
How will your emails look on Apple’s iPhone 17?
Mailosaur offers coverage for the brand new iPhone 17, iPhone 17 Air and iPhone 17 Pro Max, allowing you to preview your emails across the board.
Explore the Mailosaur blog for expert insights on email & SMS testing, automation, and quality assurance

Mailosaur offers coverage for the brand new iPhone 17, iPhone 17 Air and iPhone 17 Pro Max, allowing you to preview your emails across the board.

Let's talk email previews software; which is the best fit for your team?

If you’re sending emails out to a lot of people, it’s critical to have a good email testing plan in place.

This will show you how to test two-factor authentication using SMS, or an authenticator app, with Mailosaur and the cross-platform JMeter automated testing tool.

It sometimes feels like the robots are coming to the QA world, with automation and automated testing being such a hot topic at the moment.

Explore the significance, key metrics, methodologies, and best practices for maximizing Return on Investment (ROI).

It’s a question that has beguiled an endless list of QA teams: should I automate this test?

In this article, we will take a deeper look into the world of QA automation, exploring its benefits, as well as the challenges it faces.

Software testing types and their vital roles in development. Gain insights for robust practices and ensure high-quality software delivery.

IMAP (Internet Message Access Protocol) – a powerful communication protocol shaping modern email management. Learn how IMAP works and explore the key differences between IMAP and POP3.

Email inconsistency across different clients and devices is a common source of frustration for both senders and recipients. This inconsistency can manifest in several ways, leading to emails not appearing in the inbox, content not fully loading, or images not displaying.

SMS testing plans are important for staying on track when testing the functionality of your SMS campaigns. Without a clear test plan it’s easy to get disorganized, which can lead to inefficient testing, missing or unusable results, and other mistakes slipping through the cracks.