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AWS observability: AWS monitoring best practices for resiliency

Dynatrace

These resources generate vast amounts of data in various locations, including containers, which can be virtual and ephemeral, thus more difficult to monitor. These challenges make AWS observability a key practice for building and monitoring cloud-native applications. AWS monitoring best practices. AWS Lambda.

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AI Prowess: Harnessing Docker for Streamlined Deployment and Scalability of Machine Learning Applications

DZone

The following sections present an in-depth exploration of Docker, its role in ML model deployment, and a practical demonstration of deploying an ML model using Docker, from the creation of a Dockerfile to the scaling of the model with Docker Swarm, all exemplified by relevant code snippets. What Is Docker?

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Monitoring-as-code through Dynatrace’s Open-Source Initiative

Dynatrace

Dynatrace’s OneAgent automatically captures PurePaths and analyzes transactions end-to-end across every tier of your application technology stack with no code changes, from the browser all the way down to the code and database level. Monitoring-as-code requirements at Dynatrace.

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What is application security monitoring?

Dynatrace

Identification The identification stage of application security monitoring involves discovering and pinpointing potential security weaknesses within an application’s code, configuration, or design. If a vulnerability remains undetected, the compromised code can allow attackers access to data they’re not authorized to have.

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How zero trust architecture can improve government user experiences

Dynatrace

I filled out a form, input my government ID information, and waited for a confirmation code that never came. If they got frustrated by jumping through a series of virtual hoops to authenticate themselves, their frustration was of secondary concern (if it was of any concern at all). Fortifying the system was all that mattered.

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Accelerate and empower Site Reliability Engineering with Dynatrace observability

Dynatrace

With Davis AI’s contextual capabilities, embracing chaos engineering and making application code robust and better prepared for production deployments is easy. By identifying the exact code or trace that causes a failure, Davis AI helps teams fix problems quickly and significantly reduces MTTR. However, this is highly unlikely.

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Getting Hands-on Training into more hands in 2021

Dynatrace

And we know as well as anyone: the need for fast transformations drives amazing flexibility and innovation, which is why we took Perform Hands-on Training (HOT) virtual for 2021. Here’s what’s new this year, and how you can get a front-row seat in our virtual classroom. More flexibility, more options. The Dynatrace University Team.