Process Monitor Tutorial


We’ll be looking at a process monitoring example that provides data for individual machines in a cluster, as well as aggregate metrics for the cluster. The solution will consist of two separate applications. The first is a client application that runs on each machine in the cluster to collect monitoring information. The second is a SwimOS server application that processes results for each machine via a MachineAgent, and then aggregates cluster-level metrics across all machines via a ClusterAgent.

Monitoring Client

The Monitoring Client relies on the OSHI java library to extract system information from each host machine in the cluster. OSHI is a free JNA-based (native) Operating system and Hardware Information library for Java. Each client periodically reports its operational health to the server. Since the server runs on top of the SwimOS runtime, the monitoring client uses swim.client.ClientRuntime to send commands bearing monitoring data updates.


Though we are going to keep our example concise, we’ll still include some forward-thinking design so that you can quickly extend the example. We’ve defined an abstract base class called Monitor that defines a monitor() method to initiate monitoring, along with the two methods it invokes: sleep(), which is implemented, and pulse() which will be overridden for each monitor to respond as it needs for each interval.

Since Monitor must send data to Web Agents, it maintains a WarpRef along with URI path info for host, node, and lane. Monitor also maintains an OSHI SystemInformation object to perform monitoring on the host as well as a configurable pulseInterval.


We have a single override of Monitor in our example, with ProcessMonitor, though upon perusal, you might notice it includes usage information that really belongs in a separate monitor. We’ll just look at the usage information.

  public void pulse() {
    Value usage = getUsage(timestamp);
    this.warpRef.command(hostUri, nodeUri, Uri.parse("addUsage"), usage);

  private Value getMemoryUtilization() {
    return Record.create(6)
      .slot("total", systemInfo.getHardware().getMemory().getTotal())
      .slot("available", systemInfo.getHardware().getMemory().getAvailable());

  private Value getHardwareUtilization() {
    Value memoryInfo = getMemoryUtilization();
    return Record.of().slot("memory", memoryInfo);

  private Value getUsage(final long timestamp) {
    Value hardwareInfo = getHardwareUtilization();

    return Record.of()
            .slot("timestamp", timestamp)
            .slot("hardware", hardwareInfo);


In SwimMonitorClient, we will instantiate the SwimOS client runtime, the OSHI SystemInfo, which then starts the ProcessMonitor to feed data to the server”.

  public static final String HOST = System.getProperty("host", "warp://localhost:9001");
  public static final Uri HOST_URI = Uri.parse(HOST);

  public static void main(String[] args) {
    final ClientRuntime swimClient = new ClientRuntime();
    final SystemInfo systemInfo = new SystemInfo();
    startProcessMonitor(swimClient, systemInfo);

  private static void startProcessMonitor(final ClientRuntime swimClient, final SystemInfo systemInfo) {
    final ProcessMonitor processMonitor = new ProcessMonitor(swimClient, HOST_URI, systemInfo);
    swimClient.stage().execute(() -> {
      System.out.println("Starting ProcessMonitor");

Monitoring Server

Machine Web Agent

The information collected for monitoring can be broken into three categories:

When static information is set, the MachineAgent registers with the cluster using the following command:

command(CLUSTER_URI_PATTERN.apply("default"), ADD_MACHINE_CLUSTER_LANE_URI, Uri.form().mold(nodeUri()).toValue());

Once machine agents register, the ClusterAgent can observe the direct streaming of their state changes. For instance, when addUsage() is invoked, the usage lane receives a new value, and in response to that, the status is set with the help of StatusComputer.computeStatusFromUsage().

  CommandLane<Value> addUsage = this.<Value>commandLane()
          .onCommand(v -> this.usage.set(v));

  ValueLane<Value> usage = this.<Value>valueLane()
          .didSet((newValue, oldValue) -> {
            this.status.set(StatusComputer.computeStatusFromUsage(this.status.get(), newValue));

  ValueLane<Value> status = this.<Value>valueLane()
          .didSet((newValue, oldValue) -> {
            final long timestamp = newValue.get("timestamp").longValue(0L);
            if (timestamp > 0L) {
              this.statusHistory.put(timestamp, newValue.removed("timestamp"));

Let’s look how memory usage information is computed at the machine level using StatusComputer.computeStatusFromUsage().

  public static Value computeStatusFromUsage(Value currentStatus, final Value usage) {
    final Value memory = usage.get("hardware").get("memory");
    final long available = memory.get("available").longValue(0);
    final long total = memory.get("total").longValue(0);
    final float memoryUsage = 1.0f - (total == 0L ? 0.0f : (float) available / (float) total);
    return currentStatus.updated("memory_usage", memoryUsage);

Cluster Web Agent

The ClusterAgent receives monitoring data for all machines that register to it via a corresponding MachineAgent. When a machine registers using ClusterAgent::addMachine command lane, the ClusterAgent downlinks to the MachineAgent’s status lane via its machines JoinValueLane:

  CommandLane<Value> addMachine = this.<Value>commandLane()
          .onCommand(v ->

  JoinValueLane<Value, Value> machines = this.<Value, Value>joinValueLane()
          .didUpdate((key, newValue, oldValue) -> {

            if (newValue.get("disconnected").isDefined()) {

For an explanation of downlinking, see downlinks. The machines join value lane exposes the status of individual machines with respect to system information, usage information, and process information, so that any connected client can check detail status for any machine in the cluster.

ClusterAgent also aggregates the status of all machines and reflects that in an aggregate status to reflect the health of the cluster. The status is exposed to interested clients through the status value lane, and history is stored for the last 200 values. Note that since timestamp is the key, the field is removed from the corresponding value:

  ValueLane<Value> status = this.<Value>valueLane()
          .didSet((newValue, oldValue) -> {
            final long timestamp = newValue.get("timestamp").longValue(0L);
            if (timestamp > 0L) {
              this.statusHistory.put(timestamp, newValue.removed("timestamp"));

ClusterAgent has a computeStatus() method that updates the aggregate status as machine status updates stream in. We will cherry picks portions of computeStatus() that generate the aggregate value for memory usage:

    double clusterAvgMemoryUsage = 0.0;
    double clusterAvgMemoryUsage = 0.0;

    float totalMemoryUsage = 0.0f, maxMemoryUsage = 0.0f;
    int memoryCount = 0;

    final Set<Value> keys = this.machines.keySet();
    for (Value key : keys) {
      final Value machineStatus = this.machines.get(key);

      if (machineStatus.get("memory_usage").isDefined()) {
        float memoryUsage = machineStatus.get("memory_usage").floatValue(0.0f);
        totalMemoryUsage += memoryUsage;
        if (memoryUsage > maxMemoryUsage) {
          maxMemoryUsage = memoryUsage;

    final float avgMemoryUsage = memoryCount == 0 ? 0 : totalMemoryUsage / memoryCount;

                    .updated("average_memory_usage", avgMemoryUsage)
                    .updated("max_memory_usage", maxMemoryUsage)

Rendering Status Information

Data can be rendered to an HTML page relatively simply. To illustrate that, we include an html file /ui/index.html that illustrates how this is done. Most of this is boilerplate for displaying a chart, but the application-specific bit is here:

const histogramLink = swim.downlinkMap()
    .didUpdate(function(key, value) {
      addToPlot(key, value);
    .didRemove(function(key) {

Running the Tutorial

Running the Server

$ ./gradlew run

Running a Client

$ ./gradlew -Dhost=<warp-address-of-server> runClient


$ ./gradlew -Dhost=warp://localhost:9001 runClient

Streaming APIs

Introspection APIs

Stream High level stats

swim-cli sync -h warp://localhost:9001 -n swim:meta:mesh -l pulse

Application APIs

Streaming APIs for top level Monitor

swim-cli sync -h warp://localhost:9001 -n /monitor -l machines
swim-cli sync -h warp://localhost:9001 -n /monitor -l clusters

Streaming APIs for a given Machine

swim-cli sync -h warp://localhost:9001 -n /machine/my-machine -l status
swim-cli sync -h warp://localhost:9001 -n /machine/my-machine -l statusHistory
swim-cli sync -h warp://localhost:9001 -n /machine/my-machine -l systemInfo
swim-cli sync -h warp://localhost:9001 -n /machine/my-machine -l usage
swim-cli sync -h warp://localhost:9001 -n /machine/my-machine -l processes
swim-cli sync -h warp://localhost:9001 -n /machine/my-machine -l sessions

Streaming APIs for a Cluster

swim-cli sync -h warp://localhost:9001 -n /cluster/abc -l machines
swim-cli sync -h warp://localhost:9001 -n /cluster/abc -l status
swim-cli sync -h warp://localhost:9001 -n /cluster/abc -l statusHistory

Running the UI

Now, you can view the UI by appending “/ui” to the host address using the HTTP or HTTPS protocol, such as http://localhost:9001/ui.