maandag 11 april 2016

My first NodeJS service

Microservices implemented in JavaScript running on NodeJS are becoming quite popular lately. In order to gain some experience with this, I created a little in memory NodeJS cache service. Of course statefulness complicates scalability, but if I would also have implemented a persistent store to avoid this, the scope of this blog article would have become too large. Please mind that my experience with NodeJS is limited to a NodeJS workshop from Lucas Jellema and a day of playing with NodeJS. This indicates it is quite easy to get started. In this blog I'll highlight some of the challenges I encountered and how I solved them. Also I'm shortly describing what Oracle is doing with NodeJS. Because the JavaScript world changes rapidly, you should also take into account the period between when this blog is written and when you are reading it; it will most likely quickly become outdated. You can download the code from GitHub here.

woensdag 23 maart 2016

Oracle Integration Cloud Service (ICS): A developer's first impression

Oracle provides ICS (Integration Cloud Service) as a simple means for citizen developers to do integrations in the cloud and between cloud and on-premises. On the Oracle Fusion Middleware Partner Community Forum I got a chance to get some hand-on experience with this product in one of the workshops. In this blog post I will describe some of my experiences. I'm not the target audience for this product since I am a technical developer and have different requirements compared to a citizen developer. I've not been prejudiced by reading the documentation ;)

I experimented with ICS on two use-cases. I wanted to proxy SOAP and REST requests. For the SOAP request I used a SOA-CS Helloworld web-service and for the REST request I used an Apiary mockservice. I will not go into basics too much such as creating a new Connection and using the Connection in an Integration since you can easily learn about those in other places.

zondag 28 februari 2016

Asynchronous interaction in Oracle BPEL and BPM. WS-Addressing and Correlation sets

There are different ways to achieve asynchronous interaction in Oracle SOA Suite. In this blog article, I'll explain some differences between WS-Addressing and using correlation sets (in BPEL but also mostly valid for BPM). I'll cover topics like how to put the Service Bus between calls, possible integration patterns and technical challenges.

I will also shortly describe recovery options. You can of course depend on the fault management framework. This framework however does not catch for example a BPEL Assign activity gone wrong or a failed transformation. Developer defined error handling can sometimes leave holes if not thoroughly checked. If a process which should have performed a callback, terminates because of unexpected reasons, you might be able to manually perform recovery actions to achieve the same result as when the process was successful. This usually implies manually executing a callback to a calling service. Depending on your choice of implementation for asynchronous interaction, this callback can be easy or hard.

maandag 25 januari 2016

Service implementation patterns and performance

Performance in service oriented environments is often an issue. This is usually caused by a combination of infrastructure, configuration and service efficiency. In this blog article I provide several suggestions to improve performance by using patterns in service implementations. The patterns are described globally since implementations can differ across specific use cases. Also I provide some suggestions on things to consider when implementing such a pattern. They are technology independent however the technology does of course play a role in the implementation options you have. This blog article was inspired by a session at AMIS by Lucas Jellema and additionally flavored by personal experience.

maandag 4 januari 2016

Simple IoT security system using Raspberry Pi 2B + Razberry + Fibaro Motion Sensor (FGMS-001)

In this article I'll describe how I created a simple home-brew burglar detection system to send me a mail when someone enters my house (so I can call the police). First my choice for the components is explained. Next how these components combine to achieve the functionality wanted. Based on this article you should be able to avoid certain issues I encountered and have a nice suggestion for a simple relatively cheap burglar detection system.

My purpose was to create a simple security system based on a Raspberry Pi. A Raspberry Pi is a tiny computer which can run a Debian like Linux distribution called Rasbian. I wanted to avoid going to low-level into sensor configuration and programming. That's why I decided early on to use an extension board and not directly attach the sensors to the Raspberry Pi. I decided to go for the Razberry. I also looked at the GrovePi and Arduino. Both are still too low-level for my tastes though. The Razberry is an extension board for the Raspberry which provides a Z-Wave controller chip. Z-Wave is a wireless protocol popular in the area of home automation. This was an attractive option since if in the future I would want to use additional sensors or maybe even use a commercial home automation system, I could very well get compatibility out of the box. For the sensor, I decided on the Fibaro FGMS-001 Motion Sensor. This is a multi-sensor which allows detection of motion, temperature, luminiscence and vibrations. It can even detect tampering and earthquakes (which is relevant since I live in the Dutch city of Groningen).

Z-Wave.Me (the company providing the Razberry), provides software for the Razberry called Z-Way. There are several alternatives. One of the most popular seems to be Domoticz which is provided with OpenZWave. Domoticz allows quite extensive home automation but I was having difficulty getting the sensor to work with OpenZWave so I decided to go with Z-Way. Z-Way supported the sensor out of the box. With the Z-Way server however it was difficult to automate actions based on sensor values. How I solved this is also described in this article.

donderdag 31 december 2015

Dramatically reduce SOA Suite 11g startup time by cleaning the MDS

SOA Suite can sometimes be a bit slow to start. This is especially the case when there are a lot of composites to load. Customers using different versions of composites can benefit from undeploying non-default revisions of processes which do not have any running instances (see for example here). Undeployment in most cases is an asynchronous process which does not give feedback. It can partially fail without you noticing (apparently not an atomic transaction). This sometimes leaves composite remains; parts of the composite which are still loaded at startup but are not visible from the Enterprise Manager. Removing these can dramatically reduce server startup time. Especially in an environment which has been used for some time and environments with many versions of composites. Reducing the time required to get the soa-infra application fully up and running is of course mostly relevant for 11g SOA installations and less for 12.1.3 (which does some lazy loading) and 12.2.1 (which supports parallel deployments, also during server start-up).

In this article I'll demonstrate how these left-over composite parts can be identified and removed on an SOA environment. First try this procedure on a development or test environment before executing it in production! This method is not supported by Oracle (or me) in any way and using it is entirely at your own risk. If something breaks, tell me so I can update this article. Thanks!

Please mind that these actions, although they help with the start time and memory usage of your SOA environment, have less impact on run-time performance than for example purging of instances and reducing the amount of deployed composites (or tweaking datasources, soa-infra database, JVM, etc).

SOA Suite can be up quickly!

zaterdag 19 december 2015

A first look at Splunk. Monitor Oracle SOA Suite service response times

Measuring performance of services can be done in various ways. In this blog I will describe a method of measuring Oracle SOA service response times with Splunk a popular monitoring tool. In order to monitor service response times with Splunk, Splunk needs to obtain its data from somewhere. In this example I'll use the HTTP access log which I expand with a time-taken field. Disclaimer; my experience with Splunk is something like 2 hours. This might also be an indication of what can quickly be achieved with Splunk with little knowledge.