You may have noticed that Claude AI has had an outage today. 9to5Google reports the following:
Anthropic says it is aware of an outage and has rolled out a fix as recent as 10:53 a.m. ET. The company’s server status website indicates an issue affecting multiple models occurred at 10:19 a.m. ET.
The status update doesn’t detail which models were affected, though attempts to get a response from Sonnet and Opus returned nothing. Those models seem to be the most commonly used, especially as Fable 5 was recently pulled from user access.
The current outage did, however, affect those models across all platforms except for Claude for Government. That includes claude.ai, Claude Console, Claude Code, and Claude API. The total outage time comes close to an hour and stands out as one of the largest outages to hit Anthropic within the past 60 days.
Commenting on this news is Jamie Beckland, Chief Product Officer at APIContext:
“Ready or not, AI inference is now production infrastructure. Enterprises are no longer using these systems only for experiments or side projects. They are putting AI into customer support, coding workflows, analytics, operations and decision support. When an inference endpoint slows down, throws errors or goes unavailable, that can now break a real business process.
Enterprises must run AI with the same discipline they apply to payments, cloud, APIs and other critical services. That means continuously monitoring inference endpoints for latency, error rates, model availability, response quality and regional performance. It also means having a tested failover plan before the outage happens.
Applications with one model provider hardcoded create a single point of failure. A more resilient approach is to design AI systems with fallback models, backup providers, graceful degradation and clear routing rules. Not every task needs the same model. If the primary model is unavailable, some workloads can move to another frontier model, some can fall back to a smaller model, and some should pause rather than return a bad answer.
Six months ago, these tools were enterprise experiments. Now, AI resilience is part of operational resilience.”
If you rely on AI as part of your business, then you need to plan for downtime. Why? Downtime is part of the game and you need to be prepared for it or bad things will happen.
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This entry was posted on June 23, 2026 at 12:44 pm and is filed under Commentary with tags Anthropic. You can follow any responses to this entry through the RSS 2.0 feed.
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Claude Reports Major Outage Across Multiple Models
You may have noticed that Claude AI has had an outage today. 9to5Google reports the following:
Anthropic says it is aware of an outage and has rolled out a fix as recent as 10:53 a.m. ET. The company’s server status website indicates an issue affecting multiple models occurred at 10:19 a.m. ET.
The status update doesn’t detail which models were affected, though attempts to get a response from Sonnet and Opus returned nothing. Those models seem to be the most commonly used, especially as Fable 5 was recently pulled from user access.
The current outage did, however, affect those models across all platforms except for Claude for Government. That includes claude.ai, Claude Console, Claude Code, and Claude API. The total outage time comes close to an hour and stands out as one of the largest outages to hit Anthropic within the past 60 days.
Commenting on this news is Jamie Beckland, Chief Product Officer at APIContext:
“Ready or not, AI inference is now production infrastructure. Enterprises are no longer using these systems only for experiments or side projects. They are putting AI into customer support, coding workflows, analytics, operations and decision support. When an inference endpoint slows down, throws errors or goes unavailable, that can now break a real business process.
Enterprises must run AI with the same discipline they apply to payments, cloud, APIs and other critical services. That means continuously monitoring inference endpoints for latency, error rates, model availability, response quality and regional performance. It also means having a tested failover plan before the outage happens.
Applications with one model provider hardcoded create a single point of failure. A more resilient approach is to design AI systems with fallback models, backup providers, graceful degradation and clear routing rules. Not every task needs the same model. If the primary model is unavailable, some workloads can move to another frontier model, some can fall back to a smaller model, and some should pause rather than return a bad answer.
Six months ago, these tools were enterprise experiments. Now, AI resilience is part of operational resilience.”
If you rely on AI as part of your business, then you need to plan for downtime. Why? Downtime is part of the game and you need to be prepared for it or bad things will happen.
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This entry was posted on June 23, 2026 at 12:44 pm and is filed under Commentary with tags Anthropic. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.