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• Separate workflows for infrastructure provisioning and application deployment lead to inefficiency, higher risk of errors, longer feedback loop, and unmanageable complexity
• A unified approach using Crossplane can increase iteration speed, quality, and time to market
• Putting everything in a single release is crucial for continuous deployment pipeline and reducing cognitive load on developers
• Examples of challenges include running post-deployment tests, making changes in configuration, and dealing with multiple repositories

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• Argo CD is a tool for managing Kubernetes applications that can support large numbers of developers and objects
• The presenter offers a conservative benchmark for Argo CD scalability, suggesting that 15,000 objects and 50 clusters are safe limits
• However, the presenter notes that with tweaking, Argo CD can support much larger numbers of objects and clusters
• The presenter emphasizes the importance of security in using Argo CD, particularly in multi-tenant environments
• The presenter suggests using an app of apps pattern to manage large numbers of objects and dependencies
• The presenter recommends splitting Argo CD instances to provide better isolation and prevent noise
• The presenter suggests that a control plane may be necessary for managing large numbers of Argo CD instances
• The presenter notes that Adobe has been speaking at the conference and is part of a larger Adobe Cinematic Universe of talks

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• Adobe faced challenges with infrastructure provisioning and lacked visibility, observability, and auditability into infrastructure resources provisioned by individual teams
• Adobe leveraged Argo and Crossplane to build a scalable GitOps-based application deployment solution and broker the provisioning of cloud resources consistently and across all teams
• Adobe and Amazon designed a layered isolation mechanism for tenant teams on top of existing shared Kubernetes clusters via a mix of technologies such as OPA Gatekeeper, ServiceAccount boundaries, IAM roles, etc.
• The solution solved the non-negotiable requirements of security and multi-tenancy, which are hard to achieve natively with Crossplane and Argo
• The new solution improved the developer experience and reduced the mean time to resolution when encountering issues or outages

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• WebAssembly and edge computing can be used to run machine learning models in the browser and reduce network costs
• Edge computing is ideal for running small models that are single-threaded and require low latency
• WebAssembly can improve user experience by reducing load times and allowing for more memory in the browser
• The content authenticity initiative uses machine learning models to fingerprint images