Introduction

Use the Corda Enterprise performance test suite to stress/soak test a Corda installation, driving either a single node or a small network of nodes including a notary. It uses Apache JMeter to start flows on nodes via RPC calls, and capture the start/return rates and thus throughput of the system under test.

A typical test architecture consists of the following components:

  • A Corda network to be tested. This should be a network of Corda nodes along with a notary that is self-contained (in other words, does not depend on any external services). See the documentation on Corda Networks for information on setting up a network.
  • A CorDapp that is to be tested and needs to be installed on the cluster.
  • An app to drive the test - Apache JMeter is used here.

Apache JMeter runs tests that repeatedly trigger an action, wait for a response and record start/success/failure timings and so on, and allow to view the result data interactively or rendered as reports in various formats. Run controls like parallelising tasks, running tasks in a specific order and count and time based repetitions are already built in.

The interactions with the system under test are done via so called samplers (see JMeter Samplers) that can be triggered by JMeter and then run an action. JMeter has a number of built-in samplers, mostly around web technology, for example - for HTTP requests, database queries, starting scripts and so on. It is also possible to provide custom samplers that can run Java code when invoked.

For the Corda performance tests, a custom sampler is used that invokes one or more specific flows via remote procedure calls (RPC), where all the required parameters for the flow and RPC call are passed to the sampler as parameters from the test definition.

By default, JMeter runs in interactive mode - in other words, it brings up a graphical user interface (GUI) that allows the user to create, view, modify and run a test definition. Tests can either be in process (i.e. the sampler runs in the GUI process) or can be fanned out to a set of JMeter server instances that will run under the control of a JMeter client connected to them (see Server Mode).

Once a test definition is complete, it can be run in headless mode by providing the test definition and a report target directory on the command line.

By adding the -s flag, JMeter can run as a server process that runs samplers controlled by a client connected to it via Java Remote Method Invocation (RMI). This allows a single client to e.g. run load from various servers for one test run and collate all the results in the client.

Apache JMeter can be fairly tricky to run in a specific configuration - therefore the Corda Enterprise performance test suite provides a wrapper around JMeter that comes in a fat JAR with all required dependencies and a default configuration, and sets up the required directories and config files that JMeter needs to start. It is also bundled with a set of default Corda performance test samplers. On top of that, it supports opening SSH tunnels to machines running remote JMeter server instances.

The performance test suite contains two CorDapps that can be used for performance testing:

  • A performance test CorDapp called perftest-cordapp.jar, which is roughly modelled on the finance CorDapp shipped with Corda Enterprise. It contains a number of flows that issue tokens and pay these to other parties. For example, there are flows that issue and pay tokens with or without using coin selection, or others that create arbitrary numbers of change output or coin input states to test the behaviour of the system when using various transaction sizes and shapes.
  • A performance test CorDapp called settlement-perftest-cordapp, which models a digital asset exchange, where assets can be issued to nodes, transferred bilaterally between them, and exchanged in batch via atomic swap transactions. This CorDapp can be used to exercise scenarios of flows running across multiple nodes.

The typical set-up used for performance tests at R3 consists of a small Corda network of 2 to 4 nodes and a notary to notarise transactions. These all run inside a datacenter or virtual network in the cloud with open connectivity (or at least Corda P2P and RPC communication enabled between the nodes). On each of the node machines, an instance of JMeter is running in server mode.

The driving app sits outside the network and connects to the JMeter servers through SSH tunnels. In the basic test measuring the throughput of a node, the test definition instructs all JMeter servers to open RPC connections to one node, thus saturating the RPC handler and driving the node as hard as possible. The test might invoke a flow that can be completed locally (for example, cash issuance) or it might require exchanging P2P messages with other nodes (for example, cash payment).

jmeter network overview

There are a number of different parts of the system that can be benchmarked with different performance tests, represented by different test plans and/or samplers. In general, the closer a performance test is to real world load, the less it is possible to isolate pinch points in the system under test. Hence a typical performance test run consists a of a number of these tests that allow seeing where a performance drop off occurs.

If the reasons for a performance bottleneck cannot be figured out using a set of performance tests, it might be necessary to attach a remote profile app to one of the nodes and profile a manual performance run using any of the suite of existing JVM profiling tools available on the market.

The performance test suite contains test plans, CorDapp and sampler for the following tests:

These tests stress components in a single node, without any dependencies on other nodes in the flow.

The EmptyFlow test is part of the perftest-cordapp CorDapp. As its name suggests, this flow is empty and does not have any effect of its own - its purpose is to provide a timing for the overhead involved in starting a flow, such as RPC handling, deserialization of the request, starting/winding down a flow, and sending the response. Note that a flow that requires inputs via RPC might have a larger overhead as these might need to be deserialized.

The CashIssueFlow test is part of the perftest-cordapp CorDapp. It issues cash to the same node where the flow is invoked. In addition, it loads/starts the CorDapp, creates states in the vault, and thus uses persistence to the database.

These are flows that are, to varying degrees, closer to modelling real-world loads.

This is a set of flows (CashIssueAndPaymentFlow and CashIssueAndPaymentNoSelection) that are part of the perftest-cordapp CorDapp. They make the node under test issue some cash to itself, and then pay it to a second node. This involves initiating a transaction with the target node, and then having the transaction notarised by a network notary, thus creating a load that is similar to what a node would do under real-world conditions. These flows have a few variations that can be controlled through the test definition:

  • Use of coin selection: The flows can either just pay the issued cash, or use coin selection to select the cash to pay. This is used to isolate coin selection issues from general transaction performance.
  • Anonymous identities: The flows can turn anonymous identities on. This means that a new private/public key pair will be generated for each transaction, allowing you to measure the resulting overhead.

To test the throughput a single node can achieve, this flow is run against a single node from all JMeter servers. In order to measure network throughput, it can also be run against all nodes from their respective JMeter server.

The CashIssueFlow, CashIssueAndPaymentFlow, and CashIssueAndPaymentNoSelection flows create a somewhat realistic load but still have a very uniform, artificial usage pattern of resources. Therefore, more advanced test flows/test plans have been developed that allow to issue a large amount of cash once and then start to break it up in smaller payments, allowing the following settings to be tweaked:

  • Number of states to be transferred in one transaction.
  • Number of change states created per transaction (that is, the number of output states of the transaction).
  • Number of input states to a new transaction (that is, pay a larger sums from change shards of the previous transaction).

Advanced tests also include testing - for example, connecting to the target node via float/firewall.

This is a set of flows (SwapStockForCashFlow and SwapSpecificStockForCashFlow) that are part of the settlement-perftest-cordapp CorDapp. These flows can be used to swap assets between multiple nodes in a single atomic transaction. They can be used to exercise the performance of scenarios, where a node has to communicate with many other nodes in order to complete a transaction.

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