Operations | Monitoring | ITSM | DevOps | Cloud

The latest News and Information on API Development, Management, Monitoring, and related technologies.

Test PostgreSQL With the Queries Your App Actually Runs

The first number from my local PostgreSQL 16 test was roughly 1,600 statements per second. It looked impressive. It was also the least useful result in the run. The useful part was the workload. It came from queries the demo app had actually sent: the same prepared statements, parameters, reads and writes. A synthetic benchmark tells you how PostgreSQL handles a synthetic workload. It does not tell you whether your migration just broke the UPDATE your app depends on.

$4.48 a Gallon: Your Holiday Checkout Is the New Mall

Remember when “going shopping” meant getting in the car? This fall, filling the tank feels like applying for a small loan. U.S. regular gasoline averaged about $4.48 a gallon for the week of September 21, 2026. A round trip to the store starts competing with free shipping. And free shipping never needs a parking spot. That doesn’t tell us how many shoppers will move online this holiday season.

Free Space APIs: Useful Data for Building Smarter Applications

Space data is no longer limited to government agencies, research institutions, and specialist aerospace companies. Developers can now use APIs to bring satellite imagery, orbital information, astronomy data and other space-related datasets directly into their applications. Free space APIs are particularly useful when testing an idea or building a prototype without committing to expensive infrastructure from the outset. The right option, however, depends heavily on the type of data you actually need.
Sponsored Post

Synthetic Monitoring Is Broken. Your Production Traffic Can Fix It.

Synthetic monitoring has been a critical part of application reliability for years. It gives engineering and operations teams a way to proactively test applications, APIs, and critical customer journeys before users encounter problems. But there is a fundamental limitation with the traditional approach: Someone has to create the tests. As applications become more distributed and customer journeys become more complex, organizations can end up maintaining hundreds or even thousands of synthetic scripts. Every new feature, API, dependency, or change to a customer journey can require another update.

Upgrading the Operations Tech Stack at the Edge of Supply Chains

Warehouse management systems (WMS) and resource planning (ERP) platforms have undergone massive architectural shifts over the last decade. Microservices, event-driven cloud architectures, and real-time database synchronization have transformed how logistics organizations manage inventory levels, calculate safety stock, and track order fulfillment. Yet, despite millions invested in core IT infrastructure, operations architects frequently encounter a persistent data blind spot at the physical perimeter of the supply chain network: the loading dock.

Team-Based DLP: Give Each Group Its Own Redaction Rules

A shared Kubernetes cluster rarely belongs to one team. Payments runs checkout in one namespace, search runs search-api in another, and a risk team runs a scorer somewhere else. One Speedscale forwarder captures API traffic for all of them. Redacting that traffic before it leaves the cluster is what makes it safe to use for testing (the background is in The PII Testing Dilemma). Until now, that forwarder ran exactly one DLP rule. Every team that needed a field redacted had to edit the same JSON document.

Moving Alert and Email-to-Ticket Mail off SMTP AUTH to Microsoft Graph API

Every monitoring alert, scheduled report, and email to ticket conversion in your stack depends on a mailbox. Most monitoring and helpdesk management tools still reach that mailbox the old way. They log in with a username and password over SMTP or EWS. Exchange Online is closing both doors on a published schedule. The tools that fail will fail silently. In this blog, you will: By the end, you can run the change on a weekday afternoon and know nothing went quiet.

Use AI and traffic replay to test AI-generated code

When I ask an AI agent to change code, I also want it to run the application and test what it changed. Asking it to write some tests is a start. But if it invents the expected responses from the same assumptions it used to write the code, those tests can miss the same mistake. Traffic replay gives the agent something concrete to test against: requests and responses captured from a working application.

Why Mocks Fail at Scale #softwareengineering #devops #softwaretesting #api #aicoding

Mocking for testing starts off easy, but once you scale to multiple teams and AI agents, handcrafted mocks become a serious form of technical liability. Instead of treating mocking as an individual software engineering task, shift your mindset to treat it as a platform engineering task focused on automation and continuously refreshed modern data. Watch to see how adopting technologies like traffic replay to simulate realistic backend sandboxes can transform your modern testing workflow!