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+# Data streaming server hardware requirements
+
+This page aims to set a standard for the hardware requirements for the HRPD-X, SANDALS-II, WISH and VESUVIO instrument upgrades.
+
+The specifications listed below are for a single node, however for very high data rate instruments further benchmarking will be required.
+
+## Hardware Requirements
+
+### Network interface(s)
+
+We will require 2x 10Gigabit interfaces for each node.
+1 of these will be used for direct data transfer from detectors.
+1 of these will be used for connections to other nodes in the kafka cluster and connection to the wider ISIS network.
+
+Standard DRAC interfaces are also being assumed (meaning a total of 3 links from each node to a switch)
+
+### CPU
+
+This server will be running a Redpanda node which scales over multiple cores. It will also run a number of other processes (our software and possibly DSGs) each of which may also be multi-threaded.
+
+We tested on the ESS streaming cluster which has 8 physical cores per node. With the full stack of streaming software, although at the time these were prototypes, this was approaching performance limits of the system.
+
+SuperMuSR has experience running a cluster and streaming system on Dell Poweredge R6715s with AMD EPYC 9355Ps.
+The advantages of mirroring their machines are that we may be able to provide spares for SuperMuSR or vice versa, and they are well tested already.
+
+### RAM
+
+Redpanda requirements state that [machines must have at least 2GB of memory per core](https://docs.redpanda.com/current/deploy/redpanda/manual/production/requirements/#cpu-and-memory) - this implies at least 64GB of RAM.
+On the test cluster 32GB of RAM became a limiting factor.
+Alongside Redpanda/Kafka we need to host containers which suggests that 128GB would give reasonable overhead to do so. 
+
+### Storage
+
+Data drive should be [NVME as per the Redpanda requirements](https://docs.redpanda.com/current/deploy/redpanda/manual/production/requirements/#storage)
+
+The storage requirements are based on having at least a single run's worth of events in Kafka at a given time, as well as being able to write that file out to storage before it's moved off the machine.
+
+HRPD-X has notably lower requirements than SANDALS-II. There are two options:
+
+1. keep machines for both exact copies, which means a like-for-like can be swapped in in case of a hardware failure. This means that for HRPD-X we may be able to up retention rates of events and diagnostic data.
+2. keep machines baseline specifications the same except for storage which is tailored towards that instrument.
+
+For HRPD-X: 
+
+Worst case sustained count rate estimate is 50Mbps. There is a requirement to be able to keep 1 run's amount of events in a kafka instance along with the same amount of space for a nexus file to be written (until it is ultimately moved off this machine)
+
+We then need other space for slower streams such as sample environment and run info. 
+
+While commissioning we may also need additional space to store low-level diagnostic information such as streaming extra information from the streaming boards. 
+
+On this basis we will specify these machines with 4TB of storage along with a separate boot disk to be used for the base OS and software deployments. The latter can be 500GB-1TB. This leaves headroom for diagnostics and foreseeable future needs over the next 3-5 years. 
+
+## Notes
+
+- From dell consumer prices, we worked out that our baseline versus the SuperMuSR specifications was about 16% - with the differences being half the CPU cores and RAM.
+- The NDHes could be an option, but their chassis do not support NVME storage which is a Redpanda requirement. With a specification adjusted to allow this and a CPU upgraded to the lower bound of what is considered reasonable the SuperMuSR machines are +~60% more expensive. These were also out of stock on dell's website so may be about to be discontinued.
+- For HRPD-X, a single node will likely suffice. For SANDALS-II, it will not - performance tests showed that Repanda or Apache Kafka scale much more with multiple nodes. A single node was maxing out at ~350MB/s with kafka's built in `kafka-producer-perf-test.sh` (Exact arguments were ` ./kafka-producer-perf-test.sh --topic perf-test --record-size 1047576 --num-records 100000 --throughput -1 --print-metrics --producer-props linger.ms=50 batch.size=1048576 bootstrap.servers=localhost:9092`)