d2iq

FEBRUARY 19, 2021

2015): Hidden Technical Debt in Machine Learning Systems. While there is a large infrastructure component that can often be handled by DevOps or platform engineers, the challenges unique to machine learning mean in practice that they need to have a solid background in modelling too. Keras and TensorFlow emerged in 2015.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

Altexsoft

FEBRUARY 10, 2021

Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. DataOps is a relatively new methodology that knits together data engineering, data analytics, and DevOps to deliver high-quality data products as fast as possible.

Analytics 75

Analytics DevOps Development Software Review 75

Bernd Rucker

MAY 27, 2020

And while they started operating a central BPM platform back in 2015, they moved away from this model to allow people to run their own engine. Which brings us to microservices. This means that with microservices you deliberately accept a wild mix of Camunda installations! We set up Camunda BPM DevOps for this matter.

Programming 52

Programming Company Architecture Technical Review 52

Altexsoft

MAY 18, 2022

There has been a lot of buzz around the concept of microservices lately with quite a few businesses adopting it to get rid of huge, monolithic backends. These and other issues have made frontend developers look in the direction of microservices too. Monolithic architecture vs microservices and micro frontends.

Microservices 64

Microservices Weak Development Team Development Software Review 64

Honeycomb

SEPTEMBER 23, 2021

But there is a coherent set of practices that started to emerge about five years ago, in response to changes in how we build modern systems — particularly microservices. 2015: We started building Honeycomb and wrestling mightily with how to talk about what we were building. Similarly, DevOps (to this day!) Let’s do this.

Metrics 123

Metrics DevOps System Microservices 123

Battery Ventures

JULY 23, 2018

This was one of the drivers behind Collibra’s decision to move the majority of its management team, and its commercial headquarters, to New York in 2015. Other companies opt for San Francisco or Silicon Valley to tap what some say is a deeper pool of technical talent.

B2B 55

B2B Open Source Enterprise Culture 55

O'Reilly Media - Ideas

JANUARY 25, 2024

While we like to talk about how fast technology moves, internet time, and all that, in reality the last major new idea in software architecture was microservices, which dates to roughly 2015. Microservices saw a 20% drop. If implemented poorly, microservices deliver neither scale nor flexibility.

Trends 116

Trends Technical Review Technology Artificial Inteligence 116

Xebia

APRIL 27, 2023

In 2015 a company called CoreOS created its version of containers that could potentially fragment the container industry. The application is divided into microservices. Container History Container technology was developed over ten years ago for Linux in the form of LXC. They were the competitor of Docker.

Linux 130

Linux Software Review Technical Review Virtualization 130

O'Reilly Media - Ideas

MARCH 12, 2019

Almost as old as O’Reilly itself, Radar has a history of playing a key role in the development and amplification of influential themes, including open source , Web 2.0 , big data , DevOps , Next Economy , and others. Analysis of the O’Reilly online learning platform shows growing engagement with cloud, orchestration, and microservices topics.

Artificial Inteligence 10

Artificial Inteligence Blockchain Artificial Intelligence Architecture 10

CircleCI

OCTOBER 20, 2022

First released by HashiCorp in 2015, Nomad was initially designed to be a general orchestrator. An organization developing with microservices needs each service to communicate with the others to enable an easy flow of work. Configurations and deployments are vital aspects of the DevOps pipeline. Networking. Conclusion.

Open Source 52

Open Source Azure Resources Load Balancer 52

Altexsoft

DECEMBER 14, 2022

delivering microservice-based and cloud-native applications; standardized continuous integration and delivery ( CI/CD ) processes for applications; isolation of multiple parallel applications on a host system; faster application development; software migration; and. Common Docker use cases. Typical areas of application of Docker are.

Weak Development Team 52

Weak Development Team Linux Operating System Virtualization 52

Cloudera

JUNE 16, 2022

In 2015, Cloudera became one of the first vendors to provide enterprise support for Apache Kafka, which marked the genesis of the Cloudera Stream Processing (CSP) offering. While for a DevOps/app team, the user is primarily interested in the entities associated with their applications.

Data 83

Data Disaster Recovery Analytics Microservices 83

LeanEssays

JULY 14, 2019

In chapter 3 (Agility and Leanness) he introduces DevOps, a set of technical practices based on cross-functional teams and heavy automation that effectively does away with the tradeoff between speed and control – you can have both. Small, independent teams own a small service – called a microservice these days.

Software Review 91

Software Review Software Engineering Continuous Delivery Technical Review 91

LeanEssays

JUNE 5, 2015

Lean Software Development: 2010 - 2015 2010 saw the publication of two significant books about lean software development. A grassroots movement called DevOps worked to make automated provision-code-build-test-deployment pipelines practical. Cloud computing arrived, providing easy and automated provisioning of environments.

Software Development 55

Software Development Software Review Software Development 55