WildFly: Parallel Approach for automated deployment application server

Transcription

1 International Journal of Computer Engineering and Applications, ICCSTAR-2016, Special Issue, May.16 WildFly: Parallel Approach for automated deployment application server Deepthi C G 1,Harshitha V 2, Lavanya 3, Meghana R 4, Rajini V 5 1 Department of Computer Engineering 2 Department of Computer Engineering city engineering college, India ABSTRACT: Cloud Computing has may advantages. It provides three kinds of service to the users.one of the service is infrastructure as a service.it provides a standard service that contains OS and basic functions. Users have to manually install all the required applications for the proper deployment approach. Installation of applications are dependent on multiple servers. Previous research projects on installing applications with multi-server dependencies have deployed the server sequentially. Thus, these dependencies leads to the total deployment time which grows linearly with the total number of servers. Our approach which automates the server applications parallely which when installed across multiple servers. We have implemented a configuration manager system that evaluates all the above problems of installation and evaluates the performance of the composite application. We implemented a proto-type system on Wildfly, a widely used automatic server installation framework, and evaluated the performance of our composite application deployment on a SoftLayer public cloud using two composite application server cases. The deployment times were reduced by roughly 40% in our trials. Keywords: Wildfly, Configuration manager, Devops [1] Introduction Cloud computing infrastructure services are now becoming popular, often called Infrastructure as a Service (IaaS), which provide various services on demand, automatically provisioning as many servers as the user needs, with billing on a resource-consumed basis. For example, 100 servers might be required for a two-week evaluation of an algorithm. In general it is difficult to obtain such a large number of servers quickly and for a short period, 453

2 International Journal of Computer Engineering and Applications, Volume IV, Issue I & II, Dec.14 but a cloud computing infrastructure service can easily satisfy such demands. The user can acquire the 100 servers for two weeks by simply requesting them on a cloud portal website. A cloud computing infrastructure service generally provides a standard vanilla server that contains an OS and basic functions, even though the user also needs the server to have some set of applications. It s troublesome for the user to manually install all of the applications after the vanilla servers are automatically instantiated by the cloud computing infrastructure. Virtual appliance deployment approaches [1][2] have been used to eliminate the manual installations. With this approach, a special private server image is prepared in advance, which is cloned from a server with the required set of applications installed. A new server created from the image is ready for the applications as soon as the server is deployed in the cloud computing infrastructure. The virtual appliance deployment approach works well when the set of applications is known in advance. It needs to prepare many private server images for meeting flexible requirements, so each set of applications can be dynamically determined by each user in the server deployment request. There are many problems in managing server images, because the number of needed images can become exponential, considering all of the possible combinations of the required applications and their versions. Composite application deployment approaches [3][4][5][6] have been proposed to support flexible combinations of applications. They typically use an application-independent standard server image, without regard to the specific applications. The installation scripts for each application are bundled as an application script. The basic procedure requires the user to determine the set of applications when requesting the servers. Each server is created from a standard server image, then downloads the application script files for the selected applications, and invokes them. The applications are installed automatically after the servers are instantiated. A user can thus acquire servers with a favorite combination of applications without manual operations A composite application deployment approach invokes certain application scripts on the servers whenever they are deployed. There are applications that have installation dependencies across multiple servers. A Web application accessing a Web server and a database server is one of the typical examples. The Web application requires both the Web server and the database server, but the Web application installation should start after the installations of the other servers have been completed. Some work [7][8][9] proposes supporting application with installation dependencies across multiple servers. These projects deploy the servers sequentially (Fig. 1). The serialized execution is natural when an application script consists of shell scripts and automated installation frameworks called Infrastructure as a Code, such as Wildfly which assume the operations run on single server. However this means the deployment times increase dramatically with the number of servers, but rapid server deployment is becoming critical for many new server deployment opportunities, such as the population of DevOps. Figure: 1. Configuration manager In this paper, we propose an automated parallel approach for rapidly deploying composite application servers that have installation dependencies across multiple servers. It automatically detects installation dependencies across multiple servers from a set of application scripts, and manages the synchronized invocations of the application scripts in parallel to insure 454 Deepthi C G, Harshitha V, Lavanya, Meghana R and Rajini V

3 International Journal of Computer Engineering and Applications, ICCSTAR-2016, Special Issue, May.16 the installations are safely installed. We implemented a prototype of our approach on Wildfly, which is widely used as an automated installation framework, and show that automated parallel deployment can be done in an existing framework with minimum impact. In addition, we measured the composite application deployment performances on SoftLayer to show that our approach improves the server deployment times. [2] DESIGN Our proposed approach uses two technologies: an automated detection system for synchronization points and a synchronized installation management system for multiple servers. We call deployed by the cloud computing infrastructure for users a Virtual Machine (VM), in contrast to a management server, which is used by the infrastructure to create and control VMs. Figure: 2. Configuring the task The architecture of server deployment consists of configuration manager, the modules, wildfly server and an xml file. JAXB-B: It binds java and xml for programmatically reading and writing xml files. Command processor: It accepts the input from the user and invokes service façade. It takes the input from the user and creates new profile files, save all the input given to the task and save it as xml file and executes the tasks. It will read the profile file and executes. Service facade: It takes the input from command processor n executes it. It also called entry point to execute the tasks. Data Source: It is the connection set up to a Database from a server. The name is commonly used when creating a query to the database. The database source name (DSN) does not have to be the same as the filename for the database. For example, a database file named "friends.mdb" could be set up with a DSN of "school". Then DSN "school" would be used to refer to the database when performing a query. A data source, in the context of computer science and computer applications, is the location where data that is being used come from. In a database management system, the primary data source is the database, which can be located in a disk or a remote server. The data source for a computer program can be a file, a data sheet, a spreadsheet, an XML file or even hard-coded data within the program. Data sources can differ according to the application or the field in question. Mail session: Mail session will handle the server and control access to messaging system. Wildfly mail subsystem is contained in all server configuration and exposes a mail service bound at JNDI name. The mail session in turn references an smtp host bound at localhost at port 25. We use Simple Mail Transfer Protocol (SMTP) to send mail to clients. Queue and Topic: It is messaging standard that allows application components based on file to create, send, receive and read messages. SSL (Security Socket Layer): It is standard security technology for establishing a link between web server and browser. This link ensure that all data passed between web server and browser. Logfile: It is a status file, it find the error details. The architecture of server deployment consists of configuration manager, the modules, wildfly server and a xml file. Wildfly is a server that is flexible, lightweight, managed application runtime that helps us to build amazing applications. Wildfly takes an aggressive approach to memory management. Administration console is 100% stateless and purely client driver. It starts instantly and requires zero memory on the server. Wildfly s architecture is based on pluggable subsystems that can be added or removed as needed. 455

4 International Journal of Computer Engineering and Applications, Volume IV, Issue I & II, Dec.14 Configuration manager is an intermediate layer between end user and application manager. Configuration manager takes input from the end users, stores the input in a profile.xml file. This profile.xml file can be made run on a wildfly server. One of the end user will create a profile, give inputs to the modules such as database, mail session, queue and topic, security socket layer log file etc. End user will save all these information in the configuration manager and then run the file. The configuration manager generates a profile.xml file. The other end users now will take the profile.xml file. And then open the profile through configuration manager and gives all required data and run the file through the wildfly server. [3] IMPLEMENTATION The below figure shows the components that make up a JAXB implementation. Figure: 3. JAXB Architectural Overview A JAXB implementation consists of the following architectural components: Schema compiler: Binds a source schema to a set of schema-derived program elements. The binding is described by an XML-based binding language. Schema generator: Maps a set of existing program elements to a derived schema. The mapping is described by program annotations. Binding runtime framework: Provides unmarshalling (reading) and marshalling (writing) operations for accessing, manipulating, and validating XML content using either schema-derived or existing program elements. The above figure shows what occurs during the JAXB binding process. Figure: 4. Steps in the JAXB Binding Process The general steps in the JAXB data binding process are: 1. Generate classes: An XML schema is used as input to the JAXB binding compiler to generate JAXB classes based on that schema. 2. Compile classes: All of the generated classes, source files, and application code must be compiled. 3. Unmarshal: XML documents written according to the constraints in the source schema are unmarshalled by the JAXB binding framework. Note that JAXB also supports unmarshalling XML data from sources other than files/documents, such as DOM nodes, string buffers, SAX Sources, and so forth 456 Deepthi C G, Harshitha V, Lavanya, Meghana R and Rajini V

5 International Journal of Computer Engineering and Applications, ICCSTAR-2016, Special Issue, May Generate content tree: The unmarshalling process generates a content tree of data objects instantiated from the generated JAXB classes; this content tree represents the structure and content of the source XML documents. 6. Validate (optional): The unmarshalling process optionally involves validation of the source XML documents before generating the content tree. Note that if you modify the content tree in Step 6, below, you can also use the JAXB Validate operation to validate the changes before marshalling the content back to an XML document. 7. Process content: The client application can modify the XML data represented by the Java content tree by means of interfaces generated by the binding compiler. 8. Marshal: The processed content tree is marshalled out to one or more XML output documents. The content may be validated before marshalling. JAXB, stands for Java Architecture for XML Binding, using JAXB annotation to convert Java object to / from XML file. In this tutorial, we show you how to use JAXB to do following stuffs : 1. Marshalling Convert a Java object into a XML file. 2. Unmarshalling Convert XML content into a Java Object. Technologies used in this article 1. JDK JAXB 2.0 The Working with JAXB is easy, just annotate object with JAXB annotation, later use jaxbmarshaller.marshal() or jaxbmarshaller.unmarshal() to do the object / XML conversion. package com.mkyong.core; import javax.xml.bind.annotation.xmlattribute; import javax.xml.bind.annotation.xmlelement; import public class Customer { String name; int age; int id; public String getname() { return name; 457

6 International Journal of Computer Engineering and Applications, Volume IV, Issue I & II, public void setname(string name) { this.name = name; public int getage() { return public void setage(int age) { this.age = age; public int getid() { return public void setid(int id) { this.id = id; Convert Object to XML JAXB marshalling example, convert customer object into a XML file. The jaxbmarshaller.marshal() contains a lot of overloaded methods, find one that suit your output. Java package com.mkyong.core; import java.io.file; import javax.xml.bind.jaxbcontext; import javax.xml.bind.jaxbexception; import javax.xml.bind.marshaller; publicclassjaxbexample{ publicstaticvoidmain(string[] args){ Customer customer =newcustomer(); customer.setid(100); customer.setname("mkyong"); customer.setage(29); try{ 458 Deepthi C G, Harshitha V, Lavanya, Meghana R and Rajini V

7 International Journal of Computer Engineering and Applications, ICCSTAR-2016, Special Issue, May.16 File file =newfile("c:\\file.xml"); JAXBContext jaxbcontext= JAXBContext.newInstance(Customer.class); Marshaller jaxbmarshaller = jaxbcontext.createmarshaller(); // output pretty printed jaxbmarshaller.setproperty(marshaller.jaxb_formatted_output,true); jaxbmarshaller.marshal(customer, file); jaxbmarshaller.marshal(customer, System.out); catch(jaxbexception e){ e.printstacktrace(); Convert XML to Object JAXB unmarshalling example, convert a XML file content into a customer object. The jaxbmarshaller.unmarshal() contains a lot of overloaded methods, find one that suit yours. Java package com.mkyong.core; import java.io.file; import javax.xml.bind.jaxbcontext; import javax.xml.bind.jaxbexception; import javax.xml.bind.unmarshaller; publicclassjaxbexample{ publicstaticvoidmain(string[] args){ try{ File file =newfile("c:\\file.xml"); JAXBContext jaxbcontext = JAXBContext.newInstance(Customer.class); Unmarshaller jaxbunmarshaller = jaxbcontext.createunmarshaller(); Customer customer =(Customer) jaxbunmarshaller.unmarshal(file); System.out.println(customer); catch(jaxbexception e){ e.printstacktrace(); 459

8 International Journal of Computer Engineering and Applications, Volume IV, Issue I & II, Dec.14 Configuration manager is an intermediate layer between end user and application manager. Configuration manager takes input from the end users, stores the input in a profile.xml file. This profile.xml file can be made run on a wildfly server. Figure: 5. Configuration tool One of the end user will create a profile, give inputs to the modules such as database, mail session, queue and topic, security socket layer log file etc. End user will save all these information in the configuration manager and then run the file. The configuration manager generates a profile.xml file. The other end users now will take the profile.xml file. And then open the profile through configuration manager and gives all required data and run the file through the wildfly server. By doing these activities time is saved and it is not error prone. The configuration manager is a cross platform application that automates most of the common tasks done manually. [4] RELATED WORK This paper proposes rapid deployment of a set of composite application servers that have installation dependencies, by transforming the serial installation to a parallel processing of the application scripts. There are some research reports about composite application approaches with flexible server deployments. The Wrangler system [7] describes a set of composite application servers as a XML template. OpenStack Heat [8] and AWS CloudFormation [9] do this with JSON and YAML templates. They also support synchronized installations to deploy servers that have installation dependencies by explicitly describing the dependencies among the servers in the template files. However, their server deployment order remains serial, because the synchronized granularity is at the server level. It takes more time for the server deployments as the number of servers increases. We achieved application-script-level synchronization for parallel server deployments, and thus reduced the deployment time. Figure: 6. Deployment Comparison - Social Media Analytics Some deployment frameworks such as BOSH don t support synchronized installations across multiple servers. Our approach is independent of existing automated deployment frameworks, and does not require them to change their system architectures or components. Our technologies enable such deployment frameworks to deploy a set of the servers that have dependencies. There are other proposed approaches for rapid server deployments. It takes time to transfer large amounts of data. In this paper the time is reduced by leveraging a peer-to-peer network. We propose preparation of some private server images that install the basic applications in advance. We propose rapid execution of installation scripts by combining CPU with GPU capabilities. We propose to reduce software deployment cost by eliminating a huge number of 460 Deepthi C G, Harshitha V, Lavanya, Meghana R and Rajini V

9 International Journal of Computer Engineering and Applications, ICCSTAR-2016, Special Issue, May.16 selections on parameter values required during the deployment. Our approach can be combined with these approaches for even more rapid deployment. We have assumed that the composite application server configuration is valid. It is important to verify each pattern of a set of composite application servers before the server deployments. Our proposes verifying the pattern by using a model-driven architecture. It s also important to verify application scripts and preferable to do that automatically. There is a cloud service orchestration approach that focuses on server operations in addition to server deployments over multiple clouds. We propose an architecture for seamless management of server deployments and operations across multiple heterogeneous clouds by using unified APIs. Our approach can also be used in a cloud service orchestration framework for rapid deployment. This paper assumes dependencies between the application scripts that do not change during execution and that can be detected by investigating the program s source code. By investigating both the program s source code and their execution flows, our approach can allow for control dependency detection and dynamic dependency detection, which thereby supports complicated dependencies that are changing during execution. Our parallel execution unit is an application script that calculates in advance its minimum component splits. It might be possible to increase the parallelization by slicing the appli-cation scripts, leveraging automatic partitioning technologies and software maintenance techniques. [5] RESULTS We configure datasource, mail session, JMS queue and topic and socket binding by providing some inputs in configuration tool. We perform the task using configuration tool not directly on JBOSS advantage is the the input given by user will be saved in the xml file and next time if we want to run the task again we will just open that xml file just click run button for all task and within fraction of minutes we can complete the configuration. So that time is not wasted. After configuration we need to verify whether all these task is been created in wildfly server. So that time is not wasted. Figure: 7. Configuration tool [6] CONCLUSION The automated parallel approach that we proposed in this paper offers more rapid deployments of composite application servers that have dependencies across multiple servers, by automatically finding the data dependencies in the application scripts and guaranteeing a dependency-safe installation order over multiple servers using Checkpoint-based synchronization management. A Wildfly implementation shows our approach is practical and framework independent. Two applications with composite server deployments on the Soft-Layer cloud show that our approach is effective for more rapid deployments. In this paper, we implemented the prototype system using Wildfly server. It would be useful to support other automated installation frameworks, such as Puppet. It would be also useful to combine with a virtual appliance approach for more rapid deployments, although this paper follows only the composite application approach. 461

10 International Journal of Computer Engineering and Applications, Volume IV, Issue I & II, Dec.14 REFERENCES (NEW PAGE, FONT 10, BOLD, TIMES NEW ROMAN) [1] Constantine Sapuntzakis, David Brumley, Ramesh Chandra, Nickolai Zeldovich, Jim Chow, Monica S. Lam, and Mendel Rosenblum. Virtual appliances for deploying and maintaining software. In Proceedings ofthe 17th Large Installation Systems Administration Conference (LISA 2003), October, [2] Changhua Sun, Le He, Qingbo Wang, and Ruth Willenborg. Simplifying service deployment with virtual appliances. In Proceedings of IEEEInternational Conference on Services Computing (SCC 2008), July, [3] Alexander V. Konstantinou, Tamar Eilam, Michael Kalantar, Alexan-der A. Totok, William Arnold, and Edward Snible. An architecture for virtual solution composition and deployment in infrastructure clouds. In Proceedings of the the 3rd international workshop on virtualizationtechnologies in distributed computing (VTDC 2009), June, [4] Xavier Etchevers, Thierry Coupaye, Fabienne Boyer, and Noel de Palma. Self-configuration of distributed applications in the cloud. In Proceed-ings of the 4th IEEE International Conference on Cloud Computing (Cloud 2011), July, [5] Vanish Talwar, Qinyi Wu, Calton Pu, Wenchang Yan, and Gueyoung Jung and Dejan Milojicic. Comparison of approaches to service deployment. In Proceedings of the 25th IEEE International Conferenceon Distributed Computing Systems (ICDCS 2005), June, [6] Constantine Sapuntzakis, David Brumley, Ramesh Chandra, Nickolai Zeldovich, Jim Chow, Monica S. Lam, and Mendel Rosenblum. Virtual appliances for deploying and maintaining software. In Proceedings ofthe 17th Large Installation Systems Administration Conference (LISA 2003), October, [7] Changhua Sun, Le He, Qingbo Wang, and Ruth Willenborg. Simplifying service deployment with virtual appliances. In Proceedings of IEEEInternational Conference on Services Computing (SCC 2008), July, Deepthi C G, Harshitha V, Lavanya, Meghana R and Rajini V

11 International Journal of Computer Engineering and Applications, ICCSTAR-2016, Special Issue, May.16 [8] [9] Alexander V. Konstantinou, Tamar Eilam, Michael Kalantar, Alexan-der A. Totok, William Arnold, and Edward Snible. An architecture for virtual solution composition and deployment in infrastructure clouds. In Proceedings of the the 3rd international workshop on virtualizationtechnologies in distributed computing (VTDC 2009), June, [10] Xavier Etchevers, Thierry Coupaye, Fabienne Boyer, and Noel de Palma. Self-configuration of distributed applications in the cloud. In Proceed-ings of the 4th IEEE International Conference on Cloud Computing (Cloud 2011), July, Engineering. Deepthi C.G received her B.E from Sir M Visvesvaraya Institute of Technology, Bangalore in She also perceived her M.tech from SIT, Tumkur in She worked for various organizations like KIT, Tiptur APSCE, Bangalore. Currently she is working in City Engineering College Bangalore as Assistant Professor in Department of Computer Science and Harshitha V a student who is currently pursing her B.E in City Engineering College, Bangalore, Department of Computer Science and Engineering. Lavanya a student who is currently pursing her B.E in City Engineering College Bangalore, Department of Computer Science and Engineering. Meghana R a student who is currently pursing her B.E in City Engineering College, Bangalore, Department of Computer Science and Engineering. Rajini V a student who is currently pursing her B.E in City Engineering College, Bangalore, Department of Computer Science and Engineering. 463

12 International Journal of Computer Engineering and Applications, Volume IV, Issue I & II, Dec.14 Author[s] brief Introduction Corresponding Address- (in this address you will get your journal hard copy) (Pin code and Mobile is mandatory) 464 Deepthi C G, Harshitha V, Lavanya, Meghana R and Rajini V