Framework and Product Comparison for Big Data Log Analytics and ITOA

Posted in Analytics, Big Data, Hadoop, Microservices on February 4th, 2016 by Kai Wähner

In February 2016, I presented a brand new talk at OOP in Munich: “Comparison of Frameworks and Tools for Big Data Log Analytics and IT Operations Analytics”. The focus of the talk is to discuss different open source frameworks, SaaS cloud offerings and enterprise products for analyzing big masses of distributed log events. This topic is getting much more traction these days with the emerging architecture concept of Microservices.

Key Take-Aways

  • Log Analytics enables IT Operations Analytics for Machine Data
  • Correlation of Events is the Key for Added Business Value
  • Log Management is complementary to other Big Data Components
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Microservices = Death of the ESB? (2016, Meetup Dublin)

Posted in API Management, Big Data, Cloud, Docker, EAI, ESB, IT Conferences, Microservices, SOA on January 29th, 2016 by Kai Wähner

I was invited to speak at Microservices Meetup Dublin this week. I updated my slide deck “Microservices – Death of the ESB?” … The meetup was fully booked with a waiting list; around 120 attendees came to Gild‘s office. (see attached link).

If you have not seen the slide deck last year, you should definitely take a look at this updated version with more recent information. I also incorporated valuable information from discussions with attendees in 2015’s sessions about this topic.

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Right Technology, Framework or Tool to Build Microservices

Posted in Analytics, API Management, Big Data, Cloud, EAI, ESB, In Memory, Java / JEE, SOA on May 27th, 2015 by Kai Wähner

Last week, I gave a talk at a German conference (Karlsruher Entwicklertag 2015) about Microservices. The following slide deck shows plenty of different technologies (e.g. REST, WebSockets), frameworks (e.g. Apache CXF, Apache Camel, Puppet, Docker) or tools (e.g. TIBCO BusinessWorks, API Exchange) to realize Microservices.

Abstract: How to Build Microservices

Microservices are the next step after SOA: Services implement a limited set of functions. Services are developed, deployed and scaled independently. This way you get shorter time to results and increased flexibility.

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Micro Services Architecture = Death of Enterprise Service Bus (ESB)?

Posted in API Management, Cloud, EAI, ESB, In Memory, Java / JEE on January 8th, 2015 by Kai Wähner

These days, it seems like everybody is talking about microservices. You can read a lot about it in hundreds of articles and blog posts, but my recommended starting point would be this article by Martin Fowler, which initiated the huge discussion about this new architectural concept. This article is about the challenges, requirements and best practices for creating a good microservices architecture, and what role an Enterprise Service Bus (ESB) plays in this game.

Branding and Marketing: EAI vs. SOA vs. ESB vs. Microservices

Let’s begin with a little bit of history about Service-oriented Architecture (SOA) and Enterprise Service Bus to find out why microservices have become so trendy.

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Microservices and DevOps with TIBCO Products

Posted in API Management, Big Data, Cloud, EAI, ESB, SOA on December 29th, 2014 by Kai Wähner

Everybody is talking about Microservices these days. You can read a lot about Microservices in hundreds of articles and blog posts. A good starting point is Martin Fowler’s article, which initiated the huge discussion about this new architecture concept.

For an overview about requirements for a good Microservices architecture, also read this article: “Do Good Microservices Architectures Spell the Death of the Enterprise Service Bus?

Another great resource is an free on-demand webinar by vendor-independent analyst Gartner: “Time to Get Off the Enterprise Service Bus“. It does not even mention the term “Microservices”, but explains its basic motivation and concepts.

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Intelligent BPM Suite (iBPMS): Implementation of a CRM Use Case

Posted in Analytics, Big Data, BPM, Business Intelligence, Cloud, ESB, In Memory, Social Network on December 3rd, 2014 by admin

Today, humans have to interpret large sets of different data to make a decision. Using gut feeling is nothing but gambling. Therefore, big data analytics is getting more and more important every year to make better decisions. However, just doing big data analytics is not enough. In many use cases, systematic and monitored human interactions are as important to get best outcomes.

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Real World Use Cases and Success Stories for In-Memory Data Grids

Posted in Analytics, Big Data, Cloud, ESB, In Memory, Java / JEE, NoSQL on November 24th, 2014 by admin

NoSQL Matters Conference 2014

NoSQL Matters is a great conference about different NoSQL topics. A lot of great NoSQL products and use cases are presented. In November 2014, I had a talk about “Real World Use Cases and Success Stories for In-Memory Data Grids” in Barcelona, Spain. I discussed several different use cases, which our TIBCO customers implemented using our In-Memory Data Grid “TIBCO ActiveSpaces“. I will present the same content at data2day, a German conference in Karlsruhe about big data topics.

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Integration of Amazon Redshift Cloud Data Warehouse (AWS SaaS DWH) with Talend Data Integration (DI) / Big Data (BD) / Enterprise Service Bus (ESB)

Posted in Cloud, EAI, ESB on June 26th, 2013 by Kai Wähner

In this blog post, I will show you how to „ETL“ all kinds of data to Amazon’s cloud data warehouse Redshift wit Talend’s big data components. Let’s begin with a short introduction to Amazon Redshift (copied from website):

„Amazon Redshift is [part of Amazon Web Services (AWS) and] a fast and powerful, fully managed, petabyte-scale data warehouse service in the cloud. With a few clicks in the AWS Management Console, customers can launch a Redshift cluster, starting with a few hundred gigabytes and scaling to a petabyte or more, for under $1,000 per terabyte per year.
Traditional data warehouses require significant time and resource to administer, especially for large datasets. In addition, the financial cost associated with building, maintaining, and growing self-managed, on-premise data warehouses is very high. Amazon Redshift not only significantly lowers the cost of a data warehouse, but also makes it easy to analyze large amounts of data very quickly.“

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Book Review “Cloud Computing Architected – Solution Design Handbook” by John Rhoton and Risto Haukioja

Posted in Cloud on October 15th, 2011 by admin

“Cloud Computing Architected – Solution Design Handbook” by John Rhoton and Risto Haukioja was published by Recursive Press in May 2011.

This book is a great addition to other books about cloud computing.

Why? It does NOT give a high-level overview of cloud computing. It does NOT explain the business value. Finally, it does NOT contain tutorials for any specific cloud products.

So what is the content of the book? It covers architectural options for designing a cloud. The book explains many important decisions which have to be done when creating a cloud service or a cloud application.

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Cloud Integration with Apache Camel and Amazon Web Services (AWS): S3, SQS and SNS

Posted in Cloud, EAI, ESB, Java / JEE on August 30th, 2011 by Kai Wähner

The integration framework Apache Camel already supports several important cloud services (see my overview article at http://www.kai-waehner.de/blog/2011/07/09/cloud-computing-heterogeneity-will-require-cloud-integration-apache-camel-is-already-prepared for more details). This article describes the combination of Apache Camel and the Amazon Web Services (AWS) interfaces of Simple Storage Service (S3), Simple Queue Service (SQS) and Simple Notification Service (SNS). Thus, The concept of Infrastructure as a Service (IaaS) is used to access messaging systems and data storage without any need for configuration.

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