In this article, you will learn how to use Confluent Schema Registry with Spring Cloud Stream and Kafka in a microservices architecture. We will use Apache Avro to serialize and deserialize events exchanged between our applications. Spring Cloud Stream provides a handy mechanism for integration with Kafka and schema registry.
Ok, but before we start, let’s say some words about schema registry. What is this? And why we may use it in our event-driven architecture? Let’s imagine we change the message on the producer side, by adding or removing some fields. We sent that message to a Kafka topic, but we don’t have many subscribers is receiving such events. In a typical microservices architecture, we may have many producers and many subscribers. It is often necessary for all those microservices to agree on a contract that is based on a schema. If a schema is evolving, the existing microservices are still required to work. Here comes a schema registry server. It provides a RESTful interface for storing and retrieving schemas in different formats like JSON, Protobuf, or Avro. It also stores a versioned history of all schemas and provides schema compatibility checks.
We may choose between several available products. Spring Cloud has its own implementation of a schema registry server. Although it can be easily integrated with Spring Cloud Stream, we won’t use it. Currently, it doesn’t allow verifying compatibility between different versions. There is also an Apicurio registry. On the other hand, it is not possible to easily integrate it with Spring Cloud Stream. Therefore our choice fell on the Confluent schema registry.
We are going to run three applications. One of them is sending events to the Kafka topic, while two others are receiving them. The integration with Kafka is built on top of Spring Cloud Stream. The consumer
Consumer-A is expecting events compatible with the
v1 of schema, while the second subscriber is expecting events compatible with the
v2 of schema. Before sending a message to Kafka the producer application tries to load schema definition from a remote server. If there is no result, it submits the data to the server, which replies with versioning information. The following diagram illustrates our architecture.
#microservices #spring cloud #apache kafka #kubernetes
A multi-cloud approach is nothing but leveraging two or more cloud platforms for meeting the various business requirements of an enterprise. The multi-cloud IT environment incorporates different clouds from multiple vendors and negates the dependence on a single public cloud service provider. Thus enterprises can choose specific services from multiple public clouds and reap the benefits of each.
Given its affordability and agility, most enterprises opt for a multi-cloud approach in cloud computing now. A 2018 survey on the public cloud services market points out that 81% of the respondents use services from two or more providers. Subsequently, the cloud computing services market has reported incredible growth in recent times. The worldwide public cloud services market is all set to reach $500 billion in the next four years, according to IDC.
By choosing multi-cloud solutions strategically, enterprises can optimize the benefits of cloud computing and aim for some key competitive advantages. They can avoid the lengthy and cumbersome processes involved in buying, installing and testing high-priced systems. The IaaS and PaaS solutions have become a windfall for the enterprise’s budget as it does not incur huge up-front capital expenditure.
However, cost optimization is still a challenge while facilitating a multi-cloud environment and a large number of enterprises end up overpaying with or without realizing it. The below-mentioned tips would help you ensure the money is spent wisely on cloud computing services.
Most organizations tend to get wrong with simple things which turn out to be the root cause for needless spending and resource wastage. The first step to cost optimization in your cloud strategy is to identify underutilized resources that you have been paying for.
Enterprises often continue to pay for resources that have been purchased earlier but are no longer useful. Identifying such unused and unattached resources and deactivating it on a regular basis brings you one step closer to cost optimization. If needed, you can deploy automated cloud management tools that are largely helpful in providing the analytics needed to optimize the cloud spending and cut costs on an ongoing basis.
Another key cost optimization strategy is to identify the idle computing instances and consolidate them into fewer instances. An idle computing instance may require a CPU utilization level of 1-5%, but you may be billed by the service provider for 100% for the same instance.
Every enterprise will have such non-production instances that constitute unnecessary storage space and lead to overpaying. Re-evaluating your resource allocations regularly and removing unnecessary storage may help you save money significantly. Resource allocation is not only a matter of CPU and memory but also it is linked to the storage, network, and various other factors.
The key to efficient cost reduction in cloud computing technology lies in proactive monitoring. A comprehensive view of the cloud usage helps enterprises to monitor and minimize unnecessary spending. You can make use of various mechanisms for monitoring computing demand.
For instance, you can use a heatmap to understand the highs and lows in computing visually. This heat map indicates the start and stop times which in turn lead to reduced costs. You can also deploy automated tools that help organizations to schedule instances to start and stop. By following a heatmap, you can understand whether it is safe to shut down servers on holidays or weekends.
#cloud computing services #all #hybrid cloud #cloud #multi-cloud strategy #cloud spend #multi-cloud spending #multi cloud adoption #why multi cloud #multi cloud trends #multi cloud companies #multi cloud research #multi cloud market
This video covers how to leverage Kafka Streams using Spring Cloud stream by creating multiple spring boot microservices
🔗 Kafka setup: https://docs.confluent.io/platform/current/quickstart/cos-docker-quickstart.html
🔗 Public Domain API: https://domainsdb.info/
🔗Spring Boot Primer - https://www.youtube.com/playlist?list=PLTyWtrsGknYegrUmDZB6rcqMotOFZKvbn
🔗Spring Cloud Primer - https://www.youtube.com/playlist?list=PLTyWtrsGknYeOJHtd3Ll93GRf28hrjlHV
🔗Spring Microservices Primer - https://www.youtube.com/playlist?list=PLTyWtrsGknYdZlO7LAZFEElWkEk59Y2ak
🔗Spring JPA Primer - https://www.youtube.com/playlist?list=PLTyWtrsGknYdt079e1pyvpgLrJ48RQ1LK
🔗Java 8 Streams - https://www.youtube.com/playlist?list=PLTyWtrsGknYdqY_7lwcbJ1z4bvc5yEEZl
🔗Spring Security Primer - https://www.youtube.com/playlist?list=PLTyWtrsGknYe0Sba9o-JRtnRlkl4gXMQl
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#KafkaStreams #SpringCloudStream #TechPrimers
#kafka streams #kafka #spring cloud stream #spring cloud
Dear Spring Community,
Today it’s my pleasure to announce releases of Spring Integration for Amazon Web Services extension versions
2.5.1 and Spring Cloud Stream Binder for AWS Kinesis
These releases can be downloaded from Maven Central:
compile 'org.springframework.integration:spring-integration-aws:2.5.1' COPY
If you don’t use Kinesis Binder. Or via Binder dependency:
compile 'org.springframework.cloud:spring-cloud-stream-binder-kinesis:2.2.0' COPY
Spring Integration for AWS extension of
2.5.1 has some minor bug fixes after the previous
The Spring Cloud Stream Binder for AWS Kinesis
2.2.0 is the first release in the project generation which is based on a new independent Spring Cloud for AWS artifact. It also was upgraded to the latest Spring Cloud 2020.0.3 and has some other bug fixes and improvements.
#[object object] #aws 2.5.1 #spring cloud #spring cloud stream kinesis binder 2.2.0 available #spring integration aws 2.5.1 and spring cloud stream kinesis binder 2.2.0 available
The moving of applications, databases and other business elements from the local server to the cloud server called cloud migration. This article will deal with migration techniques, requirement and the benefits of cloud migration.
In simple terms, moving from local to the public cloud server is called cloud migration. Gartner says 17.5% revenue growth as promised in cloud migration and also has a forecast for 2022 as shown in the following image.
#cloud computing services #cloud migration #all #cloud #cloud migration strategy #enterprise cloud migration strategy #business benefits of cloud migration #key benefits of cloud migration #benefits of cloud migration #types of cloud migration
This is part 3 of “MS SQL Server- Zero to Hero” and in this article, we will be discussing about the SCHEMAS in SQL SERVER. Before getting into this article, please consider to visit previous articles in this series from below,
In part one, we learned the basics of data, database, database management system, and types of DBMS and SQL.
#sql server #benefits of schemas #create schema in sql #database schemas #how to create schema in sql server #schemas #schemas in sql server #sql server schemas #what is schema in sql server