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Rca Integration test framework

Scope

To be able to test scenarios where multiple RCA Schedulers are running on different hosts of a cluster and be able to inject a custom RCA graph, specify the metrics that should flow through the rca-dataflow-graph and then be able to test the results of the RCAs and decisions based on the RCAs by either querying the rca.sqlite files on a particular host or by hitting the REST endpoint on a particular host.

Out of Scope

This framework will not facilitate testing the PerformanceAnalyzer Reader component, writer component and how PerformanceAnalyzer interacts with ElasticSearch.

How to write your own tests using this framework ?

The RCA-IT is composed of various annotatons that you can use to configure the test environment you want your tests to run on.

Annotation Required Level Parameters Repeatable Description
RunWith Yes Class Runner class No This is to suggest the junit that something other than the default runner must be used
Category Yes Class RcaItMarker.class No This is to categorize all the RCA-IT tests so that all integration tests can be run by using the gradle target rcaIt
AClusterType Yes Class value No The cluster type that would be used to run this integration test. Types supported can be found in enum ClusterType
ARcaGraph Yes Class or Method value No The RCA graph that will be executed by the RCA scheduler.
AMetric Yes Class or Method name, dimensionNames, tables Yes The metrics that will flow through the edges of the RCA graph. This is probably the most complicated annotation and is better understood with an example. Please checkout class RcaItPocDedicated.
Expect No Method what, on, timeoutSeconds, validator, forRca Yes If you want the framework to test for an expected condition at steady state to pass or fail a test.
AErrorPatternIgnored No Method pattern, reason Yes If you want the checking framework to bypass certain pattern in error logs.

@RunWith(RcaItNotEncryptedRunner.class)

The above specifies the runner for the junit test class and in this case, it says to junit to offload it to one of the RCA-IT runners - RcaItNotEncryptedRunner. All RCA-IT tests must use this annotation for them to be run by this integ test framework.

@Category(RcaItMarker.class)

All test classes must also be marked with this masker interface.

@AClusterType(ClusterType.MULTI_NODE_CO_LOCATED_MASTER)

This annotation tells the RCA-IT to use a multi-node cluster with no dedicated master nodes . The kinds of clusters supported today are: SINGLE_NODE, MULTI_NODE_CO_LOCATED_MASTER and MULTI_NODE_DEDICATED_MASTER. This is a required annotation and must be specified at the class level.

@ARcaGraph(MyRcaGraph.class)

This helps us specify the Graph that we will be using for this test. It can be a graph that exists or the one specially contrived for this test.

@AMetric This helps us specify the metrics that will be pured over the RCA graph. It has multiple sub-fields.

Let's see an example:

@AMetric(name = CPU_Utilization.class,
    dimensionNames = {SHARDID_VALUE, INDEX_NAME_VALUE, OPERATION_VALUE, SHARD_ROLE_VALUE},
    tables = {
        @ATable(hostTag = HostTag.DATA_0,
            tuple = {
                @ATuple(dimensionValues = {"0", "logs", "bulk", "p"},
                    sum = 0.0, avg = 0.0, min = 0.0, max = 0.0),
                @ATuple(dimensionValues = {"1", "logs", "bulk", "r"},
                    sum = 0.0, avg = 0.0, min = 0.0, max = 80.0),
                @ATuple(dimensionValues = {"2", "logs", "bulk", "p"},
                    sum = 0.0, avg = 0.0, min = 0.0, max = 10.0)
            }
        ),
        @ATable(hostTag = HostTag.DATA_1,
            tuple = {
                @ATuple(dimensionValues = {"0", "logs", "bulk", "r"},
                    sum = 0.0, avg = 0.0, min = 0.0, max = 50.0),
                @ATuple(dimensionValues = {"1", "logs", "bulk", "p"},
                    sum = 0.0, avg = 0.0, min = 0.0, max = 5.0),
                @ATuple(dimensionValues = {"2", "logs", "bulk", "r"},
                    sum = 0.0, avg = 0.0, min = 0.0, max = 11.0)
            }
        )
    }
)
  • name : The Metric graph node that will be emitting these values. The expected parameter is one of the metrics classes in com.amazon.opendistro.elasticsearch.performanceanalyzer.rca.framework.api.metrics. The metrics class that you specify, should have a static final field called NAME (CPU_Utilization) and that will be used to determine the name of the metric table.
  • dimensionNames : For the dimension names for a metric, please refer to the docs here. Each of the dimension will be a column in the rca.sqlite table.
  • tables : This specifies one or more table(s). The table should be a 5 second snapshot of the metrics, similar to what exists in metricsdb files. The table is an array type , therfore it gives you the flexibility of specifying a different metrics table for each node or a group of nodes in the cluster. In the above example, the table one is to be emitted by DATA_0 and table 2 by DATA_1. This can be used to push different metrics to the node that we want to be marked unhealthy vs all other nodes in the cluster.
    • hostTag : On which cluster node should emit this metric.
    • tuple : This is an array type that can be used to specify the rows in the table. A row should be an (n+4)-tuple where n is a value per dimension of this metric and 4 represents the four aggregate columns - min, max, sum and avg.

@Expect

This is an optional annotation that can be used only at a method level. This provides an easy way to validate the result of the test. The annotation has 4 sub-fields:

  • what : What are we testing for - data in rca.sqlite file or the response returned by the rest API.
  • on : On which node should the framework look for, for the expected data.
  • forRca : Which particular RCA's value are we testing.
  • validator : This is the class that should be defined by the test writer and should implement IValidator interface. Once the framework gathers the data for the mentioned RCA from the given node, the data will be passed to the validator which returns if the check passed or not.

The Expect annotation is a repeatable type. Therefore, you can expect multiple things from the test at steady-state. So you can have two expectations one for the RCA on data node and the other on the master. If the expectations are not true for the ith iteration, then the framework, will re-run them for the i+1 the iteration till a timeout. The timeout is configurable to any number of seconds using the field timeoutSeconds but has the default of 60 seconds.

@AErrorPatternIgnored The RCA-IT will fail a test if any error is logged. If you think that some of the errors logged during your test is okay, then you can use this annotation to explicitly ignore them. The annotation takes two parameters - pattern the pattern to ignore and reason stating why it would be okay to ignore such an error. The reason is most for the reader of the test.

A test class can get access to the programmaticAPI to get information about hosts in the cluster or a particular host then the test class can declare a method with name setTestApi(final TestApi api) and the test runner will call this setter to give a reference of the TestApi to the testClass.

Cluster Types

The integration test framework let's us create three kinds of clusters as mentioned above. But you need to know the hostTags to pick a host that would publish certain metrics or its the hostTag by which you identify a host to make a REST request to. This section tells you what are the different hostTags available for different cluster types.

Dedicated Master Cluster

This cluster type is composed of three master nodes and 2 data nodes.

Host Ids Host Tags
0 HostTag.ELECTED_MASTER
1 HostTag.STANDBY_MASTER_0
2 HostTag.STANDBY_MASTER_1
3 HostTag.DATA_0
4 HostTag.DATA_1

__ Co-located Master Cluster __ A co-located master cluster is one where all the data-nodes are master eligible. In the test framework, this is composed of two nodes.

Host IDs Host Tags
0 HostTag.ELECTED_MASTER
1 HostTag.DATA_0

__ Single Node Cluster__ There is just one node in a single node cluster which is tagged as HostTag.DATA_0.

Host IDs Host Tags
0 HostTag.DATA_0

Examples

Some of the examples for how to write the integ tests can be found here: src/test/java/com/amazon/opendistro/elasticsearch/performanceanalyzer/rca/integTests/tests/poc/*

Running the integ tests

  1. All integration tests written using this framework can be run by using the command ./gradlew rcaIt

  2. If you want to all the tests in an integ test class, you can do something like this: ./gradlew test --tests RcaItPocDedicated

  3. If you want to run a particular test method in your test class, you can use something like this: ./gradlew test --tests RcaItPocDedicated.simple

Framework deep dive.

This section might be of interest to you if you are trying to enhance the test framework itself . If you just want to add more integration tests, then you may choose to skip this section.

The framework consists of four main classes:

  1. RcaItRunnerBase : This is the JUnit Runner that will be used to run all rca-it tests. It orchestrates the environment creation, initializing the test class and then executing the methods annotated with @Test.

  2. TestEnvironment : The RCA-IT environment is defined by the RCA graph it will be running, the metrics that will flow through the dataflow pipelines and the rca.conf that will be used by the hosts.

  3. Cluster and Host classes: These class initializes multiple RCAController(s) threads, each of them represent RCAFramework running on multiple nodes. In constructors, we create all the objects and create a directory per host where they will dump the rca.sqlite and rca_enabled files. In the second phase a call to createServersAndThreads is made which creates all the http and grpc servers (one per host). Then we start the RCAcontroller thread.