Operations | Monitoring | ITSM | DevOps | Cloud
The Place Where Modern Operations & Technology Come Together
The latest News and Information on APIs, Mobile, AI, Machine Learning, IoT, Open Source and more!
Supercharge your LLM Using Production Data Context
Are your LLM coding agents (like Cursor or Claude Code) hallucinating fixes because they don't know what's actually happening in production? In this video, Matt from Speedscale shows you how to bridge the gap between your local IDE and live production traffic using the Model Context Protocol (MCP). Most observability tools just give you telemetry. Speedscale’s MCP server gives your agent the "inner workings" of actual API calls and payloads, so it can check its assumptions against reality. No more "vibe-coding" and hoping it works; let your agent find the 500 errors and rate limits for you.
How To Calculate Your OpenAI Cost Per API Call (And Why It Matters Now)
OpenAI doesn’t bill per feature, per customer, or per transaction. It bills per token, across multiple models, with usage patterns that can change by the hour. As a result, two API calls that support the same feature can have very different costs. Without a clear way to translate token-level pricing into something product, engineering, and finance teams can reason about, AI spend becomes difficult to forecast and harder to control.
Automate flaky test fixes with the Bits AI Dev Agent and Test Optimization
Flaky tests are a significant source of inefficiency that impacts many engineering teams. Along with failing your build, they interrupt your entire development flow, generate excessive CI/CD noise, and, critically, compromise developer trust in the test suite itself. Datadog Test Optimization enables you to manage test suites at scale by pinpointing the flakiest tests, analyzing their history across hundreds of runs, and automatically surfacing the root cause.
How we built an AI SRE agent that investigates like a team of engineers
We built Bits AI SRE to help engineers investigate and solve production incidents, one of the most difficult aspects of operating distributed systems today. As environments grow more dynamic and complex, resolving issues becomes more challenging. Failures now span more services, involve noisier signals, and encompass larger volumes of telemetry data, making it hard for on-call engineers to find root causes quickly. Today, Bits AI SRE is already helping teams decrease time to resolution by up to 95%.
Why Reliable Payment Processing Is More Important Than Speed
If you shop online, you've been seduced by the promise of speed at least a dozen times, and it's the same thing with your customers. "3-second checkout!" sounds incredible, doesn't it? For payment companies, this is what they usually lead with, but you should know that they don't put everything in the ad. Sure, their system is fast, but what about the fact that it dropped 2 orders just this morning and flagged another as fraudulent for literally no reason?
Technology forecasting should have better tools
Technology moves in waves: breakthroughs, hype, adoption, disappointment, then quiet infrastructure building. The challenge is that traditional forecasting often lags behind reality. Reports are published after the market has moved, expert opinions can conflict, and social media trends can distort what feels important. This is why the idea of a technologies prediction market is compelling. It offers a mechanism for turning diverse beliefs into a live probability signal that updates as new information appears.
Operational Risk Management in High-Stakes Decision Environments
In high-stakes environments, every choice carries weight. Whether it is a complex financial process, a real-time cybersecurity response, or a tightly regulated operational workflow, small missteps can rapidly evolve into major failures. Organizations increasingly rely on integrated riskmanagement strategies that blend human judgment with technology. The goal is simple: reduce uncertainty before it becomes costly. But the path to that goal is rarely straightforward.
Magento vs. Shopify: The Ultimate Battle for E-commerce Visibility
Navigating the dense, often fog-filled landscape of modern e-commerce can feel remarkably like trying to steer a ship without a reliable compass. It is not easy task to choose the foundation for your business. On one side stands Magento, an open-source titan that offers limitless flexibility to anyone brave enough to tame its complex architecture. Then there is Shopify. It's the sleek, hosted alternative that promises to handle the technical headaches so you can focus strictly on selling products. But have you ever stopped to wonder which platform actually helps customers find you in the first place?
Let Your LLM Debug Using Production Recordings
Modern LLM coding agents are great at reading code, but they still make assumptions. When something breaks in production, those assumptions can slow you down—especially when the real issue lives in live traffic, API responses, or database behavior. In this post, I’ll walk through how to connect an MCP server to your LLM coding assistant so it can pull real production data on demand, validate its assumptions, and help you debug faster.