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500-level errors indicate issues on Makini's side or with the connected system. These are typically temporary and retrying the request after a brief delay often succeeds. Implement exponential backoff for retries—wait a few seconds, then progressively longer intervals. If errors persist beyond a few retries, check the Makini status page for service disruptions. The error may also stem from the connected system experiencing issues rather than Makini itself. For persistent 500 errors, contact support with the request ID from the error response. Include details about when the error started, which operations are affected, and which connections are impacted. Our support team can quickly identify whether the issue is systemic or connection-specific.
For bulk operations, we recommend batch processing with appropriate rate limiting and error handling. Makini Flows provides built-in batch processing capabilities with configurable batch sizes, delays between batches, and error handling. For API-based bulk operations, implement pagination when retrieving large datasets—our API returns results in pages with continuation tokens for fetching subsequent pages. When writing large volumes of data, break operations into smaller batches (typically 50-100 records per batch) with delays between batches to avoid overwhelming the target system. Implement comprehensive error logging to identify which specific records fail in a batch. For very large operations (thousands of records), consider asynchronous processing patterns where you queue operations and process them in the background.
Our standard SLA targets 99.9% uptime for cloud deployments, which translates to less than 9 hours of downtime per year. For enterprise customers with critical integration requirements, we offer enhanced SLAs up to 99.99% through multi-region redundancy and dedicated infrastructure. SLAs cover the Makini platform itself—availability of connected third-party systems is outside our control, though we monitor their health and alert you to issues. For self-hosted deployments, uptime depends on your infrastructure configuration, and we provide architecture guidance to help you achieve your availability targets. We maintain a public status page showing real-time system health and incident history.
Based on our market data, building industrial integrations in-house typically costs $50,000-$150,000+ per integration and takes 2-24 months depending on complexity. Maintenance requires dedicated resources—roughly one full-time person per three integrations. Makini transforms these economics: integrations go live in 1-6 weeks, costs are predictable OPEX rather than large upfront CAPEX, and maintenance is included. You gain access to 2,000+ integrations instead of building them one at a time. Our team has six years of specialization in industrial integrations, meaning we've solved problems you haven't encountered yet. For product companies, Makini allows faster time to market and frees engineering resources to focus on your core product rather than building and maintaining integration infrastructure.
