Scheduled reviews
Background analysis runs every five hours without prompting an assistant.
All resources
AI error analysis
Proactive AI error analysis for your applications
A scheduled background job reviews your apps every five hours to flag crash loops, OOM risk, CPU spikes, traffic drops, and unusual HTTP error patterns automatically—before you have to open a chat.
Different from the on-request AI assistant
5h
review interval
OOM
memory risk
Traffic
traffic changes
Loops
recurring failures
Connected outcomes
Different from the on-request AI assistant
The AI assistant helps when you start a conversation. AI error analysis works proactively in the background and creates signals for you to review.
Explore capabilitiesEnable a scheduled review
Turn analysis on per application, choose its report language, and run a review immediately when you need a new check.
Review actionable reports
Reports show a severity, status, summary, and timestamp so you can assess the detected issue in the application settings.
Resolve or investigate in AI
Mark a report resolved or open a pre-filled AI chat that carries its issue details into a focused investigation.
Built to operate
Explainable findings for a faster investigation.
Every finding is scored and timestamped, so you can triage a crash loop ahead of a minor traffic dip instead of reading reports in creation order.
Crash-loop detection
Surface recurring failures that deserve attention before they compound.
OOM risk flags
Identify memory pressure and risky resource patterns early.
Traffic-drop signals
See abnormal traffic changes that may indicate an incident.
HTTP error patterns
Unusual spikes in error responses or request patterns are flagged alongside crash and resource signals, not just raw traffic volume.
Progressive setup
Enable it once. Review when flagged.
Enable the review, let it run on its own schedule, and check back for reports instead of watching dashboards.
Get started01
Monitor the service
Run scheduled background checks every five hours.
02
Analyze patterns
Flag crash loops and repeated operational failures.
03
Review findings
Identify OOM risk before it becomes downtime.
From connection to the first decision, in one flow.
Frequently asked questions
How this resource works in practice.
After you enable it for an application, the service performs background reviews and creates reports when it finds an issue worth reviewing.
Ready to move forward
Find patterns before they become larger incidents.
Enable AI analysis and turn operational signals into a clear investigation queue.
Guided setup with no commitment
Reviews every five hours
Background analysis flags crash loops, OOM risk, and traffic drops automatically.
Resolve or investigate
Mark a finding resolved, or open a pre-filled AI chat to dig deeper.
Enable AI error analysis
Turn it on for an application and get your first review shortly after.
Connected ecosystem
Connects to the workflow your team already uses
GitHub
Connect repositories and keep every release linked to its source code.
Docker
Ship your own images with a consistent process across environments.
PostgreSQL
Connect data and applications without losing operational service context.
Shard Edge
Bring caching, TLS, and global delivery closer to your users.
Shard AI
Investigate signals and execute actions with workspace context and approval.
OpenTelemetry
Connect standardized signals to expand visibility whenever needed.
Source, data, delivery, and automation stay connected so your team can operate without switching context.
Explore connected resourcesBuild on Core
Start with the plan built for your next production service.
Launch your first application with the Core plan, then keep deployment, operations, and connected resources in one place.
Start with Core