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Aiven workshop: Learn Apache Kafka with Python

What's in the Workshop Recipe? Apache Kafka is the industry de-facto standard for data streaming. An open-source, scalable, highly available and reliable solution to move data across companies' departments, technologies or micro-services. In this workshop you'll learn the basics components of Apache Kafka and how to get started with data streaming using Python. We'll dive deep, with the help of some prebuilt Jupyter notebooks, on how to produce, consume and have concurrent applications reading from the same source, empowering multiple use-cases with the same streaming data.

Comprehensive Metrics in the SaaS Industry: 7 Reasons Why They Matter

Understanding comprehensive metrics in SaaS is crucial for your success in the industry. These numbers are more than just data; they offer insights into customer behavior, product performance, and operational efficiency. By embracing the importance of these metrics, you can drive better decision-making, ensure customer satisfaction, and promote sustainable growth. Let's dive into why these metrics are indispensable to your business strategy.

Powering Real-Time Data Processing with InfluxDB and AWS Kinesis

Imagine a data engineer working for a large e-commerce company tasked with building a system that can process and analyze customer clickstream data in real-time. By leveraging Amazon Kinesis and InfluxDB, they can achieve this goal efficiently and effectively. So, how do we get from idea to finished solution? First, we need to understand the tools at hand.

New MTTX analytics to drive your reliability roadmap

Analytics are great. We can all agree there. But not all analytics are created equal. FireHydrant has long offered incident analytics dashboards that provide an in-depth look at the entire incident lifecycle. You can see how incidents impact services and teams, understand retrospective participation and completion, and even get insight into follow-ups. But great analytics do more than simply organize data. They help you tell a story.

Data Lakes: A Comprehensive Guide

Whether you’re a Data Engineer, DevOps, Cloud Architect, or a Business Intelligence Professional, Data Lakes are indispensable tools for harnessing the power of big data, enabling advanced analytics, and driving informed decision-making across your enterprise. Back in the 90s, the internet boom led to an unprecedented expanse of data. This led to a gaping demand for better data storage solutions.

Start as an AWS reseller a simple guide for MSPs

As cloud adoption accelerates, managed service providers (MSPs) have a major opportunity to capitalize on this trend by reselling Amazon Web Services (AWS). Becoming an AWS reseller allows MSPs to expand their service offerings, achieve recurring revenue, and solidify their status as cloud experts. This comprehensive guide will walk through everything MSPs need to know to successfully start reselling AWS services.

A simple guide to becoming an Azure Reseller for MSPs

As Microsoft Azure continues its rapid growth, becoming an Azure reseller presents a major opportunity for managed service providers (MSPs) to expand their offerings and drive recurring revenue. This comprehensive guide will walk through everything MSPs need to know to successfully start reselling Azure services.

Data Storage: What Is It and Why Is It Important?

In the fast-paced and ever-changing landscape of today's digital world, the concept of data storage assumes a pivotal role in shaping how information is managed, accessed, and utilized. Data storage forms the backbone of our interconnected society, from the extensive repositories of global corporations to the personal devices we interact with daily. It is imperative to comprehend the intricacies of data storage and acknowledge its significance to navigate the complexities of our data-driven age effectively.

Augmenting Your DBA Toolkit: Harnessing the Power of Time Series Databases

Database Administrators (DBAs) rely on time series data every day, even if they don’t think of time series data as a unique data type. They rely on metrics such as CPU usage, memory utilization, and query response times to monitor and optimize databases. These metrics inherently have a time component, making them time series data. However, traditional databases aren’t specifically designed to handle the unique characteristics and workloads associated with time series data.

Unlocking the Power of IIoT with Time Series Databases

This article was originally published on IIoT World and is reprinted here with permission. In the rapidly evolving world of Industrial Internet of Things (IIoT), organizations face numerous challenges when it comes to managing and analyzing the vast amounts of data generated by their industrial processes. Data generated by instrumented industrial equipment is consistent, predictable, and inherently time-stamped.