scx/rust/scx_stats
2024-08-21 06:42:11 -10:00
..
examples scx_stats: Make server shutdown when connection is dropped and add communication channel 2024-08-19 06:23:16 -10:00
scripts scx_stats/scripts/scxstats_to_openmetrics: Retry connection 2024-08-19 12:52:57 -10:00
scx_stats_derive Version: v1.0.3 2024-08-21 06:42:11 -10:00
src scx_stats: server: open_ops must be kept throughout a client session 2024-08-19 08:38:13 -10:00
.gitignore scx_stats: Add .gitignore 2024-08-15 12:31:04 -10:00
Cargo.toml Version: v1.0.3 2024-08-21 06:42:11 -10:00
LICENSE scx_stats: Add package metadata 2024-08-15 11:09:26 -10:00
meson.build scx_stats: s/scx_stat/scx_stats/ 2024-08-15 05:31:34 -10:00
README.md scx_stats: Make server shutdown when connection is dropped and add communication channel 2024-08-19 06:23:16 -10:00

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.

  • Vecs and BTreeMaps containing the above.

The following is taken from examples/stats_defs.rs.h:

#[derive(Clone, Debug, Serialize, Deserialize, Stats)]
#[stat(desc = "domain statistics", _om_prefix="d_", _om_label="domain_name")]
struct DomainStats {
    pub name: String,
    #[stat(desc = "an event counter")]
    pub events: u64,
    #[stat(desc = "a gauge number")]
    pub pressure: f64,
}

#[derive(Clone, Debug, Serialize, Deserialize, Stats)]
#[stat(desc = "cluster statistics", top)]
struct ClusterStats {
    pub name: String,
    #[stat(desc = "update timestamp")]
    pub at: u64,
    #[stat(desc = "some bitmap we want to report", _om_skip)]
    pub bitmap: Vec<u32>,
    #[stat(desc = "domain statistics")]
    pub doms_dict: BTreeMap<usize, DomainStats>,
}

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 = ScxStatsServer::new()
        .set_path(&path)
        .add_stats_meta(ClusterStats::meta())
        .add_stats_meta(DomainStats::meta())
        .add_stats("top", Box::new(move |_| stats.to_json()))
        .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 = ScxStatsClient::new().set_path(path).connect().unwrap();

The above creates a client instance. Let's query the statistics:

    let resp = client.request::<ClusterStats>("stat", vec![]);
    println!("{:#?}", &resp);

The above is equivalent to querying the top target:

    println!("\n===== Requesting \"stat\" with \"target\"=\"top\":");
    let resp = client.request::<ClusterStats>("stat", vec![("target".into(), "top".into())]);
    println!("{:#?}", &resp);

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!("\n===== Requesting \"stats_meta\" but receiving with serde_json::Value:");
    let resp = client.request::<serde_json::Value>("stats_meta", vec![]).unwrap();
    println!("{}", serde_json::to_string_pretty(&resp).unwrap());

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"),
    },