Getting started#
Can my data be recovered once I've terminated my instance?#
Warning
We cannot recover your data once you've terminated your instance! Before terminating an instance, make sure to back up all data that you want to keep.
If you want to save data even after you terminate your instance, create a persistent storage file system .
Note
The persistent storage file system must be attached to your instance before you start your instance. The file system cannot be attached to your instance after you start your instance.
When you create a file system, a directory with the name of your file system
is created in your home directory. For example, if the name of your file
system is PERSISTENT-FILE-SYSTEM, the directory is created at
/home/ubuntu/PERSISTENT-FILE-SYSTEM
. Data not stored in this directory
is erased once you terminate your instance and cannot be recovered.
Can I pause my instance instead of terminating it?#
It currently isn't possible to pause (suspend) your instance rather than terminating it. But, this feature is in the works.
Until this feature is implemented, you can use persistent storage file systems to imitate some of the benefits of being able to pause your instance.
Do you support Kubernetes (K8s)?#
Yes. You can install and use Kubernetes, also known as K8s, on on-demand instances and 1-Click Clusters .
Additionally, Managed Kubernetes and Pre-Installed Kubernetes are available for 1-Click Clusters and Reserved Cloud .
Managed Kubernetes includes:
- Kubernetes installation and upgrades.
- Control plane maintenance and high-availability.
- NVIDIA GPU Operator installed and configured to deploy and manage NVIDIA GPUs in a Kubernetes cluster.
- Detecting node failures, node pool adjustment and failed hardware replacement.
- Gathering chassis and cluster metrics and proactive monitoring.
See our Managed Kubernetes Product Outline to learn more.
Why can't my program find the NVIDIA cuDNN library?#
Unfortunately, the NVIDIA cuDNN license limits how cuDNN can be used on our instances.
On our instances, cuDNN can only be used by the PyTorch® framework and TensorFlow library installed as part of Lambda Stack.
Other software, including PyTorch and TensorFlow installed outside of Lambda Stack, won't be able to find and use the cuDNN library installed on our instances.
Tip
Software outside of Lambda Stack usually looks for the cuDNN library files
in /usr/lib/x86_64-linux-gnu
. However, on our instances, the cuDNN library
files are in /usr/lib/python3/dist-packages/tensorflow
.
Creating symbolic links, or "symlinks," for the cuDNN library files might allow your program to find the cuDNN library on our instances.
Run the following command to create symlinks for the cuDNN library files:
How do I open Jupyter Notebook on my instance?#
To open Jupyter Notebook on your instance:
- In the GPU instances dashboard , find the row for your instance.
- Click Launch in the Cloud IDE column.
Tip
Watch Lambda's GPU Cloud Tutorial with Jupyter Notebook video on YouTube to learn more about using Jupyter Notebook on Lambda GPU Cloud instances.
How do I upgrade Python?#
Warning
Upgrading Python, that is, replacing the preinstalled Python version with a newer version, will break your instance.
Instead of upgrading Python, you should install your desired version of Python alongside the preinstalled version, and use your desired version in a virtual environment.
To install another version of Python alongside the preinstalled version:
-
Run the following command:
Replace
VERSION
with the Python version you want to install, for example,3.13
. Make sure-full
is appended to the Python version, otherwise, you won't have thevenv
module needed to create Python virtual environments.As a complete example, if you want to install Python version 3.13, run:
-
Run the following command to create a Python virtual environment:
Replace
VERSION
with the Python version you installed in the previous step. ReplaceVENV-NAME
with the name you want to give your virtual environment. -
Run the following command to activate the virtual environment:
Replace
VENV-NAME
with the name you gave your virtual environment.As a complete example, if you want to create a virtual environment named
my-virtual-environment
using Python version 3.13 (installed in the example in the previous step), run: -
Run the following command to confirm that your virtual environment is using your desired Python version:
Can I upgrade to the latest Ubuntu release?#
Warning
Do not run sudo do-release-upgrade
or try to upgrade to the latest
Ubuntu release. Doing so will break Jupyter
Notebook and unless you
have SSH access to your instance, Lambda Support
won't be able to help you recover your data.
Jupyter Notebook on our instances is configured and tested for the preinstalled version of Python. Upgrading to the latest Ubuntu release will replace the preinstalled version of Python and make Jupyter Notebook inaccessible.
Is it possible to use more than one SSH key?#
It's possible to allow more than one SSH key to access your instance. To do so,
you need to add public keys to ~/.ssh/authorized_keys
. You can do this with
the echo
command.
Tip
You can also import SSH keys from GitHub.
Note
This FAQ assumes that you've already generated another SSH key pair, that is, a private key and a public key.
Public keys look like this:
SSH into your instance as you normally do and run:
Replace PUBLIC-KEY
with the public key you want to add to your instance.
Make sure to keep the single quotes (' '
).
You should now be able to log into your instance using the SSH key you just added.
Tip
You can make sure the public key has been added by running:
The last line of output should be the public key you just added.
What SSH key formats are supported?#
You can add SSH keys in the following formats using the dashboard or the Cloud API:
- OpenSSH (the format
ssh-keygen
uses by default when generating keys) - RFC4716 (the format PuTTYgen uses when you save a public key)
- PKCS8
- PEM
Note
-
OpenSSH keys look like:
-
RFC4716 keys begin with:
-
PKCS8 keys begin with:
-
PEM keys begin with, for example:
How long does it take for instances to launch?#
Single-GPU instances usually take 3-5 minutes to launch.
Multi-GPU instances usually take 10-15 minutes to launch.
Note
Jupyter Notebook and Demos can take a few minutes after an instance launches to become accessible.
Note
Billing starts the moment an instance begins booting.
What network bandwidth does Lambda GPU Cloud provide?#
Note
Some sites limit transfer speeds. This is known as bandwidth throttling.
Lambda GPU Cloud doesn't limit your transfer speeds but can't control other sites' use of bandwidth throttling.
Further, real-world network bandwidth depends on a variety of factors, including the total number of connections opened by your applications and overall network utilization.
Utah, USA region (us-west-3)#
The bandwidth between instances in our Utah, USA region (us-west-3) can be up to 200 Gbps.
The total bandwidth from this region to the Internet can be up to 20 Gbps.
Texas, USA region (us-south-1)#
The bandwidth between instances in our Texas, USA region (us-south-1) can be up to 200 Gbps.
The total bandwidth from this region to the Internet can be up to 20 Gbps.
Note
We're in the process of testing the network bandwidth in our other regions.
How do I learn my instance's private IP address and other info?#
You can learn your instance's private IP
address with the
ip
command.
You can learn what ports are open on your
instance
with the nmap
command.
Learn your instance's private IP address#
To learn your instance's private IP address, SSH into your instance and run:
The above command will output, for example:
In the above example, the instance's private IP address is 10.19.51.71.
Tip
If you want your instance's private IP address and only that address, run the following command instead:
ip -4 -br addr show enp5s0 | grep -Eo '(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)'
The above command will output, for example:
Learn what ports on your instance are publicly accessible#
You can use Nmap to learn what ports on your instance are publicly accessible, that is, reachable over the Internet.
Note
The instructions, below, assume you're running Ubuntu on your computer.
First, install Nmap on your computer (not on your instance) by running:
Next, run:
Replace INSTANCE-IP-ADDRESS
with your instance's IP address, which you can
get from the Cloud dashboard .
The command will output, for example:
Starting Nmap 7.80 ( https://nmap.org ) at 2023-01-11 13:22 PST
Nmap scan report for 129.159.46.35
Host is up (0.041s latency).
Not shown: 999 filtered ports
PORT STATE SERVICE
22/tcp open ssh
Nmap done: 1 IP address (1 host up) scanned in 6.42 seconds
In the above example, TCP port 22 (SSH) is publicly accessible.
Note
If nmap
doesn’t show TCP/22 (SSH) or any other ports open, your:
- Instance might be terminated. Check the GPU Instances dashboard to find out.
- Firewall rules might be blocking incoming connections to your instance.
Note
nmap -Pn INSTANCE-IP-ADDRESS
only scans the 1,000 most common TCP ports.
How do I close my account?#
To close your Lambda GPU Cloud account:
-
Back up all of your data on your instances as well as in your persistent storage file systems.
!!! tip
-
Terminate all of your instances from the Cloud dashboard or using the Cloud API.
-
Delete all of your persistent storage file systems.
-
In the Cloud dashboard, under Settings , click Close my account. Carefully read the warning in the dialog box that appears. To proceed with closing your account, type in close account, then click Close account.