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
AI meets MLOps - Making sense of the mess
In this episode of AI x DevOps, Rohit sits down with Görkem Ercan, CTO at Jozu, a company building a DevOps platform for AI agents and models. Görkem, a veteran with over two decades of software experience (including contributions to the Eclipse Foundation), explains why MLOps is fundamentally different from traditional, deterministic DevOps—leading to extreme pipeline fragmentation. ### Standardization is Key Discover why OCI is the recognized standard for packaging AI/ML artifacts, and how the Model Packs project (with ByteDance, Red Hat, and Docker) is defining the artifact structure. Learn how standardization is bringing order to the fragmented MLOps landscape. ### Open Source Challenges Understand the critical challenges maintainers face when receiving large amounts of untested, verbose, AI-generated code. Görkem shares insights on the impact of AI-generated Pull Requests on open-source projects. ### LLM Economics and Strategy Explore why running small, fine-tuned LLMs in-house can be cheaper and provide more predictable, consistent results than generic large providers. Get practical insights on when to build versus buy. ### KitOps Solution Learn how KitOps creates an abstraction that allows data scientists to focus on training while leveraging existing DevOps platforms for deployment. Discover how ModelKits are simplifying the AI/ML deployment pipeline. Essential listening for platform engineers, DevOps practitioners, MLOps engineers, and anyone working at the intersection of AI and infrastructure. Tune in to understand the standardization movement reshaping the future of AI development.
Görkem ErcanInfrastructure 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.
Pravanjan ChoudhuryAI DevOps Reality: Field Report from the Enterprise Trenches
Understand the real-world impact of AI in DevOps with AWS Senior Container Specialist, Sanjeev Ganjihal
Rohit RaveendranKubernetes 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.
Anuj HydrabadiWhy 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.
Ashwin RajeevaFirst Environment Live in 1 Week with AI-Powered GCP Migration
How ZeonAI Labs leveraged Facets' AI agents to achieve the first environment migration in 1 week and establish self-service operations with 3 daily releases for their agentic platform
Biswa SinghBegin your orchestration journey today
Experience Facets in action with a founder-led demo.