As InfluxDB continues to grow and improve, more and more developers are using it as the platform of choice for their own solutions. Most of these solutions range from filling niche internal needs to solving common problems faced by entire industries, but some of them are extraordinary for their impact, innovation, or how much they push the boundaries of what is possible with the technology. In order to recognize those, we are launching the InfluxDB Inventors program.
Alerting systems centralize all IT alerts into one intuitive platform. IT alerting systems integrate with your tooling stack, and provide alert controls that help teams increase efficiency and reduce false positives. The main functions of an IT alerting system include activating incident response, automating alerts, providing intuitive reports, and enabling quick communication between roles. To enable these functions, alerting systems should be designed with quality in mind, rather than quantity.
The blessing and curse of cloud computing is flexibility. Now more than ever, companies leveraging the cloud are being revered for their ability to scale up usage of critical applications remotely for employees working from home, while in the same breath lambasted as IT costs sky-rocket. And in the midst of soaring usage, capacity, and cost come budget-cuts to fend off any other necessary evils during this challenging time.
How many website monitoring service providers are there, worldwide? Where are they from? What features do they offer? How much do they charge? You can learn the answers to these questions and much more from our infographic below. In May 2020, we conducted research analysing and comparing website monitoring offers from all over the world. Here is a graphical presentation of what we found out.
The entire country of China’s internet connectivity is shielded by the Great Firewall (GFW). There are three state-owned ISP providers, China Unicom, China Telecom, and China Mobile, that control internet in China. Essentially, all traffic between China and the rest of the world goes through a few national level and a handful of core level access points in different regions.
At Grafana Labs, we’re all big fans of the Prometheus and Grafana combination. To an extent, we just won’t shut up about it. We strongly believe in simplicity and think you shouldn’t need any extra effort to understand the metrics of your service(s) holistically. Yet we’ve all been in that situation where it is challenging to fully grasp what the metrics of our service(s) are and what they do. While naming conventions exist, at times they are not followed or enforced.
In part one of this series, I introduced you to Kubeflow, a machine learning platform for teams that need to build machine learning pipelines. In this section, we will learn how to take an existing machine learning project and turn it into a Kubeflow machine learning pipeline, which in turn can be deployed onto Kubernetes. As you are going through this exercise, think about how you can convert your existing machine learning projects into a Kubeflow one.
Today, monolithic applications evolve to be too large to deal with as all the functionalities are placed in a single unit. Many enterprises are tasked with breaking them down into microservices architecture. At LogicMonitor we have a few legacy monolithic services. As business rapidly grew we had to scale up these services, as scaleout was not an option.
