ExplorViz Landscape-Service

Scalable service that processes and provides structural data of monitored applications. Applications are grouped in an encompassing software landscape (abbr. landscape). This landscape can contain one or multiple monitored applications, depending on the initial instrumentation settings for the monitored application.

Features

The service serves two purposes

1. it persists structural data of monitored applications.
2. assembles and delivers the composition of the software hierarchy of the requested landscape to clients.

Processing Structural Information

The service consumes SpanStructure records from a Kafka topic. These records consist of the parts of spans that contain information that are related to structural/topological information of monitored applications:

• Host name and address
• Application name and language
• Identification of specific instances of the same application
• Package structures
• Classes and methods

In contrast to dynamical information, structural information describe relationships between structural entities. Each incoming SpanStructure is transformed into an internal data structure (LandscapeRecord) and persisted into a Cassandra database.

Providing Landscape Graphs

The representation of the structure of a monitored landscape is delivered to the user as a directed graph, the landscape graph. This graph embodies the composition of structural entities (hosts, applicatoins, packages, ...) within the landscape, as observed by the monitoring stack. Upon client requests, the service gathers all relevant records from the database and assembles this graph. It is then delivered to the requesting client in json format.

For example, the following JSON and image depict the landscape graph for our custom-example-application.

Fibonacci Landscape JSON

{
  "landscapeToken" : "fibonacci-landscape",
  "nodes" : [ {
    "ipAddress" : "192.168.178.1",
    "hostName" : "host",
    "applications" : [ {
      "name" : "fibonacci",
      "language" : "java",
      "instanceId" : "1",
      "packages" : [ {
        "name" : "net",
        "subPackages" : [ {
          "name" : "explorviz",
          "subPackages" : [ {
            "name" : "sampleApplication",
            "subPackages" : [ {
              "name" : "application",
              "subPackages" : [ {
                "name" : "math",
                "subPackages" : [ ],
                "classes" : [ {
                  "name" : "Fibonacci",
                  "methods" : [ {
                    "name" : "calculate",
                    "hashCode" : "0b064d846e37337db07991f806a36f4fcacab5517d2801918ba6ba65284c9888"
                  } ]
                } ]
              } ],
              "classes" : [ {
                "name" : "JavaExample",
                "methods" : [ {
                  "name" : "start",
                  "hashCode" : "05dc4a2405adf51e81214c7a8a237ad68bd329939296729619b3c50eb878c114"
                } ]
              } ]
            }, {
              "name" : "database",
              "subPackages" : [ {
                "name" : "helper",
                "subPackages" : [ ],
                "classes" : [ {
                  "name" : "SQLStatementHandler",
                  "methods" : [ {
                    "name" : "executeStatementHandler",
                    "hashCode" : "4a16407ec3a7f718dcbf29804d0f3e77307760bea7b559c0d29a2a34146e0841"
                  } ]
                }, {
                  "name" : "SQLConnectionHandler",
                  "methods" : [ {
                    "name" : "createDatabase",
                    "hashCode" : "add6b7c9487e285cb08bd11208dec851f1e73b6e4a337835b333f29a9b59c407"
                  }, {
                    "name" : "disconnect",
                    "hashCode" : "ce8f8b85e0fb0629658df0418c050521ee7ea66ee3552b1dd7d0860f90fe8117"
                  }, {
                    "name" : "connect",
                    "hashCode" : "f6576f4c545ee315e49c65605dcc851f96bf49e80845ce0ce3c958b45a87557e"
                  } ]
                } ]
              } ],
              "classes" : [ {
                "name" : "JDBCExample",
                "methods" : [ {
                  "name" : "start",
                  "hashCode" : "70bb60fab08e07532ce6e79de333541bc498a7f448c99d934685603d2f06ed8b"
                }, {
                  "name" : "runQueries",
                  "hashCode" : "c5fc10c742e58f3e344816a079e65b2c2c49b28a36659a7a0c20070a66210656"
                } ]
              } ]
            }, {
              "name" : "util",
              "subPackages" : [ ],
              "classes" : [ {
                "name" : "RandomNumberGenerator",
                "methods" : [ {
                  "name" : "getRandomNumber",
                  "hashCode" : "c66b6f4c8acbfa4a65837d721344387bcb7ad2ffa2f733ff44370abccb599c66"
                } ]
              } ]
            } ],
            "classes" : [ {
              "name" : "Main$DatabaseTask",
              "methods" : [ {
                "name" : "run",
                "hashCode" : "4b4c314927bd5061592c8c5a6a194a054216f8fa4e0324f5304ea1179bae2776"
              } ]
            }, {
              "name" : "Main$ApplicationTask",
              "methods" : [ {
                "name" : "run",
                "hashCode" : "97aca15b161345d9f5de793fbde8192a8b16b47138e9dc18d3b76a8b3c7b13d7"
              } ]
            } ]
          } ],
          "classes" : [ ]
        } ],
        "classes" : [ ]
      } ]
    } ]
  } ]
}

It corresponds to the following directed graph.

The general structure of landscape graphs is defined as follows:

The landscape token, which uniquely identifies a landscape, is the root of the tree. On requests, the user has to specify at least the token to retrieve the corresponding graph. On the topmost level, the landscape consists of one to many hosts, each of which running multiple applications. Applications contain their respective package structure and classes. The leaves of the graph correspond to methods. Each leaf contains a fingerprint, that uniquely identifies it. These fingerprints are needed to map traces, which are retrieved separately, onto the corresponding methods unambiguously.

See the avro schema for further details.

Prerequisites

• Java 11 or higher
• Make sure to run the ExplorViz software stack before starting the service, as it provides the required database(s) and the Kafka broker

Running the application in dev mode

You can run your application in dev mode that enables live coding using:

./gradlew quarkusDev

This also enables the dev configuration profile, i.e. using the properties prefixed with %dev from src/main/resources/application.properties.

Packaging and running the application

The application can be packaged and tested using:

./gradlew build

It produces the quarkus-run.jar file in the build/quarkus-app/ directory.

You can skip running the integration tests by adding -x integrationTest. To skip all tests and code analysis use the assemble task instead of build.

The application is now runnable using java -jar build/quarkus-app/quarkus-run.jar. Be aware that it’s not an über-jar as the dependencies are copied into the build/quarkus-app/lib/ directory.

If you want to build an über-jar, which includes the entire application in a single jar file, execute the following command:

./gradlew build -Dquarkus.package.type=uber-jar

The application, packaged as an über-jar, is now runnable using java -jar build/landscape-service-1.0-SNAPSHOT-runner.jar. You can add -Dquarkus.profile=dev to enable the %dev properties.

Creating a native executable

You can create a native executable using:

./gradlew build -Dquarkus.package.type=native

Or, if you don't have GraalVM installed, you can run the native executable build in a container using:

./gradlew build -Dquarkus.package.type=native -Dquarkus.native.container-build=true

You can then execute your native executable with: ./build/landscape-service-1.0-SNAPSHOT-runner

If you want to learn more about building native executables, please consult https://quarkus.io/guides/gradle-tooling#building-a-native-executable.