Many modern-day applications need to be built at an enterprise scale, sometimes even at an internet scale. Each application needs to meet scalability, availability, security, reliability, and resiliency demands.
In this article, I’m going to talk about some design patterns that can help you achieve the above-mentioned abilities with ease. I’ll be talking about each pattern, how to use that pattern in a cloud-native environment, and when to use it and when not.
Some of these patterns aren’t so new but are very useful in the current internet-scale cloud world.
Here’s the list of patterns I’ll be discussing in this…
StackOverflow recently published the results of their Developer Survey. The survey collected data from developers coming from different countries, backgrounds, and technologies.
Here is a glimpse of some demographics —
By Country —
It has been almost a decade(or more than that!) since the world has been talking about DevOps. Unfortunately many do not have a very clear idea about what DevOps means!
According to the State of DevOps Report 2021 —
Today, 83 percent of IT decision-makers report their organization is implementing DevOps practices. Yet the past four State of DevOps Reports has shown the vast majority of organizations are stuck in the middle.
EnvoyProxy & Dapr has gained a lot of popularity as frameworks that enable smoother microservices adoption by letting developers focus on the business logic. Though Envoy & Dapr are built to solve different problems, there are some obvious similarities between the two.
In this article, I am going to give a brief introduction to both frameworks and suggest their suitable usage.
So let’s get started!
Software Supply Chain attacks are growing recently. A study shows a whooping rise of 12x in just the last 3 years.
Software development and distribution have become a vulnerable space in recent times. Recent attacks like SolarWinds & CodeCov show that attackers are using the vulnerabilities in the Software Supply Chain to maximize the impact.
As stated in the SolarWinds incident —
SolarWinds and our customers were the victims of a cyberattack to our systems that inserted a vulnerability (SUNBURST) within our Orion® Platform software builds for versions 2019.4 HF 5, 2020.2 unpatched, and 2020.2 …
The Pragmatic Programmers is a very well known publication that publishes books on various topics like —
This year in Feb, they published their whole catalog on Medium. As a Medium Member, you can enjoy reading the full catalog as part of your membership.
In this article, I am trying to list down the top 5 books you…
I recently stumbled upon an article The Goals of API Testing from Pragmatic Programmers that talks in-depth about various goals to consider while testing REST APIs. My quest to know more about the topic led to me a recent publication from Microsoft Research that talks about API Fuzz Testing.
In this article, I am going to explain the concept and try out an open-source tool to fuzz test some sample APIs. This article expects you have a basic knowledge about REST APIs.
According to OWASP —
Fuzz testing or Fuzzing is a Black Box software testing technique, which basically consists…
Recently I got a chance to learn about eBPF from Liz Rice at one of the InfoQ live sessions. And I was surprised to see the superpowers and capabilities it can bring to the table when it comes to networking, security, and observability.
In this article, I am going to explore eBPF and tools built on top of it and see how they can help in the cloud-native world.
The Linux Kernel consists of two parts —
Using containers for application development and deployment is very common these days.
While containers certainly bring a lot of value, they also bring some challenges like —
The most common solution to this problem is — using smaller distros!
Using lightweight distros like Alpine is a very common technique amongst the developers to avoid making the container image bulky. …
Data Discovery has become one of the most important capabilities that Enterprise Data Platforms must provide. Over the years many big companies like Airbnb, LinkedIn, Uber, Netflix, Lyft, etc. have talked about how they solved the data discovery problem by building an in-house metadata search engine.
With the rise in Analytics, Machine Learning & Data Science projects, data discovery has got the top priority in many data teams.
Even modern-day enterprise data architectures like Data Mesh talks about the importance of Data Catalogs.