Computer science is full of complex hard-to-understand algorithms. Understandability of an algorithm - ability to explain an algorithm in simple terms - is generally under appreciated. Often poor understandability of an algorithm has a direct impact on practical real-world applications. In my opinion, if we can’t develop intuitions about algorithm it will be very difficult to implement or extend the algorithm for real-world use cases.

If we start thinking containers in terms of objects, it abstracts away the low-level details but reveals higher-level patterns that are common to a variety of applications and algorithms. A recent paper, published by Google Researchers Brendan Burns and David Oppenheimer, suggests that containers are particularly well-suited as the fundamental “object” in distributed systems by virtue of the walls they erect at the container boundary .

Setting and running Kubernetes on Amazon Web Services (AWS) is a very involved process. AWS has decided to not implement Kubernetes as a Service but built something of its own - Amazon EC2 Container Service (ECS). Hence, you need to know and consider a lot of things before you can successfully roll out Kubernetes on AWS. These are the consideration which can make or break it your Kubernetes rollout.

Function as a Service (FaaS) remains at the core of the serverless movement. That said, most of practical serverless implementations I have seen use a combination of serverless functions and more conventional microservices running in containers. Instead of a one-size-fits-all approach, i.e. trying to use serverless function for everything, a balanced approach is highly recommended.

Functions as a service (FaaS) is an emerging pattern to build APIs and microservices at scale. You can use various FaaS implementations such as AWS Lambda, Azure Functions, and Google Cloud Functions to build APIs ecosystem for your organisation. If you remove serverless requirements, stored procedures can be considered as a variation of FaaS because they share similar traits and concerns.

Implementing agile which works and delivers can be a very challenging task, especially in corporate and enterprise environment. According to 10th State of Agile Survey, two of the top five causes of failure were related to company culture – company philosophy or culture at odds with core agile values. A good company culture means a resilient workforce and overall better business performance.

To unlock the true value of data, organisations will need internal data services. Data services provide streamlined and centralised data access to a diverse set of users which removes the friction in delivering faster insights, products and services. Data services promote innovation. In addition, effective implementation of data services can reduce data duplication hence reducing the cost of data management and storage.

When using Amazon Redshift, distribution style plays an important role in optimising the table design for best performance. In a nutshell, table’s distribution style dictates how the data is distributed across Redshift node and slices. A key objective is to avoid the data redistribution during query execution or runtime. This is accomplished by locating or co-locating the data where it needs to be before the query is executed.

Hundreds of marketing technologies, thousands of tags - effective tag management requires more than just an enterprise tag management solution. In this post, I present you my 10 commandments for effective tag management. I think these 10 simple rules are quite obvious and useful for anyone interested in implementing a more robust and effective tagging regime.

DevOps is a cultural shift with immediate focus on maximising the business value by opting better communication, collaboration and feedback within and across IT development and operation teams. Infrastructure as Code (IaC) is a key element of DevOps philosophy with benefits for both development and operation teams. The term infrastructure as code is sometimes also referred to as programmable infrastructure.

Ever since the Amazon introduced the AWS Lambda service at AWS re:Invent 2014, a variety of new applications for the service has emerged which highlights tremendous potential and traction for the AWS Lambda service. Over last one year, Amazon has been actively working towards integrating other AWS services with AWS Lambda.