Operations | Monitoring | ITSM | DevOps | Cloud

Enterprises are hemorrhaging their cloud budget: respondents in 49% of organizations estimate their cloud spending is wasted due to unchecked provisioning and lack of predictive cost governance. This cost inefficiency stems not just from financial blind spots, but also from operational gaps: poor visibility into network reliability and user experience. Real-time, end-to-end visibility is the foundation of cloud optimization.

Your security teams face escalating data volumes, vendor changes, and cost pressures when they migrate between SIEM platforms. Cribl simplifies these migrations by giving you flexible data routing, reducing storage costs, and accelerating time-to-value. How? Let’s look at how a global customer used Cribl Stream to migrate CrowdStrike FDR logs from Splunk to Microsoft Sentinel efficiently and cost-effectively.

Learn how to achieve and maintain HIPAA compliance on AWS with this comprehensive guide. Understand the shared responsibility model, essential architectural principles, and a practical checklist to protect PHI and avoid costly compliance violations. Discover how automation can reduce human error and streamline your security posture.

Retail is no longer defined by the checkout counter or button. What used to end with a purchase has expanded into an always-on ecosystem of engagement, media, and service. Every interaction, from browsing to post-purchase, now carries both experience value and monetization potential. This shift has made Retail Media Networks (RMNs) the fastest-growing profit center for retailers, but their scale and complexity demand more than human-led operations or rule-based automation.

We’ve seen the same story play out time and time again in numerous SaaS companies: The problem often begins when engineers — with a technical understanding of cloud costs and a deep understanding of how to build robust products — struggle to communicate the actual business impact of their efforts to company leaders.

Fall is here again! These headlines might not be as good as a maple-sugar doughnut and a pumpkin-spiced coffee, but they’re excellent news for FinOps practitioners nonetheless (and they won’t put you into a sugar coma).

Your dashboard shows a latency spike. To investigate it, you copy the query, open logs in a new tab, paste and modify the query, lose your dashboard filters, and repeat for traces. By the time you find the issue, you have 15 tabs open. Starting today, you can click any panel and investigate right there. All your filters and variables carry over. No more tab juggling.

When your database stops accepting connections or your mail server becomes unreachable during business hours, the impact is immediate and costly. Fortunately, the right monitoring strategy can help you detect these TCP connection failures early on, and prevent them from impacting the user experience.

If you’ve been following my public journey with LLMs this year, it probably won’t surprise you to learn that this blog post is an announcement about the general availability of Honeycomb’s hosted MCP server. I want to share a few updates about what’s new in the GA release, discuss some interesting learnings from building it, and share examples of how we’re using MCP internally. First: if you're still in the dark about MCP and AI agents, go read the earlier blogs I linked.

AI agents for SREs were supposed to slash mean time to resolution and eliminate alert fatigue. Instead, most teams got expensive, unreliable tools that burn through tokens without delivering insights. But what if the problem isn't the AI models themselves? Recent benchmarking reveals the real bottleneck: context engineering. When we tested our context engineering approach against conventional methods, the results were dramatic: Scroll down for our benchmark results to see the full comparison.