A data-centric transformation of monoliths into microservices
Project description
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
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 │
└──────────┴────────────────────┘
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