In this article I’m going to show you how to easily monitor the rate at which Logstash is ingesting data, as well as in future articles the rate at which Elasticsearch is indexing it. It’s a nice little touch to add to any project involving Logstash, and it’s easy to do. Logstash is powerful tool for data ingest, processing, and distribution. It originated as simply the pipe to slurp at log files and put them into Elasticsearch, but has evolved into a whole bunch more.

Here’s a collection of useful articles that I’ve found over the years that give good advice on writing a good abstract, mistakes to avoid, etc: Adam Machanic - Capturing Attention: Writing Great Session Descriptions Gwen Shapira - Concrete Advice for Abstract Writers Kellyn Pot’Vin-Gorman - Abstracts, Reviews and Conferences, Oh My! Russ Unger - Conference Proposals that Don’t Suck Martin Widlake - Tips on Submitting an Abstract to Conference Bridget Kromhout - give actionable takeaways (post photo courtesy of Calum MacAulay on https://unsplash.

Kibana is a tool from Elastic that makes analysis of data held in Elasticsearch really easy and very powerful. Because Elasticsearch has very loose schema that can evolve on demand it makes it very quick to get up and running with some cool visualisations and analysis on any set of data. I demonstrated this in a blog post last year, taking a CSV file and loading it into Elasticsearch via Logstash.

Two vulns for OBIEE in the latest critical patch update (CPU): http://www.oracle.com/technetwork/security-advisory/cpuapr2016v3-2985753.html?elq_mid=45463&sh=91225181314122121267715271910&cmid=WWMK10067711MPP001C140 Patches is bundle patch .160419: 12.2.1: https://support.oracle.com/epmos/faces/ui/patch/PatchDetail.jspx?parent=DOCUMENT&sourceId=2102148.1&patchId=22734181 11.1.1.9: https://support.oracle.com/epmos/faces/ui/patch/PatchDetail.jspx?parent=DOCUMENT&sourceId=2102148.1&patchId=22393988 11.1.1.7: https://support.oracle.com/epmos/faces/ui/patch/PatchDetail.jspx?parent=DOCUMENT&sourceId=2102148.1&patchId=22225110 Note that April 2016 is the last regular patchset for 11.1.1.7, ref: https://support.oracle.com/epmos/faces/DocumentDisplay?id=2102148.1#mozTocId410847. If you’re still on it, or earlier, time to upgrade! (Photo credit: https://unsplash.com/@jenlittlebirdie)

Recently added to the oracledi project over at java.net is an adaptor enabling Oracle GoldenGate (OGG) to send data to Elasticsearch. This adds a powerful alternative to [micro-]batch extract via JDBC from Oracle to Elasticsearch, which I wrote about recently over at the Elastic blog. Elasticsearch is a ‘document store’ widely used for both search and analytics. It’s something I’ve written a lot about (here and here for archives), as well as spoken about - preaching the good word, as it were, since the Elastic stack as a whole is very very good at what it does and a pleasure to work with.

I’ve recently been playing around with the ELK stack (now officially known as the Elastic stack) collecting data from an IRC channel with Elastic’s Logstash, storing it in Elasticsearch and analysing it with Kibana. But, this isn’t an “ELK” post - this is a Kafka post! ELK is just some example data manipulation tooling that helps demonstrate the principles. As I wrote about last year, Apache Kafka provides a handy way to build flexible “pipelines”.

On a family holiday in South Devon last week I had some good food experiences. Top of the pile was a Lardy Cake, a delicacy new to me but which I’ll be sure to be searching out again. It reminded me of an Eccles cake, but bigger and lardier! I got mine from Vinnicombes on the High Street in Sidmouth. Just down the coast from Sidmouth is a village called Beer.

Timelion was released in November 2015 and with the 4.4.2 release of Kibana is available as a native visualisation once installed. It adds some powerful capabilities to Kibana as an timeseries analysis tool, using its own data manipulation language. Installing Timelion is a piece of cake: ./bin/kibana plugin -i kibana/timelion After restarting Kibana, you’ll see it as an option from the application picker There’s a bit of a learning curve with Timelion, but it’s worth it.

OBIEE supports JDBC as a connection protocol, using the driver available on all installations of OBIEE, bijdbc.jar. This makes connecting to OBIEE from custom or third-party applications very easy. Once connected, you issue “Logical SQL” against the “tables” of the Presentation Layer. An example of logical SQL is: SELECT "Time"."T05 Per Name Year" saw_0 FROM "A - Sample Sales" To find more Logical SQL simply inspect your nqquery.log (obis-query.log in 12c), or Usage Tracking.

OK, maybe that’s not entirely true. But my read-only client, certainly. I was perusing the Logstash input plugins recently when I noticed that there was one for IRC. Being a fan of IRC and a regular on the #obihackers channel, I thought this could be fun and yet another great example of how easy the Elastic stack is to work with. Installation is a piece of cake: wget https://download.elasticsearch.org/elasticsearch/release/org/elasticsearch/distribution/zip/elasticsearch/2.2.1/elasticsearch-2.2.1.zip wget https://download.