Data masking is a necessary, but error prone process. You only need to forget the mask one time to leak sensitive data. SQL Server 2016 attempts to address this with a feature called Dynamic Data Masking.
The web-based LastPass password management service has been hacked according to the company, and the result is that some user data, including email addresses and authentication hashes were obtained by unknown assailants. The breach highlights the risks users take by storing all of their passwords in a centralized location.
A common criticism for SQL Server’s security model is that it only understands tables and columns. If you want to apply security rules on a row-by-row basis, you have to simulate it using stored procedures or table value functions, and then find a way to make sure there is no way to bypass them. With SQL Server 2016, that is no longer a problem.
Performance is key to mobile apps. Google provides a lot of training material to improve performance in Android apps. A brief overview of tips and techniques.
SQL Server 2016 seeks to make encryption easier via its new Always Encrypted feature. This feature offers a way to ensure that the database never sees unencrypted values without the need to rewrite the application.
Creating documentation is boring, it's often obsolete and misleading but with a new mindset both your documentation and code can improve, Cyrille Martraire explained in a presentation showing how to create living documentation when working with Domain-Driven Design (DDD) at this year’s DDD Exchange conference in London.
SQL Server 2016’s new Temporal Table feature makes it easy to work with data that needs to be versioned.
Last week, RedHat hosted a "Microservices Architecture Developer Day" in London, and presented a set of technologies and patterns that can be used to create microservice-based applications using open-source solutions like Kubernetes, Docker, Fabric8 and Maven. Read on for more details about the day, including links to the presentations and demo videos.
There is tremendous value in microservices, probably giving us the best environment we have ever had for doing Domain-Driven Design (DDD), Eric Evans stated in his keynote at this year’s DDD Exchange conference in London. Iteration is the most important key to good design and microservices is the second attempt, after SOA, to get things right.
At QCon New York 2015, Kolton Andrus discussed Netflix’s Failure Injection Testing (FIT) platform, which allows the injection and monitoring of arbitrary failure scenarios to a targeted group of customers using the Netflix production web services. FIT allows Netflix to maintain an ‘antifragile’ programming culture, which results in the creation of systems that are resilient to failure.
Michael Bryzek, co-founder and ex-CTO at Gilt, discussed at QCon New York how ‘dependency hell’ could impact the delivery and maintenance of microservice platforms. Bryzek suggested that dependency hell may be mitigated by making API design ‘first class’, ensuring backward and forward compatibility, providing accurate documentation, and automatically generating client libraries.
At QCon New York 2015, Paul Payne discussed a project at Nordstrom that required modifying and re-deploying a live application service within twenty minutes, which was made possible due to the use of Go-based microservices, Docker container technology, and a continuous delivery methodology.
Owen Garrett, heads of products at Nginx, Inc., has described on Nginx’s blog which design decisions allow NGINX to provide top-in-class performance and scalability.
Twitter has replaced Storm with Heron which provides up to 14 times more throughput and up to 10 times less latency on a word count topology, and helped them reduce the needed hardware to a third.
Apache Parquet, the open-source columnar storage format for Hadoop, recently graduated from the Apache Software Foundation Incubator and became a top-level project. Initially created by Cloudera and Twitter in 2012 to speed up analytical processing, Parquet is now openly available for Apache Spark, Apache Hive, Apache Pig, Impala, native MapReduce, and other key components of the Hadoop ecosystem.