Event-Driven Microservices
Microservices simplify development, testing, deployment, fault tolerance, and scaling. Utilizing a rapid, lightweight infrastructure for modern enterprise architectures enhances throughput and reduces latency. Event-driven microservices employ message buses for inter-service communication, enabling cohesive workflows for business processes.
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Introduction
In intricate, data-intensive settings, microservices architectures offer pragmatic solutions. Breaking down sizable applications into smaller tasks creates a modular, maintainable, fault-tolerant, and scalable system that can evolve over time.
Modern microservices projects require fast data storage and streaming integration. Hazelcast Platform is valuable for boosting microservices endeavors, offering high performance and effective inter-service communication.
Business Requirements
The business requirements that drive architects and developers to adopt a microservices architecture include:
- Faster time-to-market for business-critical applications that must be continually updated to serve important business processes
- Greater transparency and understanding around business logic that is otherwise buried deeply in the code of a monolithic application, to be able to enhance and extend existing capabilities
- Higher throughput and lower latency of business processes via architectures that promote scale and parallelism
- Reduced total cost of ownership by getting more computing power out of your hardware investment
From a developer standpoint, microservices architectures especially need planning, as well as the right technologies, to support the following:
High performance. Hazelcast Platform provides a fast data store that delivers in-memory data access speeds. It can easily be embedded into your microservices deployment, giving you fast data lookups as well as a medium for saving state. The in-memory advantage ensures you are not adding unnecessary latency to your pipeline when reading and writing data.
Efficient communications. The next generation of stateful microservices are using streaming technologies to simplify inter-service communications. You can also use Hazelcast Platform or even Apache Kafka as a messaging system to let a microservice pass its data to the next, instead of using traditional REST APIs or databases that require writing coordination code. Develop microservices using the Hazelcast stream processing engine, which offers an API that can read messages from your messaging system of choice, process them, and then pass them back to the messaging system for the next stage of the microservices pipeline.
Technical Challenges
While a microservices architecture can offer numerous advantages, there are significant hurdles you face if you don’t leverage the right technologies. These challenges include:
- Inability to achieve responsiveness service-level agreements (SLAs) due to the latency caused by an inefficient, siloed architectures
- The complexity of relying on external databases for stateful storage
- The disruptive effort of swapping out existing microservices with updated versions, resulting in downtime
- Added complexity of separate orchestration frameworks that drive your microservices workflows, instead of leveraging an event-driven paradigm that simplifies the process flows
Why Hazelcast
Hazelcast works with many data-driven customers who turn to us for speed at scale, security, and reliability. Hazelcast platform is a unified real-time data platform that uniquely combines a distributed, fast data store with a high-speed stream processing engine, to run the fastest applications in any type of data-intensive environment. Consider some of the technology advantages listed below that let Hazelcast customers run their critical business applications based on a microservices architecture.
Easy to Develop and Deploy
Hazelcast Platform was designed to simplify the application development process by providing a familiar API that abstracts away the complexity of running a distributed application across multiple nodes in a cluster. This allows developers to spend more time on business logic and not on writing custom integration and orchestration code. Our platform can seamlessly integrate with your IT architecture to add new capabilities without having to rip and replace your existing stack. The Hazelcast cloud-native architecture requires no special coding expertise to get the elasticity to scale up or down to meet highly fluctuating workload demands.
Performance at Scale
Whether you process a large volume of transactions, enhance online experiences with faster responsiveness, run large-scale transformations on data, or cut costs with a mainframe integration deployment, Hazelcast Platform is designed for the ultra-performance that today’s banking workloads require. The proven performance advantage is especially valuable for data-focused experimentation that enables ongoing business optimization, especially in data science initiatives including machine learning inference for fraud detection.
Mission-Critical Reliability
With built-in redundancy to protect against node failures, and efficient WAN Replication to support disaster recovery strategies that safeguard against total site failures, Hazelcast Platform was built to provide the resilience to run mission-critical systems. The extensive built-in security framework protects data from unauthorized viewers, and security APIs allow custom security controls for sensitive environments.
Use Cases
Many businesses know that offering the right deal at the right time boosts customer engagement. Yet, the challenge is often identifying the best offer once the right time is recognized. Customer interactions give signals about specific preferences, but your systems might lack the capability to calculate the ideal offer details. A microservices-based system with Hazelcast allows seizing customer opportunities in real-time. By gathering pertinent customer information during interactions within an event-driven workflow, you can swiftly provide tailored offers, such as calculating a suitable loan offer based on their immediate needs.
Payment processing often entails a series of computations to determine the validity of a payment request, and the optimal routing of a transaction across payment partners. This is ideal for a microservices architecture since each component of a payment processing lifecycle is a contained, well-defined task that aligns with a microservices pattern. With Hazelcast, banks can run complex operations including sophisticated, machine learning-based fraud algorithms as part of a payment processing workflow to reduce fraud loss while also reducing other operational costs.
Mainframes still run many banking operations today, but extending these systems to do more often comes with much higher MIPS cost. By leveraging Hazelcast Platform in a mainframe optimization initiative, much of the workloads that do not have to run on the mainframe can be handled in a microservices architecture that breaks up the work formerly done by the mainframe into discrete tasks. This enables a more cost-effective way to process data while retaining similar performance and availability characteristics on commodity hardware or in the cloud.