Getting Started With Microservices

Microservice-based architecture is a style that helps development teams launch new products faster, scale more easily, and respond better to customer demands while minimizing costs and complexity. The result is that enterprises reduce time-to-market for new service development, often from projects measured in months to days. 

In a microservices environment, services running in real time must compensate for networking overhead. Redis Enterprise delivers sub-millisecond latency for all Redis data types and models. In addition, it scales quickly and linearly to almost any throughput needed.

We’re inviting you to a webinar to understand the design patterns for microservice architectures, including

• Microservice query caching is a pattern commonly used to reduce microservice response times. It works by deploying a Redis Enterprise cache alongside each microservice to deliver data needed within a single business context.
• Caching cross-domain shared data via Command Query Responsibility Segregation (CQRS) is a critical pre-fetch cache pattern within microservice architectures that decouples reads (queries) and writes (commands). Cross-domain data must be available to each microservice in real time without breaking the scope of its focused business context and goal.
• API gateway caching for global data: Microservice applications cache globally accessed data at the API gateway level to distribute and speed data accessed by all services. Typically, this would be session data (such as user ID and preferences) and authentication data (such as tokens, authorization status, and permissions). This means frequently needed data is available in real-time to all services. The result? Reducing application latency without breaking the bounds of each microservice business context.
• Asynchronous messaging for inter-service communication: Microservices must communicate state, events, and data with one another without breaking isolation, and they have to stay decoupled. Redis Streams is an immutable time-ordered log data structure that enables a service (producer) to publish asynchronous messages to which multiple consumers can subscribe. 

Agenda:

1. Why microservices matter
2. Microservices challenges
3. How Redis helps
   1. Session and auth management
   2. Configuration
   3. Discovery
   4. Caching (Query/CQRS)
   5. Communication
   6. Rate limiting
   7. Speed, scale & availability
4. Demo 

We look forward to getting started with microservices together with you.

Cheers,

The Redis Team

Event Speaker

Eric Preston

Senior Solution Architect
Redis