Operations | Monitoring | ITSM | DevOps | Cloud

Modern production environments generate massive volumes of logs every day. As systems become more distributed and cloud-native, that volume only increases. The real challenge isn’t collecting logs—it’s identifying what matters fast enough to act using effective log visualization. Most log views fail at this point. Every entry looks the same, forcing engineers to scan them manually and interpret lines under pressure.

Choosing a Data Center Infrastructure Management (DCIM) platform is one of the more consequential decisions a data center team will make. Get it right, and you gain an accurate digital twin of your physical infrastructure, a single source of truth across teams, improved operational visibility, and a platform for planning, reporting, and automation. Get it wrong, and you risk a failed deployment, a platform that doesn't fit your needs, or a shelfware investment that's hard to justify renewing.

The OpenTelemetry Collector is usually deployed as a long-running process: a sidecar, a DaemonSet, an EC2 instance, a docker container on my computer. It sits there listening for telemetry. That's fine when I want to send telemetry all day, but not when telemetry is rare. Like right now, when I have an agent defined on AgentCore, and it runs a few times a week maybe. Or my website that hardly sees any traffic. Can I run the OpenTelemetry Collector as a Lambda function?

Finding the right information across dashboards, monitors, and telemetry sources takes time, even for experienced engineers. When something breaks, it often means figuring out where to start, rebuilding queries, and jumping between metrics, logs, and traces before you can take action. The challenge isn’t a lack of data but the effort required to surface the right information at the right moment.

Every time your app asks the database 'does this row exist,' it pays the cost of a database query to get back 'no'.

Sentry’s SDK teams maintain and support SDKs for a vast ecosystem of languages and frameworks. See our release registry for a source of truth. We’re currently at 159 published packages across the entire ecosystem. If you use it, we probably support it. All of these SDKs are open source and have their own GitHub repositories that we maintain on a daily basis. And like any other open source project, we get tons of bug reports and issues on these.

A Hardware Asset Management (HAM) audit is a formal check of whether your hardware inventory reflects physical reality. It covers what devices exist, where they are, who has them, what state they're in, and how retired assets were documented out of the system. Most organizations don't fail HAM audits because their IT teams are negligent.

Standardize the route from code to production. Everything else is a team decision, not a platform problem. Most app delivery problems do not start with bad engineering. They start with too much variation. One team provisions environments manually. Another keeps deployment notes in a wiki. A third has a staging setup that only one engineer understands. Security reviews happen late because the platform does not make the safe path obvious.