CLOUDPREM: Update sizing recommendations

Author: guilload

content/en/cloudprem/configure/cluster_sizing.md

@@ -26,33 +26,30 @@ These are starting recommendations. Monitor your cluster's performance and resou
 
 ## Indexers
 
-- **Performance:** To index 5 MB/s of logs, CloudPrem needs approximately 1 vCPU and 2 GB of RAM.
-- **Recommended Pod Sizes:** Datadog recommends that you deploy indexer pods with either:
-  - 2 vCPUs and 4 GB of RAM
-  - 4 vCPUs and 8 GB of RAM
-  - 8 vCPUs and 16 GB of RAM
-- **Storage:** Indexers require persistent storage (preferably SSDs, but local HDDs or remote EBS volumes can also be used) to store temporary data while constructing the index files.
-  - Minimum: 100 GB per pod
-  - Recommendation (for pods > 4 vCPUs): 200 GB per pod
-- **Example Calculation:** To index 1 TB per day (~11.6 MB/s):
-  - Required vCPUs: `(11.6 MB/s / 5 MB/s/vCPU) ≈ 2.3 vCPUs`
-  - Rounding up, you might start with one indexer pod configured with 3 vCPUs and 6 GB RAM, requiring a 100 GB EBS volume. (Adjust this configuration based on observed performance and redundancy needs.)
+- **Performance:** Indexing performance depends heavily on the characteristics of the ingest logs, such as their size, number of attributes, and level of nesting. However, we recommend using a baseline indexing throughput of **5 MB/s per vCPU** to determine your initial sizing.
+- **Memory:** We recommend 4 GB of RAM per vCPU.
+- **Recommended Pod Sizes:** Datadog recommends deploying indexer pods with at least 2 vCPUs and 8 GB of RAM.
+- **Storage:** Indexers require at least 200 GB of persistent storage (preferably local SSDs, but local HDDs or network-attached block storage volumes such as Amazon EBS, or Azure Managed Disks can also be used) to store temporary data while creating and merging index files. In addition, each indexer vCPU writes on disk at a rate of approximately 20 MB/s. For Amazon EBS volumes, this is equivalent to 320 IOPS per vCPU (assuming 64 KB IOPS).
+- **Example Calculation:** To index 1 TB of logs per day (~11.6 MB/s):
+  - Required vCPUs: `11.6 MB/s / 5 MB/s per vCPU ≈ 2.3 vCPUs`
+  - Required RAM: `2.3 vCPUs × 4 GB RAM ≈ 9 GB RAM`
+  - Adding some headroom, you could start with one indexer pod configured with 3 vCPUs, 12 GB RAM, and a 200 GB disk. Adjust these values based on observed performance and redundancy needs.
 
 ## Searchers
 
-- **Performance:** Search performance depends heavily on the workload (query complexity, concurrency, data scanned).
+- **Performance:** Search performance depends heavily on the workload (query complexity, concurrency, data scanned). For instance, term queries (`status:error AND message:exception`) are usually computationally less expensive than aggregations.
 - **Rule of Thumb:** A general starting point is to provision roughly double the total number of vCPUs allocated to Indexers.
 - **Memory:** We recommend 4 GB of RAM per searcher vCPU. Provision more RAM if you expect many concurrent aggregation requests.
 
 ## Other services
 
-The following components are typically lightweight:
+We recommend allocating the following resources for these lightweight components:
 
-- **Control Plane:** 1 vCPU, 2 GB RAM
-- **Metastore:** 1 vCPU, 2 GB RAM
-- **Janitor:** 1 vCPU, 2 GB RAM
+- **Control Plane:** 2 vCPUs, 4 GB RAM, 1 replica
+- **Metastore:** 2 vCPUs, 4 GB RAM, 2 replicas
+- **Janitor:** 2 vCPUs, 4 GB RAM, 1 replica
 
-## Postgres Metastore backend
+## PostgreSQL Database
 
 - **Instance Size:** For most use cases, a PostgreSQL instance with 1 vCPU and 4 GB of RAM is sufficient
 - **AWS RDS Recommendation:** If using AWS RDS, the `t4g.medium` instance type is a suitable starting point