Is it the app or the platform?

We operate a (paid) community of experts building the industry's largest library of automated troubleshooting steps and AI Assistants in your environment that know what to run.

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For Platform Teams Who Are Guilty Until Proven Innocent

Are you busy triaging noisy alerts, doing someone else's troubleshooting or joining 20 person incident calls to prove the problem wasn't in the platform?

For Developers Who Do Not Want A PhD In Kubernetes

Is the problem your code, or one of your dependencies? Are you blocked until someone from the platform team can make some progress?

For Executives Managing Operational Risk

How much risk are you taking while your team is getting up to speed on Kubernetes? A new cloud platform? Are you set up to measure, mitigate and automate?

3,432

Automated Troubleshooting
Steps In The Library

46,124

Automated Next Steps Suggested To Devs, Platform Engineers and SREs

15,562

Engineering Hours Saved Avoiding and Reducing Downtime

Enterprises observe... Hyperscalers automate

Most enterprise teams focus on metrics and logs that fire alerts. Sometimes they have runbooks that help, but more often they require teams of experts to be available 24/7 across dev, test, and production.

Hyperscale teams, on the other hand, focus on automating small troubleshooting steps that an expert would take after receiving an alert. Their massive libraries instantly pinpoint where problems are (and are not), reducing operational risk, downtime, and lost productivity.

Coverage matters

It takes 2+ years for a team to build enough runbook automation coverage to have impact. We reduce this time to zero with a unique "paid community" model. When users import accredited automation, the author receives royalty.
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Ready to use
‍in one afternoon

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Most teams start by using RunWhen Local to scan a staging environment's Kubernetes clusters and/or cloud accounts.

It makes thousands of troubleshooting steps available immediately for Digital Assistants to find and run in response to questions in the web UI or slack, alerts, CI/CD jobs, etc.

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Where to next?

RunWhen is intended to be useful for Platform/SRE teams troubleshooting out of the box. It doesn't stop there...

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Connect To Slack

Connect AI Assistants to Slack so anyone on the team can ask an AI Digital Assistant for root cause or remediation help 24/7.

Connect To Alerts

Connect Digital Assistants to alerts so they can run autonomous troubleshooting sessions and report back with a root cause, severity, suggested next steps and a full diagnostic report with output from all automation they ran.

Add No-Code Steps

Add No-Code "Generics," simple application troubleshooting steps like checking a REST API, a SQL query or pre-canned log search. These require only a few lines of configuration to be Digital Assistant-ready

Connect To CI/CD Pipelines

Connect to CI/CD pipelines and use Digital Assistants to run thousands of troubleshooting tasks. They report back on issues found and severity, creating metrics for operational readiness.

Distribute The VSCode Plugin

When you are ready to give your developers the gift of self-serve troubleshooting, consider distributing our VSCode plugin.

Chaos Engineering?

Connect to your chaos engineering stack or use our lightweight fault-injection scripts to see how Digital Assistants respond to incidents in staging before going to production

Manage to SLOs

RunWhen's defaults include automation to generate fine-grained SLIs, SLOs and Monthly Error Budgets based on community benchmarks that are useful in dev, staging and production.

A (paid) community?

Expert authors in our community receive royalties and bounties when RunWhen customers import troubleshooting steps they automated. The community's efforts span infrastructure, cloud services and platform components alongside popular OSS components, programming languages and frameworks.

Become a Paid Author Join the Slack Community

Integrate with your existing tools

Our community has contributed integrations with numerous tools and in addition to troubleshooting applications written on popular code frameworks, platform components and cloud infrastructure.

View Example Code Collection

Less operational risk,
same operational budget

Most organizations moving to Kubernetes or to a new cloud platform need to manage massive operational risk without a massive increase in budget. AI can help.