As Black Friday 2020 fast approaches, companies far and wide have started advertising mega sales in their droves. With slashed prices as high as 75% off, Black Friday has become one of the highest revenue days of the year for the retail industry. This year, however, is different.
IntegrationHub spokes accelerate ServiceNow-Microsoft workflow automation One of the features of the Now Platform Paris release is built-in Microsoft Azure Active Directory integrations that simplify common workflows ServiceNow Onboarding and Software Asset Management (SAM).
Air quality monitoring is important as poor air quality is responsible for an estimated 60,000 premature deaths in the United States each year, and annual costs from air pollution-related illness are estimated at $150 billion. Air quality monitoring can help track and guide action to reduce air pollution, which can cause short-term and long-term health effects for children, older adults, and people with heart disease, asthma, and other respiratory conditions.
Netdata is zero-configuration monitoring. It’s a principle that we’ve stood behind since the project’s beginning, when it was only our CEO Costa trying to solve a “painful, real-world problem,” and it’s one we stand by today. Our insistence on zero-configuration guides every product decision we make, every grooming process, and every React component our frontend teams design.
On our journey to democratize monitoring, we are proud to have open source at the core of both our products and our company values. What started as a project out of frustration for lack of existing alternatives (see anger-driven development), quickly became one of the most starred open-source projects on all of GitHub.
Modern applications are changing, and traditional testing practices are no longer up to the task. Learn more about the changing landscape of QA and how Chaos Engineering provides the necessary framework for testing modern applications. Chaos and Reliability Engineering techniques are quickly gaining traction as essential disciplines to building reliable applications. Many organizations have embraced Chaos Engineering over the last few years.
We created the Fleet Project to provide centralized GitOps-style management of a large number of Kubernetes clusters. A key design goal of Fleet is to be able to manage 1 million geographically distributed clusters. When we architected Fleet, we wanted to use a standard Kubernetes controller architecture. This meant in order to scale, we needed to prove we could scale Kubernetes much farther than we ever had.
By design and tradition, telecoms networks are built to last. But in a world where the rate of innovation seems to be accelerating, the end result is that a lot of legacy infrastructure needs to keep pace with, and accommodate, multiple ‘next generation’ phases. How long this can be maintained before the imperative to rip and replace becomes impossible to ignore is the multi-million-dollar question.
A few years ago, we realized that spending in our AWS product test environment had jumped significantly from one month to the next. We drilled down into the issue and traced it to some RDS database instances that had been spun up to test new product features. No one realized that these expensive instances were left running after the tests were complete, and subsequently racking up charges for several months.
That’s the question ops personnel have been asking for decades whenever something goes wrong in the production IT environment. Everything was working before, so the reasoning goes, and now it’s not. We have an incident. And to figure out what caused the incident – and hence, to have any idea how to fix it – we must know what changed. There’s just one problem with this approach. What if everything is subject to change, all the time?
