More and more companies are going global, and businesses are digitizing on a massive scale-this is the new normal. Cloud, mobile, big data, and social technologies have had a significant impact on our daily lives.
But these digital disruptions demand change at a much faster rate. So, this new normal implies that business leaders must efficiently scale their applications and deliver existing features coherently.
And microservices are the perfect approach to achieve this.
Microservices are a software development and organizational style in which software is divided into small, self-contained services that interact via well-defined APIs. Typically, each service is owned by a small, independent team.
The cloud-computing platform AWS has building blocks that make it easy to build microservices. This article attempts to discuss theAWS microservices architecturebriefly.
Microservices are autonomous. That is, each service in the microservices architecture should be developed, deployed, operated, and scaled without affecting the other services in the microservice mesh.Since every team works on a different microservice, it brings agility to the entire application development process.
Since each microservice runs independently, it can be scaled whenever required to meet customer demands. This helps in ideal resource allocation and cost-efficiency.
As microservices run as separate pieces of code, they can be updated as and when required. If any fault occurs in any one of the services, it can be rolled back and redeployed without affecting other parts of your application.
Due to the atomic nature of microservices, you can allot costs to important features of your application. This substantially decreases the overall cost of your application.
The "publish-subscribe" framework lies at the core of microservices. This architecture allows for real-time data processing, which is essential for providing instant output and insights for applications such as electronic banking, customer support systems, radar systems, and data streaming.
When you are working with Big Data, voluminous amounts of data are to be collected, processed, and delivered at an agile rate, using data pipeline-oriented architecture. Microservices are a perfect fit for this design because each step in a data pipeline is responsible for a single small task. Microservices in big data applications include identifying credit and debit card fraud, traffic management, adaptive learning, and the analysis of food-borne illnesses.
Read our latest blog titled "Kubernetes vs. OpenStack" to learn about how the two technologies stand up against one another.
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Adding new functionality can be made much easier by using a microservices approach to large legacy systems. It's also helpful for changing the functioning of legacy systems. The new business functionality is implemented as one or more microservices, which are then linked to the legacy system. If you need to extend a system to support additional external partners, markets, or devices, for example, you could utilize microservices to establish co-existing new services for your existing modules while gradually modernizing the remainder of the application into a microservices design to reduce risk.
Scaling microservices takes a different approach than other IT solutions. When you run a monolithic application on a single server, scalability means you may add more instances and evenly distribute the load.
When you are scaling microservices, you have to manage a variety of distinct components and services. This means that either all of the components must be scaled at the same time, or you must identify which individual components must be scaled. This ensures that the different microservices can still integrate with the rest of the system.
How do you achieve the perfect scale for your application to run smoothly, without affecting the user experience? It is a three-step process: first measure performance, then maintain the performance, and allocate resources.
Of course, like with all services, it is the end-user experience that is most important, regardless of what is going on in the backend of your system. If the consumer notices a loss in speed or reliability, the solution you provided has failed in its job.
You should design a strategy for sustaining optimal performance once you have an effective monitoring system in place and a clear idea of what your performance and efficiency goals should be. And with those results, allocate the resources to maintain that optimal performance.
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Because of the range of IaaS, PaaS, SaaS, and SDK packages offered by Amazon Web Services (AWS), it is one of the finest choices for launching a microservice-based application. AWS offers a diverse set of building blocks that may be used to support software of any complexity or scale.
Let’s take a look at the microservices architecture tools that AWS offers:
Amazon Elastic Container Service: For delivering microservices, containers are widely regarded as the compute platform of choice. ECS is a highly scalable, high-performance container management technology that allows Amazon Web Services customers to operate Docker containers on a managed Amazon EC2 cluster.
AWS Lambda: As an Amazon Web Services serverless offering, Lambda allows customers to upload and run application code without having to provision servers. Users simply upload their code, and Lambda takes care of the rest, including running, scaling, and maintaining high availability. Users only pay for computing when their code is actually running.
Amazon DynamoDB: This is a key-value and document database with single-digit millisecond response times. For every application, it's a fully managed, long-lasting database with built-in backup, security, and restoration, as well as in-memory cache.
Amazon S3: Scalability, data availability, security, and performance are all industry-leading features of the Amazon Simple Storage Solution. It offers simple administration capabilities that allow you to organize your data and establish fine-grained access controls to fit your specific business, organizational and compliance needs.
Take a look at how SoundCloud moved into microservices.Read through our blog titled "The Journey into Microservices at SoundCloud".
Amazon ElastiCache: With ElastiCache, you can boost microservice speed by allowing users to access in-memory caches that are exponentially faster than disk-based databases.
Amazon RDS: This tool simplifies the setup, management, and scaling of relational databases. Microsoft SQL, MySQL, PostgreSQL, Maria DB, and Oracle are all supported by RDS.
Amazon Aurora: Aurora is AWS's own database engine that combines the ease of use and low cost of open source databases with the performance of high-end commercial databases.
With AWS App Mesh, different microservices can communicate with each other, enabling you to easily monitor and control your microservices.
Amazon’s API Gateway enables your microservices to process thousands of API calls simultaneously.
You can also check out Amazon SNS and SQS for messaging and notifications, Cloudtrail for logging and monitoring-as we mentioned, the list doesn’t end here.
This is just the tip of the iceberg. AWS is a gold mine of tools that facilitate improving microservices’ efficiency. You can dive deep into AWS’ ocean of solutions that deliver their best performance to empower your app with microservices.
You have now got an idea of some of the tools that the cloud computing platform uses to set up and manage microservices architecture efficiently.
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A majority of the big corporations in the world are going the microservices way. Microservices are small independent but interconnected services that make up an application. This is unlike the earlier approach, when companies functioned with a single larg
Monolith means ‘composed in just one single piece’. A monolith application with reference to software is today a single-tiered application package that has all the different components combined into one behemoth.
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