With the introduction of Elastic Kubernetes service at re: Invent last year, AWS finally threw their hat in the ever booming space of managed Kubernetes services. In this blog post, we will learn the basic concepts of EKS, launch an EKS cluster and also deploy a multi-tier application on it.
Internet of things (IoT) is maturing rapidly and it is finding application across various industries. Every common device that we use is turning into the category of smart devices. Smart devices are basically IoT devices. These devices captures various parameters in and around their environment leading to generation of a huge amount of data. This data needs to be collected, processed, stored and analyzed in order to get actionable insights from them. To do so, we need to build data pipeline.
In this blog we will be building a similar pipeline using Mosquitto, Kinesis, InfluxDB and Grafana. We will discuss all these individual components of the pipeline and the steps to build it.
GraphQL is a new hype in the Field of API technologies. We have been constructing and using REST API's for quite some time now and started hearing about GraphQL recently. GraphQL is usually described as a frontend-directed API technology as it allows front-end developers to request data in a more simpler way than ever before. The objective of this query language is to formulate client applications formed on an instinctive and adjustable format, for portraying their data prerequisites as well as interactions.
The Phoenix Framework is running on Elixir, which is built on top of Erlang. Elixir core strength is scaling and concurrency. Phoenix is a powerful and productive web framework that does not compromise speed and maintainability. Phoenix comes in with built-in support for web sockets, enabling you to build real-time apps.
Custom resources definition (CRD) is a powerful feature introduced in Kubernetes 1.7 which enables users to add their own/custom objects to the Kubernetes cluster and use it like any other native Kubernetes objects. In this blog post, we will see how we can add a custom resource to a Kubernetes cluster using the command line as well as using the Golang client library thus also learning how to programmatically interact with a Kubernetes cluster.
As per this article, Custom Resource Definitions are part of a wider effort to refine and enhance Kubernetes as an extensible application platform, factoring everything but the bare essentials out of “core” Kubernetes in favour of modular and maintainable extensibility mechanisms.
In this blog we understand how one can go about writing their own CRDs with a hand-on demonstration.
Asynchronous programming is a type of parallel programming in which a unit of work is allowed to run separately from the primary application thread. Asynchronous programming has been gaining a lot of attention in the past few years, and for good reason. Typically Node.js is associated with Asynchronous programming. Although, nowadays other languages including Python do support Asynchronous programming.
This blog acts an introduction to asynchronous programming in Python and explores different ways in which to achieve that.
Jenkins X is a project which rethinks how developers should interact with CI/CD in the cloud with a focus on making development teams productive through automation, tooling and DevOps best practices.
In this blog, we explore Jenkins X, understand how it differs from Jenkins and how to go about building and deploying our first application using it.
There is a recent trend in change in architecture of the way data is stored and compute is done. Edge computing is one of such phenomena in which either the data or the compute is decentralized and taken to the nearest nodes of the user it can either be smartphone or local region servers.
In this blog we will delve into what Edge Computing really is, it’s various types, and see how it is implemented and managed in the real world.
Zappa makes it super easy to build and deploy server-less, event-driven Python applications (including, but not limited to, WSGI web apps) on AWS Lambda + API Gateway. Think of it as "serverless" web hosting for your Python apps. That means infinite scaling, zero downtime, zero maintenance - and at a fraction of the cost of your current deployments!
This blog acts a simple tutorial to deploy a sample Django/Python application using Zappa.
Kubernetes allows deployment and management container-based applications at scale. One of the main advantages of Kubernetes is how it brings greater reliability and stability to the container-based distributed application, through the use of dynamic scheduling of containers. But, how do you make sure Kubernetes itself stays up when a component or its master node goes down?
In this blog we look at the steps to ensure that your kubernetes cluster is always highly available and fault tolerant.
In the age of continuous delivery and agility where the software is being deployed 10s of times per day and sometimes per hour as well using container orchestration platforms, a seamless upgrade mechanism becomes a critical aspect of any technology adoption. In this blog we explore the various upgrade strategies available for Statefulsets in Kubernetes with Cassandra as the database.
According to the OpenAI Gym GitHub repository “OpenAI Gym is a toolkit for developing and comparing reinforcement learning algorithms. This is the gym open-source library, which gives you access to a standardized set of environments.”
Open AI Gym has an environment-agent arrangement. It simply means Gym gives you access to an “agent” which can perform specific actions in an “environment”. In return, it gets the observation and reward as a consequence of performing a particular action in the environment.
Recently, the author was involved in building a custom ETL(Extract-Transform-Load) pipeline using Apache Airflow which included extracting data from MongoDB collections and putting it into Amazon Redshift tables.
Each ETL pipeline comes with a specific business requirement around processing data which is hard to be achieved using off-the-shelf ETL solutions. This is why a majority of ETL solutions are built manually, from scratch. In this blog, I am going to talk about my learnings around building an optimized, efficient, near real-time and fault tolerant custom ETL solution using Apache Airflow which involved moving data from MongoDB to Redshift.