Table of Contents Python is one of the most popular programming languages used in data engineering, particularly in the ETL (Extract, Transform, Load) process. Its flexibility, extensive libraries, and ease of use make it a great choice for building and optimizing ETL pipelines.

Table of Contents SQL (Structured Query Language) is one of the most commonly used tools for transforming data within ETL (Extract, Transform, Load) processes. SQL transformations are essential for converting raw, extracted data in CSV, JSON, XML or any format into a clean, structured, and meaningful format before loading it into a target database or cloud data warehouse like BigQuery or Snowflake.

Transactions-per-Second (TPS) is a valuable metric for evaluating system performance and is particularly relevant for engineers overseeing Kubernetes environments.TPS, alongside average response time, provides critical insights into system performance during load testing. This post covers two approaches to calculating TPS; a manual approach applicable in all environments, and an automatic Kubernetes-specific solution using production traffic replication.

At some point, your development team may be considering implementing load testing (also known as stress testing) as part of your software testing process. Load testing validates that your web app is able to withstand a large number of simultaneous users, decreasing the chance that any traffic spikes will bring down your services once deployed. These stress tests can be highly granular, giving you the opportunity to test run virtually unlimited strategies before they are set into the wild.

As developers, one of the most important things we can consider when designing and building applications is the ability to know if our application is running in an ideal operating condition, or said another way: the ability to know whether or not your application is healthy. This is particularly important when deploying your application to Kubernetes. Kubernetes has the concept of container probes that, when used, can help ensure the health and availability of your application.

As businesses continue to digitize, the importance of load testing has surged, with the market witnessing a significant rise in the adoption of load testing tools. According to a recent report, the global load testing market is expected to grow at a CAGR of 12.5% from 2021 to 2026, reflecting the increasing demand for reliable and scalable applications.

The comprehensive guide to Selenium, the industry-standard open source testing framework.

The software testing in earlier times was a purely manual method, which was quite labor-intensive and included a high chance of errors. Over the years, the complexity of systems led to the need for a better and more effective method for testing these software systems. This is where automation testing transforms the face of software testing. First, automation was used for unit tests or simple checks of the components of a system that are not connected with other components.

At first glance, ClearML’s AI Development Center and alternatives such as Weights & Biases seem to offer similar capabilities for MLOps. For example, both solutions support experiment management, data management, and orchestration. However, each product is designed to solve a different use case. It is important to understand how these approaches affect the user experience.

Unsurprisingly, consumers base their purchase decisions on customer experience. Despite 73% of consumers placing a high value on customer experience, only 49% believe companies meet their expectations. Testlio October 4th, 2024 Businesses that integrate customer experience into the software development life cycle have shown better customer retention and satisfaction rates. There is a direct correlation between product quality and customer satisfaction.