To this day, I’m a firm believer in the benefits of simple, informative, and spontaneous conversations with my colleagues – at least with the ones who can stand me long enough to chat with me . Chewing the fat with other like minded folks over a beer or two is a bloody good thing. It’s how ideas are born, knowledge is shared, and relationships are formed. It’s an important aspect of any business that is sadly all too often overlooked.
My commute to and from work on the train is on average 17 minutes. It’s the usual uneventful affair, where the majority of people pass the time by surfing their mobile devices, catching a few Zs, or by reading a book. I’m one of those people who like to check in with family & friends on my phone, and see what they have been up to back home in Europe, while I’ve been snug as a bug in my bed.
Stay with me here folks.
But aside from getting up to speed with the latest events from back home, I also like to catch up on the latest tech news, and in particular what’s been happening in the rapidly evolving cloud area. And this week, one news item in my AppyGeek feed immediately jumped off the screen at me. Google have launched yet another game-changing product into their cloud platform big data suite.
It’s called Cloud Dataproc.
“In our (admittedly limited) experience, Redis is so fast that the slowest part of a cache lookup is the time spent reading and writing bytes to the network” – stackoverflow.com
It’s very rare that a project can cause an engineer to get excited about the prospect of working with a database they’ve never worked with previously, especially when it’s a relational one. That mainly boils down to the fact that the majority of them are clunky monstrosities that are painfully slow and cause us to grimace at the thought of having to integrate them into our applications, not to mention having to piece together gnarly and over engineered SQL statements.
In a recent project we needed to deploy application changes to a Tomcat cluster without outage to the end user. To accomplish this the Tomcat sessions needed to be shared across the nodes. We opted to implement a variant of the Session-In-Cookie pattern popular in the Rails framework, a simple solution to session sharing. This blog shows how to implement this Session-In-Cookie pattern in Java.
