Operations | Monitoring | ITSM | DevOps | Cloud

As the number of connected gadgets in our homes, offices, and industrial networks continues to grow exponentially, keeping IoT devices secure has become a vital part of our everyday lives. However, our webcams, printers, and smart plugs often lack security features due to their fast time to market, making them particularly vulnerable to attack. And because security metrics themselves can be tricky to assess, tracking IoT device security is increasingly a challenge.

It’s one thing to set up an observability strategy. But what’s it like to introduce and scale observability effectively across an organization? In a wide-ranging conversation at ObservabilityCON 2021, three technical pros from Snyk, TripAdvisor, and Citibank joined Grafana Labs VP Global Solutions Engineering Steve Mayzak and — with more than 75 years experience between them — they shared the triumphs and turbulence in their respective observability journeys.

Back in May, we announced the Kubernetes integration to help users easily monitor and alert on core Kubernetes cluster metrics using the Grafana Agent, our lightweight observability data collector optimized for sending metric, log, and trace data to Grafana Cloud. Since then, we’ve made some improvements to help our customers go even further.

On 2021-10-29, initial support for Prometheus Agent was merged, and it is slated for inclusion in Prometheus v2.32! This feature has a bit of a lengthy history to it: It took a little while to get to where we are today, but I’m thrilled that we were able to use the Grafana Agent code to enable agent-like functionality in the prometheus/prometheus repository.

In today’s cloud environments, a typical observability stack might include an Elasticsearch cluster for logging, a few Prometheus servers for metrics monitoring, and an AppDynamics deployment for APM. You may run something similar – most observability stacks consist of multiple siloed tools dedicated to collecting and analyzing specific types of monitoring data.