agile-process

Agile Software Development

Although every team has its flavor of following and implementing the Agile software development process, some best practices can be followed to have a streamlined development process.

Vision: Every project starts with a vision. Vision is captured as a high-level (60,000 feet) view of the project. The stakeholder defines their vision in a few sentences.

I want to develop a mobile banking platform.

Project Planning in Agile Software Development: Once the vision is defined, it’s time to get together with stakeholders, project managers, engineers, etc., and develop a high-level (30,000 feet) view of the project by defining Epics. These Epics intend to capture the feature set required for accomplishing the overall vision.

EPIC-1: Customers can send money to other members using their phone numbers.

agile software development process

Milestone Planning: After capturing Epics, project milestones need to be defined, which will also help in release planning. Based on priorities, Epics are assigned to milestones in an Agile Software Development Process.

Milestone 1.0 will include EPIC-1, EPIC-2, and EPIC3.

Milestone 2.0 will consist of EPIC-4 and EPIC-5.

agile software development process

Sprint Planning: Engineers commit to developing these prioritized features during the sprint planning sessions. In these sessions, engineers get together with the product owners and stakeholders to dive deep into the committed features. It is essential to define acceptance criteria during this process.

agile software development process

Story Estimation: Engineers vote on estimating the features in this Agile Software Development stage. Estimation determines the effort level required to implement the story. Every team has its flavor of assessment. Some follow the Fibonacci series, and some follow the number of days, etc. The story is broken into smaller stories if the estimate is too big and can not be completed in one sprint. The story should be short enough to be completed within the sprint.

agile software development process

Iteration Start: Stories are then assigned to the next iteration. Engineers start working on it when the iteration begins. Iterations represent the heartbeat of the project. Iterations are usually between 1–4 weeks, but most teams follow two-week iterations. At the end of the iterations, there should be some demo-able product.

agile software development process

Daily Stand Ups: Quick feeback is vital to the Agile Software Development process; therefore, the engineering team meets with their product owners daily and provides updates on the project progress. These updates are short and are focused on three things.

What did I do yesterday?

What do I plan on doing today?

Does something block me?

agile development process

QA: Good quality software is essential for the project’s success. Therefore it is also crucial to ensure the software is built per acceptance criteria, can handle various error scenarios, and meets the security and performance criteria. All these are verified and tested during the QA phase. Once the engineer feels comfortable with the implementation, the story becomes Demoable.

agile development process

Demo: At the end of the iterations, there should be some demo-able stories. During the demo meeting, engineers demo the completed stories to the product owner and stakeholders. If the demo meets the acceptance criteria defined in the story, the story is accepted and considered complete else; it goes back to in progress.

agile development process

Retrospectives: A retrospective meeting usually follows a demo meeting. During the retrospective, the team reviews their performance and deficiencies. They focus on identifying what worked and areas that need improvement. Once the team identifies problem areas, they brainstorm for a solution. They pick a solution to try out in the next iteration, and that’s how they engage in a continuous improvement cycle. Retrospectives are also the time for the team members to appreciate or encourage each other.

Release:

After achieving a milestone during the Agile Development Process, a project release may be necessary to get the project out in the hands of the customers and get early feedback.

Feedback: After the software is released, feedback is collected, and more stories or epics are added to either improve an existing feature or add a new feature.

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We follow all these steps of the Agile Software Development process while developing our client’s application. For that reason, we can deliver quality products within tight deadlines without compromising on quality.

microservices

Microservices? What’s in it for me?

I would like to set the stage for this article with an opening sentence.

Microservice architecture is not a swiss army knife

Understanding this phrase will make us ready to dive into the world of Microservices and discover its advantages as well as drawbacks. This phrase will help us perceive if Microservices Architecture is the right choice for our next project.

Microservices architecture is a way of architecting software applications involving multiple self-contained services. Each service provides specific business functionality and follows its own development and deployment cycle. This is synonymous to the Lego bricks which can be connected to create different objects. Similarly, multiple microservices can be mashed up to create an application that provides a more concrete value to the end users.

Microservices thus offer a reusable infrastructure which can be used in different contexts, e.g., a Messaging app encapsulates messaging service so it can be used with a Banking App, eCommerce App, Ticketing App, etc. It encapsulates the messaging domain so that other applications don’t have to worry about re-inventing the wheel for the messaging system.

Microservices are genuinely independent of each other; they are loosely coupled without any binary dependency between them. They only use each other’s services defined by messaging protocols or external API contracts.

Each of these services can evolve independently, one thing to keep in mind is that these services need to be evolved in a backward compatible way. If care is not taken, it will create a situation where other microservices need to be deployed in lock-step.

Microservices are small, easily manageable applications; therefore it is easy for engineers to get up to speed and be able to contribute without understanding the overall applications architecture. If the whole system is reasonably complex, this also helps with creating agile teams that focus on particular microservices.

Microservices are easy to test, writing the end to end acceptance or integration tests do not require a pile of data to be set up. Each microservice focuses on its domain; therefore data setup for testing is relatively straight forward.

Each properly crafted microservice has its database, which is chosen based on the requirements for that particular domain. Significant schema changes in one microservice do not affect other microservices. This helps tremendously with fewer down times.

If one microservice is hit with the outage, it does not have a significant impact on the usability of the entire system, as other microservices continue to provide their services. This, however, may not be true in case of a microservice which is central to the system such as Authentication App.

Each microservices can use the technology stack, including development language, frameworks, databases, etc suitable for solving problems for that particular domain.

In terms of security, even though microservices have a larger surface area that needs to be secured, but even in case of a breach, only the data managed by that microservice is at risk. Other microservices are not affected as they either have their separate databases or if they share the same database, they will have a different schema and credentials.

Best of all each service can be deployed on the most optimized hardware for that service. If one service requires more memory whereas others require more CPU, then they can each be deployed on the hardware which fulfills those requirements.

Microservices have a fairly small footprint; therefore it takes less time to build and launch, this helps engineers tremendously, giving them the ability to make changes and get much quicker feedback.

Deployment of microservices is effortless, provided they are enhanced in a backward compatible fashion. So utmost attention should be paid not to make changes which will break the contract with external clients, as it will require external clients to be upgraded in lockstep.

Microservices applications are easy to scale, it is easy to identify highly utilized services and focus on scaling just those services rather than scaling the whole infrastructure.

So far we were focused entirely on the good parts of microservices. However, as I mentioned early, it’s not a one size fits all architecture. It is well suited for some applications but not for others.

One issue is with designing the microservices, as it is difficult to come up with a microservice with well-defined boundaries. If the microservices are not crafted with the correct boundaries, they can drive the application towards a big, and messy dependency web. Where each microservice depends on various other services which in turn depend on more services and so on, microservices need to be modularized based on the business domain or functional boundaries which have minimal dependency on each other.

Transaction management across multiple services is the most challenging part of the microservice architecture. Imagine on an e-commerce website, a customer places an order by calling order management microservice, and payment processing is handled by some other microservice. What will happen if the order is placed successfully, but the payment processing fails. There needs to be appropriate infrastructure in place to reverse the order if the payment fails, which of course would be more challenging to handle compared to transactions handled at the database level.

If we look at the overall application comprising of multiple microservices, there are more moving parts, so a lot more places where things can go wrong.

Debugging an issue in microservices based platforms is also exceptionally difficult. The request has to travel through multiple microservices, so pinpointing the exact location where an error or exception occurred is cumbersome.

Hopefully, the advantages and disadvantages outlined in this article will help the reader decide which architecture to choose when designing an application.

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Not knowing these cloud storage differences can impact success of your project

Storage is an essential component of any architecture. Storage is necessary because it is responsible for storing valuable data produced by the applications. Whether you are an architect or an application developer, you need to understand various storage options, their differences, and the applicable use cases. Knowing this will help you choose the right storage solution for your application and avoid any headaches down the road.

This blog will talk about different storage options and the portfolio of equivalent storage services offered by AWS. I will also discuss use cases that each solution supports.

Choice of storage option is influenced by the semantics of the data that need to be stored or processed. These semantics often define specific scalability, durability, and availability requirements. Therefore it is vital to understand the project’s needs, criticality, and sensitivity of the data, before selecting a particular storage technology.

Block storage: is the one that architects and developers are most familiar with. In this storage technology, each file is divided into several blocks or chunks and stored on the hard disk attached to the server. The disk is usually formated as NTFS, ext3, or some other standard. This technology is mostly used in environments that require frequent updates of the stored files such as databases. As these files are stored in chucks, only the changed section of the file needs to be updated.

Amazon Elastic Block Store — EBS is the block storage solution in AWS Cloud. Before using EBS, you need to mount it to an Elastic Compute Cloud EC2. However, once it is mounted, it can not be mounted to another EC2 instance simultaneously. Therefore it does not support simultaneous access of data from different compute resources. If the EC2 instance stops or terminates, the data on EBS is not lost and can be mounted to another EC2 instance for access.

File Storage: File Storage is also well known among consumers and developers alike. Nowadays, it is common to have an external Network Attached Storage — NAS to store large files or for backups. NAS Servers empower this type of file storage. This storage solution allows sharing of data between different servers over the network.

Amazon Elastic File Storage — EFS is a file-based storage solution available in AWS Cloud. Data in EFS backed storage can be easily shared between multiple EC2 instances.

For Windows-based high-performance workloads, Amazon FSx provides a similar file storage solution.

Object Storage: Object storage is a modern storage technology of the internet. Although both EBS and EFS need to be mounted to EC2 instances, object storage is an entirely independent storage service. Any client that supports the HTTP protocol can communicate with object storage over the internet using API calls. If there is a change in the file in this storage solution, the complete file needs to be replaced.

Amazon Simple Storage Service — S3 is the object store provided by AWS. There are multiple ways to interact with S3, either using AWS Console, AWS CLI, or AWS SDK regardless; the underlying communication occurs using API calls over the HTTP protocol. S3 provides virtually limitless amount of data storage and can empower various workloads such as data lakes.

In summary, AWS provides multiple storage solutions to support different workload requirements. It would be best if you understood the pros and cons of each storage technology to use them effectively.