Operations | Monitoring | ITSM | DevOps | Cloud

Single Step Instrumentation (SSI) simplifies Datadog Application Performance Monitoring (APM) by automatically discovering and instrumenting services across a host. For many teams, SSI is the ideal starting point because it helps them achieve full visibility with minimal setup. However, as environments grow, teams often want more control over which services get traced. Auxiliary workloads such as batch jobs and cron tasks might not require distributed tracing.

As organizations continue to heavily invest in AI and build more agentic workflows, their telemetry data volumes can surge quickly, and the associated costs can become unpredictable. To regain control of their data, many AI-forward teams are turning to high-throughput, low-latency pipelines to collect and route data to tools such as OpenTelemetry (OTel) and ClickHouse. But these self-hosted solutions come with drawbacks.

Last week was a great reminder for me about the challenges of the traditional model of observability defined by the “three pillars” of metrics, logs, and traces. One of the customers I’m currently working with is a large financial institution that has a robust three pillar implementation. Every critical application ships their telemetry to either or both their cloud-native tool and a central tool.

If you’ve spent time in industrial environments, you know the problem isn’t a lack of data. It’s collecting it reliably, contextualizing it, and storing it at scale. Most stacks weren’t built to fight all three battles.

Most cloud cost dashboards are built for one audience. The finance team wants to see totals by department. The engineering team wants to see costs by service. The DevOps team wants to see environment-level breakdowns. When everyone looks at the same dashboard, nobody gets what they actually need. This is where tailored cloud cost visibility starts to matter. When a team can see its own costs clearly, it moves faster, takes ownership, and starts treating cost data like it actually matters.

The expectations placed on infrastructure leaders have shifted in a way that is subtle on the surface but significant in practice, and much of that shift comes down to infrastructure cost visibility. Reliability and performance still matter, but they are no longer the differentiators they once were. Most enterprise environments are stable by design, and uptime is assumed. What has changed is the level of scrutiny around cost and decision-making.

The tension between shipping speed and application performance has not changed much since this post was first published in 2020. What has changed is how quickly a team can detect, diagnose, and fix a problem. That difference is significant enough to warrant a revisit. The scenario from the original still plays out every week. Sales brings a priority feature that might degrade performance for some customers. The developer ships it and watches what happens.

When we launched AppSignal MCP in beta, OAuth was on the roadmap but not yet shipped. We were issuing static bearer tokens — enough to connect Claude Desktop, Cursor, and Windsurf, but not the one-click install path in the MCP Registry, and not GitHub Copilot's recommended setup. That's fixed.

IncidentHub tracked 48000 SaaS and Cloud outages in 2025. The average organization depends on 100+ SaaS apps, making third-party vendor monitoring a crucial aspect of risk management and business continuity for almost all modern organizations. Better SaaS outage alerting is about monitoring the right parts of your third-party services, and routing alerts to the right people at the right time.