Systems | Development | Analytics | API | Testing

Real-World Security Considerations for MCP

Every new protocol introduces complexities—onboarding new tools and SDKs, adapting to new processes, evaluating security and performance implications, ensuring compatibility with existing systems, and overcoming the learning curve. So when a new protocol shows up, the first question to ask is: is it really necessary? Let’s ask that about MCP—what problem is it trying to solve?

Confluent Enables Agility and Helps You Drive Savings as Markets Shift

Businesses need to be able to respond quickly to macroeconomic uncertainty and changing market conditions, whether those are caused by trade disputes, public health crises like the COVID-19 pandemic, or simply abrupt changes in consumer demand. Amid that swirl of disruptions, technology leaders are also being pressured by management and investors to optimize their businesses and drive as much efficiency as possible.

From CI pipelines to sheet-metal sorcery: Bitrise introduces "Mini Orchard"

TL;DR – No flaky builds because of “data‑center air” at Bitrise! We built our own chassis that can talk to the Bitrise scheduler, can pre‑cool itself, and squeezes 32 Mac minis into a 6 rack unit oversized pizza box—while looking downright gorgeous doing it. We call it the mini Orchard.

Rate Limiting vs Throttling: Multi-Tenant API Use Cases

Rate limiting and throttling are two key strategies for managing API traffic in multi-tenant systems. While both aim to maintain performance and prevent misuse, they work in different ways: Rate Limiting: Sets strict caps on the number of requests a user can make within a specific time frame. Extra requests are rejected outright with an HTTP 429 status code. Throttling: Dynamically adjusts request processing speeds based on system load. Extra requests are slowed down or queued rather than blocked.

Introducing Konnect Debugger: Get Unprecedented API Traffic Visibility

We're excited to announce the general availability of Konnect Debugger, formerly known as Active Tracing during its tech preview phase. This powerful debugging and observability solution in Kong Konnect has evolved from a focused tracing tool into a comprehensive debugging platform.

GDPR Compliance in Software Development: Principles, Tools, and Development Practices

Since GDPR rolled out in 2018, enforcement has intensified. In 2023 alone, EU regulators levied roughly €2.1 billion in fines for non-compliance. That includes a jaw-dropping €1.2 billion strike against Meta for unlawful data transfers between the EU and the U.S., marking it the most significant GDPR penalty. Let’s be real. Data is serious business, and building software without GDPR compliance is like launching a bank without a vault.

Top Software Development Models Explained(2025): From Waterfall to Agile

Ever wondered why some software projects soar while others stall out? It’s not just the tech stack, it’s the game plan behind it. With the global software development market projected to hit $570 billion in 2025 and growing at 12.9% CAGR, picking the right development model isn’t just smart-it’s survival.

Introducing NeoLoad MCP: AI-Powered performance testing

NeoLoad has long been at the forefront of modern performance testing, trusted by enterprises around the world to help them test earlier, test faster, and scale performance across even the most complex environments. Its intuitive design and powerful automation have made it the go-to solution for teams seeking speed, reliability, and breadth of capabilities. Today, expectations for software teams continue to grow.

Elixir background jobs: choosing the right tool for the job

With its vast ecosystem, Elixir offers multiple solutions for running things in the background. To a newcomer or even an experienced developer, the variety of options might seem daunting. Some tools that used to be popular have fallen into the maintenance limbo, while others have emerged as default choices.

Choosing the Right Digital Analytics Tools in 2025

Choosing an analytics tool demands being conscious of the responsibility that comes with it. When you're handing over behavioral data about your users while relying on third-party infrastructure to manage it, and trusting that their policies and security remain sound, you cannot leave anything to chance. You'd also have to factor in possible scenarios like a vendor being shit down or changing direction, or whether you'll be able to extract your data. Will you be locked into a state of dependency?