The java.lang.IndexOutOfBoundsException in Java is thrown when an index used in arrays, lists, or strings is not valid. A valid index must be a number from 0 up to one less than the total number of items. For example, in a list of 3 items, the valid indices are 0, 1, and 2. Here’s a quick example: The error message you’d get would look something like this: Here are some other common ways the IndexOutOfBoundsException might be thrown.

Application programming interfaces (APIs) have quickly become vital to modern businesses. APIs work by allowing different systems to talk to each other and share data. The commercial use of APIs and web APIs has skyrocketed over the last decades in accordance with the rise in app development, mobile apps, and e-commerce. However, how do you estimate API development time? Well, API creation and the development time frame will always vary from project to project.

The Ably service handles massive amounts of data throughput and concurrent connections for many customers while maintaining a highly reliable and available service, with a 5x9s uptime guarantee. Ably has no scale ceiling, and that’s challenging work (it’s one of the reasons I joined Ably). While the challenges we face in delivering our service are compelling, we sometimes face novel internet scale problems, such as breaching the limits of AWS services!

Embedding analytics into your application? New browser restrictions are on the way for Google Chrome that can block some third-party content that uses cookies from being accessible to users by default, in addition to restrictions in Safari and Firefox you may have already seen.

Data integrity refers to protecting data from anything that can harm or corrupt it, whereas data quality checks if the data is helpful for its intended purpose. Data quality is a subset of data integrity. One can have accurate, consistent, and error-free data, but it is only helpful once we have the supporting information for this data. Data integrity and quality are sometimes used interchangeably in data management, but they have different implications and distinct roles in enhancing data usability.

By combining speech-to-text with BigQuery's analytics capabilities, you can understand things like customer sentiment and recurring product issues.

Did you know data scientists spend around 60% of their time preprocessing data? Data preprocessing plays a critical role in enhancing the reliability and accuracy of analytics. This blog will discuss why data preprocessing is essential for making data suitable for comprehensive analysis.

As Augmented Reality (AR) becomes more prevalent, imagine entering a world where digital overlays seamlessly blend with your physical surroundings, enriching your reality with interactive information and immersive experiences. This is the promise of AR, a groundbreaking technology reshaping how we interact with the digital world.

Today, we’re excited to share that Serverless GPUs are available for all your AI inference needs directly through the Koyeb platform! We're starting with GPU Instances designed to support AI inference workloads including both heavy generative AI models and lighter computer vision models. These GPUs provide up to 48GB of vRAM, 733 TFLOPS and 900GB/s of memory bandwidth to support large models including LLMs and text-to-image models.

The ever-growing threat landscape of hackers, cyberattacks, and data breaches makes data security a top priority, especially when integrating analytics capabilities directly into customer-facing applications. To make informed decisions, it’s crucial to understand how embedded analytics platforms function from a security standpoint.