Tripple cost constraint

The age-old knowledge we have that when building a product, you can choose two of the three – Cheap, Good and Fast.

So if you need something to built with good quality and fast speed, it won’t come cheap.

In terms of a software project, these constraints take the form of –

Scope
Budget
Schedule

Quite often, a project manager is caught in the dilemma of controlling these aspects of the project. Striking a good balance among three is often difficult.

Let’s take a look at some of the practices we can use to manage these three aspects.


Scope

In a traditional project management approach, you would use Work breakdown structure (WBS), to define feature components which we need to develop. If a change comes in at a later point of time, that has to go through a Change Control Board (CCB), which will analyze the impact and approve if required.

In a lean project management approach, the scope is controlled in the form of tickets and requests.

In the more popular agile project management approach, we control scope in terms of the product backlog and sprint backlog.


Schedule

To manage the schedule in a traditional waterfall approach, techniques like Program Evaluation and Review Technique (PERT) and Critical Path Method (CPM) are used

In the Lean project management approach, Kanban & Queues are used to manage the work. The work is managed in a list and executed based on priority. Service Agreements sets the priority of work by defining what is critical, major, or minor.

In an Agile project management approach, a Sprint based model is popular to manage scope, where releases and roadmaps are used to set goals for major features to be released together.


Budget

In the traditional project management approach, we use Earned Value Management (EVM) approach which compares current performance Earned Value (EV) to the Planned Value (PV) and evaluate it over Actual Cost (AC) which is the cost so far to complete the work

In the Lean project management approach, we control KPIs or Key performance indicators to showcase the outcome of the work done.

In Agile project management, we measure Return on Investment or ROI, and Burndown charts to measure performance.

Cloud Computing – an Introduction

When I started my career, analyzing and finalizing hardware needs for deployments was a major task and had to be taken up months before actual production deployments. Hardware was costly. Though we had providers which would provide machine virtually, you would need to decide the requirements beforehand as once you procured a machine, you had to pay at least a month’s rent. And if you decide to upgrade or downgrade the server machine, it was a painful manual task.

Just imagine what a nightmare it would have been to scale up during a surge in requests. You had to foresee it, plan for it, arrange hardware for it (monthly rents).

With the cloud, things have changed for the better. You have a pay as you go model, so you actually pay for the usage of hardware only. With autoscaling features inbuilt into the cloud infrastructure, it is easy to increase or decrease compute power without any human intervention. Setting up databases and scaling them is another area which the cloud takes care for us. Most of the cloud service providers support both relational and NoSQL databases in an easy to use manner.

Security, access management, monitoring, encryption, and storage are some of the other services which are provided by cloud services providers of the shelf. Another popular set of services off-late is serverless compute. This means one can write code directly which can be run as functions on the cloud, without worrying about the deployment details completely. Cloud provider is responsible for scaling and maintaining such functions. This is in sync with the microservice approach where each function can behave as an independent microservice.

With one’s mind taken away from hardware details, it is easier for software engineers to focus on building quality products. But it is important that we design our products in a manner which are capable of taking advantage of cloud services. For example, it will be easier for a microservices-based application to autoscale in a cloud than a monolith application. A stateless service is easier to be deployed and scaled on cloud than stateful service. One still needs to take care of the fact which services are exposed on the internet and which should be exposed only to internal service. With the ease of deployment, it might be easier to mess up a running service, so proper automated and manual checks are required to be implemented.

Cloud, though makes things easier, but one needs to be cautious of using its capabilities and designing the system in a manner to make maximum use of services being provided

Developing With Containers

In the last few years, the cloud has completely changed the way we used to think about and design applications. With our eyes taken away from hardware availability, we can think more in terms of scalability and reliability. This has given a rise to microservices based design. Containers further support our idea of microservices based implementations by providing another layer of hardware independence.

What is a container?

Let’s start from the beginning. a decade or so back, when you need to deploy an application, you would go to your hardware department and tell them to get you a new box. So if you are deploying 10 applications, you would end up having 10 different sets of hardware being managed. In all probability, you were using less than half the processing power of a machine your application was deployed on because you would not take a risk of running a production application on a low powered machine.

Then came the era of Virtual machines, which helped us installing multiple virtual machines on the same machine. With the popularity of the cloud, virtual machines got more popular. Now you could easily boot up a virtual machine and deploy your application on that. One pressing downside of a virtual machine is that if you have 4 virtual machines running on a box, that would mean you have an overhead of running 4 operating system which ends up eating a lot of processing power.

This gave rise to the thought process for Containers, which helps us run an application inside its own container rather than an independent physical or virtual machine.

Let’s look at what a container is and how is it different from a VM with help of Docker container technology.

Image source – https://www.docker.com/

What is Docker?

Docker the technology, created by a company namesake, gives us tools to implement the concept of containers. As we can see in the image above, in case of a virtual machine, every virtual box has its independent Operating System image. That would mean that each Virtual machine is somewhat an independent system in itself. On the contrary, Docker installs a Docker engine on top of OS, which can further run multiple containers with a different set of applications.

Here are some useful docker commands

docker run
— Run an image
Docker ps
— Lists down all the running containers
Docker ps -a
— Lists down all the containers
Docker images
— Lists down all the images

More docker commands.
https://docs.docker.com/engine/reference/commandline/docker/

What is Kubernetes?

Running your application using Docker containers is the job half done. In the modern world, you need to take care of problems like how your application will handle the increase or decrease of load? How will we handle a situation when a node is down? Kuberenetes answers these questions helping us orchestrating the nodes and applications. It keeps a check on load and helps us increase or decrease firepower or add/ remove application instances. It takes care of failing nodes and brings in more nodes if required.

Spring Cloud

With more and more applications moving to the cloud, it is important for developers and architects to start thinking in terms of applications which are ready for cloud deployment. Spring cloud in an umbrella which consists of a set of spring projects that can help us create applications which are cloud ready. The advantage of using a spring cloud is that you get a solution to most of the challenges you face when you deploy on the cloud at one place.

Let’s look at some of the core tools provided by spring cloud.

Spring Config: An important challenge distributed applications poses is how to manage your configurations. Each application and service need to manage some configuration properties. Spring config server provides a centralized way to manage configurations. It can read configuration from multiple sources, by default it would expect the configuration to be available at Git, but this can be modified. The most important factor of about using spring configuration server is that you can refresh properties or configuration in services without the need for redeployment or restarting the services.

Discovery service- Eureka: Spring cloud borrows a lot of services from Netflix open sourced projects. Eureka is one such service from Netflix, which provides a discovery mechanism for services deployed, Spring provides seamless integration to Eureka. With a design supporting deployment and autoscaling fo microservices, this becomes important the services can be deployed and removed on the fly without manual interaction. A challenge in this approach is how will the calling services know about the location or URL for the services to be called. A discovery service mechanism provided by Eureka comes to help. Any new service getting added to the system will register itself with Eureka server. A service that needs to access this remote service will communicate with the Eureka server and ask for the service location. Eureka server returns the location of the service, which is then accessed by the client service.

Fault Tolerance with Hytrix: Another important factor one needs to be worried about is how failure is managed in an application. In a distributed system, where multiple services are calling each other, will the failure in a service bring down the whole system? Or is there a way we can contain the failure to a single service. Spring integrates with hystrix, which again is a project by Netflix, that provides us mechanism like a circuit breaker to manage failures in an application. For example, if a remote service is down or not responding, Hystrix helps us configure an alternate service or method which can take over. Also, we can add settings that after N number of failures, client service will stop calling remote service (the circuit is open), and set a timer when next retry happens (if the service has healed itself, operations continue as usual).

Routing with Zuul: With multiple services being part of the system, it becomes difficult for client service to keep a track of all the remote services. A routing gateway in such an environment is like a front gate, behind which all the services are available. A client system need not be aware of details of deployment of each service, and it will just request routing server to get the required information, which in turn will communicate with remote service and returns a response. The advantage of this approach is we can implement security, logging, auditing of incoming requests in a centralized manner and each individual service need not worry about these factors.

Load Balancing with Ribbon: Load balancing is an important feature in order to manage autoscaling of the services. If there are 10 instances of a service, we want to make sure each of the instances manages almost equal load to take advantage of scale. Load balancing can be implemented at the server level for which various cloud service provider already give us a certain option. But there can be cases when you want to implement Load balancing at the client side. For this, Spring integrates with Ribbon project from Netflix and provide us seamless load balancing with the help of annotations like @LoadBalance and @RibbonClient.

Additional Spring Cloud projects: As already mentioned spring cloud is an umbrella which contains a number of projects that help us make our application cloud ready. The number of projects under this umbrella keeps on increasing with an increase in the popularity of cloud-based deployment and distributed applications. For a detailed view of all the projects under spring cloud, one can visit and explore projects under https://spring.io/projects/spring-cloud

Top Free BI Tools

Here are some old notes from my analysis of the comparison of leading free BI tools.

1. Pentaho

Pros:
Can be considered as a complete BI tool
The learning curve is short
Has both paid and community edition.

Cons:
Community edition has some restrictions, so one needs to look carefully if looking for a free solution.

2. Talend

Pros:
Has support for charts and graphs
Has support for advanced features like big data

Cons:
Slower than Pentaho
The learning curve is more than Pentaho

3. Birst

Pros-
Can connect to Apps and Big data

Cons-
Does not provide too many details is documentation
Does not provide a free version
Looks interesting but does not open up too many details. If one is going for a paid solution, one can explore other options like Tibco as well.

4. Dynamic Reports

Pros:
Uses Jasper Report API to develop
One can write Java based code and use libraries to provide graphics

Cons:
Too much coding Required
It is like writing code to generate reports
Reports will be static (based on code).

5. Spago World / Spago BI

Pros: Completely open source solution

Cons: Community support does not look too active. One can get stuck with issues.

6. JasperSoft

Pros: Better quality graphics
Provides mobile support

Cons:
Lesser functionality than competitors like Pentaho.
It is suggested to use more in terms of reporting rather than a complete BI solution.

7. BIRT

Pros: Eclipse-based, hence low learning curve to get started
hosted reporting

Cons:
Looks more of ETL tool rather than a complete BI solution

Building Reactive Systems

In today’s world, we are always striving for building applications which can adapt to constantly changing needs. We want our systems to flexible, resilient, scalable and withstand end user’s high expectations.

Considering these needs, a Reactive Manifesto was put together, with best practices which will help us build robust applications. Following four pillars makes a strong base of reactive application.

1. Responsive
2. Resilient
3. Elastic
4. Message Driven

You can see none of these concepts are new in nature, and you might be already implementing them in the applications you build. Reactive Manifesto brings them under one umbrella and emphasizes their importance. Let’s take a look at these pillars one by one and see what all well-known patterns we can use to implement each of them.

Responsive: An application is responsive if it responds to the user in a timely manner. A very simple example is you clicked on a button or link in a web application, it does not give you a feedback that button was clicked and the action gets completed after few seconds. Such an application is non-responsive as the user is left guessing if he is performing the right action.

Some of the well-known practices and design patterns which help us make sure if the application is responsive
– Asynchronous communication
– Caching
– Fanout and quickest reply pattern
– Fail-fast pattern

Resilience: An application is called resilient if it can handle failure conditions in a graceful manner.

Some of the patterns that help maintain resilience
– Circuit breaker pattern
– Failure handling pattern
– Bounded Queue Pattern
– Bulkhead Pattern

Elasticity: An application is called elastic if it can stand increase or decrease in load without any major impact on overall working and performance.

Some of the practices and patterns to implement elasticity
– Single responsibility
– Statelessness
– Autoscaling
– Self-containment

Message Driven: An application which uses message driven communication makes sure we are implementing various components and services in a loosely coupled manner. This helps us keep our components scalable and makes failure handling easy.

Practices used to implement Message driven communicaiton
– Event driven
– Publisher Subscriber pattern
– Idempotency pattern

I have covered some of these patterns in details in my book on Design Patterns and Best Practices.

Design before you code

Somehow, with the penetration of agile development practices, I have been observing that less and less time is spent on designing the solution. Engineers treat Agile as a license to develop without design.

What is the problem with developing without designing or architecting the system first? I still remember when I was in college, my professor drew a parallel between architecting a building and architecting a software. Would you start building a house without thinking about design? you will not just start placing bricks without considering how many rooms you need? Where all these rooms go? How large should be every room? Where will the kitchen and bathroom be? Where all the wiring and plumbing will go? You will come up with the design, put in on a paper or a software and then calculate the feasibility.

Think of the complications that can happen if you build your house without thinking about design first. One room might be so big that there is very little space for the others. Or you are not left with any space to create a bathroom. These mistakes are costly. And that brings me to the other important factor which is causes ignoring of design in software. The manager thinks that change at a later state is going to be easy. At the end it is code, we can just change it. Well, changing the code is definitely possible, but never easy or cheap. It comes with its own cost.

More than often, where developers need to make changes at a later stage, they would be more inclined to apply quick fixes or hacks rather than making a bigger correct change. Of course, you have a tried and tested code in hand, why would you make too many changes to it, even if you know that is the right thing. And then there is developer ego, I mean, let’s admit it, it is not easy to accept one’s fault, especially if that means you would need to put in extra hours to fix that. More than ego, it is actually denial at times. People would try to stick to the solution they developed initially even though it is realized at a later stage that there could have been a better solution. Reason being, you have already invested too much.

This situation can be avoided if we think about design first. We can make sure our design covers all the possible requirements. It will not be possible to anticipate all the changes that are going to come at a later stage, but we can try to keep our design flexible. The idea is, set the ground rules, understand what all component and services we are required to create? What all data needs to be persisted and how are we going to do that? How security and error handling will be done? We need not get into implementation details, but the high-level design is a good start. We can fill in the details as and when requirements are clearer and we start actual work on the given piece of requirement.

In the end, all I would like to highlight is, if you think you are saving time by not thinking about the design of the application before you start to code, you are going to end up spending more time applying patches and fixes at the end.

Getting started with Spring Boot

This is a short tutorial about creating a simple REST webservice with spring boot. This assumes you have basic knowledge of Spring and Java.

To get started we will create a Spring project. The simplest way to do this is to go to http://start.spring.io/ and create a project.

This will give us a blank project on which we can build upon. Import the project as Maven project to Eclipse or any other ID. By default, it will provide a class which will look like 

@SpringBootApplication
public class NewtestApplication {

	public static void main(String[] args) {
		SpringApplication.run(NewtestApplication.class, args);
	}
}

As you can see this is the main class and all the execution starts here. Also, note the @SpringBootApplication annotation. Spring documentation states that

“The @SpringBootApplication annotation is equivalent to using @Configuration, @EnableAutoConfiguration, and @ComponentScan with their default attributes”

For this example, we will keep it simple and introduce a controller 

@RestController
public class HelloController {
	
	@GetMapping("/sayhello")
	public String sayHello() {
		return("Hello");
	}
}

Finally, Run the main class as a normal Java application, it will automatically start the Spring Boot server at 8080.

We can now access our application at http://localhost:8080/sayhello

Updating Java version in Linux

Recently I upgraded my Java version from 9 to 10 on a Linux machine. I was able to set JAVA_Home in .bashrc file properly but version did not get updated when checked java -version on shell.

Following commands helped to change the system’s Java version

sudo update-alternatives --install "/usr/bin/java" "java" "/path/to/jdk-10.0.1/bin/java" 1

And then 

sudo update-alternatives --config java

This showed all the Java versions available and I was able to choose correct version i.e. 10.
Similary executed same commands for java compiler. 

sudo update-alternatives --install "/usr/bin/java" "java" "/path/to/jdk-10.0.1/bin/javac" 1
sudo update-alternatives --config javac