In this release, we’ve focussed on providing exceptional capability for our customers - both enterprise and software companies - to create and deploy embedded analytics experiences that drive user adoption with minimum amount of effort and coding.

As first-party customer data continues to explode, companies have struggled to make it actionable for personalization, advanced analytics, and other business purposes. As a result, customer data platforms that consolidate and activate known customer information have emerged to help companies generate ROI from their data. At present, nearly 80% of marketing organizations already have a customer data platform or are developing one.

You may have spent a considerable amount of time configuring Postman requests for your in-house API tests, and you wish to use them without having to create them again from scratch on Octoperf. That’s one of the many situations where Octoperf’s compatibility with Jmeter is going to come in a handy.

A brittle ETL pipeline, a mix of different code languages and degrading warehouse performance inhibited customer retention analysis. With a modern data stack, Ritual has a 95% reduction in data pipeline issues, a 75% reduction in query times, and a threefold increase in data team velocity. By empowering the business with data, the business has seen a sustained improvement in retention.

We are happy to announce the much-anticipated Kuma 0.6 release! This new release ships with major improvements, especially when it comes to supporting service meshes that can span across multiple clouds, multiple Kubernetes clusters and hybrid platforms (Kubernetes + VMs) in enterprise environments. Kuma has also been donated to the CNCF as a Sandbox project: the first Envoy-based service mesh to ever be donated to the foundation. Let’s unwrap these announcements.

Learn how to integrate Genymotion Cloud Android Virtual Devices into your workflows and use the testing framework of your choice on Bitrise.

When it comes to furnishing our living spaces, it seems we go through phases. When I was just setting out and leaving home, IKEA was my preferred furniture store. You make your choice, collect all the flat-pack boxes, lug them home, and after some hex key gymnastics: voilà. You’ve truly made it! Since then, I’ve drifted from the “some assembly required” phase to the “ready-made” one.

Flutter blurs the lines between designer and developer and endorses a new designer developer archetype. Part designer part engineer, part Picasso and part Pascal. With ambitious designs comes the responsibility to make those designs run on the screen without losing frames. While Flutter is performant by design, how much should we really pay attention to performance optimisation? In most cases … we don’t.

We interviewed the product managers at a number of the larger API-first companies that are based in San Francisco. The companies are all publicly traded, have TTM revenue of more than $100M and are in the fields of billing, security, communications and workflow automation. The PMs were asked what were their favorite tools and what API metrics they cared most about.

When you set out to build your first API, it can very well be that you are either overwhelmed or forget essential points. The ecosystem for API tools is vast, and it’s vital to get the right tool for every phase of your project. In this article, we will go through the different phases an API project usually has. For every phase, I will list the significant points and tools that help there.