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Monitoring AI Applications in 2026: What You Actually Need

Last updated: July 2026. Your AI feature works in development. It demos well. Then it hits production and you discover three problems your test suite did not catch: the LLM hallucinates product names that do not exist, the RAG retrieval step adds 4 seconds to every request, and your OpenAI bill is 3x what you budgeted because one prompt template is burning tokens on context that does not help the output. Traditional APM would have caught the latency.

AI Is Reshaping the Tech Industry in 2026: What Consumers and Businesses Need to Know

Artificial intelligence has evolved from an emerging technology into one of the biggest drivers of innovation across the global technology industry. In 2026, AI is influencing everything from smartphones and laptops to cybersecurity, cloud computing, enterprise software, and digital productivity tools. Companies worldwide are investing heavily in AI powered products that improve efficiency, automate repetitive tasks, and deliver more personalized user experiences.

The DevOps Hiring Crunch: How Distributed Teams Are Closing the Gap

Ask any engineering leader what keeps them up at night and "who's covering the pager next Tuesday" is usually somewhere on the list. DevOps and SRE roles have become some of the hardest positions to fill in software, and the shortage is starting to show up in the metrics ops teams care about most: MTTR, alert fatigue, and how many people are burned out on the on-call rotation.

Why AI agents need a job description | The future of agentic AI in IT

An AI agent is only as useful as the job you can safely hand it. In this Zero Ticket Minute, Ian Coppock, Resolve Customer & Partner Marketing Manager, breaks down why enterprise AI is moving toward purpose-built agents with defined roles, scoped permissions, and real guardrails. That is the foundation for autonomous IT operations and Zero Ticket IT. Subscribe for weekly insights on AI, IT automation, and where enterprise operations are heading.

How to Use Your Knowledge Base to Increase AI Chatbot Deflection

Ticket deflection is the metric IT leaders point to when they talk about AI chatbot ROI, and the knowledge base is the part of the equation that determines whether that number moves. A chatbot can run natural language processing well and still deflect almost nothing if the content behind it is thin, outdated, or scattered across articles that don't match how people actually ask questions.

We rebuilt Spike app for Slack

The new Spike app for Slack brings incident response into the channel your team already works in. This walkthrough covers the @Spike AI assistant, the redesigned incident alert template, Statuspage syncing, and on-call overrides. To get started, head to Slack settings inside Spike and reconnect the app. Chapters Statuspage syncing is available on all plans. Spike is an incident response and on-call management platform. Alert routing, escalation policies, on-call schedules, and incident management, built for engineering teams.

OpenSearch 3.6: Agentic Applications Meet Long-Term Support

TL;DR OpenSearch 3.6 makes agentic search production-ready, with the AI-powered Launchpad provisioning full search apps in minutes and faster default vector search, and it's the first LTS release, bringing 18+ months of guaranteed support, SBOMs, and an upstream-first commitment (every fix goes back to the main project) so teams get fast-moving open source and a stable, supported platform at once.

Making agentic token costs visible in production

In some organizations, high token counts have become a proxy for productivity. Some engineering teams are being pushed to max out context windows and wire in sprawling tool sets. More tokens can mean better agent reasoning and richer context during development, but token costs compound in production. Tokens accumulate across sessions, users, and tool calls in ways that are easy to overlook. Datadog’s 2026 State of AI Engineering report quantifies the scale of this problem.

The AI Software Engineering Revolution, feat. Anthropic | Big Tent S3E9

In this episode of Grafana's Big Tent, hosts Mat Ryer (Senior Director of AI, Grafana Labs) and Tom Wilkie (CTO, Grafana Labs) sit down with Eric Burns, Field Executive Architect at Anthropic, to talk about building trust between tech and business execs, why Anthropic bet early on running across every major cloud, and what it was like watching large language models go from "interesting" to "obviously the future" in real time.

How Upstash Monitors Every Redis Replica with Checkly

There's a support ticket every SRE dreads: "is something wrong with my database?" The outage is bad enough. Worse is the possibility that the customer knew first. At Upstash, we treat that scenario as two failures rather than one: the incident itself, and the uptime monitoring gap that let a customer beat us to it. We write a postmortem for the gap, too.