> ## Documentation Index > Fetch the complete documentation index at: https://cockroachlabs.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Topology Patterns Overview export const InternalLink = ({version, path = "", children, ...props}) => { let detectedVersion = version || "stable"; if (typeof window !== 'undefined' && !version) { const match = window.location.pathname.match(/\/docs\/([^/]+)/); if (match) { detectedVersion = match[1]; } } const normalizedPath = path.startsWith("/") ? path.slice(1) : path; return {children} ; }; This page describes recommended topology patterns for running CockroachDB in a cloud environment and the expected impacts of these patterns on latency and resiliency. You can observe latency for your cluster on the Network Latency page of the DB Console. ## Single-region When your clients are in a single geographic region, choosing a topology pattern is straightforward. | Deployment Type | Latency | Resiliency | Configuration | | ------------------------------------------------------------------------------ | --------------------------------------- | -------------------------------- | ------------------------------------------------------------------------ | | Development |

Fast reads and writes

None

1 node
No replication

| | Basic Production |

Fast reads and writes

1 zone failure

1 region
3 zones
3+ nodes across zones

| ## Multi-region When your clients are in multiple geographic regions, it is important to deploy your cluster across regions properly and then carefully choose the right: * Survival goal for each database. * Table locality for each table. Failure to consider either of these aspects can result in unexpected impacts on latency and resiliency. For more information, see the Multi-Region Capabilities Overview. The multi-region patterns described in the following table are almost always table-specific. For example, you might use Regional Tables for frequently updated tables that are tied to a specific region, and Global Tables for reference tables that are not tied to a specific region, and that are read frequently but updated infrequently. | Pattern | Latency | | ------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------------------------- | | Regional Tables | Low latency for single-region writes and multi-region stale reads. | | Global Tables | Low-latency multi-region reads from all regions, at the expense of higher latency cross-region writes. | | Follower Reads | Fast regional (historical) reads, slower cross-region writes. | | Follow-the-Workload | Fast regional reads in the active region; slower cross-region reads elsewhere. Slower cross-region writes. | In multi-region databases, the resiliency of each database depends on its survival goal settings. If you want low-latency read-only access to your data in multiple regions, Cockroach Labs recommends that you default to using stale follower reads on `REGIONAL` tables (the default locality). However, there are two reasons you might want to upgrade a table to `GLOBAL`: * You want low-latency consistent (non-stale) read access to the table in multiple regions from read-write transactions. One case where this is important is if the table is referenced by a foreign key from a `REGIONAL BY ROW` table. In these cases, the foreign key check that accompanies a write cannot use a stale read because it must be transactionally consistent with the write. To keep this foreign key check fast, you can make the reference table `GLOBAL`, at the expense of slower writes to that table. * When an ORM or application-level tool makes follower reads too hard to use. In these cases, `GLOBAL` tables can allow you to achieve low-latency reads through a schema-level setting. In summary, Cockroach Labs recommends that you use follower reads whenever you can, and use `GLOBAL` tables when you can't. In the following demo, we show the importance of choosing the correct topology patterns for your tables: