Ship Software 10x Faster with AI-Powered Orchestration
Transform your 30+ disconnected tools into a unified platform. Achieve 100% standardization. Give developers self-service.




AI Accelerated Development not Delivery
Delivery is still Fragmented with multiple tools orchestrated through humans
Where Code Gets Stuck
- AI writes features in hours. Infra takes weeks.
- 30+ tools need manual coordination per deploy.
- Weeks for environments.
- Every team needs custom infra setup.
Orchestration Closes the Gap
- Deploy code as fast as you merge.
- Unifed Orchestration. Zero manual steps.
- Self-service environments in minutes.
- Reusable blueprints & standardized deployments.
Three Steps towards Intelligent Orchestration
Modern Delivery is missing a unified model and a way to orchestrate
Platform Team Builds Contracts
Centralized, reusable infrastructure modules with standardized interfaces
- Eliminate fragmentation across teams
- Contracts = Centrally sourced modules
Developers create a Blueprint
Developers use contracts to provide a blueprint of their project
- Drag-and-drop modules to create their blueprint
- Blueprint = Single Unifed Model
Orchestrator puts them together
Joins Blueprints and Contracts to create environments
- Automated delivery of Terraform, Helm, CI/CD, and monitoring
- Unifed Orchestration = Zero Drift
Platform Team Builds Contracts
Centralized, reusable infrastructure modules with standardized interfaces
- Eliminate fragmentation across teams
- Contracts = Centrally sourced modules
Developers create a Blueprint
Developers use contracts to provide a blueprint of their project
- Drag-and-drop modules to create their blueprint
- Blueprint = Single Unifed Model
Orchestrator puts them together
Joins Blueprints and Contracts to create environments
- Automated delivery of Terraform, Helm, CI/CD, and monitoring
- Unifed Orchestration = Zero Drift
Viewing: Platform Team Builds Contracts
The Problems You're Solving Today
Without an orchestrator, challenges compound as you scale - but the right solutions scale with your organization
Managing Environments
New deployments for regional expansion & customer deployments
- Launch a new environment in 15 mins
- Zero Configuration Drifts
- Multi-cloud environments from a single blueprint
Environment-as-a-commodity
" We manage 15+ global deployments with 20+ services each. Facets made this complex setup surprisingly efficient."

What Facets Can Orchestrate
Plus Extend the Integration suite with Terraform
Technology & Architecture
Built for Enterprise Reality
Enterprise Deployment
Your infrastructure, your control, your data
Terraform-Native Orchestrator
All operations transparent and auditable through Terraform
AI Agent Ecosystem
Next-generation AI agents with organizational context
Stay Updated with Facets
Latest insights, customer stories, and live content
Infrastructure Platform Engineering: Facets Mentioned in Gartner's Reference Architecture Brief
Gartner’s Reference Architecture Brief: Infrastructure Platform Engineering named Facets Cloud in its Catalog access section.

AI DevOps Reality: Field Report from the Enterprise Trenches
Understand the real-world impact of AI in DevOps with AWS Senior Container Specialist, Sanjeev Ganjihal

AI x DevOps with Sanjeev Ganjihal - AWS Solutions Architect
Join Rohit Raveendran as he sits down with Sanjeev Ganjihal, Senior Container Specialist at AWS and one of the first 100 Kubernetes certified professionals globally. This deep dive conversation explores the transformative shift from traditional DevOps to AI-powered operations and what it means for the future of infrastructure management. ### Evolution of DevOps and SRE Explore Sanjeev's unique journey from being an early Kubernetes adopter in 2017 to becoming a specialist in AI/ML operations at AWS. Discover how the industry has evolved from manual operations to automated, intelligent infrastructure management and what this means for traditional SRE roles. ### Multi-LLM Strategies in Practice Get insider insights into Sanjeev's personal AI development toolkit, including how he uses Claude, Q Developer, and local models for different tasks. Learn practical multi-LLM routing strategies, code review workflows, and how to choose the right AI tool for specific infrastructure challenges. ### Kubernetes Meets AI Infrastructure Understand the unique challenges of running AI workloads on Kubernetes, from GPU resource management to model serving at scale. Sanjeev shares real-world experiences from supporting financial services customers and the patterns that work for high-performance computing environments. ### The Future of AIOps Dive into discussions about Model Context Protocol (MCP), autonomous agents, and the concept of "agentic AI" that will define 2025. Learn how these technologies are reshaping the relationship between humans and infrastructure, with the memorable analogy of "you are Krishna steering the chariot." ### Security and Best Practices Explore critical security considerations when implementing AI in DevOps workflows, including safe practices for model deployment, data handling, and maintaining compliance in enterprise environments. Perfect for DevOps engineers, SREs, platform engineers, and technical leaders navigating the intersection of AI and infrastructure operations.

Kubernetes Agent for Natural Language Debugging
Discover how Facets' new Kubernetes Agent revolutionizes cluster management by enabling natural language debugging and secure troubleshooting. This episode showcases our AI-powered orchestrator that maintains proper guardrails and permissions while making Kubernetes operations conversational and intuitive. ### Live Demonstrations & Key Features Watch real-time troubleshooting as we diagnose a pod restart issue caused by missing sidecar files, identify and fix Redis deployment memory configuration problems, and demonstrate CPU usage analysis with Prometheus integration. See how the agent maintains security through user-scoped access controls while providing powerful debugging capabilities. ### Technical Deep Dive Explore the architecture behind Facets' Kubernetes Agent and how it orchestrates AI agents with secure infrastructure access. Learn about multi-tool integration supporting kubectl, Helm, and pod exec operations, plus natural language debugging that works with your existing permissions and kubeconfig setup. ### Audience Q&A Highlights Get answers to key questions about historical log analysis capabilities, chat history persistence and session management, integration possibilities with tools like Cursor and MCP, and comparisons with existing tools like ChatGPT and K9s. Plus, discover future plans for custom tool integration and blueprint generation. ### Perfect For DevOps Engineers looking to streamline Kubernetes troubleshooting workflows, Platform Engineers interested in AI-powered infrastructure management, Site Reliability Engineers seeking efficient debugging solutions, and Development Teams wanting to reduce time spent on cluster-related issues.

Why Speed is the Only Moat: Acceldata’s Approach to Developer Velocity
Join Acceldata's engineering leadership as they reveal how speed became their ultimate competitive advantage. This isn't just another productivity talk — it's a deep dive into the systematic approach that transformed their development organization into a velocity powerhouse. In enterprise software delivery, speed has long been treated as a tradeoff, something to be sacrificed in favor of reliability, security, and stability. Acceldata, serving data observability needs for global enterprises, takes the opposite view: sustained speed is the only durable competitive moat. Key insights you'll gain: - **Friction assessment:** A practical method to find where developers lose time (local setup, environment drift, CI/CD bottlenecks) - **Platform blueprint:** How an internal platform standardizes the happy path for development - **Service templates:** Consistent starting points for new projects - **Golden pipelines:** Battle-tested CI/CD with sensible defaults - **Ephemeral environments:** On‑demand environments for realistic validation - **Progressive delivery:** Safe rollout patterns that reduce shipping anxiety - **Automated rollbacks:** Safety nets that make it cheap to change direction Measurement strategy: - **Core metrics:** Cycle time, change failure rate, lead time, deployment frequency - **Keep it practical:** Focus on a few signals that reflect real work, not hundreds of vanity metrics Cultural transformation: - **Autonomy with alignment:** Empower teams while keeping standards - **Lifecycle automation:** Automate the unglamorous but critical parts - **Paved‑road workflows:** Standardized paths with room to experiment - **Development observability:** Visibility across the entire delivery flow - **Feedback loops:** Continuous, high‑quality feedback to drive improvement Real‑world results: - **Shipping velocity:** 30 major releases in six months - **Service creation:** New services in minutes, not days - **Onboarding:** Hours instead of weeks - **Deployments:** Higher frequency with greater reliability - **Process visibility:** Clear insight into bottlenecks and waste This session provides a complete roadmap—from friction mapping to platform capabilities to the metrics that prove impact. It’s designed for engineering leaders, platform engineers, DevOps teams, and team leads looking to scale velocity without sacrificing reliability.

MPL Spinoff—GGX Transforms DevOps with Facets' Platform Engineering Solution
Good Game Exchange (GGX) achieved a 3X boost in Ops efficiency, expedited cloud migration by 75% to GCP, and streamlined developer workflows by leveraging Facets' platform engineering approach

Begin your orchestration journey today
Experience Facets in action with a founder-led demo.