cloud.redu/mcp

THE WAY TO MAKE AN EXISTING APP HIGHLY AVAILABLE. If the user asks for high availability, redundancy, no single point of failure, surviving a host or VM failure, or 'stay up if a machine dies', this is the tool: point it at their running VM and pass high_availability:true. It needs no rebuild and no redeploy, and the URL does not change. Turns a single running instance into a horizontally-autoscaling cluster: snapshots the instance and puts your SOURCE VM behind a load balancer as its ALWAYS-ON BASELINE MEMBER, then an autoscaling group adds EXTRA members (booted from that snapshot) on CPU load and scales them back down to zero. FLAVOR — LEAD WITH A MEMORY-OPTIMIZED SMALL-DISK FLAVOR (m1.mem16/m1.mem32) for the cluster, and ideally have the SOURCE VM on one too: clustering snapshots the source VM's FULL disk, so DISK size (not RAM) drives how long the cluster takes to build and to add each member under load — a 40 GB mem flavor is several times faster to snapshot and scale than a 160 GB standard flavor (m1.xlarge) and costs less for the same RAM. If the source VM is on a big-disk flavor, RECOMMEND migrating the app onto a mem-flavor VM first (a root disk cannot be shrunk in place), even though it is extra work — it pays off on every scale-out, and a clustered app is stateless anyway (state in the managed DB) so the lean disk fits. Expect a DRASTICALLY better clustering experience on a mem flavor: far faster cluster-create, snapshots, and every scale-out. The user can override with any flavor. At rest ONLY your source VM serves — there is NO idle extra VM to pay for (the source VM is the cluster's minimum, so the floor is 0 extra members). Use it to LOAD-SCALE a stateless app tier while managed services hold state: it becomes highly-available UNDER LOAD (multiple members behind the LB), but at rest a SINGLE source VM serves — and that source VM is a plain VM, not an autoscaled member, so it is NOT auto-replaced if it fails while idle (only the autoscaled extra membe…

Turns an EXISTING, running single-machine managed Postgres or ClickHouse into a THREE-machine highly available cluster, in place, keeping the data and the same username, password and database name. Use this when the user has a live database and wants it to survive a machine or host failure: they do NOT have to create a new one and migrate by hand. How it works: a full backup is taken first (kept whatever happens), the cluster is built alongside, the data is copied in and verified by counting both sides, and only then does the database's address move to the load balancer. The original machine is left running and untouched throughout, so a failure changes nothing and the user is never without a database. SAY THREE THINGS TO THE USER AND GET A YES BEFORE CALLING: (1) COST, it becomes three machines behind a load balancer instead of one, so roughly 3x the hourly rate, and the old single machine keeps billing until they delete it; (2) WRITE LOSS, anything written to the old machine during the copy is not carried over (see acknowledge_write_loss); (3) THEY MUST REPOINT THE APP afterwards, the connection address changes and nothing redeploys their app for them. Takes about 20 minutes and returns immediately; poll list_databases / list_clickhouse_databases until the address changes. Requires a payment method: high availability is not available on the no-card trial. ⛔ CLICKHOUSE ONLY, a FOURTH thing to say: after the upgrade every table has to use a REPLICATED engine. The existing tables are converted for them as part of the copy, but any NEW `CREATE TABLE ... ENGINE = MergeTree` is refused from then on (ClickHouse error 56) and has to be written `ENGINE = ReplicatedMergeTree`. It is refused rather than accepted because a plain MergeTree on three machines replicates its schema and not its rows, which would leave two of the three answering with an empty table and no error. If their app ships plain-MergeTree migrations (Plausible, PostHog and Langfuse all do), those migration…

Asks redu to re-probe a deployment's public URL and update its status from what it actually observes. USE THIS AFTER YOU HAVE FIXED A FAILED DEPLOY - a deployment that ended 'error' or 'build_failed' but is now serving becomes 'ready' again, and you do NOT need to redeploy it to get a green status. Redeploying working infrastructure to clear a red flag wastes the user's money and throws away the fix. You cannot set the status yourself: this tool triggers a check, and the probe decides. Readiness means the URL answers with a non-5xx (401/403/404 count - they prove the app is answering), the same rule the deploy's own health gate uses. A deployment with no public URL (a headless worker) cannot be verified this way; use get_containers for its container state instead.

Checks the DNS TXT ownership record for a custom domain and marks it verified when the record is present. Call get_domain_verification first, add the TXT record at your DNS provider, then call this until status is verified.

⭐ CALL THIS INSTEAD OF POLLING. Blocks until the deployment reaches a TERMINAL state (ready, build_failed, error or vm_missing) and returns, in ONE response, everything you would otherwise fetch afterwards: the HTTP status of the PUBLIC url (not the VM's private interface, which can answer 401 while the public path still 502s), the container table with health and restarts, the host's memory/disk/load, and the .env KEY NAMES. Do NOT loop on get_deployment: that is 8-9 round trips per deploy that learn nothing, and then three more asking for what this already returned. ⚠️ A TIMEOUT IS NOT A FAILURE: if it returns timed_out:true the build is simply still running, so call again, optionally with a larger timeout_s. Only status decides success. On build_failed or error, call get_deployment(id) for the full build_log, which is the diagnosis.

Verifies your redu.cloud credential with a REAL server round-trip and returns your identity + live quota. A green result means the key actually works — not merely that one is configured. Use this first if anything is 401ing.