Why Get Certified with DevNetwork?
- Practitioner-Led, Production-Focused
Learn from engineers shipping software at scale, not academics theorizing about it. Sessions cover the technologies, frameworks, and processes to go from siloed AI pilot to enterprise production solutions that scale. - Role-Relevant, Career-Accelerating
Each certificate maps to specific job functions, — Engineering Manager, AI Developer, Architect, and other software development and technology operation leadership roles, so you understand which certificates are right for you to explore. - Event-Powered Learning
Live sessions where you can meet, interact with, and ask questions of people doing the work. - Measurable ROI
Certificates provide assurance that you attended the right sessions to elevate your knowledge and ability to apply your learnings when you return to the office.
How to Secure a Certificate
- Step 1: Register for a PRO or PREMIUM conference pass (contact [email protected] to upgrade OPEN passes)
- Step 2: Attend eight (8) or more sessions under a Certificate on the schedule. Please scan your badge at each session to get credit.
- Step 3: Attendees who complete a Certificate during a conference will receive an email with their Certificate(s).
Platform Engineering
This certificate is aimed at engineers responsible for designing and supporting enterprise-level internal developer platforms, from incident response to observability pipelines to self-service API endpoints and AI primitives. It covers how to design platform interfaces, manage and prepare for probabilistic agent traffic, architect tool-first platform abstractions, and build for observability, reliability, and developer velocity. Participants explore patterns like eBPF signal intelligence, capacity planning for bursty workloads, streaming-native platform telemetry, and golden path templates, along with the trade-offs that matter in production. Certificate holders can build internal platforms that accelerate development while maintaining operational excellence across engineering teams.
Cloud-Native AI Infrastructure
This certificate is aimed at engineers and architects responsible for designing enterprise-level cloud-native AI infrastructure, from GPU orchestration to distributed inference pipelines and self-healing reliability systems. It covers how to design AI-ready cloud interfaces, separate control planes from probabilistic model execution, architect tool-first inference runtimes, and build for observability, reliability, and cost efficiency. Participants explore patterns like model-aware scheduling, dynamic batching optimization, streaming-native observability, and heterogeneous accelerator fabrics, along with the trade-offs that matter in production. Certificate holders can deploy reliable, cost-efficient AI infrastructure across hybrid/multi-cloud environments at organizational scale.