Operations | Monitoring | ITSM | DevOps | Cloud

Backstage is a platform for building developer portals. Originally developed internally at Spotify, it’s now open source and available through GitHub. Backstage allows DevOps teams to create a single-source, centralized web application for sharing and finding software (through the software catalog feature), as well as templates and documentation.

While the cloud is recognized as more secure than on-premises servers and infrastructures, it does come with the often talked about shared responsibility model. Cloud providers are responsible for security ‘of’ the cloud, while their clients are responsible for security ‘in’ the cloud. It’s ‘differently secure’, rather than the traditionally secure organizations have been used to when working with on-premises environments.

At Datadog, we have always been deeply involved with open source software—producing it, using it, and contributing to it. Our Agent, tracers, SDKs, and libraries have been open source from the beginning, giving our customers the flexibility to extend our tools for their own needs. The transparency of our open source components also allows them to fully audit the Datadog software that is running on their systems. But our commitment to open source only starts there.

I used to think my job as a developer was done once I trained and deployed the machine learning model. Little did I know that deployment is only the first step! Making sure my tech baby is doing fine in the real world is equally important. Fortunately, this can be done with machine learning monitoring. In this article, we’ll discuss what can go wrong with our machine-learning model after deployment and how to keep it in check.

Azure Functions offers a serverless solution that streamlines the development process, minimizes infrastructure overhead, and results in cost savings. The beauty of this approach is that you no longer need to grapple with server deployment and maintenance; the cloud infrastructure automatically furnishes the essential resources to support your applications.

As technology advances and business environments become increasingly competitive, your DevOps team has to continuously improve your product. The challenge is to free up their time so that they can release new product features and improve existing ones. Automating repetitive tasks is one way to accomplish this. Manual approaches also tend to generate or miss errors, slow time to market, and fail to test and monitor system health quickly enough.