A Jenkins job to push repo contents to an S3 bucket after a merge
Jenkins, one of the most popular open-source CI/CD tools provides you an easy, powerful interface to configure your project workflow. With few clicks and configurations, you are able to create a Jenkins job that could fetch code from Github on various events (PR, Merge, Commit), compile those (build), push or deploy them to any destination entity (S3, Server).
Let's create a simple scenario with a Jenkins job. For that, click on the “New item” in Jenkins to create a new job and then give an appropriate name for the job.
Then select the “Freestyle project” and then click “Ok”.
Then configure your job as follows:
Under general settings, tick the “GitHub project” to indicate that this is a GitHub hosted project and then enter the git project URL without the tree/master or tree/branch part.
Then under Source Code Management Section tick “Git” to tell Jenkins that the version control system of this project is as git. Then give the URL of the remote repository which when you use to git clone.
Here for Branches to build, give the branches that you need to build. Note: if your intention is to do a PR analysis within this job, then give ${ghprbActualCommit} as the branch.
Then under the build triggers section, tick the “GitHub hook trigger for GITScm polling”.
Under the Build section, if you have programs that need to be built (compiled) chose to execute shell category and write the relevant shell commands to build those programs. Note that if your project contains only scripts like shell scripts or SQL scripts you can omit this build section as those are not needed to be compiled or built.
Install S3 Plugin in Jenkins
Go to Dashboard -> Manage Jenkins -> Manage Plugins and select the Available tab. Find “S3 publisher” and install it. After that Go to “Manage Jenkins” -> select “Configure System”, there look for “Amazon S3 Profiles” and click the “Add” button to add an S3 profile.
As shown above, you can either use the IAM Role attached to your Jenkins server (for this create an IAM role who has write/read access to the relevant S3 bucket and attach it to ec2 instance where Jenkins is set up) or use an access key / secret key pair.
Go back to your job configurations -> “Post Build Actions” and add a new post-build action of type “Publish Artifacts to S3 Bucket”.
With sudoers users can be granted to run commands as the root user without needing the root password — hence they only need to enter their password, not the root password. So if not done correctly, those misconfigured users or groups at sudoers may be god-like.
When you issue a “sudo” or “su” command, Linux checks a special file called “sudoers” file (Or LDAP) and sees if you are allowed to be granted the root privileges. If your name is not on the list, then no rights. If you don’t have sudo privileges then you may have to manually add your username to the sudoers file. You can find the sudoers file in “/etc/sudoers”.
Here the “tim” is the name of the account or the group. And first ALL is for specifying all the machines (the sudoers file can be shared between multiple systems). And (root) is for specifying that “tim” can log in as root user (after issuing tim’s password). Last, ALL is for specifying that after tim logged in as root user, he can issue any of the commands.
Example 2: tim ALL = (root) NOPASSWD: command_a
Here tim can log in as the root user and issue the command “command_a” without needing to type the password. So now when tim run the command: “sudo command_a”, he will not be prompted for the password.
User Aliases And Command Aliases
In sudoers scripts, we can create a User Alias for a set of users. If not we would have to write many policies for each user, where all of them need to have the same scenario. Ex:
In the above example, we have created a user alias called USR_ALIAS1 (which is for all the users user_1, user_2, user_3, usenr_n) and then a policy for all of those users (by just placing the created Alias) to say that they can log in as root and execute the command “command_a”.
Similar to User Aliases, we can create Command Aliases for a set of commands. As before, If we did not have this feature, we would have to write many policies for each command, where all of them need to have the same scenario. Ex:
Single Responsibility principle states that any software entity (class, method) should have only one responsible assigned to it. If you are in any doubt on whether should you change a class or a method code, the only thing you need to do is ask the following two questions and if the answer is yes, then you need to change the class code/method code.
Does the class or method do more than one procedure? If so, it is advisable to separate it into two distinct classes/methods, so that each will handle a single responsibility.
Does that logic solely represent or belong only to the relevant class? If not, you should abstract out those methods (logic) and put or implement them in interfaces.
Here in the highlighted section, the method addPagesAndPrint() violates the S of SOLID principles - which is Single Responsibility. As you can see it does two tasks, it updates the number of pages in the book and prints the book's current details. These two tasks should be separated and should be in two different methods as below:
With that separation, we come to the next question which is checking whether are we still violating S of SOLID?. According to the second question, does these addPages() and printBookInfo() methods bound to a Book?, Is it sensible and beneficial to abstract out these two methods and put in a higher-level entity (like in an interface) of the application.
If your application has classes like Articles, Posts, and sort of entities that they also need the ability to add pages, then the method addPages() shouldn’t be within this class. Because then it’s violating S of SOLID. That should be placed in an interface so that all Book, Article and Post classes able to implement.
It is obvious that a printBookInfo() shouldn’t be within this class. Because there have to be many Classes that require the ability to print details of its object.
Enterprise Service Bus (ESB) is a pattern/middleware which allows systems (applications) implemented in incompatible technologies to communicate with each other. Hence an ESB can be thought of as a pluggable backbone where one can plug incompatible applications, and expect them to communicate with each other without any hassle.
Point to Point Integration (P2P)
Point to point integration is integrating systems or applications with each other directly. This is a legacy integration pattern which has many disadvantages and obstacles as listed below:
Single Points Of Failure
No Course Of Action For Emergencies
Exponential Increase in Complexity
Loss of Agility
Enterprise Service Bus Pattern (ESB)
ESB pattern is a more flexible approach for application integration. This integration is achieved by encapsulating and exposing each application functionality as a set of discrete reusable capabilities. Hence applications do not integrate directly with each other instead, they integrate through an ESB infrastructure, as illustrated below:
Anypoint Studio
MuleSoft’s Eclipse-based development environment for designing and testing Mule ESB applications is known as Anypoint Studio. With Anypoint Studio one can develop their message flows between application to application with a graphical drag-and-drop editor (or edit the XML file if preferred). The designer can select all of the different components offered by Mulesoft in their message flows and configure them easily.
Out-of-the-box Components
Anypoint studio has hundreds of built-in components which are needed for integration development:
Connectors — Anypoint studio comes with numerous connectors to third-party applications such as Amazon, Facebook, Google products, Sharepoint, MongoDB, Salesforce...
Dataweave Language
DataWeave is an expression language for accessing and then transform the data that travels through a Mule app.
In a mule message flow, the data being transferred from a component to the next component is called a Message. Hence mostly DW (Dataweave) is used to access and transform data in this Message. For example, after a source component in your flow gets a Message from one system, you can use DW to modify and output selected fields in that Message to a new data format, then use the next component in your flow to pass on that data to another system.
Mulesoft Message Structure
As stated earlier data transferred between components in a mule flow is called Messages. So one component will change/filter the input Message that it receives and export them to the next component so that it’s input Message will be that changed data.
Example 1: Listen to a Post Request from an HTTP Listener, Change the payload structure and save in a MySQL DB.
HTTP Listener Component
Here you should configure the HTTP Listener on what port is this Listener will be listening on and on what path should the caller call to invoke this Mule flow. For example, Listener Configuration would look like below:
So according to the above configuration of HTTP Listener, it would be listening via port 8081 and on path /insert-path .
And above code snippet shows the generated XML code for the configured HTTP Listener. So for every component that we configure in Mulesoft can be edited, created in XML too.
Logger Components
Loggers are used for logging the output message (mostly the payload) from the previous component. This is very helpful when you want to know and debug the output from a component.
Transform Message Component
This is one of the important components in Mulesoft. For all of the message transformations, this component is used mainly. And for doing the transformations, the Dataweave language is used.
DB Insert Component
This component is used to make a connection to the DB and insert the relevant data passed through the mule flow.
Example 2: Listen to a Post Request from an HTTP Listener, Invoke a Java method by passing the received payload, do the necessary changes to the payload from the java method, send the output from java method to another API Endpoint.
Note- The delta value of an output neuron in a multilayer perceptron, is the minus error times, the first derivative of activation function fed the weighted sum.
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