CIO

DECEMBER 13, 2024

Banking on hybrid cloud Discovers decision to take a container-based approach as early as 2018 reflects the hybrid approach many consumer financial services have adopted to have maximum control over their workloads. But introducing a container-based approach to cloud computing can introduce complexities and challenges, analysts note.

Cloud 147

Cloud Generative AI AWS Artificial Inteligence 147

Palo Alto Networks

NOVEMBER 12, 2019

With Google Cloud’s native security toolkit and deep integrations with Palo Alto Networks cloud security products such as the VM-Series , Prisma Cloud , and Prisma SaaS , you can define a consistent security posture in Google Cloud and on-premises. Let’s look into some of these integrations. .

Google Cloud 8

Google Cloud Cloud Firewall Load Balancer 8

Palo Alto Networks

JUNE 4, 2019

In this post, guest bloggers Vineet Bhan, Sheba Roy and Ashish Verma of Google Cloud share a closer look at product integrations between Google Cloud and Palo Alto Networks. Security for hybrid containerized workloads: Anthos (formerly Cloud Services Platform) lets you build and manage modern hybrid applications.

Google Cloud 40

Google Cloud Network Cloud Load Balancer 40

O'Reilly Media - Ideas

JUNE 5, 2019

Get hands-on training in Docker, microservices, cloud native, Python, machine learning, and many other topics. AI-driven Future State Cloud Operations , June 7. Fundamentals of Machine Learning and Data Analytics , July 10-11. Real-Time Streaming Analytics and Algorithms for AI Applications , July 17.

Course 67

Course Training Artificial Inteligence Software Review 67

Perficient

JUNE 27, 2024

As of this writing, and as a Premier Partner with Google, Perficient currently holds two specializations: Data and Analytics , and Infrastructure. Anthos Service Mesh increased deployment velocity, enabling service monitoring and orchestration of GKE microservices.

Google Cloud 52

Google Cloud Applications Cloud Automotive 52

O'Reilly Media - Ideas

MARCH 6, 2019

Business Data Analytics Using Python , April 29. Developing Applications on Google Cloud Platform , April 29-30. Introduction to Google Cloud Platform , April 3-4. Cloud Computing on the Edge , April 9. Microservice Fundamentals , April 15. Microservice Collaboration , April 16.

Course 15

Course Artificial Inteligence Training Machine Learning 15

CIO

JANUARY 26, 2023

Cost containment is a big issue for many CIOs now and the cloud companies know it. See Azure Cost Management , Google Cloud Cost Management , and AWS Cloud Financial Management tools for the big three clouds. Once your cloud commitment gets bigger, independent cost management tools start to become attractive.

Tools 174

Tools Cloud Artificial Inteligence Artificial Intelligence 174

Confluent

MAY 22, 2019

What role will analytics play in future? Most IoT-based applications (both B2C and B2B) are typically built in the cloud as microservices and have similar characteristics. Enterprises typically accumulate large amounts of data over time from different sources and data types, such as IoT devices and microservices applications.

IoT 98

IoT Google Cloud Scalability Microservices 98

CIO

JULY 13, 2022

Universal Data Movement Use Cases with Streaming as First-Class Citizen : The service needs to address the entire diversity of data movement use cases: continuous/streaming, batch, event-driven, edge, and microservices.

System 133

System Enterprise Data Cloud 133

O'Reilly Media - Ideas

FEBRUARY 6, 2019

Get hands-on training in machine learning, microservices, blockchain, Python, Java, and many other topics. Business Data Analytics Using Python , February 27. Microservice Collaboration , March 7. OpenStack for Cloud Architects , March 7-8. Google Cloud Certified Associate Cloud Engineer Crash Course , March 11-12.

Artificial Inteligence 17

Artificial Inteligence Course Training Artificial Intelligence 17

Kentik

MAY 14, 2019

Powerful analytics: The tool must unlock powerful analytics and enable in-depth visibility. The tool must also be able to help manage the top challenges we face with modern cloud infrastructures, including performance, cost, and security. Kentik for Multi-Cloud: AWS + Azure + GCP.

Cloud 103

Cloud Azure How To AWS 103

Linux Academy

MAY 28, 2019

To use Docker Compose to deploy Microservices to Docker. Google Cloud Essentials – This course is designed for those who want to learn about Google Cloud: what cloud computing is, the overall advantages Google Cloud offers, and detailed explanations of all major services – what they are, their use cases, and how to use them.

Linux 104

Linux AWS Azure Technical Review 104

Confluent

FEBRUARY 6, 2019

It takes much more effort than just building an analytic model with Python and your favorite machine learning framework. No matter what other platforms are supported, chances are very high that your data scientists will build and train their analytic models with Python. You need to think about the whole model lifecycle.

Machine Learning 107

Machine Learning Artificial Inteligence Scalability Data Engineering 107

OTS Solutions

SEPTEMBER 5, 2023

Microservices Microservices have emerged as a powerful approach in the field of DevOps, especially in the cloud environment. By breaking down complex applications into smaller, independent components, microservices allow for better scalability, flexibility, and fault tolerance.

DevOps 130

DevOps Cloud Software Review Weak Development Team 130

OTS Solutions

JUNE 9, 2023

These applications are used to manage and streamline various business processes and operations, including customer relationship management, enterprise resource planning, enterprise resources planning, supply chain management, human resource management, and business intelligence and analytics.

Enterprise 130

Enterprise Applications Development Scalability 130

OTS Solutions

JUNE 9, 2023

These applications are used to manage and streamline various business processes and operations, including customer relationship management, enterprise resource planning, enterprise resources planning, supply chain management, human resource management, and business intelligence and analytics.

Enterprise 130

Enterprise Applications Development Scalability 130

Mobilunity

APRIL 7, 2025

With the increasing adoption of next-gen technologies 94% of enterprises adopting cloud services, 97% using or planning to embrace microservices, and 97% relying on APIs for digital transformation businesses demand resilient and flexible backend solutions to stay competitive.

UI/UX 40

UI/UX Technical Review Development Software Review 40

Linux Academy

APRIL 30, 2019

Introduction to Migrating Databases and Virtual Machines to Google Cloud Platform — This course covers the various issues of migrating databases and virtual machines to Google Cloud Platform. AWS Essentials – AWS Essentials is a course for those who are completely new to AWS. No prior AWS experience is required.

Linux 113

Linux AWS Big Data Course 113

Confluent

OCTOBER 10, 2019

Microservices, Apache Kafka, and Domain-Driven Design (DDD) covers this in more detail. In some scenarios, the main challenge and requirement is to ingest data into Kafka for further processing and analytics in other backend systems. MQTT Proxy for data ingestion without an MQTT broker.

IoT 20

IoT Internet Weak Development Team Scalability 20

Altexsoft

FEBRUARY 24, 2023

Containers have become the preferred way to run microservices — independent, portable software components, each responsible for a specific business task (say, adding new items to a shopping cart). Modern apps include dozens to hundreds of individual modules running across multiple machines— for example, eBay uses nearly 1,000 microservices.

Weak Development Team 83

Weak Development Team Load Balancer Technical Review Microservices 83

Cloudera

JUNE 2, 2022

Universal Data Movement Use Cases with Streaming as First-Class Citizen : The service needs to address the entire diversity of data movement use cases: continuous/streaming, batch, event-driven, edge, and microservices.

System 104

System Enterprise Data Cloud 104

Confluent

JULY 10, 2019

If you recall from part 1, we added Kafka Streams to our architecture for some final repackaging of our messages before sending them off to the different APIs in Oracle Warehouse Management Cloud (Oracle WMS Cloud): Figure 1. The packaging of payloads for Oracle WMS Cloud. Gradle analytics with Apache Kafka.

Lambda 89

Lambda Analytics Testing Groups 89

Altexsoft

AUGUST 30, 2018

The most popular are Chef, Puppet, Azure Resource Manager, and Google Cloud Deployment Manager. Microservices. The microservice architectural approach entails building one application as a set of independent services that communicate with each other, but are configured individually. Cloud infrastructure.

DevOps 90

DevOps Engineering Continuous Delivery Systems Administration 90

O'Reilly Media - Ideas

APRIL 3, 2019

Introduction to Google Cloud Platform , June 3-4. Fraud Analytics Using Python , April 30. Introduction to Google Cloud Platform , June 3-4. Google Cloud Certified Associate Cloud Engineer Crash Course , May 15-16. Getting Started with Cloud Computing , May 16. Getting Unstuck , June 3.

Course 65

Course Artificial Inteligence Training Google Cloud 65

Altexsoft

APRIL 22, 2021

When you’re employing a lot of APIs to digitize, adopt a microservices architecture, or build your business strategy around APIs, you need to control not just one aspect of your APIs, but their full life cycle, including such tasks as: Defining API schemas and publishing them. Reviewing usage analytics and improving APIs.

Microservices 64

Microservices Weak Development Team Analytics Software Review 64

Perficient

DECEMBER 7, 2023

These range from cloud-based solutions like AWS, Google Cloud, and Azure to specific BI tools like Tableau, Power BI, Pyramid Analytics, and Looker. This means setting up systems for real-time data analysis, predictive analytics, and automated reporting.

How To 52

How To Analytics Scalability Google Cloud 52

Altexsoft

OCTOBER 27, 2020

In a microservice architecture , dozens of containers will be interconnected making up the app. As we mentioned before, usually DevOps projects deal with cloud infrastructure. The most prominent cloud infrastructure providers are: Amazon Web Services. Google Cloud Platform. Oracle Cloud Platform. Prometheus.

DevOps 116

DevOps Tools Continuous Delivery Open Source 116

Mobilunity

DECEMBER 5, 2024

Managing the expenses of cloud providers such as AWS, Azure, and Google Cloud has become a major difficulty for modern businesses. This article presents the goal of cloud cost optimization, best practices, such as adjusting resource sizes and utilizing automation and predictive analytics, and effective tools.

Cloud 52

Cloud Strategy Technical Review Database Administration 52

O'Reilly Media - Ideas

MAY 1, 2019

Real-Time Streaming Analytics and Algorithms for AI Applications , May 15. Fraud Analytics using Python , June 25. Deploying Container-Based Microservices on AWS , June 10-11. Cloud Computing on the Edge , June 11. Microservices Caching Strategies , June 17. Microservice Fundamentals , July 10.

Course 60

Course Training Artificial Inteligence Machine Learning 60

Lacework

SEPTEMBER 28, 2022

Here are the primary ones to consider: Microservices : These offer increased flexibility at runtime and better resource utilization efficiency, but the need to manage every microservice in a cloud app can quickly up your complexity level. These workloads, and the cloud environments they’re in, change rapidly.

Cloud 52

Cloud Microservices Firewall Compliance 52

Mobilunity

MARCH 25, 2025

Consequently, Python can be as efficient as Java in terms of AI and data analytics projects. Microservices Architecture : Java frameworks like Spring Boot and Eclipse MicroProfile simplify the creation and deployment of microservices, enabling flexible and scalable applications.

Software Review 40

Software Review Software Development Software Development 40

Altexsoft

JUNE 29, 2021

It is common in designing apps that rely on microservices (when every service runs its own process.). While there may be a greater number of microservices involved in the process, we’ll cover the three key ones. Moreover, creating a functional event-driven architecture requires complementary services, say, cloud data storages.

Architecture 75

Architecture Microservices IoT Scalability 75

Kentik

NOVEMBER 7, 2018

Dynamically orchestrated” and “microservices-oriented” are key aspects of “cloud-native” architecture that make this especially challenging. Are there hidden fees behind your cloud bill? Google Cloud interconnects, ? from workloads to Google services. Kentik’s Cloud Visibility Solution. over VPNs, ?

Cloud 53

Cloud Azure AWS Google Cloud 53

Altexsoft

JULY 4, 2022

Ansible , Puppet , and Chef working with both physical and cloud environments; Terraform — a platform-agnostic solution for cloud infrastructures; and. AWS CloudFormation , Azure Resource Manager , or Google Cloud Deployment Manager , which are cloud-specific IaC services. Google Cloud Fundamentals.

Infrastructure 64

Infrastructure Engineering Technical Review Google Cloud 64

Confluent

MAY 29, 2019

In part 3, we’ll explore using Gradle to build and deploy KSQL user-defined functions (UDFs) and Kafka Streams microservices. Red Pill Analytics has made the gradle-confluent plugin available under the Apache 2.0 Introduction. License on GitHub , as well as in the Gradle plugin portal. m2 directory. id 'maven-publish'.

Groups 96

Groups Windows Testing Microservices 96

Altexsoft

DECEMBER 28, 2018

If you are interested in the application structure and how it performs on Azure, you may check the volume report containing detailed information on analytics and expenses. Google Cloud Functions (GCF). One of the four largest, Google released its solution only in 2017. Google-driven mobile development.

Serverless 68

Serverless Azure AWS Architecture 68

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