Operations | Monitoring | ITSM | DevOps | Cloud

For large enterprises, the health and resilience of Business Services define customer experience and business reputation. Yet as technology estates grow in complexity, fragmented toolsets and siloed teams make it difficult to maintain service availability and prevent incidents before they impact the business and ultimately, customers.

Data has exploded — and so have the challenges that come with it. Every click, transaction, and sensor ping generates mountains of data that traditional databases can’t handle. That’s why more than 94% of organizations now rely on cloud platforms, according to CloudZero’s 2025 cloud report. The goal isn’t just to store data, but rather, to make sense of it fast. And this is exactly where tools such as Google BigQuery step in.

When a critical alert fires at 2 AM, the last thing your on-call engineer should be doing is manual administrative work. Yet, for many teams, that’s exactly what happens. You see the alert in your monitoring tool, then you have to switch contexts, open a new browser tab, log into your ITSM platform, and manually create an incident—all while your systems are failing.

On October 19th and 20th, 2025, the AWS region US-EAST-1 suffered a massive outage. What started with a 3-hour Amazon DynamoDB outage from a DNS issue led to an Amazon EC2 outage that lasted an additional 12 hours before normal service was restored. Over the course of the outage, there were over 17 million outage reports as companies like Snapchat, Roblox, Amazon, Reddit, Venmo, and more were impacted.

The Playwright framework is known for its UI testing features, but it also has robust tools for testing API capabilities. Playwright API testing tools allow you to build faster and more reliable end-to-end tests. Because you can combine both the UI and API tests into one test suite, your testing efforts become more efficient.

We’ll always remember 2025 as the year AI code assistants went big. Copilot, Cursor, Claude, Windsurf, whatever. Developers went from mistrusting these tools, to being expected to turn over much of their coding labor to them. Even if, according to an extensive Stack Overflow survey, only 3 percent of professional developers say they ‘highly trust’ AI coding tools.