RapidValue

JUNE 16, 2020

Having a DevOps mindset and incorporating an Agile approach for building and deploying apps faster is one of the key elements of Cloud Native application development. While working on Cloud Native application development, we need to make our application architectures more reactive leveraging Microservices.

Applications 90

Applications Cloud Development Microservices 90

Gorilla Logic

MAY 19, 2021

Not surprisingly, the skill sets companies need to drive significant enterprise software builds, such as big data and analytics, cybersecurity, and AI/ML, are among the most competitive. Ready to have a conversation about outsourcing your development to a top-ranked Agile development team? Let’s talk. Talk to us.

Software Review 94

Software Review Technical Review Software Development Team Review 94

Apiumhub

OCTOBER 18, 2022

We are proud to have had a lineup of speakers from different nationalities, including: Mark Richards is an experienced, hands-on software architect involved in the architecture, design, and implementation of microservices architectures, service-oriented architectures, and distributed systems. Eswaran Thandi has over 2.5

Software Review 52

Software Review Architecture Technical Review Software 52

Xicom

AUGUST 30, 2021

For the security element, the technologies like Big Data and Data Analytics are used to find a malicious activity, speed fraud investigations, prevent fraudulent transactions, and automate anti-fraud processes. Key Trend 6: More and More Microservices . Finastra ).

Fintech 52

Fintech Trends Development Blockchain 52

O'Reilly Media - Ideas

JANUARY 2, 2019

Artificial Intelligence for Big Data , February 26-27. Agile for Everybody , February 20. Data science and data tools. Apache Hadoop, Spark, and Big Data Foundations , January 15. SQL Fundamentals for Data , February 19-20. Apache Hadoop, Spark and Big Data Foundations , February 21.

Course 57

Course Artificial Inteligence Training Blockchain 57

Altexsoft

FEBRUARY 10, 2021

New approaches arise to speed up the transformation of raw data into useful insights. Similar to how DevOps once reshaped the software development landscape, another evolving methodology, DataOps, is currently changing Big Data analytics — and for the better. How DataOps relates to Agile, DevOps, and MLOps.

Analytics 75

Analytics DevOps Development Software Review 75

RapidValue

MARCH 17, 2019

It is driven, according to the report, by customer demand for agile, scalable and cost-efficient computing. Microservices are taking the market by storm as companies look to transition from a slow monolithic infrastructure to a much more agile microservice-based structure, allowing them to deploy applications more frequently and reliably.

Trends 45

Trends Cloud Serverless Microservices 45

Kaseya

NOVEMBER 9, 2023

Here are some of them: Function-as-a-Service (FaaS) or Serverless Computing: FaaS provides a platform that allows users to execute code in response to specific events without managing the complex infrastructure typically associated with building and launching microservices applications.

Cloud 105

Cloud Disaster Recovery Artificial Inteligence Infrastructure 105

RapidValue

AUGUST 18, 2019

The major shift to dynamic provisioning, shared resources and cloud computing have reaped huge benefits around IT speed, agility and cost. The ability to deploy applications in the cloud and the move to agile and DevOps methodologies has improved both scale and speed. This has helped to improve application development.

Games 50

Games Microservices DevOps Open Source 50

Linux Academy

JANUARY 26, 2019

Compute- and storage-intensive applications find their way to the cloud because of the need to scale so large that on-premises data centers are simply no longer feasible. Statistics show that as many as 60% of all newly developed applications are deployed in public, private, or hybrid cloud infrastructures.

Cloud 60

Cloud Artificial Inteligence Data Center Artificial Intelligence 60

O'Reilly Media - Ideas

MAY 1, 2019

Spotlight on Data: Caching Big Data for Machine Learning at Uber with Zhenxiao Luo , June 17. Core Agile , May 9. Spotlight on Data: Data as an Asset with Friederike Schüür and Jen van der Meer , May 20. Agile for Everybody , June 19. Core Agile , July 10. Data science and data tools.

Course 45

Course Training Artificial Inteligence Machine Learning 45

OTS Solutions

MAY 2, 2023

Digital transformation enables business models and revenue streams to enhance operational efficiency and agility and improves customer engagement and loyalty. It enables businesses to become more agile and responsive to market trends and customer needs. Embrace AIOps (AI operations) to support multi-cloud and microservices.

Artificial Inteligence 130

Artificial Inteligence Artificial Intelligence Machine Learning Blockchain 130

O'Reilly Media - Ideas

DECEMBER 5, 2018

Data science and data tools. Apache Hadoop, Spark, and Big Data Foundations , January 15. Python Data Handling - A Deeper Dive , January 22. Practical Data Science with Python , January 22-23. SOLID Principles of Object-Oriented and Agile Design , January 11. Reactive Spring Boot , January 7.

Artificial Inteligence 102

Artificial Inteligence Course Training Blockchain 102

Trigent

MARCH 24, 2021

Integrating AI into IT operations or AIOps has empowered IT teams to perform complex tasks with ease and resolve agility issues in complex settings. 74% of CIOs were reportedly using cloud-native technologies, including microservices, containers, and Kubernetes, and 61% said these environments changed every minute or less.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning Infrastructure 52

Apiumhub

MARCH 9, 2023

In 2023, as tech-driven businesses look to save costs and stay agile, we predict this trend will continue regardless of global inflation and market volatility. Codurance improves business agility and accelerates innovation while driving business growth – quickly, safely, and securely – with confidence.

Software Review 76

Software Review Technical Review Software Software Development 76

OTS Solutions

AUGUST 16, 2023

It can also help organizations better understand their data and make data-driven decisions. With the increasing adoption of cloud computing and big data analytics, AI and ML will continue to play a crucial role in application modernization in the future. ML and AI in mobile apps have become the norm.

Artificial Inteligence 130

Artificial Inteligence Applications Artificial Intelligence Machine Learning 130

OTS Solutions

AUGUST 16, 2023

It can also help organizations better understand their data and make data-driven decisions. With the increasing adoption of cloud computing and big data analytics, AI and ML will continue to play a crucial role in application modernization in the future. ML and AI in mobile apps have become the norm.

Artificial Inteligence 130

Artificial Inteligence Applications Artificial Intelligence Machine Learning 130

BPM

JANUARY 18, 2019

The microservice movement will reignite the need for orchestration. Some analyst is bound to rename BPM engines to Microservice Orchestration Engines (MOE).wait Continuing the journey toward true business agility initiated in the software realm. DMN will progressively replace traditional Business Rule Management Systems (BRMS).

Artificial Inteligence 111

Artificial Inteligence Artificial Intelligence Machine Learning Weak Development Team 111

Trigent

MARCH 24, 2021

Integrating AI into IT operations or AIOps has empowered IT teams to perform complex tasks with ease and resolve agility issues in complex settings. 74% of CIOs were reportedly using cloud-native technologies, including microservices, containers, and Kubernetes, and 61% said these environments changed every minute or less.

Artificial Inteligence 52

Artificial Inteligence Artificial Intelligence Machine Learning Technical Review 52

OpenCredo

MAY 14, 2020

A significant factor in this journey has been the ability to automate infrastructure delivery – and as complexity has grown with the adoption of microservices, big data and IOT, this automation has evolved to become more sophisticated. We give up agility and the ability to out-deliver our competitors.

System 52

System Weak Development Team Microservices Off-The-Shelf 52

Apiumhub

MARCH 26, 2019

He was involved in the early Agile movement and one of his passions is helping organizations recognize the impact of their internal organization and communication on the long term viability of their software products – putting interactions in place to prevent the accumulation of technical debt and lost business opportunities.

Software Review 44

Software Review Architecture Technical Review Systems Review 44

Hu's Place - HitachiVantara

JANUARY 3, 2019

Public cloud, agile methodologies and devops, RESTful APIs, containers, analytics and machine learning are being adopted. Workloads are becoming increasingly distributed, with applications running in public and private clouds as well as in traditional enterprise data centers.

Trends 86

Trends Artificial Inteligence Data Center Machine Learning 86

Trigent

APRIL 14, 2022

Enterprise software also has disaggregated from a monolithic form split into microservices (via containers) where code, debugger, utilities, and algorithms may be contained within the container and control routed appropriately to the parent code block as required. And that can be a cause for worry.

Enterprise 52

Enterprise Technology Artificial Inteligence IoT 52

RapidValue

JUNE 30, 2019

In general, we are moving away from a slow, and sluggish world of traditional applications to one which is smarter, faster and more agile. The container orchestrator provides a dynamic, high-density virtualization on top of your VM matching microservices. The results shine through in customer experience and speed of innovation.

Load Balancer 75

Load Balancer Applications Cloud Development 75

O'Reilly Media - Ideas

APRIL 3, 2019

Spotlight on Data: Creating Smart Products Requires Collaboration, with Gretchen Anderson , April 15. Agile for Everybody , April 18. Data science and data tools. Apache Hadoop, Spark, and Big Data Foundations , April 22. Data Structures in Java , May 1. Cleaning Data at Scale , May 13.

Course 47

Course Artificial Inteligence Training Google Cloud 47

UruIT

DECEMBER 31, 2018

Course titles include Fundamentals of Software Architecture; Developing Microservices; The Architect Elevator; Building Evolutionary Architecture; and Domain-Driven Design and Event-Driven Microservices. These immersive courses run for two full days, 9:00 a.m. to 5:00 p.m., Have an idea for a presentation or workshop?

Conference 89

Conference CTO Coach Fractional CTO Serverless 89

Palo Alto Networks

APRIL 23, 2020

The ability to automate repeatable tasks and common incidents while minimizing the investigation time from compromise to detection to incident resolution helps to mitigate risk and provides invaluable speed and agility, strengthening the security posture in a SOC. Economic Consideration.

Artificial Inteligence 54

Artificial Inteligence Artificial Intelligence Technical Review Machine Learning 54

Openxcell

DECEMBER 27, 2021

From the development of business applications to backend development, Python has widened its reign even to AI development, automation, scientific computing, and big data. Highly flexible for microservice development. For microservice architecture, multiple module execution and development are required. Python 3.10

Technical Review 52

Technical Review Technology Software Review Open Source 52

Hu's Place - HitachiVantara

FEBRUARY 15, 2019

Hybrid and Multi-cloud Benefits Hybrid and multi-cloud strategies offer flexibility, scalability, and agility by providing the freedom to choose where and how to deploy workloads, without the complexity and delays of acquiring and deploying infrastructure and operations resources.

Cloud 49

Cloud AWS Azure Data Center 49

The Agile Monkey

OCTOBER 4, 2016

It’s interesting that, in spite of the current trend of serverless and microservices architectures and the introduction of modern and faster languages like Go and Swift, more than a half of the e-commerce installed base is built over the classic LAMP stack, featuring monolithic architectures. Do you want to join us in this quest?

Microservices 40

Microservices Weak Development Team Architecture System 40

Altexsoft

JULY 4, 2022

In a small company, infrastructure engineers will likely be masters of all trades while in enterprises, this position may focus on a specific problem like cloud migration, continuous app deployments, or designing big data structures. Agile and DevOps methodologies. Most common duties of an infrastructure engineer.

Infrastructure 64

Infrastructure Engineering Technical Review Google Cloud 64

LeanEssays

JUNE 5, 2015

Agile and Lean Software Development: 2000 - 2010 It’s hard to believe these days, but in the mid 1990’s, developing software was a slow and painful process found in the IT departments of large corporations. In 2001 the Agile Manifesto (Beck et al., 2001) gave this new approach a name – “Agile.”

Software Development 55

Software Development Software Review Software Development 55

Apiumhub

OCTOBER 2, 2019

Advanced Agile Testing. Architecture, Agility and DevOps in Amazon AWS, Microsoft Azure and Google Cloud. Agile methodologies. Microservices with AWS Lambdas. Building Reliable Microservices with Microsoft Service Fabric. You can benefit from their expertise in any of the courses they offer: Introduction to Scala.

Software Review 9

Software Review Software Development Technical Review Course 9

Exadel

DECEMBER 4, 2019

We found that our commitment to agile development, open source and innovation-based technologies helped organizations create and maintain amazing products and platforms the most effectively. Agile excellence is at the core of all we do and receiving this recognition amplified and validated this principle.

Software Review 10

Software Review Blockchain Open Source Technical Review 10

Apiumhub

AUGUST 12, 2021

This year you will have 6 unique tracks: Cloud Computing: IaaS, PaaS, SaaS DevOps: Microservices, Automation, ASRs Cybersecurity: Threats, Defenses, Tests Data Science: ML, AI, Big Data, Business Analytics Programming languages: C++, Python, Java, Javascript,Net Future & Inspire: Mobility, 5G data networks, Diversity, Blockchain, VR.

Industry 59

Industry Technical Advisors CTO Coach Azure 59

d2iq

FEBRUARY 19, 2021

We shall see that end-to-end machine learning platforms for the big data era have only emerged over the last five years at various tech companies such as Facebook, Twitter, Google, Uber, and Netflix. Unit and integration tests are pretty standard for data pipelines and microservices.

Artificial Inteligence 103

Artificial Inteligence Machine Learning Technical Review Software Review 103

Apiumhub

DECEMBER 20, 2018

Alejandro Lujan is having fun with Big Data at Shopify and leads ScalaQuest, the game to learn Scala. Microservices vs Monolithic architecture. This blog serves as a hub for everything related to this series. Scala Days. Scala generics II: covariance and contravariance . Scala Generics III: generalized type constraints.

Programming 42

Programming Conference Software Development Scalability 42