Redis and Kafka – Advanced Microservices Design Patterns Simplified
We are now, simply, Redis
Microservices architectures make it possible to launch new products faster, support greater scale, and be more responsive to customer demands. With multiple modern data models, fault tolerance in any scenario, and the flexibility to deploy across multiple environments, Redis Enterprise enables developers and operators to optimize their data layer for a microservices architecture.
In a monolithic architecture, processes are tightly coupled and run as a single deployable artifact. While this is relatively simple to begin with, scaling up or modifying one part of your application requires updating the entire service, resulting in inefficient scalability and increased complexity as your codebase grows in size.
Microservices architecture involves a collection of loosely coupled services that can be independently updated and scaled by smaller teams. Because individual services are easier to build and manage than a single monolithic application, microservices enables more frequent deployments, data store autonomy, and increased flexibility.
Organizations are transitioning their applications to microservices architecture in order to drastically decrease time to market, more easily adopt new technologies, and respond faster to customer needs.
In a microservices environment, services that need to run in real-time must compensate for networking overhead. Redis Enterprise delivers sub-millisecond latency for all Redis data types and modules, as well as the ability to scale instantly and linearly to almost any throughput needed.
To ensure your applications are resilient to failure in any scenario, Redis Enterprise uses a shared-nothing cluster architecture and is fault tolerant at all levels: with automated failover at the process level, for individual nodes, and even across infrastructure availability zones, as well as tunable persistence and disaster recovery.
Redis Enterprise allows developers to choose the data model best suited to the performance and data access requirements for their microservices architecture, while retaining a unified operational interface that reduces technology sprawl, simplifies operations, and reduces service latency.
Microservices provide a great deal of technology flexibility, and choosing where you want to run your database should be no exception. Redis Enterprise can be deployed anywhere—on any cloud platform, on-premises, or in a multi-cloud or hybrid cloud architecture.
In a microservices architecture, choosing a database that is optimized for the data modeling and performance requirements of each service is critical. Redis Enterprise provides multiple data models that run in-memory so that developers can choose the right data model for each service without sacrificing performance.
Ensuring that services can properly communicate state, events, and data between each other can be a significant challenge in a microservices environment. Redis Enterprise can be used to manage inter-service communication, or act as an event store with Redis Streams.
Storing user session data enables applications to remember user identity, login credentials, personalized information, recent actions, and more—all while making sure that application response times are as fast as possible. Redis Enterprise makes session management fast with support for extremely large datasets using Redis on Flash and data-persistence that don’t impact performance.
We migrated our monolithic application to a microservices architecture, and we power many of those services using Redis Enterprise. We wanted to supercharge our service performance with a database that delivers low latency, and Redis Enterprise stood out from the rest.
Software Architect, eHarmony
“Since Redis and microservices [removed] the constraints of our old architecture, it [increased] our speed of deployment 2x – 3x within the first year.”
Director of Strategic Product Development, Mutualink
A microservices architecture has many connected services, yet faces the same performance demands as other approaches. To minimize latency, data should reside as close to the services as possible. Ensuring databases are consistent with one another in the event of failures or conflicting updates can also be challenging. Redis Enterprise can be deployed as an Active-Active, conflict-free replicated database to handle updates from multiple local installations of your services without compromising latency or data consistency, and providing continuity in the event of failures.
Redis Enterprise allows developers to choose the data model best suited to the performance and data-access requirements of individual microservices, while retaining a unified operational interface that reduces technology sprawl, simplifies operations, and reduces service latency.
Within a microservices architecture, a single Redis Enterprise cluster can provide databases to many different services, each with its own isolated instance, tuned for the given workload. Each database instance is deployed, scaled, and modeled independently of the others, while leveraging the same cluster environment, isolating data between services without increasing operational complexity.
Microservices provide a great deal of technology flexibility, and choosing where you want to run your database should be no exception. Redis Enterprise can be deployed anywhere: on any cloud platform, on-premises, or in a multi-cloud or hybrid-cloud architecture. It is also available on Kubernetes and as a native service on platforms like Pivotal Cloud Foundry (PCF), Pivotal Kubernetes Service (PKS), and Red Hat OpenShift.