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Cloud-Based Integrations vs. On-Premise Models

This is an article from DZone's 2022 Enterprise Application Integration Trend Report.

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For large enterprises, where integration with different platforms is important for various business activities, enterprise integration is the most popular term for the integration architecture. Enterprise integration has evolved a lot from traditional batch processing using ETL (extract, transform, and load), where data feeds from sources were used for business processing/ transformation and loading to the target data source. 

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When To Use Apache Camel vs. Apache Kafka?

Should I use Apache Camel or Apache Kafka for my next integration project? The question is very valid and comes up regularly. This blog post explores both open-source frameworks and explains the difference between application integration and event streaming. The comparison discusses when to use Kafka or Camel when to combine them, and when not to use them at all. A decision tree shows how you can quickly qualify one for the other.

The History of Application Integration and Event Streaming

My personal history and experience in application integration and event streaming are the following. It shows my background and how I see the integration and data streaming markets.

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How to Configure Apache ActiveMQ on AWS

Apache ActiveMQ is an open-source message broker. It is one of the most popular Apache open source products and supports multiple industry-standard connectivity protocols. Clients can choose among multiple different languages and platforms for connectivity to ActiveMQ. Apache ActiveMQ provides client libraries in C++, Python, Java, C, etc. for developing applications. Some of the most popular protocols supported by ActiveMQ are AMQP, STOMP, MQTT, and JMS. ActiveMQ supports a wide variety of messaging use cases to meet almost all the needs of a production-grade messaging system.

Amazon MQ

AWS provided Amazon MQ is a managed service that can be used for Apache ActiveMQ or RabbitMQ. Amazon MQ service makes the management, configuration, deployment, and usage of these two message brokers easy on AWS. Amazon MQ makes the lifecycle management and operation of these services easy for an IT organization as this is a fully managed service provided by AWS. Code written to connect to on-prem Apache ActiveMQ can be transparently migrated to use ActiveMQ using AWS.

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What Is BizTalk Server?

If you wanted to explain BizTalk Server to a technology guy, the answer would be:

BizTalk Server is a middleware product from Microsoft that helps connect various systems together.

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Connecting Red Hat Single Sign-on on Openshift to an External Database

The Red Hat Single Sign-On or just RHSSO is an enterprise version of Keycloak, which is an open-source Identity and Access Management solution aimed at modern applications and services. 

In the last few days, I needed to install RHSSO on Openshift version 4.8, however, I needed to implement small customization in the database connection.  By default a non-ephemeral RHSSO installation uses an embedded installation of PostgreSQL database, however, I would change the type of database from PostgreSQL to MySQL, and even change the location of this one to the outside of Openshift.

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When To Use Reverse ETL and When It Is an Anti-pattern

Most enterprises store their massive volumes of transactional and analytics data at rest in data warehouses or data lakes. Sales, marketing, and customer success teams require access to these data sets. Reverse ETL is a buzzword that defines the concept of collecting data from existing data stores to provide it easy and quick for business teams.

This blog post explores why software vendors (try to) introduce new solutions for Reverse ETL, when it is needed, and how it fits into the enterprise architecture. The involvement of event streaming with tools like Apache Kafka to process data in motion is a crucial piece of Reverse ETL for real-time use cases.

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Apache Kafka in the Insurance Industry

The rise of data in motion in the insurance industry is visible across all lines of business, including life, healthcare, travel, vehicle, and others. Apache Kafka changes how enterprises rethink data. This blog post explores use cases and architectures for event streaming. Real-world examples from Generali, Centene, Humana, and Tesla show innovative insurance-related data integration and stream processing in real-time.

Digital Transformation in the Insurance Industry

Most insurance companies have similar challenges:

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ELI5: What Is the Publish-Subscribe Messaging Pattern?

Introduction

Used in microservices architecture (a method of designing software applications that is rapidly growing in popularity), the publish-subscribe messaging pattern is a form of asynchronous communication where messages are published to a topic and received – in real-time – by consumers who subscribe to the topic.

Now, what does that really mean? What are the advantages of publish-subscribe? How can you explain it to someone non-technical?

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A Postmodern ERP With Apache Kafka

Enterprise resource planning (ERP) exists for many years. It is often monolithic, complex, proprietary, batch, and not scalable. Postmodern ERP represents the next generation of ERP architectures. It is real-time, scalable, and open. A Postmodern ERP uses a combination of open source technologies and proprietary standard software. This blog post explores why and how companies, both software vendors and end-users, leverage event streaming with Apache Kafka to implement a Postmodern ERP.

What Is ERP (Enterprise Ressource Planning)?

Let's define the term "ERP" first. This is not an easy task, as ERP is used for concepts and various standard software products.

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Untangling SAP for Serverless Deployment

There are few technology trends that are a better fit for the current moment than serverless computing – particularly with its benefits of greater scalability, faster development, more efficient deployment, and lower cost. 

But it can be difficult to harness the power of serverless when critical data and workflows are housed in the powerful, widely used enterprise resource planning (ERP) system SAP. Organizations typically rely on SAP to centralize data management and optimize critical business functions like accounting, financials, human capital management, enterprise performance management, etc.

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Kafka for XML Message Integration and Processing

XML messages and XML Schema are not very common in the Apache Kafka and Event Streaming world! Why? Many people call XML legacy. It is complex, verbose, and often associated with the ugly WS-* Hell (SOAP, WSDL, etc). On the other side, every company older than five years uses XML. It is well understood, provides a good structure, and is human- and machine-readable.

This post does not want to start another flame war between XML and other technologies such as JSON (which also provides JSON Schema now), Avro, or Protobuf. Instead, I will walk you through the three main approaches to integrate between Kafka and XML messages as there is still a vast demand for implementing this integration today (often for integrating legacy applications and middleware).

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Apache Kafka and SAP ERP Integration Options

A question I get every week from customers across the globe is, "How can I integrate my SAP system with Apache Kafka?" This post explores various alternatives, including connectors, third party tools, custom glue code, and trade-offs between the different options.

After exploring what SAP is, I will discuss several integration options between Apache Kafka and SAP systems:

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Perform Remote Caches With JBoss Fuse and Red Hat Data Grid

Nowadays, the reality of companies demands even more integration between different technologies, working together, changing, and processing data. In this ecosystem, the use of an integration platform is essential. Still, the use of an in-memory database is necessary for a significant gain in information processing performance. In this article, we will demonstrate the use of the JBoss Fuse integration platform, in conjunction with the In-memory database named  Red Hat Data Grid.

JBoss Fuse is an integration platform based on the framework Apache Camel. It focuses on mediation, transformation, and data routing among many applications, services, and devices. 

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Event Streaming and Apache Kafka in Telco Business (OSS/BSS)

Event Streaming is a hot topic in Telecommunications Industry. In the last few months, I have seen various projects leveraging Apache Kafka and its ecosystem to implement scalable real-time infrastructure in OSS and BSS scenarios. This blog post covers the reasons for this trend. Finally, we'll show a whiteboard video recording exploring the different use cases for event streaming in telcos in detail.

The Evolution of the Telecommunications Industry

The telecommunications industries within the sector of information and communication technology is made up of all telecommunications/telephone companies and internet service providers. It plays a crucial role in the evolution of mobile communications and the information society.

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Smart City With an Event Streaming Platform Like Apache Kafka

A smart city is an urban area that uses different types of electronic Internet of Things (IoT) sensors to collect data and then use insights gained from that data to manage assets, resources, and services efficiently. This includes data collected from citizens, devices, and assets that are processed and analyzed to monitor and manage traffic and transportation systems, power plants, utilities, water supply networks, waste management, crime detection, information systems, schools, libraries, hospitals, and other community services.

You may also like: Smart Cities: Who Wins and Who Loses?

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PostgreSQL Connection Pooling: Part 1 – Pros and Cons

PostgreSQL Connection Pooling

A long time ago, in a galaxy far, far away, ‘threads’ were a programming novelty rarely used and seldom trusted. In that environment, the first PostgreSQL developers decided forking a process for each connection to the database is the safest choice. It would be a shame if your database crashed, after all.

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Since then, a lot of water has flown under that bridge, but the PostgreSQL community has stuck by their original decision. It is difficult to fault their argument, as it’s absolutely true that: