Once, dashboards and reports were limited to being embedded into our apps as standalone modules - essentially, as separately accessed product features. This limitation sometimes meant analytics is forgotten by users, and more often than not, underutilized in its potential. Today, contextual analytics makes it possible to embed analytics directly into the core workflow of your software.
One of the best ways to stay current in the fast-evolving field of artificial intelligence and machine learning is by following thought leaders, evangelists, and influencers in the industry. In this article, we’ve selected 10 of the most influential thought leaders (listed alphabetically) that are helping drive the field forward.
The field of data analytics is rapidly evolving alongside advances in technologies such as AI and machine learning. There are many valuable resources online that can help you stay up-to-date with the industry — from news sites, industry analysis, and the latest scientific research. We’re listing the top 10 websites and blogs (listed alphabetically) for anyone interested in keeping up with recent industry developments.
In the world of software development, there’s no such thing as writing perfect code. As such, almost every software developer ends up spending a great deal of their time debugging code. Therefore, one of the best ways to increase your efficiency as a developer is to have the ability to locate errors, identify the root cause, and fix it to resolve problems in your codebase.
As all dev managers, including ourselves, have witnessed, the last few years have been characterized by unprecedented and rapid technological advances. Due to this, there has been a fundamental change in the way applications are being developed. The software world as we knew it shifted from monolithic app development to new methods such as microservices architectures, cloud functions, and distributed systems that are faster and more agile.
Over the last few years, we have seen an avalanche of tools to enable easier software development on Kubernetes (let’s face it, it is quite hard out of the box). As often happens in growing ecosystems, some tools grow and adapt, while others get left behind, or at the very least, merged into new offerings. What’s a better way to open 2021 than with an up-to-date review of the options we have?
Cumulative Layout Shift or CLS, Web Vitals and Core Web Vitals, these terms seem complicated, but it’s actually not that hard to understand what they stand for.
2020 was a testing year for one and all. There were many challenges we had to face and still continue to face. One of them was the challenge to continue working even with the pandemic situation. But, thanks to technological advancements, most of us were able to figure out a way to keep working. And that gave birth to a new style of working for the majority of people around the world. The new style of working includes working from home.
Kong is a popular open-source API gateway to help manage your APIs. With Kong, you can handle authentication, rate limiting, data transformation, among other things from a centralized location even though you have multiple microservices. Kong is built on NGINX at it’s core, one of the most popular HTTP servers. Being open-source, Kong is very easy to deploy on-premises usually in just a few minutes without requiring the installation of many components other than a Postgres or Cassandra store.
GKE is a Google Cloud service that offers a managed Kubernetes cluster, the nodes of the clusters are running on Google Cloud VM instances, the control plane and network is fully managed by GKE. GKE offers a sandboxing feature (https://cloud.google.com/kubernetes-engine/docs/concepts/sandbox-pods ), based on gVisor (https://gvisor.dev/docs/ ) it protects the host kernel from untrusted code.
