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tackle-container-advisor's Introduction

example branch parameter

Tackle Container Advisor (TCA)

Table of Contents

Usage

  1. TCA Pipeline
  2. Run TCA
  3. API description
  4. References

Development

  1. Knowledge Base
  2. Knowledge Base Utilities
  3. Entity standardizer
  4. Developer Guide

Purpose

TCA provides APIs to standardize natural language description of technology stack components, cluster a portfolio of technology stacks into similar technology stack groups, match technology stacks to docker, openshift or operator catalog images.

1. App1: rhel, db2, java, tomcat
2. App2: .net, java, oracle db
3. App3: dot net, java, oracle dbms

TCA takes the following steps to recommend the containerization.

Standardize: Standardize natural language inputs to relevant named entities of technology stacks present in our knowledge base. For details on the knowledge base please check the db folder. For example, the inputs in App1,App2,App3 get mapped as the following named entities.

1. App1: rhel: RedHat Enterprise Linux, db2: DB2, java: Java, tomcat: Apache Tomcat
2. App2: .net: .NET, java: Java, oracle db: Oracle DB
3. App3: dot net: .NET, java: Java, oracle dbms: Oracle DB

Clustering: Cluster the standardized technology stack components into groups of similar technology stacks. For example, the standardized technology stacks for App1,App2,App3 get clustered into the two technology stack clusters.

1. Cluster1: {App1}
2. Cluster2: {App2, App3}

Containerize: Determines whether a technology stack is fully containerizable, partially containerizable or not containerizableat all. If a technology stack is recommended as fully or partially containerizable, it also generates container images based on DockerHub or Openshift image catalogs. It is also possible to provide custom user-defined catalogs for matching to catalog images. For example, if a user decides to generate DockerHub related images, then TCA generates the following images.

1. Cluster1: tomcat|https://hub.docker.com/_/tomcats
2. Cluster2: db2|https://hub.docker.com/r/ibmcom/db2

For OpenShift, TCA generates the following images.

1. Cluster1: tomcat|https://access.redhat.com/containers/#/registry.access.redhat.com/jboss-webserver-3/webserver31-tomcat8-openshift
2. Cluster2: db2|https://access.redhat.com/containers/#/cp.stg.icr.io/cp/ftm/base/ftm-db2-base

TCA Pipeline

TCA Pipeline

The pipeline ingests raw inputs from clients data and standardizes the data to generate named entities and versions. For standardizing or normalizing raw inputs we use a tf-idf similarity based approach. To find container images we represent images in terms of named entities as well. The normalized representation helps to match legacy applications with container images to suggest the best possible recommendations.

Code of Conduct

Refer to Konveyor's Code of Conduct page

tackle-container-advisor's People

Contributors

allyishida avatar divsan93 avatar jqjordan avatar kaliaanup avatar lamwassi avatar mihirc-github avatar mmerler avatar mrizzi avatar rofrano avatar salaimadhavan avatar savitharaghunathan avatar

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tackle-container-advisor's Issues

Performance Bottleneck on Compose App

The recommendation has some bottlenecks. It takes .6 sec for processing 1 record. This is only for compose-app module. The rest of the modules are pretty fast. Thanks to @Salai123 for reporting it.

Older code with old mentions (2k+)

Request Received 1631602243.2549899
Triggered Planning 1631602243.2552867
call containerization plan  1631602243.3072283
detect access token 1631602243.3079007
detected access token 1631602243.3079774
composed app 1631602243.4333582
missing infer tech 1631602243.4339461
app validate 1631602243.434026
assessment ui 1631602243.4362257
planning ui 1631602243.4396195
return final response  1631602243.4432805

New Code with new mentions (6k+)

Request Received 1631609691.3319073
Triggered Planning 1631609691.3320363
call containerization plan  1631609691.3685682
detect access token 1631609691.368657
detected access token 1631609691.368682
composed app 1631609691.911315
app validate 1631609691.911479
assessment ui 1631609691.9115021
return final response  1631609691.9117076

Unit test has an old API

One of the unit test has an old API

app_data = [
{
'application_id': 'App ID 0114',
'application_name': 'App Name 0114',
'application_description': 'App Desc 0114',
'component_name': 'Comp 1',
'operating_system': 'RHEL',
'programming_languages': 'Java',
'middleware': 'WebSphere Application Server',
'database': 'db2 10.0',
'integration_services_and_additional_softwares': 'Redis',
'technology_summary': 'angularJs,express.js,jenkins',
'versioning_tool_type': '1',
'application_inbound_interfaces': 5,
'application_outbound_interfaces': 1,
'devops_maturity_level': 'Moderate',
'devops_tooling': 'Jenkins, Git, JIRA',
'test_automation_%': '50%',
'performance_testing_enabled': 'No'
}

Can we change it?

Containerization API

As a user I should be able to get the containerization recommendation for my legacy apps.

Openshift recommendations has errors

{
"status": 201,
"message": "Container recommendation generated!",
"containerization": [
{
"Name": "App",
"Desc": "string",
"Cmpt": "string",
"Valid": true,
"Ref Dockers": "1. {'openjdk_Linux': 'https://access.redhat.com/containers/#/registry.access.redhat.com/ubi8/openjdk-11'}",
"Confidence": 0.56,
"Reason": "Containerization feasibility unknown for COTS applications: Apache Tomcat, MySQL",
"Recommend": "Partially Containerize"
}
]
}

Requiring inputs on couple of things

Dear Team,

  1. What would be expected for technology summary here as it seems to unable to create an output?
  2. How to upload bulk files onto the page? Here I can see only one input is allowed

Input : -
[
{
"application_name": "Sample",
"application_description": "This is a Sample App",
"component_name": "Framework",
"operating_system": "RHEL",
"programming_languages": "Java",
"middleware": "Kafka",
"database": "PostGreSQL",
"integration_services_and_additional_softwares": "",
"technology_summary": "Web"
}
]

Output : -
{
"status": 201,
"message": "Assessment completed successfully!",
"assessment": [
{
"Name": "Sample",
"Desc": "This is a Sample App",
"Cmpt": "Framework",
"OS": "{'RHEL': {'Linux|Red Hat Enterprise Linux': ''}}",
"Lang": "{'Java': {'Java': ''}}",
"App Server": "{}",
"Dependent Apps": "{'Kafka': {'Apache Kafka': ''}, 'PostGreSQL': {'PostgreSQL': ''}}",
"Runtime": "{}",
"Libs": "{}",
"Reason": "Reason 101: Medium or low confidence for the inferred data: {"Web": {"Java|Java Web Start": "", "Apache HTTP Server": "", "Java|Google Web Toolkit (GWT)": ""}}",
"KG Version": "1.0.0"
}
]
}

Documentation needed to interface with TCA from Tackle Inventory

Hi @kaliaanup , I'm onboarding to the Tackle project along with @jortel and @mansam right now.

We are working to learn how the Tackle App Inventory can interface with other tools in the Tackle suite, and trying to define the requirements of the App Inventory data model.

It would be helpful to have a reference doc on the public interface of TCA so that we can get an idea of how TCA this would tie in with Tackle Inventory, and what changes might be needed to the Tackle Inventory data model:

  • Expected inputs / outputs of TCA (examples would be useful)
  • Methods for invoking TCA (REST? CLI? Something else?)
  • Is there a Quay.io container auto-build set up so we can consume TCA easily running as a Pod on OpenShift?
  • Is there a deploy YAML available with a deployment definition for TCA and any required auxiliary OpenShift resources (e.g. namespaces, services, routes). This would let us quickly play around with TCA using other info provided. We may be able to assist here if needed.

Do documents detailing the public interface of TCA exist? Even some simple examples would be useful to get started.

cc @rromannissen @jwmatthews @PhilipCattanach

General clean up of unwanted repository files

There are many binary, metadata, and other duplicate files in this repository that should never have been checked in like:

  • Python binaries in multiple __pycache__ folders
  • Sphinx _build folders
  • Log files *.log
  • Database binaries *.db
  • Duplicate data folders like aca_db and ontologies
  • OS specific metadata like .DS_Store

Once deleted, a proper .gitignore file should be added to keep these files out of the repo for good.

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