What can Troubleshooting Digital Assistants do for your colleagues?

Spend more time on improving platform capabilities and less time doing basic dev/test troubleshooting.

With 24/7, instant availability of AI troubleshooting assistance, platform owners will see a dramatic increase in 'customer satisfaction' from their app developers and start to free up engineering bandwidth for platform roadmap or strategic projects.

Most Kubernetes teams are too small to emulate the 6+ month on-call training in hyperscale companies. When they can ask Troubleshooting Digital Assistants for help 24/7, on-call is less intimidating and requires far less training. The Digital Assistants produce triage reports with quick summaries of the issues requiring further attention as well as long form descriptions of all commands run with their input and output for learning purposes.

Connecting Digital Assistants to alert systems (PagerDuty, AlertManager, etc) provides material reduction in MTTR (mean time to identify) as they run hundreds of troubleshooting commands in response to alerts and build sophisticated summary reports in seconds.

Rather than give app developers production credentials, RunWhen users typically give credentials to Digital Assistants that can only access a pre-reviewed set of automated tasks.

This is managed at scale by giving different teams access to different Assistants, e.g. any engineer at RunWhen’s can use Eager Eager (read-only) but only a few can use Admin Ali (read-write access)

Digital Assistants connected to key alerts can generate advanced triage reports whenever a key metric goes out of range.  Since the triage reports typically include the output needed for troubleshooting, the vast majority of metrics, logs and traces stored in expensive observability systems become redundant for users embracing this approach.

RunWhen itself reduced our monitoring/logging bills by $40k/month with this approach across our dev clusters.