Dynatrace

OCTOBER 7, 2021

Instead of worrying about infrastructure management functions, such as capacity provisioning and hardware maintenance, teams can focus on application design, deployment, and delivery. Lambda functions can be written in the language of your choice, and the service also supports container tools. Simplicity. Data Store.

Serverless 276

Serverless AWS Lambda Storage 276

Dynatrace

JANUARY 26, 2021

This allows teams to sidestep much of the cost and time associated with managing hardware, platforms, and operating systems on-premises, while also gaining the flexibility to scale rapidly and efficiently. AWS Lambda functions are an example of how a serverless framework works: Developers write a function in a supported language or platform.

Serverless 242

Serverless Efficiency Lambda Azure 242

Dynatrace

JUNE 30, 2020

We came up with list of four key questions, then answered and demoed in our recent webinar. Stephan demoed how avodaq internally leverages Dynatrace Synthetic. In the demo, Stephan showed the waterfall view highlighting issues in connectivity, bad HTTP requests or even JavaScript errors.

Lambda 174

Lambda Monitoring Cloud DevOps 174

Dynatrace

AUGUST 12, 2020

Despite its benefits, serverless computing introduces additional monitoring challenges for developers and IT Operations, particularly in understanding dependencies and identifying issues in the end-to-end traces that flow through a complex mix of dynamic and hybrid on-premise/cloud environments. Azure Functions in a nutshell.

Serverless 234

Serverless Azure Monitoring Lambda 234

Dynatrace

AUGUST 12, 2020

Despite its benefits, serverless computing introduces additional monitoring challenges for developers and IT Operations, particularly in understanding dependencies and identifying issues in the end-to-end traces that flow through a complex mix of dynamic and hybrid on-premise/cloud environments. Azure Functions in a nutshell.

Serverless 140

Serverless Azure Monitoring Lambda 140

All Things Distributed

NOVEMBER 30, 2016

Today, there are thousands of machine learning scientists and developers applying machine learning in various places, from recommendations to fraud detection, from inventory levels to book classification to abusive review detection. in ML and neural networks) and access to vast amounts of data.

AWS 165

AWS Lambda Artificial Intelligence Mobile 165