Last month, members of the Datadog community convened in Seattle for our customer summit. There, they discussed new developments in monitoring dynamic infrastructure and applications, learned about the latest updates to the Datadog platform, and shared tips, tools, and techniques from their own experiences.
The early adopters have begun to find a great degree of success and it is now time for the more mainstream enterprise to get off the proverbial wall and begin exploring containers and other areas of the cloud-native landscape. However, there is a need to mitigate or manage the risk of adopting new technology as it does introduce a dimension of change that accompanies any transformation.
Everybody climb aboard the hype train with me. Today, we’re going to study a new job title: the DevOps engineer. This role is getting popular in the same way that the full-stack developer role became popular before it. In fact, one could argue that the DevOps engineer is an extension of the full-stack developer in that both seek to extend our ownership of our software.
Some time ago, the Register published an article titled “Lambda and serverless is one of the worst forms of proprietary lock-in we’ve ever seen in the history of humanity”. It received a lot of attention, and vendor lock-in has become a perennially popular question at conferences. But I’m here to tell you that you are probably thinking about vendor lock-in all wrong when it comes to serverless.
For years, traditional infrastructure provisioning and management followed a specific operating model that depended on Network Operations Centers (NOCs) to process operational events. As enterprise companies started to undergo digital transformation, the cloud created a different operating model: One that was much more agile and, some would argue, more efficient—and would replace all other operating models to create IT homogeneity.
If you’re running a production application, you need metrics. There are great products out there that allow you to gain visibility into how your application is performing, give some nice graphs, and charge you for it. In the Rails community, this is commonly achieved by using NewRelic and Skylight. But for some of us, we achieve visibility by using Prometheus and Grafana that we build and host ourselves.
Docker is a powerful tool for creating and deploying applications. It simplifies rolling out applications across multiple systems and is a useful tool for integrating new technologies. An application that runs using Docker will start up the same every time on every system. This means that if the application works on your local computer, it’ll work anywhere that supports Docker. That’s great news! It simplifies your development process and can be a powerful tool for continuous delivery.
While using Kubernetes clusters of different distributions like – AKS, GKE, EKS, OpenShift, and ICP we need to give specific privileges to a specific user/user group. During this process, to give restricted access to a cluster we can make use of a service account.
In today’s software-driven economy, every organization faces an imperative to modernize the way they deliver software in order to adapt and enable the digital era — or perish. Digital transformation across industries is driving the need for IT to enable Cloud-Native applications. This has led enterprises to adopt Kubernetes as the most effective way to support cloud-native architectures and to modernize their applications and IT infrastructure.
While Logz.io provides Kibana — the ELK Stack’s visualization tool — as part of its service, a lot of users have asked us to support Grafana. One of the leading open source visualization tools today, Grafana has some added value when compared to Kibana, especially around visualizing time-series data.
