Adrian Cockcroft

FEBRUARY 9, 2023

The layers of platforms start at the bottom with hardware choices such as which CPU architectures and vendors you want to use. Above that there’s a deployment platform such as Kubernetes or AWS Lambda. Open source tools which have an open development model that allows your team to make contributions may be a better approach.

Engineering 137

Engineering Serverless Lambda AWS 137

Dynatrace

JUNE 30, 2020

This not only works for your custom developed applications, but also works for 3 rd party applications you host, e.g: Stephan demoed RUM for both a custom developed application as well as for Office 365 where he logged on to SharePoint and navigated through some pages.

Lambda 174

Lambda Monitoring Cloud DevOps 174

The Morning Paper

MARCH 1, 2020

Firecracker is the virtual machine monitor (VMM) that powers AWS Lambda and AWS Fargate, and has been used in production at AWS since 2018. The first version of AWS Lambda was built using Linux containers. A modern commodity server can contain up to 1TB of RAM, and Lambda functions can use as little as 128MB.

Serverless 101

Serverless Virtualization Lambda AWS 101

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 239

Serverless Azure Monitoring Lambda 239

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 143

Serverless Azure Monitoring Lambda 143

All Things Distributed

JULY 14, 2015

Many happy developers are using DynamoDB to handle trillions of requests every day. In traditional database architectures, database engines often run a small search engine or data warehouse engines on the same hardware as the database. Let me expand on each one of them. DynamoDB Streams.

Database 167

Database Lambda AWS IoT 167

cdemi

FEBRUARY 20, 2017

Let's talk about the elephant in the room; Serverless doesn't really mean that there are no Software or Hardware servers. It just means that from Software Development perspective, servers are abstracted and outsourced to another entity, so you don't need to worry about it. Amazon: AWS Lambda. Advantages. Disadvantages.

Serverless 64

Serverless Architecture Lambda Azure 64

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

Dotcom-Montior

NOVEMBER 11, 2020

those resources now belong to cloud providers, such as AWS Lambda, Google Cloud Platform, Microsoft Azure, and others. In serverless architecture, when applications are developed, they are typically composed of many different services. Focus on Application Development. Benefits of a Serverless Model.

Serverless 57

Serverless Monitoring Lambda Latency 57

The Morning Paper

FEBRUARY 27, 2020

If Gandalf doesn’t like what that data is telling it, it will pause a rollout and send an alert to the development team. memory leaks that take hours to build up into an issue); and there can be problems that only exhibit themselves with certain user, hardware, or software configurations. Gandalf system design.

Analytics 68

Analytics Infrastructure Cloud Hardware 68

All Things Distributed

OCTOBER 7, 2015

However, the data infrastructure to collect, store and process data is geared toward developers (e.g., Amazon Redshift, DynamoDB, Amazon EMR) whereas insights need to be derived by not just developers but also non-technical business users.

Cloud 137

Cloud Big Data AWS Analytics 137

Highly Scalable

AUGUST 20, 2013

This article is an effort to explore techniques used by developers of in-stream data processing systems, trace the connections of these techniques to massive batch processing and OLTP/OLAP databases, and discuss how one unified query engine can support in-stream, batch, and OLAP processing at the same time. Partitioning and Shuffling.

Big Data 154

Big Data Processing Lambda Database 154