Systems | Development | Analytics | API | Testing

In February 2024, Kong became the first API platform to launch a dedicated AI gateway, designed to bring production-grade performance, observability, and policy enforcement to GenAI workloads. At its core, Kong’s AI Gateway provides a universal API to enable platform teams to centrally secure and govern traffic to LLMs, AI agents, and MCP servers. Additionally, as AI adoption in your organization begins to skyrocket, so do AI usage costs.

The digital landscape is changing. More and more, consumers are realising the importance of data privacy. This shift in mindset is something businesses must attune to if they hope to build strong relationships with their customers. The phasing out of third-party cookies by Google at the end of 2024 and global regulations like GDPR and CCPA tightening data collection mean companies that embed privacy as a core part of their operations have the most to gain.

Choosing one over the other can come down to a few key differences. Let’s take a look at both to help you make an informed decision.

Data completeness in ETL pipelines refers to whether all expected data has been successfully processed without missing values or records. The Data Completeness Index (DCI) is a metric that quantifies the percentage of complete data fields in your ETL processes, helping organizations identify gaps that could lead to faulty analytics or business decisions. When your data completeness testing in ETL processes reveals a high DCI score, it indicates reliable data that stakeholders can confidently use.

In data pipelines, timing is everything. When data doesn't arrive when expected, it can create ripples throughout your entire analytics ecosystem. Late-arriving data refers to information that reaches your data warehouse after the expected processing window has closed. The Late-Arrival Percentage for ETL pipelines measures the proportion of data that arrives behind schedule, directly impacting the reliability and usefulness of your business intelligence systems.

Last quarter, something remarkable happened that reminded me why I love working in software testing. I was consulting with a major retail client preparing for their Memorial Day sale, traditionally their second-biggest revenue event of the year. We had just implemented test observability across their entire suite of 3,000+ automated tests. And instead of frantic debugging sessions and emergency war rooms, I watched our dashboards reveal insights in real time.

Data is vital to everything we do in the modern world. When it comes to data, we cannot ignore APIs. They act as the internet’s functional backbone, helping in the smooth transfer of data between servers, apps, and devices. APIs must be protected from risks and vulnerabilities because they are used at every step. This is where security testing for APIs comes in.

Here's what I've learned after working with hundreds of QA teams: the bugs that hurt most aren't the obvious ones. They're the edge cases we once deemed "unlikely." When it comes to test coverage, these overlooked scenarios often become your biggest headaches. I see it constantly: teams with impressive coverage metrics still miss critical scenarios. Like when a major retailer's checkout system failed because nobody tested what happens when a discount code expires mid-transaction during Black Friday!

Today, we’re excited to introduce Message Reactions in Ably Chat - a quintessential part of any modern chat experience, now available as a native feature. How message reactions work Each reaction in Ably Chat is defined by a simple string, often a UTF-8 emoji like , but it could also be a tag (:like:) or text (+1). Reactions are aggregated in realtime based on their name.

APIs are the digital lifelines powering modern applications, microservices, IoT devices, and everything in between. They act as the universal translators of data, ferrying information between diverse software platforms. API security encompasses the technologies, practices, and protocols dedicated to protecting these invisible workhorses from unauthorized access, data breaches, and malicious misuse.