LaunchDarkly

JANUARY 17, 2019

Edith joins the show to discuss how to implement feature flagging, why an intelligent release process can lead to a more scientific predictable environment for software development and many other topics. Whereas if AWS comes out with AWS Feature Flagging, it’s not existential and it might take a little more work to convince the customers.

Software Engineering 40

Software Engineering Engineering Software Technical Cofounder 40

Hu's Place - HitachiVantara

FEBRUARY 15, 2019

Another aspect of agility is the self-service resources that enables the DevOps culture to run dev/test workloads in the cloud. Operational policies and methods are different and aggregation of data across multiple clouds boundaries makes it difficult for governance, analytics, and business intelligence.

Cloud 49

Cloud AWS Azure Data Center 49

Protera

MAY 23, 2023

There are several quality cloud providers on the market, but you want to choose the one that best aligns with your unique business requirements and objectives. Other areas of focus to this end could include security, performance efficiency, scalability, and of course cost.

Cloud 52

Cloud Testing Data Center Systems Review 52

Altexsoft

FEBRUARY 24, 2023

Deployment and scaling automation to boost CI/CD Kubernetes has become an important part of a DevOps toolchain. It enables DevOps and site reliability engineer (SRE) teams to automate deployments, updates, and rollbacks. But even a seasoned software developer or DevOps engineer can find Kubernetes intimidating in the beginning.

Weak Development Team 83

Weak Development Team Load Balancer Technical Review Microservices 83

Altexsoft

JANUARY 14, 2021

Thanks to the capability of data warehouses to get all data in one place, they serve as a valuable business intelligence (BI) tool, helping companies gain business insights and map out future strategies. Source: AWS. It is usually created and used primarily for data reporting and analysis purposes. Performance.

Backup 115

Backup Azure Software Review Systems Review 115

Altexsoft

JULY 19, 2022

This basic principle corresponds to that of agile software development or approaches such as DevOps, Domain-Driven Design, and Microservices: DevOps (development and operations) is a practice that aims at merging development, quality assurance, and operations (deployment and integration) into a single, continuous set of processes.

Architecture 52

Architecture Data Analytics Data Engineering 52

Existek

JANUARY 27, 2023

Analytics and business intelligence (BI) systems are commonly used in the financial services industry to analyze large amounts of data and generate insights for informed business decisions. DevOps is another trend becoming increasingly popular in financial services software development.

Software Development 52

Software Development Trends Technology Software 52

Altexsoft

JANUARY 26, 2022

Such an approach is called DataOps — a new methodology that ties together data engineering, data analytics, and DevOps. The list may include data warehouses like Snowflake, Amazon Redshift, and Google BigQuery; ETL tools like AWS Glue, Talend, or others; Business Intelligence tools like Tableau , Looker, or equivalent.

Analytics 59

Analytics Engineering Data Engineering Software Engineering 59

O'Reilly Media - Ideas

SEPTEMBER 11, 2019

In the domain of stream processing, there’s Kafka, Flink, and a spate of cloud stream-processing services (AWS Kinesis, Azure Stream Analytics). a straightforward option for processing data workloads: they submit code to and have it execute in any of several cloud FaaS engines (AWS Lambda, Azure Functions, etc.)

Conference 8

Conference Data Data Engineering Artificial Inteligence 8

Cloudera

JUNE 16, 2022

While for a DevOps/app team, the user is primarily interested in the entities associated with their applications. The DevOps/app dev team wants to know how data flows between such entities and understand the key performance metrics (KPMs) of these entities. Getting started today.

Data 90

Data Disaster Recovery Analytics Microservices 90

Altexsoft

MARCH 30, 2023

Here are four main applications of the platform across industries: data warehousing — SQL queries and business intelligence (BI) at scale; data engineering — building and maintaining data pipelines , running ETL and ELT workloads; data streaming and real-time analytics , and data science and machine learning projects.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

Datavail

SEPTEMBER 8, 2022

According to an IDG survey , companies now use an average of more than 400 different data sources for their business intelligence and analytics processes. Datavail suggested that the client focus on Fivetran while also adopting a new tool, AWS Glue, which was better suited for its needs. DevOps consulting and managed services.

Data 40

Data Nonprofit Quality Assurance Education 40