Statistics transport library for sched_ext schedulers
sched_ext is a Linux kernel feature which enables implementing kernel thread schedulers in BPF and dynamically loading them.
This library provides an easy way to define statistics and access them through a UNIX domain socket. While this library is developed for SCX schedulers, it can be used elsewhere as the only baked-in assumption is the default UNIX domain socket path which can be overridden.
Statistics are defined as structs. A statistics struct can contain the following fields:
-
Numbers - i32, u32, i64, u64, f64.
-
Strings.
-
Structs containing allowed fields.
-
Vec
s andBTreeMap
s containing the above.
The following is taken from examples/stats_defs.rs.h
:
scx_stats_derive::Stats
is the derive macro which generates everything
necessary including the statistics metadata. The stat
struct and field
attribute allows adding annotations. The following attributes are currently
defined:
struct and field attributes
- desc: Description.
struct-only attributes
- top: Marks the top-level statistics struct which is reported by default. Used by generic tools to find the starting point when processing the metadata.
In addition, arbitrary user attributes which start with "_" can be added to both structs and fields. They are collected into the "user" dict of the containing struct or field. When the value of such user attribute is not specified, the string "true" is assigned by default. For example, scripts/scxstats_to_openmetrics.py recognizes the following user attribute:
-
_om_prefix
: The value is prefixed to the field name to form the unique OpenMetrics metric name. -
_om_label
: Labels are used to distinguish different members of a dict. This field attribute specifies the name of the label for a dict field. -
_om_skip
: Not all fields might make sense to translate to OpenMetrics. This valueless field attribute marks the field to be skipped.
examples/stats_defs.rs.h
shows how the above
attributes can be used. See
scx_layered
for practical usage.
Note that scx_stats depends on serde
and
serde_json
and each statistics
struct must derive Serialize
and Deserialize
.
The statistics server which serves the above structs through a UNIX domain socket can be launched as follows:
let _server = new
.set_path
.add_stats_meta
.add_stats_meta
.add_stats
.launch
.unwrap;
The scx_stats::Meta::meta()
trait function is automatically implemented by
the scx_stats::Meta
derive macro for each statistics struct. Adding them
to the statistics server allows implementing generic clients which don't
have the definitions of the statistics structs - e.g. to relay the
statistics to another framework such as OpenMetrics.
top
is the default statistics reported when no specific target is
specified and should always be added to the server. The closure should
return serde_json::Value
. Note that scx_stats::ToJson
automatically adds
.to_json()
to structs which implement both scx_stats::Meta
and
serde::Serialize
.
The above will launch the statistics server listening on @path
. Note that
the server will shutdown when _server
variable is dropped. The client side
is also simple. Taken from examples/client.rs
:
let mut client = new.set_path.connect.unwrap;
The above creates a client instance. Let's query the statistics:
let resp = client.;
println!;
The above is equivalent to querying the top
target:
println!;
let resp = client.;
println!;
If ("args", BTreeMap<String, String>)
is passed in as a part of the
@args
vector, the BTreeMap
will be passed as an argument to the handling
closure on the server side.
When implementing a generic client which does not have access to the statistics struct definitions, the metadata can come handy:
println!;
let resp = client..unwrap;
println!;
For this example, the output would look like the following:
{
"ClusterStats": {
"desc": "cluster statistics",
"fields": {
"at": {
"datum": "u64",
"desc": "update timestamp"
},
"bitmap": {
"array": "u64",
"desc": "some bitmap we want to report",
"user": {
"_om_skip": "true"
}
},
"doms_dict": {
"desc": "domain statistics",
"dict": {
"datum": {
"struct": "DomainStats"
},
"key": "u64"
}
},
"name": {
"datum": "string"
}
},
"name": "ClusterStats",
"top": "true"
},
"DomainStats": {
"desc": "domain statistics",
"fields": {
"events": {
"datum": "u64",
"desc": "an event counter"
},
"name": {
"datum": "string"
},
"pressure": {
"datum": "float",
"desc": "a gauge number"
}
},
"name": "DomainStats",
"user": {
"_om_label": "domain_name",
"_om_prefix": "d_"
}
}
}
The protocol used for communication on the UNIX domain socket is line based
with each line containing a json and straightforward. Run examples/client
with RUST_LOG=trace
set to see what get sent on the wire:
> cargo run --example server -- ~/tmp/socket
Finished `dev` profile [unoptimized + debuginfo] target(s) in 0.02s
Running `target/debug/examples/server /home/htejun/tmp/socket`
Server listening. Run `client "/home/htejun/tmp/socket"`.
Use `socat - UNIX-CONNECT:"/home/htejun/tmp/socket"` for raw connection.
Press any key to exit.
$ RUST_LOG=trace cargo run --example client -- ~/tmp/socket
...
===== Requesting "stats" but receiving with serde_json::Value:
2024-08-15T22:13:23.769Z TRACE [scx_stats::client] Sending: {"req":"stats","args":{"target":"top"}}
2024-08-15T22:13:23.769Z TRACE [scx_stats::client] Received: {"errno":0,"args":{"resp":{"at":12345,"bitmap":[3735928559,3203391149],"doms_dict":{"0":{"events":1234,"name":"domain 0","pressure":1.234},"3":{"events":5678,"name":"domain 3","pressure":5.678}},"name":"test cluster"}}}
Ok(
Object {
"at": Number(12345),
"bitmap": Array [
Number(3735928559),
Number(3203391149),
],
"doms_dict": Object {
"0": Object {
"events": Number(1234),
"name": String("domain 0"),
"pressure": Number(1.234),
},
"3": Object {
"events": Number(5678),
"name": String("domain 3"),
"pressure": Number(5.678),
},
},
"name": String("test cluster"),
},