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Cake Team Blogs

Cake Solutions architects, implements and maintains modern and scalable software, which includes server-side, rich browser applications and mobile development. Alongside the software engineering and delivery, Cake Solutions provides mentoring and training services. Whatever scale of system you ask us to develop, we will deliver the entire solution, not just lines of code. We appreciate the importance of good testing, Continuous Integration and delivery, and DevOps. We motivate, mentor and guide entire teams through modern software engineering. This enables us to deliver not just software, but to transform the way organisations think about and execute software delivery.

 

 

Multiple teams and work streams: doing more by doing less

Posted by Pallay Raunu

02/03/15 14:29

In this article, I am going to explore how projects can be successfully delivered when there are multiple stakeholders and multiple streams of work a.k.a work streams. I use the work streams intentionally here, even though it is a significantly overloaded term and varies across organisations. In this context, it is a logical grouping of business value improvements, activities and tasks so that they can be managed appropriately and any expectation met. As our teams develop and work on larger and more complex projects, these different groups need to complete a continuous but progressive list of technical tasks. These tasks are grouped by whatever domain ontology is pertinent to the project and yet deliver the customer centric, business feature. For example, for UK's leading organisation that help save money by comparing a range of insurances, a cross-functional squad of engineers regularly delivered the aggregation engine theme of work, another squad delivered the client services that consumed various systems and this was all unpinned by a DevOps squad that delivered the continuous integration and continuous delivery strategy. This is how we aim to deliver all projects and forms part of Cake's software delivery process model.

The main basis is around reducing waste
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This week in #Scala (02/03/2015)

Posted by Petr Zapletal

02/03/15 09:00

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Topics: Scala, Akka, Spark, Reactive

Cassandra on Mesos with Docker

Posted by Cornel Foltea

27/02/15 16:00

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Topics: DevOps, AWS EC2, Docker, Mesosphere, Cassandra, Mesos, Best Practices, Architecture

This week in #DevOps (24/02/2015)

Posted by Laura Glasu

26/02/15 17:50

Welcome to the 11th edition of #ThisWeekInDevOps ! 

This blog aims to keep you up to date with the latest news from the world of DevOps.

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Topics: DevOps, Cloud, AWS, Docker, Kubernetes, Azure, Google Cloud Platform, OpenStack, Logging, Software Defined Storage, Elastic Box

This week in #Scala (23/02/2015)

Posted by Petr Zapletal

23/02/15 09:00

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Topics: Scala, Akka, Spark, Reactive

This week in #DevOps (17/02/2015)

Posted by Laura Glasu

19/02/15 16:59

Welcome to the 10th edition of #ThisWeekInDevOps ! 

This blog aims to keep you up to date with the latest news from the world of DevOps.

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Topics: DevOps, AWS, Docker, Rocket, Puppet, Azure, Security, Docker Swarm, Logging, Pachyderm, Monitoring, HAproxy, Hadoop

This week in #Scala (16/02/2015)

Posted by Petr Zapletal

16/02/15 09:00

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Topics: Scala, Akka, Spark, Reactive

This week in #DevOps (10/02/2015)

Posted by Laura Glasu

12/02/15 18:35

Welcome to the 9th edition of #ThisWeekInDevOps ! 

This blog aims to keep you up to date with the latest news from the world of DevOps.

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Topics: DevOps, AWS, Docker, Puppet, Chef, Ansible, Azure, Security, GHOST, Box, Software Collections, Blue-Green Deployment, OpenStack

This week in #Scala (09/02/2015)

Posted by Petr Zapletal

09/02/15 09:00

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Topics: Scala, Akka, Spark, Reactive

Isotonic regression implementation in Apache Spark

Posted by Martin Zapletal

08/02/15 22:48

In one of my previous blog posts I introduced MLlib, Apache Spark's machine learning library. It discussed the basics of MLlib's api, machine learning vocabulary and linear regression http://www.cakesolutions.net/teamblogs/spark-mllib-linear-regression-example-and-vocabulary. Today I will have a bit deeper look at Spark's internals and the programming model - the options it provides to a programmer to implement and parallelise algorithms. I will demonstrate it on implementation of parallel pool adjacent violators solution to isotonic regression. The code was sent as a pull request to Spark and should be included in Spark 1.3 when it is released.

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Topics: Scala, Spark, Cassandra, Data Mining, Machine Learning

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