Systems | Development | Analytics | API | Testing

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A Complete Guide to Exploratory Testing

Traditional testing approaches can struggle to keep up with the dynamic nature of modern development cycles. While effective in certain contexts, these methods may miss some defects, which can lead to costly fixes, customer dissatisfaction, and damage to the product's reputation. The problem lies in the limitations of scripted testing, which might lack the flexibility required to identify novel defects.

Mocking Your APIs in Minutes with Choreo

Do you have an open API specification that needs to be transformed into a functional mock server? With Choreo’s latest release, you can now use Prism Mock service components to mock your open API specifications. This is powered by Prism, an open source technology, allowing you to tap into Choreo’s robust functionalities, including API management, observability, DevOps, and more.

The true cost of consumption-based pricing: Why MAU models fall short and how to optimize for customers

Consumption-based pricing has become a popular model for SaaS and PaaS businesses, allowing customers to pay only for what they use. Pioneers like Slack and AWS have successfully adopted this approach, offering flexibility and reducing waste. However, not all consumption-based models are created equal. The Monthly Active Users (MAU) model, while appealing in its simplicity, often leads to inefficiencies and unexpected costs.

Efficient Snowflake ETL: A Complete Guide for Data Analysts

In today’s data-driven world, a powerful ETL (Extract, Transform, Load) process is essential for effective data management. For data analysts, Snowflake has emerged as a popular cloud data platform, offering powerful data storage, processing, and analytics capabilities. Integrating ETL processes with Snowflake allows analysts to streamline workflows and focus on delivering valuable insights rather than wrestling with data logistics.

Unlocking the Power of Snowflake Data with Data Integration Platform

In the world of data analysis, handling vast quantities of information across diverse data sources efficiently and securely is crucial. Snowflake, a cloud-based data platform, has revolutionized how analysts manage and derive insights from data. Paired with Integrate.io's ETL (Extract, Transform, Load) capabilities, the process of working with Snowflake data becomes streamlined, enabling data analysts to focus on generating valuable insights instead of dealing with the complexities of data movement.

MuleSoft vs ETL: Understanding the Key Differences

In the digital era, data integration is not just a luxury—it’s a necessity for efficient business operations and informed decision-making. With data stored across different platforms, applications, and cloud environments, businesses need tools that can help them unify these disparate data sources. MuleSoft and ETL are two commonly discussed solutions in the data integration space, but they serve very different purposes.

Accelerate Development Cycles, Reduce Bottlenecks, and Decrease Time to Market

Hosted By: What is the impact of development velocity? One of the leading financial services companies reduced test execution time from 6 days to 36 hours, equating to 4x time savings. The pressure to innovate quickly and keep up with competitors is real. Watch Marc Hornbeek, CEO of Engineering DevOps Consulting and author of Engineering DevOps, and Marcus Merrell, Principal Technical Advisor at Sauce Labs, for a discussion on innovation velocity and to learn how DevOps teams are iterating quickly so they can focus on delivering innovative software.