In the third episode of our podcast, Mobile DevOps is a thing! , we talk to John Sundell. Join us as we discuss how mobile teams can level up their skills and benefit from test automation and continuous delivery.

Most modern web applications are heavily reliant on persisting data with relational databases, and so it’s no surprise that a large part of application performance monitoring relates to keeping an eye on database performance to ensure that our SQL queries are as efficient as possible. With this in mind, Scout features a Database Addon module, and in this video we are going to take a closer look at what it has to offer.

At Google Cloud, we work with organizations performing large-scale research projects. There are a few solutions we recommend to do this type of work, so that researchers can focus on what they do best—power novel treatments, personalized medicine, and advancements in pharmaceuticals.

We hear from our users in the scientific community that having the right technology foundation is essential. The ability to very quickly create entire clusters of genomics processing, where billing can be stopped once you have the results you need, is a powerful tool. It empowers the scientific community to spend more time doing their research and less time fighting for on-prem cluster time and configuring software.

ERP systems enable businesses to bring together and manage core processes and technologies under one system. But the truth is, an out-of-the-box ERP system rarely fits a business perfectly, and even if it does, it is only temporary. A business’s challenges, needs, and strategies change and grow over time, and its tools must too. When an ERP’s functionality does not fully meet your business’s needs, it’s time to think about extending it.

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.