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How to Tackle Kubernetes Complexity with AI-Driven Infrastructure Monitoring

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Organizations are feeling mounting pressure to accelerate their digital transformation plans, in order to create new revenue streams, manage customer relationships and deliver exceptional user experiences. Containers especially have taken off. A 2020 Cloud Native Computing Foundation survey found that 84% of organizations currently use containers in production, with Kubernetes -- used by 78% of those enterprises deploying containers -- emerging as the de facto solution for managing them. The dynamic nature of Kubernetes and containers, and the speed at which they can be spun up and down, also means that as enterprises speed up digital transformation, they're also speeding into an extremely complex IT environment. And due to the limits of traditional monitoring, that level of complexity results in little observability or insight across the technology stack.


Dynatrace Expands AI-powered Observability For Kubernetes Environments - Liwaiwai

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Software intelligence company Dynatrace, today announced it has extended its Software Intelligence Platform to provide AI-powered observability into the infrastructure layer of Kubernetes environments to include every container, pod, node, and cluster. This is the latest enhancement to Dynatrace, which already provides automatic distributed tracing and deep code-level insights into applications and microservices running in Kubernetes. The pressure to accelerate digital transformation has driven enterprises to increase their investment in cloud-native development using microservices and container architectures. According to a recent Cloud Native Computing Foundation survey, 84 percent of organizations are using containers in production, and 78 percent of these use Kubernetes as their preferred container management solution. Maintaining complete observability into applications and microservices, as well as the infrastructure they run on, is critical to ensure the performance and availability of complex and distributed Kubernetes environments.


Dynatrace Expands AI-Powered Observability for Kubernetes Environments

#artificialintelligence

Software intelligence company Dynatrace announced it has extended its Software Intelligence Platform to provide AI-powered observability into the infrastructure layer of Kubernetes environments to include every container, pod, node, and cluster. This is the latest enhancement to Dynatrace, which already provides automatic distributed tracing and deep code-level insights into applications and microservices running in Kubernetes. The pressure to accelerate digital transformation has driven enterprises to increase their investment in cloud-native development using microservices and container architectures. According to a recent Cloud Native Computing Foundation survey, 84 percent of organizations are using containers in production, and 78 percent of these use Kubernetes as their preferred container management solution. Maintaining complete observability into applications and microservices, as well as the infrastructure they run on, is critical to ensure the performance and availability of complex and distributed Kubernetes environments.


What AIOps means to modern IT environments - DevOps Online

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Working with over 2,000 customers globally, Dynatrace aims to help some of the world's biggest brands to tackle cloud complexity and deliver better business outcomes. Andi Grabner, a self-proclaimed DevOps activist who works for the software intelligence company, is the Director of Strategic Partner Enablement at the firm. He says his mission is helping developers, testers and operations teams become more efficient at their jobs by applying DevOps practices. In an exclusive Q and A with DevOps Online, he discusses how AI and DevOps are coming together and companies can do to make the most of it. Businesses need to understand their IT environment and how changes, or performance problems, affect the user experience.


Dynatrace 2020 Predictions: The 3 Trends That Will Define How Enterprises Conquer IT Complexity in 2020 : @VMblog

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AI and cloud environment adoption has changed the game for IT over the past decade. These technologies have opened the door for businesses to create compelling digital experiences. But they have also come with a cost, introducing new levels of complexity into enterprise technology stacks. Now it's more difficult than ever to understand your IT environment, let alone identify and resolve any problems that may be occurring in that environment. That's why, as 2020 and a new decade get under way, I'm predicting that these three trends will define how enterprises finally rein in IT complexity.