Codenet Minerva Cargo

Cargo is part of the Minerva project working on refactoring monoliths to microservices. It leverages Data Gravity Insights from the Konveyor.io project and provides recommendations for partitioning code taking into account code relationships, data relationships, and database transaction scope.

CARGO: AI-Guided Dependency Analysis for Migrating Monolithic Applications to Microservices Architecture

Paper: ArXiV Preprint

Abstract

CARGO (short for Context-sensitive lAbel pRopaGatiOn) is a novel un-/semi-supervised partition refinement technique that uses a comprehensive system dependence graph built using context and flow-sensitive static analysis of a monolithic application to refine and thereby enrich the partitioning quality of the current state-of-the-art algorithms.

Figure 1. Overview of CARGO

Kick-the-tires Instructions (~15 minutes)

The instructions will reproduce the key results in Figure 6 (RQ1), Figure 7 (RQ2), and Table 1 (RQ3).

Pre-requisites

A Linux/Mac system with Docker.
Python >= 3.8, and Pip. Tested with Python 3.9.

Step 1: Set up Data Gravity Insights CLI

We will use Data Gravity Insights (aka. DGI) to first build a system dependency graph and persist the graph in a Neo4j.

1.1 Install DGI

Clone this repository and install dgi using pip.

git clone https://github.com/vikramnitin9/tackle-data-gravity-insights/

Note: Henceforth, unless specified otherwise, all commands are to be executed from within this folder (we'll refer to it as $REPO_ROOT.

We'll save this repository location for future reference.

cd tackle-data-gravity-insights
export REPO_ROOT=$(pwd)

Before proceeding, you may need to install geos with sudo apt install libgeos-dev or brew install geos.

To install dgi globally:

sudo pip install --editable .

You can also install dgi locally, for that you can drop sudo

pip install --editable .

This will install the dgi command locally under your home folder in a hidden folder called: ~/.local/bin. If you choose this approach, you must add this folder to your PATH with:

export PATH=$HOME/.local/bin:$PATH

1.2 Creating a Neo4j Docker container

Make sure that your Docker daemon is running, either by starting up the service (on linux) or by opening the desktop application (on mac).

We will need an instance of Neo4j to store the graphs that dgi creates. We will start one up in a docker container and set an environment variable to let dgi know where to find it.

docker run -d --name neo4j \
    -p 7474:7474 \
    -p 7687:7687 \
    -e NEO4J_AUTH="neo4j/tackle" \
    -e NEO4J_apoc_export_file_enabled=true \
    -e NEO4J_apoc_import_file_enabled=true \
    -e NEO4J_apoc_import_file_use__neo4j__config=true \
    -e NEO4JLABS_PLUGINS=\["apoc"\] \
    neo4j

export NEO4J_BOLT_URL="bolt://neo4j:tackle@localhost:7687"

Installation complete

We can now use the dgi command to load information about an application into a graph database. We start with dgi --help. This should produce:

Usage: dgi [OPTIONS] COMMAND [ARGS]...
  Tackle Data Gravity Insights
Options:
  -n, --neo4j-bolt TEXT  Neo4j Bolt URL
  -q, --quiet            Be more quiet
  -v, --validate         Validate but don't populate graph
  -c, --clear            Clear graph before loading
  --help                 Show this message and exit.
Commands:
  c2g    This command loads Code dependencies into the graph
  cargo  This command runs the CARGO algorithm to partition a monolith
  s2g    This command parses SQL schema DDL into a graph
  tx2g   This command loads DiVA database transactions into a graph

Step 2: Setting up a sample application

Get the source for Daytrader 7 :

wget -c https://github.com/WASdev/sample.daytrader7/archive/refs/tags/v1.4.tar.gz -O - | tar -xvz -C .

Note - you may need to brew install wget or apt install wget before running this.

If you would like to build and deploy the application yourself, please consult the instructions in the Daytrader Github repo (https://github.com/WasDev/sample.daytrader7). For convenience, we have provided the .jar files in $REPO_ROOT/jars/daytrader.

Step 3: Build a Program Dependency Graph

3.1 Getting facts with DOOP

We first need to run DOOP. For ease of use, DOOP has been pre-compiled and hosted as a docker image at quay.io/rkrsn/doop-main. We'll use that for this demo.

From the root folder of the project, run the following commands :

mkdir -p doop-data/daytrader
docker run -it --rm -v $REPO_ROOT/jars/daytrader:/root/doop-data/input -v $REPO_ROOT/doop-data/daytrader:/root/doop-data/output/ quay.io/rkrsn/doop-main:latest rundoop

Notes:

1. If you encounter any error above, please rerun the docker run ... command

2. Running DOOP for the first time may take up to 15 minutes

3.2 Run DGI code2graph

In this step, we'll run DGI code2graph to populate a Neo4j graph database with various static code interaction features pertaining to object/dataflow dependencies.

dgi -c c2g -i $REPO_ROOT/doop-data/daytrader

This will take 4-5 minutes. After successful completion, we should see something like this :

$ dgi -c c2g -i doop-data/daytrader
    code2graph generator started...
    Verbose mode: ON
    Building Graph...
    [INFO] Populating heap carried dependencies edges
    100%|█████████████████████| 7138/7138 [01:37<00:00, 72.92it/s]
    [INFO] Populating dataflow edges
    100%|█████████████████████| 5022/5022 [01:31<00:00, 54.99it/s]
    [INFO] Populating call-return dependencies edges
    100%|█████████████████████| 7052/7052 [02:26<00:00, 48.30it/s]
    [INFO] Populating entrypoints
    code2graph build complete

Extracting Database Transactions with Tackle-DiVA

Note that this step is only for applications with database transactions, like Daytrader. In particular, if you are running these steps for plants, jpetstore or acmeair sample applications as part of the "full" evaluation, skip this step.

Now we will run Tackle-DiVA to extract transactions from Daytrader. DiVA is available as a docker image, so we just need to run DiVA by pointing to the source code directory and the desired output directory.

docker run --rm \
  -v $REPO_ROOT/sample.daytrader7-1.4:/app \
  -v $REPO_ROOT:/diva-distribution/output \
  quay.io/konveyor/tackle-diva

This should generate a file transaction.json containing all discovered transactions. Finally, we run DGI to load these transaction edges into the program dependency graph.

dgi -c tx2g -i $REPO_ROOT/transaction.json

After successful completion, we should see something like this :

Verbose mode: ON
[INFO] Clear flag detected... Deleting pre-existing SQLTable nodes.
Building Graph...
[INFO] Populating transactions
100%|████████████████████| 158/158 [00:01<00:00, 125.73it/s]
Graph build complete

Step 4: Running CARGO

Once we have created the Neo4j graphs by following the above steps, we can run CARGO as follows:

minerva-cargo --app-name=daytrader --neo4j-url=bolt://neo4j:minerva@localhost:7687 --mode=standalone

[12:52:07] INFO     Running CARGO in standalone mode.                                                                                                                                                                                              logger.py:12
           INFO     Loading graphs from Neo4j. This could take a couple of minutes                                                                                                                                                                 logger.py:12
100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ • 0:00:00 • 0:00:00
Running with seed 42
[12:52:34] INFO     Number of partitions = 7                                                                                                                                                                                                       logger.py:12
           INFO     Cargo with unique initial labels                                                                                                                                                                                               logger.py:12
           INFO     Doing LPA on graph with database edges temporarily added                                                                                                                                                                       logger.py:12
           INFO     Final partition sizes : [ 5  8  6 55  2]                                                                                                                                                                                       logger.py:12



╔════════════════════════════════════════════════════════════════════════════════════════════════╗
║                                            daytrader                                           ║
╚════════════════════════════════════════════════════════════════════════════════════════════════╝


                                                 Partitions
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┓
┃ Package                                            ┃ Class Name                              ┃ Partition ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━┩
│ com.ibm.websphere.samples.daytrader.web.websocket  │ JsonDecoder                             │         0 │
│ com.ibm.websphere.samples.daytrader.web.websocket  │ JsonMessage                             │         0 │
│ com.ibm.websphere.samples.daytrader.web.websocket  │ JsonEncoder                             │         0 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingServlet31AsyncRead                  │         0 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingServlet31AsyncRead$ReadListenerImpl │         0 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingManagedThread                       │         1 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingManagedThread$1                     │         1 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingCDIBean                             │         1 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingServletCDI                          │         1 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingServletCDIBeanManagerViaCDICurrent  │         1 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingServletCDIBeanManagerViaJNDI        │         1 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingManagedExecutor                     │         1 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingManagedExecutor$1                   │         1 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingServlet2Servlet                     │         2 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingBean                                │         2 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingServlet2Jsp                         │         2 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingSession3                            │         2 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingSession3Object                      │         2 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingServlet2PDF                         │         2 │
│ com.ibm.websphere.samples.daytrader.web.prims.ejb3 │ PingServlet2TwoPhase                    │         3 │
│ com.ibm.websphere.samples.daytrader.util           │ TradeConfig                             │         3 │
│ com.ibm.websphere.samples.daytrader.ejb3           │ TradeSLSBBean                           │         3 │
│ com.ibm.websphere.samples.daytrader.util           │ FinancialUtils                          │         3 │
│ com.ibm.websphere.samples.daytrader.entities       │ HoldingDataBean                         │         3 │
│ com.ibm.websphere.samples.daytrader.entities       │ OrderDataBean                           │         3 │
│ com.ibm.websphere.samples.daytrader                │ TradeAction                             │         3 │
│ com.ibm.websphere.samples.daytrader.util           │ CompleteOrderThread                     │         3 │
│ com.ibm.websphere.samples.daytrader.entities       │ AccountDataBean                         │         3 │
│ com.ibm.websphere.samples.daytrader.entities       │ AccountProfileDataBean                  │         3 │
│ com.ibm.websphere.samples.daytrader.entities       │ QuoteDataBean                           │         3 │
│ com.ibm.websphere.samples.daytrader.direct         │ TradeDirect                             │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims.ejb3 │ PingServlet2SessionLocal                │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingJDBCRead                            │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingJDBCWrite                           │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims.ejb3 │ PingServlet2MDBTopic                    │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims.ejb3 │ PingServlet2Session2CMROne2Many         │         3 │
│ com.ibm.websphere.samples.daytrader.direct         │ KeySequenceDirect                       │         3 │
│ com.ibm.websphere.samples.daytrader.util           │ MDBStats                                │         3 │
│ com.ibm.websphere.samples.daytrader.web            │ TradeConfigServlet                      │         3 │
│ com.ibm.websphere.samples.daytrader.web            │ TradeServletAction                      │         3 │
│ com.ibm.websphere.samples.daytrader.web            │ TradeBuildDB                            │         3 │
│ com.ibm.websphere.samples.daytrader.beans          │ MarketSummaryDataBean                   │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims.ejb3 │ PingServlet2Entity                      │         3 │
│ com.ibm.websphere.samples.daytrader.web            │ TradeScenarioServlet                    │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims.ejb3 │ PingServlet2SessionRemote               │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims.ejb3 │ PingServlet2Session2Entity              │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims.ejb3 │ PingServlet2Session2Entity2JSP          │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingServlet2Include                     │         3 │
│ com.ibm.websphere.samples.daytrader.ejb3           │ MarketSummarySingleton                  │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingJDBCRead2JSP                        │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims.ejb3 │ PingServlet2Session2CMROne2One          │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims.ejb3 │ PingServlet2Session2EntityCollection    │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims.ejb3 │ PingServlet2MDBQueue                    │         3 │
│ com.ibm.websphere.samples.daytrader.web.jsf        │ AccountDataJSF                          │         3 │
│ com.ibm.websphere.samples.daytrader.web            │ OrdersAlertFilter                       │         3 │
│ com.ibm.websphere.samples.daytrader.beans          │ RunStatsDataBean                        │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingServlet2DB                          │         3 │
│ com.ibm.websphere.samples.daytrader.util           │ KeyBlock                                │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingJSONP                               │         3 │
│ com.ibm.websphere.samples.daytrader.web.websocket  │ ActionDecoder                           │         3 │
│ com.ibm.websphere.samples.daytrader.web.websocket  │ ActionMessage                           │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingUpgradeServlet$Handler              │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingUpgradeServlet$Listener             │         3 │
│ com.ibm.websphere.samples.daytrader.web            │ TradeWebContextListener                 │         3 │
│ com.ibm.websphere.samples.daytrader.web            │ TestServlet                             │         3 │
│ com.ibm.websphere.samples.daytrader.web.jsf        │ PortfolioJSF                            │         3 │
│ com.ibm.websphere.samples.daytrader.web.jsf        │ HoldingData                             │         3 │
│ com.ibm.websphere.samples.daytrader.web.jsf        │ QuoteData                               │         3 │
│ com.ibm.websphere.samples.daytrader.web.jsf        │ JSFLoginFilter                          │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingCDIJSFBean                          │         3 │
│ com.ibm.websphere.samples.daytrader.web.jsf        │ OrderData                               │         3 │
│ com.ibm.websphere.samples.daytrader.web.jsf        │ QuoteJSF                                │         3 │
│ com.ibm.websphere.samples.daytrader.web            │ TradeAppServlet                         │         3 │
│ com.ibm.websphere.samples.daytrader.web.jsf        │ MarketSummaryJSF                        │         3 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingServlet31Async                      │         4 │
│ com.ibm.websphere.samples.daytrader.web.prims      │ PingServlet31Async$ReadListenerImpl     │         4 │
└────────────────────────────────────────────────────┴─────────────────────────────────────────┴───────────┘
       Database Transactional Purity
┏━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃            ┃ Txn Purity (higher=better) ┃
┡━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ Original   │                         -- │
│ With CARGO │                        1.0 │
└────────────┴────────────────────────────┘
      Architectural Metrics
┏━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┓
┃ Metric   ┃              CARGO ┃
┡━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩
│ Coupling │                0.0 │
│ Cohesion │ 0.9860000014305115 │
│ ICP      │                0.0 │
│ BCP      │              1.621 │
└──────────┴────────────────────┘

minerva-cargo
Release 1.1.0

Release 1.1.0

0.1.1

1.0

1.1

1.1.0

Documentation

Codenet Minerva Cargo

CARGO: AI-Guided Dependency Analysis for Migrating Monolithic Applications to Microservices Architecture

Paper: ArXiV Preprint

Abstract

Figure 1. Overview of CARGO

Kick-the-tires Instructions (~15 minutes)

Pre-requisites

Step 1: Set up Data Gravity Insights CLI

1.1 Install DGI

1.2 Creating a Neo4j Docker container

Installation complete

Step 2: Setting up a sample application

Step 3: Build a Program Dependency Graph

3.1 Getting facts with DOOP

3.2 Run DGI code2graph

Extracting Database Transactions with Tackle-DiVA

Step 4: Running CARGO

Stats

Development practices

Releases

Contributors

minerva-cargo Release 1.1.0

Release 1.1.0 Toggle Dropdown 0.1.1 1.0 1.1 1.1.0

Documentation

Codenet Minerva Cargo

CARGO: AI-Guided Dependency Analysis for Migrating Monolithic Applications to Microservices Architecture

Paper: ArXiV Preprint

Abstract

Figure 1. Overview of CARGO

Kick-the-tires Instructions (~15 minutes)

Pre-requisites

Step 1: Set up Data Gravity Insights CLI

1.1 Install DGI

1.2 Creating a Neo4j Docker container

Installation complete

Step 2: Setting up a sample application

Step 3: Build a Program Dependency Graph

3.1 Getting facts with DOOP

3.2 Run DGI code2graph

Extracting Database Transactions with Tackle-DiVA

Step 4: Running CARGO

Stats

Development practices

Releases

Contributors

minerva-cargo
Release 1.1.0

Release 1.1.0

0.1.1

1.0

1.1

1.1.0