Systems | Development | Analytics | API | Testing

The Two Generals’ Problem is a well-known thought experiment about how asynchronous – and potentially unreliable – communications can cause, shall we say, issues. These great generals from history are facing a cunning and capable enemy. Think of someone like Khalid ibn al-Walid, Napoleon, Erwin Rommel or Sun Tzu. If the generals attack together, they will win. If they attack separately, they will lose. The problem is that they are communicating over an unreliable and slow medium.

Moesif and Datadog are both platforms that provide monitoring and the ability to view metrics. At their core, though, both platforms do very different things for your organization and the teams that use them. Both can complement each other very well and contain features that can aid in making better products that scale seamlessly.

Bayer Crop Science uses Google Cloud to analyze billions of acres of land to better understand the characteristics of the soil that produces our food crops. Bayer’s teams of data scientists are leveraging services from across Google Cloud to load, store, analyze, and visualize geospatial data to develop unique business insights. And because much of this important work is done using publicly-available data, you can too!

For the next interview in our series speaking to technology and IT leaders around the world, we’ve welcomed Patrick Gleeson, CTO at Basubu to share his insights on being a CTO at a fast-paced startup.

In this series of blog posts, we will showcase an end-to-end hybrid cloud ML workflow using the Iguazio MLOps Platform & Feature Store combined with Azure ML. This blog will be more of an overview of the solution and the types of problems it solves, while the next parts will be a technical deep dive into each step of the process.

With hundreds of SaaS products in a given company, it’s getting more and more challenging and time-consuming to manage supplier relationships and negotiate contracts. Vendr has completely transformed this entire process by creating a SaaS buying platform where stakeholders can easily handle the relationships and contracts of their different software suppliers in a centralized platform.

Flaky tests are automated software tests that sometimes pass and sometimes fail without an obvious reason. Often these tests will work well for a while, then occasionally start to fail. If the test passes on a second or third try without any obvious reason for the failures, the tester typically chalks it up to a glitch in the system and ignores the failed test result.