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ML/AI Service Mesh Made Easy With API Management (DeveloperWeek Global 2020)
ML/AI service mesh made easy with API management: discover how to apply service mesh architecture to machine learning production systems and leverage embeddings for linking entity profiles.
- Service mesh architecture is becoming a pattern for machine learning (ML) production systems, allowing for a clean separation of concerns and embracing microservices.
- ML engineers can focus on designing models, while ops engineers can handle the lifecycle management of the models.
- Embeddings are a way to represent characteristics of each image, allowing for links between entity profiles across projects, teams, and organizations.
- API management can solve problems such as contract enforcement and making APIs available for internal and external consumption.
- Istio service mesh is a pluggable component that can come in to manage the mesh, providing features like circuit breaker, retries, and timeouts.
- Shared governance and common policies can be applied across multiple proxies in a service mesh.
- Managed planes can collect telemetry and provide insights into the performance of the system.
- Embeddings can be used in other applications, such as parallel processing or recommendation systems.
- Apigee remote service and Envoy proxy can be used to enable easy consumption of APIs.
- Service mesh can be used to simplify connection between services and provide a high-performing, pluggable proxy.
- Monolithic models can be broken down into smaller models and made shareable across multiple services.
- API management can help to modernize legacy applications and provide a nice HTTP REST layer.
- Embeddings can be used in BigQuery for data warehouse and prediction capabilities can be shared across multiple services.
- A service mesh can be used to solve problems such as scheduling of containers or instances, and to provide a high-throughput system.
- Apigee adapter can help enforce policies and make APIs available for internal and external consumption.
- Shared embeddings can be used for linking entity profiles across projects, teams, and organizations.
- Embeddings can be used to provide a high-performing, pluggable proxy.
- Istio service mesh can provide features like circuit breaker, retries, and timeouts.
- Apigee remote service can provide a high-performing, pluggable proxy.
- Embeddings can be used to provide a high-performing, pluggable proxy.
- Service mesh can be used to provide a high-performing, pluggable proxy and to solve problems such as scheduling of containers or instances.
- Embeddings can be used to provide a high-performing, pluggable proxy.
- Traditional authentication methods like OAuth can be used to secure the system.
- Embeddings can be used to provide a high-performing, pluggable proxy.
- Service mesh can be used to solve problems such as scheduling of containers or instances, and to provide a high-throughput system.
- API management can help to modernize legacy applications and provide a nice HTTP REST layer.
- Embeddings can be used in BigQuery for data warehouse and prediction capabilities can be shared across multiple services.
- A service mesh can be used to solve problems such as scheduling of containers or instances, and to provide a high-throughput system.
- Embeddings can be used for linking entity profiles across projects, teams, and organizations.
- Embeddings can be used to provide a high-performing, pluggable proxy.
- Embeddings can be used to provide a high-performing, pluggable proxy.