Operations | Monitoring | ITSM | DevOps | Cloud

Choosing a HIPAA-compliant messaging app is rarely about security alone. Healthcare teams need messages that get read, on-call schedules that route to the right provider, and reliability that holds up at 3 a.m. Most apps clear the encryption bar. Fewer guarantee a missed page never happens. Or that critical alerts from medical systems and urgent after-hours calls from a discharged patient reach the right on-call staff.

More code is being written right now than at any point in our industry’s history. A year’s worth of software is now created every month, and most of it is no longer written by people. GitHub COO Kyle Daigle recently said, “There were 1 billion commits in 2025.

InfluxDB 3 Explorer 1.9 makes it easier to work with your existing queries. Whether you’re migrating Flux queries to SQL or you’ve been writing in InfluxQL for years, this release helps bring your existing queries forward instead of starting from scratch. For teams moving to v3 from earlier versions of InfluxDB, query migration is often one of the last major hurdles.

Coding agents like Claude Code, Cursor, and Codex CLI handle the coding parts of building an AI application well. The harder work comes after: understanding why a response went wrong, building eval sets that reflect real production behavior, and keeping up with an application that changes faster than any one-off script can. Teams spend 60–80% of their time on evaluation and error analysis, and much of that work needs to be redone every time the stack shifts.

Developer experience, commonly known as DevEx, describes how an organization’s systems, workflows, tools, and culture affect developer productivity. A positive DevEx leads to tangible organizational benefits, including faster releases, increased innovation, and reduced technical debt. Measuring DevEx enables engineering management to quantify their team’s impact and understand where to direct improvement efforts.

Off-the-shelf models are easy to deploy, but they are rarely enough to solve complex, domain-specific challenges in production. The key to sustained AI value is not in the models themselves but in the ability to tune, evaluate, and refine those models against your organization’s real-time signals. We are excited to announce that Adaptive ML is joining Datadog to accelerate this vision by combining our deep observability data with their expertise in building specialized, high-performance AI agents.

In cloud computing, teams use elasticity and scalability as if they mean the same thing. In reality, the two describe different ways a system handles load, and they solve different problems. Mixing them up can be very expensive. You either pay for capacity that sits idle, or your app buckles the moment traffic spikes, and the bill and the incident report both feel it.