Labs for Gloo AI Gateway Have Arrived!
AI is making waves across industries, with an expected annual growth rate of 37.3% over the next decade. If you’re integrating AI gateways into your applications, you know it can be a complex process requiring time and resources. That’s where Gloo AI Gateway from Solo.io comes in. Building on Gloo Gateway, Gloo AI Gateway brings the same speed, security, and scalability to your AI applications.
Gloo AI Gateway streamlines deployment, cuts down development friction, and eliminates boilerplate code and errors. You get robust security to protect your applications and data, along with advanced governance controls. Plus, it scales effortlessly, supporting high-volume, zero-downtime AI connectivity. Whether you need multi-LLM (Large Language Model) provider support, API key management, consumption control, prompt management, or retrieval augmented generation (RAG), Gloo AI Gateway has you covered.
There’s also no substitute for hands-on experience. Trying out the technology yourself is a must for understanding its capabilities and how it fits into your workflows. That’s why we’ve launched a set of four short hands-on technical labs, available for free, to help you explore Gloo AI Gateway.
Keep reading to learn more about each of the hands-on labs, or feel free to go sign up for them now:
- Credentials and Access Control
- Prompt Management and Prompt Guards
- Rate Limiting and Model Failover
- Retrieval Augmented Generation (RAG) and Semantic Caching
Credentials and Access Control Labs
These labs highlight the essential features for integrating AI seamlessly into your applications: “Credential Management” and “Access Control.”
Part One: Managing LLM Provider Credentials with Gloo AI Gateway
In this lab, you’ll learn to configure Gloo AI Gateway for automated authorization management with LLM APIs. Begin by setting up environment variables with your API keys, securely storing them in Kubernetes secrets. Then, create Upstream resources to define LLM model properties and reference the stored keys. Finally, configure HTTPRoute resources to direct requests to both Open AI and Mistral AI APIs, testing the setup by sending prompts.
Part Two: Controlling Access to LLM providers with Gloo AI Gateway
In this access control exercise, you’ll use JSON Web Tokens (JWTs) to secure LLM provider APIs. JWTs authenticate users and offer precise control based on roles and claims. Begin by defining a JWT provider in VirtualHostOption to validate incoming tokens with a public key. Generate JWTs for users with specific claims granting API access, configure RouteOptions to enforce these permissions, and test by sending requests with various JWTs.
Prompt Management and Prompt Guards Labs
These labs empower you with strategies to secure data integrity in LLM provider APIs using prompt guards through Gloo AI Gateway. Learn to defend against unauthorized access and manipulation, ensuring compliance and fostering trust in your APIs.
Part One: Managing Prompts and LLM Configuration with Gloo AI Gateway
Prompt management lies at the core of enhancing the capabilities of LLMs to generate accurate and relevant responses. Effective management of system prompts (which establish initial guidelines) and user prompts (which provide specific contextual inputs) significantly elevates the coherence and quality of model outputs.
- System prompts encompass foundational instructions, behavioral guidelines, and background details, laying the groundwork for the model’s operation.
- Meanwhile, user prompts encompass direct queries, sequential inputs, and task-specific instructions, ensuring precise responses tailored to user requirements.
This approach not only streamlines the interaction process but also optimizes the model’s performance by directing its focus on pertinent information.
Part Two: Content Safety with Prompt Guard
In this lab, explore securing data interactions within LLM provider APIs, vulnerable to sophisticated attacks compromising data integrity. Using Gloo AI Gateway, you can implement prompt guards to detect and block sensitive content like credit card numbers, ensuring compliance and preventing misuse. Configuring RouteOption resources with prompt guards and pattern matching effectively shielded sensitive information, enhancing data protection and bolstering the reliability of API-driven applications.
Rate Limiting and Model Failover Labs
These labs focus on configuring backup models with Gloo AI Gateway to ensure uninterrupted service. Explore how failover mechanisms automatically switch to redundant models like gpt-4.0-turbo and gpt-3.5-turbo, maintaining reliability and resilience in scenarios where primary models encounter issues such as downtime or latency spikes.
Part One: Rate Limiting and Usage Management
Learn practical strategies to safeguard your APIs in this rate limiting lab, designed to enhance security and stability while managing costs. These labs focus on controlling token usage within LLM provider APIs using Gloo AI Gateway. Implement rate limiting to enforce budget constraints across teams, create JWT tokens for controlled access, and set per-user rate limits based on token claims. Monitor usage metrics with Grafana to optimize resource allocation, ensuring your APIs remain resilient and cost-effective in real-world applications.
Part Two: Model Failover
Discover the power of failover mechanisms in the lab focused on ensuring uninterrupted service in LLM provider APIs. Failover switches dynamically to backup models such as gpt-4.0-turbo and gpt-3.5-turbo if the primary model, like gpt-4o, faces issues like downtime or high latency. Configure upstreams and RouteOptions in Gloo AI Gateway to seamlessly redirect requests to alternative models, ensuring reliability and resilience in LLM-dependent applications. See this failover strategy in action as requests are automatically rerouted, maintaining continuous operation and minimizing disruption during unforeseen model failures.
Retrieval Augmented Generation (RAG) and Semantic Caching Labs
Explore advanced features like semantic caching and RAG with Gloo AI Gateway. Learn to optimize query performance with semantic caching, reducing response times and API costs, and implement RAG to enhance model accuracy by augmenting prompts with relevant data, ensuring smoother interactions with language models for superior application performance.
Part One: Retrieval Augmented Generation (RAG)
RAG enhances LLM provider APIs by integrating context retrieved from datasets directly into prompts, improving response accuracy and mitigating model hallucinations. Enabled through Gloo AI Gateway, this lab guides you in securely configuring API credentials and implementing RAG. See how this feature refines query responses by embedding relevant information, ensuring precise outputs tailored to user inquiries.
Part Two: Semantic Caching
Semantic caching in Gloo AI Gateway enhances query performance by reusing responses for semantically similar prompts, leveraging Redis as the efficient caching datastore within Kubernetes. Through deploying a RouteOption resource, developers configure Gloo AI Gateway to utilize Redis, ensuring rapid retrieval of cached responses for repeated queries, reducing response latency. See firsthand the benefits of semantic caching, where even slight variations in prompts trigger cached responses marked by the x-gloo-semantic-cache: hit header, showcasing its effectiveness in optimizing API performance and minimizing operational costs.
Get Started with Gloo AI Gateway
Ready to elevate your AI integration? Gloo AI Gateway is designed to make your journey smoother, faster, and more secure. These hands-on technical labs will help you gain invaluable experience and insights into how Gloo AI Gateway can transform your application development process. Sign up to explore our AI gateway solutions in a practical, interactive environment.
If you’re considering or running GenAI apps, feel free to reach out to us here, or sign up for a demo to learn more.
