Overview
This comprehensive MLOps suite is designed to enhance and streamline the machine learning lifecycle, from data handling to deployment. Our product offers a robust set of features for the development process, ensuring efficiency, scalability, and security.
Highlights
- The platform includes security features to safeguard both data and models, complemented by extensive support services and thorough documentation. Integration with external tools and platforms is seamless, and cost management tools allow for detailed tracking and optimization per user and project. Our Guided ML Workflow and on-demand process-level visibility enhance productivity, while easy integration with DevOps practices supports agile development and continuous improvement.
- Our data pipeline streamlines the AI lifecycle by ensuring reproducible data builds. It features sharding and dynamic resource optimization. The system stops data contamination and corrects errors, guarding against lookahead. The feature store complements by enhancing data reusability and ensuring consistency across builds. The platform optimizes data for fast random access and integrates EDA and visualization tools to empower developers with deeper insights and clearer data interpretation.
- The model authoring features include deep learning capabilities with custom reusable components and automatic dimensionality transformations, underpinned by state-of-the-art architecture. Experiment tracking supports hyperparameter tuning, model evaluation, and evolution tracking. The model registry secures models, providing full traceability and preventing accidental deletions. Deployment is one-click and supports versatile environments (cloud, on-premises, edge).
Details
Typical total price
$3.678/hour
Pricing
Free trial
Instance type | Product cost/hour | EC2 cost/hour | Total/hour |
|---|---|---|---|
m6id.xlarge | $0.12 | $0.237 | $0.357 |
c5.9xlarge | $0.87 | $1.53 | $2.40 |
p4d.24xlarge | $20.32 | $32.773 | $53.093 |
g5.8xlarge Recommended | $1.23 | $2.448 | $3.678 |
g5.24xlarge | $4.05 | $8.144 | $12.194 |
g5.48xlarge | $8.10 | $16.288 | $24.388 |
Additional AWS infrastructure costs
Type | Cost |
|---|---|
EBS General Purpose SSD (gp3) volumes | $0.08/per GB/month of provisioned storage |
Vendor refund policy
Thank you for choosing our product. Please note, we do not offer refunds as our fees cover the immediate allocation and usage of digital resources. We encourage you to schedule an initial ideation meeting to ensure the product meets your needs. We value your feedback and are committed to your satisfaction.
Contact Us:
Email: help@lit.ai
Phone: (660) 250-0002
Your success is our priority, and we are here to assist you every step of the way.
Legal
Vendor terms and conditions
Content disclaimer
Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
LIT Platform Release Notes - Version 0.3.4 Release Date: August 28, 2024
We are excited to announce the release of version 0.3.4, which introduces several new features and improvements to enhance the LIT platform's functionality and user experience.
Improvements to Discovery:
- Full-Screen Discovery View: The Discovery view can now be expanded to full-screen mode, allowing for a more detailed and immersive exploration of your data.
- Search Tool in Discovery View: We've added a search tool to the Discovery view. When used, all packets matching that string will be highlighted on the chart, making it easier to identify specific data conditions.
Model Deployment
- Custom REST API Endpoint: AI models can now be deployed to a custom REST API endpoint managed by the platform. This new feature provides enhanced flexibility for integrating models into different applications. Access to this endpoint is fully logged and secured with token management, which users can control to ensure data security and compliance.
Improvements to Experiments:
- Server-Side Paging for Experiments Grid-View: We have implemented server-side paging to speed up the experiments grid-view. This enhancement is especially beneficial when live-monitoring multiple training sessions concurrently, each with tens of thousands of epochs, as it significantly reduces loading times.
- Model Weights Format Change: Model weights are now stored as .keras files instead of .h5 files. This change optimizes compatibility and performance with modern TensorFlow versions.
- Bug Fix for Archiving Experiments: A race condition that occurred when archiving large batches of experiments has been identified and resolved, ensuring smoother and more reliable data management.
Improvements to Assets:
- Optimized Table Sizing: The asset tables are now automatically sized for the best fit on your screen, improving readability and user experience.
- Sample Count in List Views: We have added a 'sample count' column to the asset list views. This allows users to quickly compare the total number of samples for each asset of multiple assets matching a search criteria in a single view. Administrative Improvements
- Sudo Access for Platform-Created Accounts: Accounts created within the platform can now be granted sudo access on the underlying machine. This new option provides administrators with greater flexibility in managing user permissions and system access.
Additional details
Usage instructions
To begin using the application after installation browse to the default endpoint. If the machine has not been provided with an SSL proxy be sure to use thehttp protocol, rather than https. Follow the instructions to bind the application to the ip address of your choice.
Full step-by-step instructions for installing and configuration LIT can be found here: https://docs.lit.ai/install/
Sensitive Customer Data
- Saved by Vendor No sensitive customer data is saved or retained by LIT or its authorized partners. All data is removed upon termination of instances and their associated volumes.
- Saved by customers All data saved by customer is saved to the /data folder on the host of the application. No customer data is ever moved or copied to any other host.
Data Encryption While the customer is extend the app by adding their own encryption to their data pipeline, LIT does not employ data encryption configuration out of the box other than encrypting passwords for identity, access control, and licensing. LIT uses Secure Hash Algorithm 256-bit for license generation. LIT (via Keycloak) uses Argon2 password hashing for identity and access control. Argon2 was the winner of the 2015 password hashing competition and is the recommended hashing algorithm by OWASP.
Data Decryption Not Applicable
Rotating credentials/keys
Rotation of credentials & keys can be accomplished using the administration console. Credentials for logging into the admin console can be found on the host where LIT is installed in the /opt/lit-server/api/.env file. Use the KEYCLOAK_ADMIN_USERNAME and KEYCLOAK_ADMIN_PASSWORD credentials contained therein to log into the Keycloak administrative console:
After updating keys and/or credentials, update the file /opt/lit-server/api/.env file to match. Follow your IT administrators best practices; by default the file permissions are 600.
Rotate keys Navigate to the LIT realm and select Clients. Under the lit-api client, update the client secret by generating a new secret and securely storing it here.
Rotate credentials Click on the account control in the upper-right corner. Select Manage. Select Expand Account security. Select Signing in. Click the Update button.
Assess & monitor health
- Navigate to your Amazon EC2 console and verify that you're in the correct region.
- Choose Instance and select your launched instance.
- Select the server to display your metadata page and choose the Status checks tab at the bottom of the page to review if your status checks passed or failed.
Resources
Vendor resources
Support
Vendor support
Support Channels:
Email Support: Reach out to us at help@lit.ai for any inquiries or issues you might encounter. Our technical support staff will respond within 24 hours.
Comprehensive User Guides: Detailed manuals covering all features are accessible at https://docs.lit.ai/ . These guides are designed to help you navigate the complexities of operation smoothly. In addition to operational guides, a detailed installation guide can be found at https://docs.lit.ai/install/ . A detailed guide covering first-time initialization can be found at https://docs.lit.ai/usage/ .
Video Tutorials: Visual learners can benefit from our step-by-step video tutorials available at https://tutor.lit.ai/ , which demonstrate key operations and functionalities.
Onsite Support: For enterprise-level packages, we offer the option of onsite support where our technicians will assist you at your location.
Customized Support Plans: Tailor a support plan that best fits your organization's needs. Contact our sales team for more information.
Our support team is equipped with the tools and knowledge to assist you, ensuring you have the best possible experience with our product. For any assistance, please do not hesitate to reach out through any of our support channels. Your success is our priority, and we look forward to supporting you every step of the way.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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