Operations | Monitoring | ITSM | DevOps | Cloud

Migrating to SAP S/4HANA is one of the most consequential system changes your organization will undertake. The technical complexity alone is significant. But the real risk is operational: maintaining uninterrupted service delivery while transforming the core systems your business depends on. Failure to manage this well causes outages, data inconsistencies, user disruption, and cost overruns. None of those are acceptable outcomes. The good news is these risks are manageable.

Zabbix is one of the most popular open source monitoring platforms in the world, with first class capabilities for monitoring networks and infrastructure at scale. It also boasts a rich ecosystem of adapters and plugins for collecting telemetry from thousands of device types.

Checkly is a modern reliability platform that combines testing, monitoring and observability in one place. Its integration with Playwright and languages such as TypeScript means that developers can write tests using tools they are familiar with and then run them in Checkly. Its Monitoring as Code philosophy also means that Checkly tests can be incorporated into CI/CD pipelines.

Honeycomb is proud to share that we have achieved the Amazon Web Services (AWS) Financial Services Competency. This recognition validates our technical expertise and proven customer success in assisting financial services organizations with building, running, and understanding their production systems on AWS. Securing this competency is a direct response to our customers’ feedback in this space: observability in regulated, high-stakes environments requires more than dashboards and alerts.

The traditional dashboard workflow, teams slowly handcrafting visualizations to track critical KPIs, is dying in a world of AI agents. A few years ago, in a pre-agentic-everything world, we tried to make it easier for developers to monitor critical experiences. We introduced Insights pages, which were pre-configured dashboards any Sentry user could adopt instantly that surfaced common health signals, like Web and Mobile Vitals.

Micro-frontend architectures, where independent teams build and deploy separate parts of a frontend application, introduce an observability challenge: Telemetry data is fragmented across services, making it difficult to determine which micro-frontend caused a performance degradation or error spike.

AI adoption is accelerating across organizations, and spending often follows a similar pattern: rapid growth, multiple providers, and limited visibility into where costs originate. Each provider exposes billing data differently, with distinct schemas, dimensions, and interfaces. FinOps and engineering teams often spend significant time consolidating fragmented data, only to end up with partial attribution and limited context about who or what generated the AI spending.

The uptime & availability of our status pages hasn't been great these past few days. The root cause is a persistent and pretty aggressive DDoS attack targeted at our own status page, status.ohdear.app. As a result, the overload on our systems also affected all other status pages we host for clients. We're not yet at Github or Claude levels of uptime sadness, but this isn't acceptable to us. In this post, I'll share what's happening and what steps we've already taken.

AI coding assistants have made it possible for a single developer to build and ship a production application in a weekend. Claude Code, Cursor, GitHub Copilot, and similar tools can scaffold a Rails app, write the models, generate the views, wire up the API, and push to production before Monday. This is genuinely exciting. It is also genuinely dangerous if you do not have monitoring in place before you ship.

Last updated: May 2026 If your team is 2 to 20 developers and you do not have dedicated DevOps, SRE, or platform engineering, most APM tools were not built for you. They were built for the team that has you: a team with specialists who can tune dashboards, configure alerting pipelines, manage data retention policies, and explain the monitoring system to everyone else. You do not have that team. You have developers who also handle deploys, on-call, and debugging production issues between writing features.