Operations | Monitoring | ITSM | DevOps | Cloud

Incident response has a well-known efficiency problem. The tools teams use to detect and investigate issues are often disconnected from the tools they use to manage and resolve them. Engineers spend a significant portion of each incident switching between platforms, assembling context that should already be at hand. Even when the data is available, correlating signals across user, app, infrastructure, and security events to pinpoint a root cause remains manual and slow.

Hashicorp's co-founder Mitchell Hashimoto decided to pull out his Ghostty project from GitHub in April 2026 due to GitHub's reliability issues. He did this after 18 years of using GitHub, saying that GitHub "is no longer a place for serious work". GitHub has experienced a significant decline in reliability over the past 6 months, and Hashimoto is not alone in expressing this sentiment.

The first two weeks of Claude Code are exciting. The third week is when you realize you don’t have visibility into what it’s doing or what it’s costing you. You would not run a production service without metrics, logs, and dashboards or deploy an API without knowing its latency, error rate, or cost per request.

I recently gave a talk at Experts Live India 2026 about SquaredUp, and even before getting into the demo, there was one question I knew I had to address: Is the dashboard era over? It's something we're all hearing more. "Just ask AI." "Agentic AI will build your dashboards automatically." "Why bother with static views when a chatbot can answer anything?" It's a fair question. Answering it requires a clear understanding of what a dashboard represents.

When an unexpected alert fires these days, most engineers' first move is to ask their AI assistant for help.You ask why your checkout service is slow and the assistant gets to work, but it can't get any meaningful insights—at least not quickly—without the proper guidance. So, the next thing you know you're sharing deals about your existing data sources, the services you have running, how they connect, which labels and metrics matter, and on and on.

You’re comparing error monitoring tools. You’ve narrowed it down to two or three options. Now you need to know what this actually costs before you bring it to your team. Here’s what Rollbar costs, what’s included at each tier, and how it compares to Sentry and Datadog on pricing. No sales pitch, just the math.

InfluxDB 3 Explorer 1.8 is all about writing data and keeping it under control. You can now subscribe to MQTT, Kafka, and AMQP streams directly from Explorer, generate custom sample datasets, stream live sample data continuously into your database, and validate your line protocol and preview the resulting schema before you write it. You can now also view and edit retention periods on both databases and individual tables.

Modern enterprise architectures increasingly need to bridge the gap between resource-constrained IoT devices and heavyweight enterprise backend systems. ActiveMQ MQTT support makes this possible: devices running the MQTT protocol - sensors, actuators, edge nodes, publish telemetry on standard topics, while JMS-based backend services consume and process the data without any client-code changes.