value
18 MY_ENV_VAR: my-value
19
20# Copy the contents of the current directory onto the remote machine
21workdir: .
22
23# Typical use: pip install -r requirements.txt
24# Invoked under the workdir (ie. can use its files)
25setup: |
26 echo "Running setup operations"
27
28# Typical uses:
29# torchserve ..
30# python -u -m vllm.entrypoints.openai.api_server ...
31# Invoked under the workdir (ie. can use its files)
32run: |
33 python -m http.server --port 8000
34
35service:
36 replica_policy:
37 min_replicas: 1
38 max_replicas: 5
39 # When the average QPS (queries per second) per replica goes above this number,
40 # Outpost will dynamically scale up the number of replicas running your service,
41 # up to a maximum of max_replicas.
42 # Similarly, when the average QPS per replica goes below this number, Outpost will
43 # scale down the number of replicas running your service, down to a minimum of min_replicas.
44 target_qps_per_replica: 10
45
46 readiness_probe:
47 # this is the endpoint path within your service that Outpost uses to check if your service is running
48 path: /