Dynatrace

AUGUST 12, 2020

As companies strive to innovate and deliver faster, modern software architecture is evolving at near the speed of light. Following the innovation of microservices, serverless computing is the next step in the evolution of how applications are built in the cloud. Optimize your code with code-level visibility.

Serverless 232

Serverless Azure Monitoring Lambda 232

O'Reilly

NOVEMBER 28, 2023

Even with cloud-based foundation models like GPT-4, which eliminate the need to develop your own model or provide your own infrastructure, fine-tuning a model for any particular use case is still a major undertaking. That pricing won’t be sustainable, particularly as hardware shortages drive up the cost of building infrastructure.

Open Source 108

Open Source Artificial Intelligence Google Infrastructure 108

Dynatrace

NOVEMBER 15, 2021

Logs can include data about user inputs, system processes, and hardware states. Log analysis can reveal potential bottlenecks and inefficient configurations so teams can fine-tune system performance. Accelerated innovation. “Logging” is the practice of generating and storing logs for later analysis.

Analytics 202

Analytics Monitoring Artificial Intelligence DevOps 202

Dynatrace

AUGUST 12, 2020

As companies strive to innovate and deliver faster, modern software architecture is evolving at near the speed of light. Following the innovation of microservices, serverless computing is the next step in the evolution of how applications are built in the cloud. Optimize your code with code-level visibility.

Serverless 140

Serverless Azure Monitoring Lambda 140

The Morning Paper

JUNE 27, 2019

Systems researchers are doing an excellent job improving the performance of 5-year old benchmarks, but gradually making it harder to explore innovative machine learning research ideas. Named dimensions improve readability by making it easier to determine how dimensions in the code correspond to the semantic dimensions described in,e.g.,

Systems 87

Systems Tuning Programming Innovation 87

The Netflix TechBlog

APRIL 29, 2019

Such applications track the inventory of our network gear: what devices, of which models, with which hardware components, located in which sites. One example is the Spectator Python client library, a library for instrumenting code to record dimensional time series metrics. We use Python to help generate TLS certificates using Lemur.

Open Source 279

Open Source Network Infrastructure Big Data 279

All Things Distributed

MARCH 19, 2018

Amazon SageMaker training supports powerful container management mechanisms that include spinning up large numbers of containers on different hardware with fast networking and access to the underlying hardware, such as GPUs. This can all be done without touching a single line of code. Post-training model tuning and rich states.

Scalability 159

Scalability Hardware AWS Tuning 159

The Morning Paper

NOVEMBER 10, 2019

Rather than reimplement TCP/IP or refactor an existing transport, we started Pony Express from scratch to innovate on more efficient interfaces, architecture, and protocol. Once the whole fleet has turned over, the code for the now unused version(s) can be removed. Emphasis mine). The little engine that could.

Network 92

Network Transportation Latency Entertainment 92

All Things Distributed

OCTOBER 8, 2014

Let’s now look at the history behind the service and the context for new innovations that make me think that. Look for a more detailed blog on the architecture of this application and its sample source code in the next few days! NoSQL and Scale. Expanding the freedom to invent.

Availability 145

Availability Performance Scalability AWS 145

SQL Server According to Bob

JANUARY 11, 2020

​​ With new ​​ innovations ​​ come ​​ new terms, designs, ​​ and ​​ algorithms. ​​ Extended Data: ​​ “incorrect checksum (expected:​​ ## ; actual:​​ ## )” Contact your hardware manufacture for assistance.

Servers 40

Servers Cache Database Media 40

All Things Distributed

NOVEMBER 30, 2016

Effectively applying AI involves extensive manual effort to develop and tune many different types of machine learning and deep learning algorithms (e.g. automatic speech recognition, natural language understanding, image classification), collect and clean the training data, and train and tune the machine learning models.

AWS 165

AWS Lambda Artificial Intelligence Mobile 165

High Scalability

NOVEMBER 25, 2019

Java used to power core file system code. Python used to power client-side code, certain microservices, migration scripts, internal scripts. We use event-based sync in our desktop sync client code, as server events are happening they get pushed to the client from server and the client replays them locally.

Architecture 52

Architecture Cache Azure Storage 52