Author Archives: Vikas Hazrati

About Vikas Hazrati

Vikas is the CTO @ Knoldus which is a group of software industry veterans who have joined hands to add value to the art of software development. We do niche product and project development on Scala, Spark and Java. We consult and coach on effective software development and agile practices. With our focus on software craftsmanship you can be assured of a good quality at the right price. To know more, send a mail to info@knoldus.com or visit www.knoldus.com

Semantic Web – The lure to a better world


The story of the Semantic Web is not new, however, it is interesting how some things become more and more important with the passage of time. The term was coined by Sir Tim Berners-Lee in May 2001 however, it took … Continue reading

Posted in Scala, Best Practices, big data | Tagged , | Leave a comment

And you thought you were doing Microservices


If you have been in the software industry for some time you would have heard things like. Yes we do Scrum but …we do not have timeboxed sprints. Yes, we write automated user acceptance tests but … as a part … Continue reading

Posted in Microservices, Scala | Tagged | 1 Comment

Another Apache Flink tutorial, following Hortonworks’ Big Data series


Background A couple of weeks back, I was discussing with a friend of mine, on the topic of training materials on Apache Spark, available online. Of the couple of sites that I mentioned, the hadoop tutorial from Hortonworks, came up. … Continue reading

Posted in Apache Flink, Batch, Flink, http://schemas.google.com/blogger/2008/kind#post, IOT, Scala | 1 Comment

Is Flink the shiny(err..) toy on the block?


If you are following the Big Data space especially from a Scala Space perspective then you would have noticed a troll of blogs, tweets and more blogs comparing the two. The two being Spark and Flink. That said, you would … Continue reading

Posted in Scala | Tagged , | 1 Comment

Expression Oriented Programming


In a conversation with one of the lead architects of a large publishing company, we were discussing around the coding standards and suddenly the term EOP brought the discussion to a standstill. Ok, just for a few seconds. Once I … Continue reading

Posted in Scala | Tagged | 3 Comments

Getting close to Apache Flink, albeit in a Träge manner – 3


In the last two blogs on Flink, I hope to have been able to underline the primacy of Windows in the scheme of things of Apache Flink’s streaming. I have shared my understanding of two types of Windows that can … Continue reading

Posted in Apache Flink, Scala, Streaming | Leave a comment

GPU, the soul


For all these years, we have have been galvanized by the advancements in the field of computing. Most of it is aligned with the introduction of better and powerful CPUs. First there was a single CPU whose speed was the … Continue reading

Posted in Scala | Tagged , , , | 1 Comment

CQRS in a jiffy!


Segregate operations that read data from operations that update data by using separate interfaces. This pattern can maximize performance, scalability, and security; support evolution of the system over time through higher flexibility; and prevent update commands from causing merge conflicts … Continue reading

Posted in Scala | Tagged , , | 1 Comment

Classification using AWS Machine Learning


One of the most common uses of Machine Learning algorithms is for the purpose of classification. Classification comes in couple of varieties. Binary classification is when we classify a given set of inputs into two classes. If there are more … Continue reading

Posted in Amazon, Scala | Tagged , , | Leave a comment

Getting close to Apache Flink, albeit in a Träge manner – 2


From the preceding post in this series In the last blog , we had taken a look at Flink’s CountWindow feature. Here’s a quick recap: As a stream of events enter a Flink-based application, we can apply a transformation of … Continue reading

Posted in Flink, Scala, Streaming | 2 Comments