A Long Hard Look at AIOps

A Long Hard Look at AIOps

AIOps or Artificial Intelligence for IT operations means applying artificial intelligence (AI) to improve IT operational effectiveness. AIOps makes use of aspects like analytics, big data, and machine learning abilities to perform its functions like –

  • Gathering and aggregating large and ever-increasing amounts of operations data created by several IT infrastructure components, performance-monitoring tools, and applications.
  • Intelligently zeroing in on the ‘signals’ in all that ‘noise’ to categorize important patterns and events associated with the availability issues and system performance.
  • Diagnosing root causes and reporting them to the IT section for swift response and recovery actions. In some cases, it helps to resolve these issues automatically without any need for human intervention.
  • Enabling IT operations teams to react rapidly by replacing several individual, manual IT operations tools with one intelligent and automated IT operations platform. It also helps to avoid slowdowns and outages proactively, without effort.

Many experts believe that AIOps will become the future of overall IT operations management.

 

A Long Hard Look at AIOps

The Need for AIOps

Nowadays, several organizations are abandoning the traditional infrastructure consisting of individual, static physical systems. Today, it’s all about a dynamic combination of on-premise, managed, private, and public cloud settings. They prefer running on virtualized or software-oriented resources that upgrade and reconfigure continually.

Various systems and applications across these environments create an ever-rising tidal wave of operational data. The average enterprise IT infrastructure, as estimated by Gartner, produces three-times extra IT operations data annually.

Traditional domain-based IT management solutions can be brought to their knees by volume of data. Intelligently sorting the important events out of the mountain of data is a dream, at best. Correlating data through various but interdependent environments is out of the question. Adding to that, providing predictive analysis and real-time insight for IT operations teams and enabling them to respond to issues promptly, becomes unrealistic. Then, we could wave goodbye to meeting user and customer service level expectations.

With AIOps, you can secure deep visibility into data performance and dependencies through various environments through a unifying solution. You can analyze the data and parse out significant events associated with outages or slowdowns. It can automatically alert IT staff to the issues, their origin and suggest actionable solutions.

 

How does AIOps work?

The easiest way to understand the working of AIOps is by reviewing the role played by each AIOps component. It includes machine learning, big data, and automation in the operational process.

AIOps makes use of big data platforms to combine siloed IT operations data. This includes:

  • System logs and metrics
  • Historical performance and event data
  • Streaming real-time operations events
  • Incident-related data and ticketing
  • Network data, including packet data
  • Related document-based data

AIOps then taps focused on machine learning and analytics capabilities.

  • Individual important event alerts from the ‘noise’: AIOps applies analytics like pattern matching and rule application to sift through the IT operations data and individual signals that denote any important anomalous event alerts.
  • Recognize the origin of the issues and suggest solutions: By utilizing environment-specific or industry-specific algorithms, AIOps can compare abnormal events with other event data from all the environments to pinpoint the reason for any performance or outage problem and propose apt remedies.
  • Automate responses together with actual proactive resolution: AIOps can route alerts automatically and suggest solutions to the right IT teams. It can also generate response teams depending on the problem’s nature and the solution. In several instances, it can process the results from machine learning to activate automatic system responses. It can address the problems happening in real-time, even before the users become aware of their occurrence.
  • Learn always to improve future managing problems: Depending on the machine learning capabilities, analytics AIOps can alter algorithms or develop new ones to recognize problems before occurrence and propose practical solutions. AI models can also support the system to learn about and become accustomed to environment changes, like a new infrastructure installed or reconfigured by DevOps.

Benefits of AIOps

The all-encompassing benefit of AIOps is that it allows IT operations to detect, address, and resolve outages and slowdowns quicker than manually through alerts from several IT operations tools. It results in quite a few benefits, such as –

  • Attain faster mean time to resolution (MTTR): AIOps can identify the root causes of problems earlier and more precisely than humanly possible. It helps the organizations to fix and attain ambitious MTTR goals. For instance, Nextel Brazil, a telecommunications service provider, could minimize incident response times from 30 minutes to 5 minutes with AIOps.
  • Moving from responsive to proactive to prognostic management: AIOps keeps on learning and better detects less-urgent signals or alerts as opposed to more-urgent circumstances. It can offer predictive alerts that allow the IT teams to address impending problems before they cause outages or slowdowns.
  • Streamline IT operations and IT teams: As an alternative to being buried under every alert from every environment setting, only alerts that meet particular service level thresholds or parameters can be sent to AIOps operations teams. It carries the full context necessary for the team to decide on the best possible diagnosis and carry out the fastest corrective measure. As AIOps keeps on learning, improving, and automating, it results in more efficiency with less human effort. Your IT operations team can concentrate on tasks that bring immense strategic value to the business.

AIOps Use-Cases

On top of optimizing IT operations, the visibility and automation support offered by AIOps can help drive other vital aspects of business and IT initiatives. Some of its use cases are as follows –

  • Digital transformation: AIOps is designed to handle complex digital transformation in IT operations. It encompasses virtualized resources, multiple environments, and dynamic infrastructure. This enables freedom and flexibility.
  • Cloud adoption or migration: Cloud adoption is a gradual process. The norm is a hybrid and multi-cloud setup with several interdependencies that can alter too frequently and quickly to document. AIOps can radically decrease the operational risks by offering a clear vision of the interdependencies in cloud migration in such situations.
  • DevOps adoption: DevOps drives development forward by offering more power to setting up and reconfiguring infrastructure for the development teams. However, IT still has to tackle that infrastructure. AIOps offers the necessary automation support to DevOps for effortless management.

AIOps promises to decouple organizational ambitions from the management headache imposed by ballooning IT Infrastructure. This intelligent, automated, and optimized approach to managing the IT backbone could well become an enterprise technology mainstay soon.

Get AIOps Suggestions From our Experts

Best CI/CD Practices

What It Takes To Get CI/CD Right?

The world of software development has changed significantly over the past decade. Applications are everywhere. Mobile and web-based digital channels are the preferred routes for consumers. Expectations are rising on, what seems like, a daily basis. And that holds true for enterprise users as well as common folks.

Developers are increasingly under pressure to keep their codebases agile and open to extensions and upgrades always. Traditional modes of product, app, and solution delivery have found themselves turning to the DevOps methodology in search of ways to address ever-evolving customer needs. DevOps is helping bring much-needed flexibility and agility into practices that developers follow while building the digital assets today’s world demands.

Best CI/CD Practices

One foundation of DevOps relies on automating the deployment of new code versions for a digital offering. This automation has 2 critical categories into which activities fall:

In simple terms, CI and CD are development principles that encourage automation across the process of an app development project. This empowers developers to make continuous changes in their code without disrupting the actual application that may be in use by end-users. Automation helps development teams deliver new functionalities faster in the product. This allows continuous product iteration.

In wake of the COVID 19 pandemic, software development teams across the world became more distributed than ever. For them, effective collaboration determines the efficiency of the software engineering process. In this scenario, CI and CD-led automation can also lead to better software quality and promote active collaboration between different teams working on a software project like Front-end, back-end, database, QA, etc.

Despite the benefits, several organizations are still not very confident in turning to CI and CD their deployments. A recent survey pointed out that only 38% of the 3650 respondents were using CI and CD in their DevOps implementations.

We believe that one of the key reasons for the slow adoption of CI and CD is the lack of awareness of what it takes to get CI/CD right. With that in mind, let us take a look at some of the best practices in CI/CD that every organization involved in developing digital applications must cultivate in their software engineering teams:

1. Treat CI and CD Individually:

While the end product requires a combination of CI and CD, the operational style for a DevOps-enabled project necessitates that development teams need to focus equally on CI and CD as two separate entities.

In CI, they can manage code changes that are smaller in size for either adding a new feature to an existing software product or making modifications or corrections of faults in the same. In CD, developers have to focus on transitioning their code from release to production through a series of automated steps that encompasses building and testing the code for readiness and finally sending it to end-user view. CI may be easier to implement and companies can focus on moving ahead with CI first and then slowly set the pace for CD which encompasses testing, orchestration, configuration, provisioning, and a whole lot of nested steps.

2. Design a Security-first Approach:

One of the key outcomes of implementing CI and CD is that organizations are equipped to make changes and roll out these changes to production on demand. At that accelerated pace, however, vulnerabilities may creep into the application due to confusion about roles and permissions.

Therefore, it is essential to bake security into the application at every step. Apart from focusing on the architecture and adopting a comprehensive safety posture, it is also essential to address the human element, often the weakest link in security. As a best practice, people need to be assigned specific roles and permissions to be able to perform only what they are tasked to do and not access sensitive or confidential application components in production. Valuable deliverables can be protected by enabling role-based access control for staff who practice CI and CD regularly in their development activities.

3. Create an enabling Ecosystem:

The technology leaders of organizations must make the effort of educating team members about the fact that CI and CD are part of holistic app development and delivery ecosystem and not a simple “input-output” process that can be linearly handled like in an assembly line.

Much is spoken about the need to create a culture of adherence to such practices. A key element of that culture is inculcating process discipline. DevOps, in general, and CI and CD, in particular, hold the potential to dramatically accelerate product delivery timelines. At that pace, alignment is super-critical. The people, processes, and tools must be brought into one page, roles defined, standards assured, and integrations meticulously planned to ensure that the activity moves forward with all stakeholders understanding and drawing value from the implementation.

4. Improve with Feedback:

The fundamental objective app development teams seek to achieve with CI and CD is the ability to release fast and iterate often. This only makes sense when the product iterations, feature additions, and quality improvements are driven by the need to give the users what they need. Also, as with any software development paradigm, applications built with CI and CD can be susceptible to incidents, defects, and issues in their lifecycle. Therefore, it is important for app development teams to build processes that allow them to capture user feedback, work it into the product (or app), test it for its ability to deliver value to the users, and release it fast. Teams must gain feedback, identify patterns through retrospective analysis, and use this learning to improve future CI and CD deployments.

CI and CD open the doors to higher-quality software. Organizations that leverage CI/CD best practices and concepts will gain the ability to differentiate their digital assets from the competition. With faster time to market and lower defects guaranteed, CI and CD help create a development ecosystem suited for high-end products needed by the consumers of today.

Get CI/CD Suggestions From our Experts

Test automation in Devops World

Test Automation in the DevOps World

It’s reasonable to assume that DevOps has two parallel, and equally important, objectives. One primary aim of DevOps is to reduce the development lifecycle with continuous delivery of software to the clients and end-users and the other crucial objective is to improve the software quality. 

It’s never been up for debate that testing is an extremely critical phase in software development. Now, with transformations in the development cycles with fast-paced approaches, such as DevOps and Agile, how we look at testing has evolved. It is now essential to implement smart ways of testing software products and applications. Test automation is one of the approaches to improve testing speed and accuracy. 
Test automation in Devops World

DevOps Testing Strategy 

Before moving to the test automation mechanisms in the world of DevOps, it is necessary to make a pitstop to examine the factors feeding into the DevOps testing strategy. DevOps supports and includes a continuous testing strategy which means testing is conducted at every phase of the process. Testers are involved in the testing of the development plan, design testing, and operations testing with functional and non-functional testing. For example, risk-based or exploratory testing can be executed to test the software designs. When it comes to releasing, the combination of tests can run on the production and test environments.

The primary idea in the DevOps testing strategy is to continuously look for possible gaps and errors. DevOps involves testing right from the initiation till the very end.

Test Automation and DevOps

As stated earlier, DevOps supports and follows a continuous testing strategy. Also, continuous development and delivery are involved in DevOps. At that pace, a high level of collaboration and fast-paced execution is required to meet the expected efficiency and quality levels. 

This is where test automation becomes the key to support the DevOps practices and make sure software quality is always maintained and improved. Some of the best practices for beginning test automation include: 

  • Begin with the test automation flows that are easy and increase the complexity and coverage over time.
  • Develop independent and self-contained automation test cases.
  • Maintain collective ownership during test automation.
  • Collaborate with design, development, and deployment teams.

While following the practices illustrated above, the Test Automation Engineers may still get confused about the mechanisms to integrate these with DevOps. A common workflow is presented below to enable test automation teams to amalgamate automation testing in DevOps practices. 

  • The test engineers shall meet with the developers to discuss the user story and list down the behaviors from a business standpoint. The behaviors identified shall then be converted to Behavior-driven development (BDD) tests
  • Developers shall work on the user story and create unit and integration tests in collaboration with the testing team under test-driven development (TDD). The shared code repository shall be set-up and the tests and codes must be deployed in the repository. 
  • DevOps Engineers shall create Continuous Integration (CI) servers to execute the code in the shared repository and execute all the tests in TDD and BDD. 
  • Automation Engineers shall analyze these workflows and tests to create the automated test scripts. The engineers shall also develop additional tests around performance, security, and non-functional testing. 
  • DevOps Engineers shall reuse the test scrips loaded in the shared repository for acceptance testing.

DevOps’ continuous testing strategy involves several resources and the Automation Test Engineers must collaborate with these resources to effectively conduct test automation.

DevOps Test Automation Tools 

Obviously, there are many test automation tools available in the market, and making the right choice is complex. To conduct test automation in DevOps, the tool selected must have the following features: 

  • Seamless integration in the CI/CD pipeline. 
  • Platform-independence to run in any of the infrastructures. 
  • Multi-user access to be used by testers, developers, and others at the same time. 
  • The short learning curve for better release management. 
  • Maintenance of automation tests and scripts.
  • Multiple language options – JavaScript, PowerShell, C#, etc.

Each tool will come with a set of features and benefits that will decide its aptness for each specific situation. For instance, TestComplete is a typical automation tool that can meet some test automation requirements in DevOps. This is an automated UI testing tool that can support a variety of test cases with enhanced test coverage. The tool comes with record and replay capabilities and an AI-equipped customizable object repository. Tools like these can allow automation test engineers to develop end-to-end tests quickly and efficiently. Good test automation tools can be easily integrated with the various continuous integration systems. Given the prevailing environment with remote teams, it’s also useful to look if the tool comes with distributed testing capabilities. The right set of features will help enhance the testing abilities of the team and also simplify the maintenance tasks. 

The bar for software quality has been raised very high and the consequences for failing this test can be dire for a product or application. In the uber-accelerated world of DevOps, software testing has to take on a completely new dimension. Given the need to test more, test faster, and test better, automation presents itself as the most appropriate strategy to achieve software quality. 

Is your Software Testing Strategy DevOps Ready?

 

all you need to know about devops containers

All You Need to Know About Containers

Visualize this: In the coming two years, more than 500 million new applications will be built — a number equal to total applications developed in the last four decades. 

This explosion in applications will be the result of businesses’ efforts to turn into “digital innovation factories”. Intrinsically, businesses will create digital products and services with speed and scale that will be at the heart of their digital value proposition. And a number of these applications will be built and deployed in containers. 
all you need to know about devops containers

Container-powered infrastructure is pulling enormous interest world-wide because containers enable agile and automated deployment of modern applications at scale and economy. A single server can host several containers as compared to virtual machines (VMs) for higher utilization. Considering the speed, efficiency, and practicality of containers in managing cloud-native applications, businesses are adopting containers at never before rates.

Here are five things that you must know about containers:

  1. Containers Enhance Continuous Integration (CI) and Continuous Delivery (CD) Processes:

  2. The advancement in continuous integration and continuous delivery processes has enabled developers to implement and deliver applications rapidly and frequently. Containers drive CI/CD advantages further via portability. When each container can be seamlessly and dependably moved to different platforms, like between a developer’s device and a private/public cloud, CI/CD processes become seamless. 
     
    Containers can also be replicated or scaled without suspending other processes, and each container’s individuality enables applications to be developed, tested, deployed, and modified simultaneously, thereby eliminating interruptions and delays. By utilizing containers combined with CI/CD, the entire software delivery life cycle (SDLC) speeds up, with lesser manual tasks, and challenges of migrating between different environments. 

  3. Containers Refashion Legacy Applications:

  4. Most businesses don’t have the luxury to build “all-new” applications for cloud-based platforms. Rather they prefer migrating existing or legacy applications to the cloud. Many applications can utilize the ‘lift and shift’ approach to the cloud, signifying that most will need to be radically refactored to benefit from the cloud features as code alterations are made. The applications are revamped, recoded, and repurposed for cloud platforms giving the application – a new purpose. 
    This is not easy, and there are innovative technologies that need to be considered. Applications are enabled to externalize APIs, and microservices allow applications to leverage the best functionality on cloud platforms. Containerization of the applications guarantees a seamless distributed architecture and cloud-to-cloud portability. 
    Containerizing legacy applications comes with several benefits, such as reducing complexity by utilizing container abstractions. The containers eliminate the dependencies on the underlying infrastructure services, which further lessens the complications of dealing with those platforms. This implies that developers can abstract the access to resources, like storage, from the application itself. This makes the application portable, but at the same time also speeds the refactoring of the applications.

  5. Containers Create Dependable and Resilient Environments:

  6. With the help of Kubernetes, containers can either operate on the same server and utilize similar resources or can even be distributed. Individual containers allow the parallel development of applications and ensure that a break down in one application does not disturb or cause a failure in other containers. This isolation also enables teams to quickly detect and fix technical problems without triggering any downtime in other areas.
     
    Containers offer the best of both worlds, enabling resource sharing while reducing downtime and permitting teams to prolong developing innovative functions. The result is highly-efficient environments that enable teams to march forward with software development and delivery, although other teams are caught up testing or fixing errors.

  7. Containers – A Better Option for Virtualization:

  8. In the conventional approach of virtualization, a hypervisor virtualizes physical hardware. Every virtual machine holds a guest OS, a computer-generated copy of the hardware that the OS needs to stream, and an application and its related libraries and dependencies.
    Rather than virtualizing the fundamental hardware, containers virtualize the operating system (usually Linux), so every independent container encompasses only the application along with its libraries and dependencies. Containers are slim, speedy, and portable because, as opposed to virtual machines, containers don’t require a guest OS in every instance and can utilize the features and resources of the host OS.
    Just like virtual machines, containers enable developers to enhance CPU and memory utilization. However, containers go a step further because they also power microservice architectures, where application components can be employed and scaled more minutely. This is a lucrative option to scale up a monolithic application because a single component takes the load.

  9. Containers Offer Superior Performance:

  10. The slashed resource load is a key reason for businesses to leverage containerized platforms over virtual machines. Containers provide more than ten times the density suggesting that developers can operate up to ten times more containers in a single host.  

    Additionally, hypervisors are susceptible to latency issues. As compared to virtual machines, containers considerably reduce latency. Furthermore, containers load much faster than virtual machines. Containers thus offer a substantial boost in performance by decreasing the resource load and latency. And the quicker load time caters to a seamless user experience.

Containers will continue to grab market share from conventional virtualization technologies. This technology is already fast-tracking digital transformation and application modernization efforts for several businesses and across diverse applications. We may not physically see containers being utilized, but the truth be told, we utilize them every day. Be it Google or Netflix, we are using containers every day in the back end. 

The adoption of containers is real and is revolutionizing how businesses are deploying IT infrastructure. From rapidly delivering applications to amplifying development to deployment processes, to slashing infrastructure and software costs, containers offer brilliant business outcomes to application developers. 

 

Is your DevOps initiative pushing up your Cloud bills?

First, there were developers. And then software development got more challenging, more complex, less straightforward. That resulted in the emergence of a new “combo” discipline – DevOps. DevOps was seen as a medium for fuelling software teams into supercharged IT powerhouses.

DevOps was introduced to improve collaboration. It is a working culture that smashes the conventional siloes between software development, quality assurance, and operations teams, empowering all application life-cycle stakeholders to work collectively – from conception to design, development, production, and support.

But all is not what it seems in the world of DevOps. DevOps puts pressure on teams to deliver faster releases while scaling with demand. On this path, the cloud is one of the significant resources needed to make a DevOps environment run smoothly. And this is where the challenge lies.

Where Does The Cloud Come Into Picture?

DevOps fast-tracks the growth in cloud infrastructure needs far beyond what conventional application development methods may have required. As the organization shifts from monthly to daily releases, the infra needs keep scaling, often in an unplanned manner.

If DevOps is the most significant transformation in the IT process in decades, renting infrastructure on demand was the most disruptive transformation in IT operations. With the change from traditional data centers to the public cloud, infrastructure is now leveraged like a utility. Like any other utility, there is a waste here too. (Think: leaving the fans on or your lights on when you are not home.)

The extra cloud costs encompass several interrelated problems: ongoing services when they do not need to be, wrongly sized infrastructure, orphaned resources, and shadow IT. People leveraging AWS, Azure, and Google Cloud Platform are either already feeling the pressure — or soon will. Since DevOps teams are primarily cloud users in many organizations, DevOps cloud cost control processes must become a priority in every organization.

Why Is It So Challenging For Organizations To Get Their Cloud Costs Under Control?

In an excellent analysis on CIO.com, the following three challenges were highlighted :

  1. Playing too safe with Cloud Provisioning:

    During most of the primary generations of public cloud initiatives, the goal of the DevOps team was the development speed and quality of the solution. In the standard three-way trade-off of products, organizations can accomplish two of three goals – speed, quality, and low-cost – but not all three. Often, low cost has been the odd-man-out. With a “better-safe-than-sorry” attitude, several DevOps teams habitually purchased more cloud capacity and functionality than their solutions needed. More capacity means more cost.

  2.  Complex public cloud offerings:

    As public cloud platforms like AWS and Microsoft Azure are maturing, their portfolios of service options have radically grown. For example, AWS catalogs roughly 150 products grouped under 20 categories (compute, database, developer tools, AI, analytics, storage, and so forth). This sort of portfolio makes for roughly a million distinct potential service configurations. Incorporate frequent price changes for services and picking the best and most cost-effective public cloud options make assessing cell-phone plans look like child’s play. More complexity often means poor choices that drive higher costs.

  3. Lack of transparency and effective analysis:

    Organizations don’t have good visibility into how much infrastructure their cloud apps require to provide the necessary functionality and service levels. Without tools that provide such analysis, organizations can’t pick the best options, right-size existing public cloud deployments, or eliminate “deadwood” cloud apps that never got eliminated as DevOps teams moved on to create new cloud solutions. It’s time for organizations to get serious about optimizing and controlling their use of cloud resources and – in so doing – cutting unnecessary public cloud costs. To do this, they must utilize analytics tools and services that can offer actionable data about their cloud deployments and aid them to traverse through the jungle of public cloud service and pricing options.

The Cultural Behavior of Controlled Costs

While Continuous Cost Control is an idea that organizations must apply to development and operations practices right through all project phases, organizations can do a few things to begin a cultural behavior of controlled costs. Build a mindset and apply the principles of DevOps to control cloud costs.

  • Holistic Thinking: In DevOps, organizations need to think about the environment as a whole. Organizations have budgets. Technology teams have budgets. Whether you care or not, that also implies that DevOps has a budget, it needs to stay within. At some point, the infrastructure cost must come under scrutiny.
  • No silos: No silos imply not only no communication silos but also no silos of access. This applies to cloud cost control when it comes to challenges such as absconding compute instances running when they’re not required. If only one person in the organization possesses the ability to turn instances on and off, then that’s an undesirable single point of failure.
    The solution is removing the control silo by enabling users to access their instances to turn them on as and when they require them, utilizing governance via user roles and policies to make sure that cost control strategies remain uninhibited.
  • Quick and Valuable Feedback: In eradicating cloud waste, the feedback required is – where is waste occurring? Are your instances appropriately sized? Are they functioning when they don’t need to be? Are there orphaned resources eating the budget?
    Valuable feedback can also come in total cost savings, percentages of time instances were shut down over the previous month, and overall coverage of your cost optimization efforts.  Reporting on what is working helps organizations choose how to address the challenges. Organizations need monitoring tools to discover the answers to these questions.

Following this cultural behavior shift, DevOps teams can transition from preserving, archiving, and destroying data to collecting and utilizing it for data-driven insights. This transformation in mindset toward cloud removes constraints and enables to innovate faster and more susainably.

Act Now

Inspect your DevOps processes today and see how you can integrate a DevOps cloud cost control mindset. Consider automating cost control to lessen your cloud expenses and make your CFO’s life happier.

How microservices comes together brilliantly with DevOps?

How Microservices Comes Together Brilliantly with DevOps?

Do you know what’s common to Amazon, Netflix, and NASA?

All three of them use DevOps.

Amazon uses it to deploy new software to production at an average of every 11.6 seconds!

Netflix uses it to deploy web images into its web-based platform. They have even automated monitoring wherein they ensure that in the event of a failure in implementing the images, the new images are rolled back, and the traffic is rerouted to the old version.

NASA, on the other hand, used it to analyze data collected from the Mars Rover Curiosity.

It’s become such that every organization that focuses on quick deployments of software and faster go-to-market uses DevOps.

Statista reveals that 17% of enterprises had fully embraced DevOps in 2018 as compared to 10% in 2017.

Given the advantages, these numbers will only grow every year as companies transition from the waterfall approaches to develop fast, fail quickly, and move ahead on the principles of the agile approach.

But for DevOps to deliver to its fullest potential, companies need to move from the monolithic architecture of application development to microservices architecture.

What is Microservices Architecture?

Unlike monolithic architecture, where the entire application is developed as a single unit, Microservices structures applications as a collection of services.It enables the team to build and deliver large, complex applications within a short duration.

How can Microservices Work with DevOps?

Microservices architecture enables organizations to adopt a decentralized approach to building software. This allows the developers to break the software development process into small, independent pieces that can be managed easily. These developed pieces can communicate with each other and work seamlessly. The best part about microservices architecture is it allows you to trace bugs easily and debug them without leading to redeveloping the entire software. This is also great from the customer experience perspective as they can still use the software without any significant downtime or disruption. It’s a perfect fit for organizations that use DevOps to deploy software products.

No wonder organizations like Netflix, Amazon, and Twitter that were using a monolithic architecture have transitioned towards a microservices architecture.

Let’s look at the benefits of Combining DevOps with Microservice Architecture:-

  • Continuous Deployment: Remember the Netflix example we gave at the beginning about how Netflix reroutes the traffic to the old version of web images if they are not deployed on time? Imagine if Netflix still used monolithic architecture or the waterfall method of software deployment, do you think they would have been able to give the same kind of customer experience you witness today? Most likely, not! Microservices architecture coupled with DevOps enables continuous delivery and deployment of software, which means more software releases and better quality codes.
  • More innovations and More Motivation: Imagine working on a product for 2-3 years and then knowing it is not acceptable to the market!It becomes hard to pivot too. Often you realize that there are several bugs, the process has become unnecessarily lengthy, and you have no clue which team is working on what. Wouldn’t it lower your morale? However, those days have gone. Today, organizations have transitioned from a project to a product approach. There are smaller decentralized teams of 5-7 people that have their own set of KPIs and success metrics to achieve. This allows them to take ownership of “their” product and it gives them better clarity on the progress. It also gives them the freedom to innovate, which boosts their morale.
  • High-quality Products: With the power of continuous deployment and the freedom to experiment and innovate, organizations can continuously make incremental changes to the code leading to better quality products. It allows teams to mitigate risks by plugging the security loopholes, make changes to the product based on customer feedback, and reduce downtimes.

As you can see, using DevOps and microservices architecture together will not only boost the productivity of the team, but it will also enable them to develop a more innovative and better quality product at a faster pace. It helps product teams develop products in a granular manner rather than taking a “do it all at once” approach.

However, to embrace DevOps and microservices, you have to ensure that your teams understand the core benefits and make the most of the change.

Teams usually work in silos – the development team works independently, the testing team does its job, and so on. There is an obvious gap in communication, which leads to a delay in completing development and testing. DevOps and microservices require teams to work in tight collaboration. You will have to foster an environment where there are cross-functional teams of testers and developers communicating and working together to complete a task. This will help the teams to accelerate the process of developing, testing, and deploying their piece of work at a faster pace.

Of course, it is not easy to introduce a culture of collaboration, given that people are accustomed to working in silos. Hence, it is essential to reduce friction before starting the initiative. Once everyone shares in the vision and understands their own role in getting there, developing products with DevOps while leveraging a microservices architecture will become much easier.

microservices Application development in Devops age

Application Development with Microservices in the DevOps Age

Does anyone even remember when companies developed an entire product, tested it, fixed it, and then shipped it? The entire process would take months, even years, before a functioning product made it to the customer. Before the product hit the market, neither did the potential customers know what it held for them and neither did the product owners know if it would hit or miss the mark.

Today, product users expect to be a part of the development process. They want to contribute their insights to develop a product that matches their ongoing needs. The need is for continuous innovation and improvements. The need is for DevOps!

DevOps combines technology and cultural philosophies to deliver products and services quickly. It is a continuous process of developing, testing, deploying, failing, and fixing applications to achieve market-fit. Jez Humble, one of the leading voices of DevOps sums it up “DevOps is not a goal, but a never-ending process of continual improvement.”

Today, DevOps is not just for a handful of large enterprises. According to Statista, the number of companies adopting DevOps went up by 17% in 2018

A quick look at what has made DevOps popular?

Apart from the continuous innovations and improvements, DevOps also helps in:

  • Improving customer satisfaction: With a DevOps mindset, companies use advanced methods to identify issues and fix them real-time before the customer is impacted. There is also scope to improve the product on-the-go driven by frequent suggestions and feedback from customers. Continuous improvement in quality leads to customer delight. Take Rabobank of Netherlands, for example. This large financial institution has over 60,000 employees and hundreds of customer-facing applications. As the deployments were manual, the failure rate was over 20%, and they received many complaints about delays. When they moved to DevOps, they were able to deploy applications 30x more frequently with a lead time that was 8,000 times faster than their peers.
  • Change in organizational culture: DevOps has played a significant role in breaking silos and boosting the collaborative culture in companies. In an agile environment, working in silos can slow down the process of developing, testing, and releasing the product. A DevOps team will be able to collaborate better and ramp up the process of developing, testing, and troubleshooting the product. 
  • A decrease in failure rates: According to the State of DevOps report, high-performing DevOps organizations have seen a reduction of failure rates of 3x, thanks to their ability to find and fix errors early in the cycle.
  • Higher productivity: DevOps organizations can deploy products 200x more frequently than a non-DevOps organization, leading to happier and highly motivated teams. Take Microsoft’s Bing, for example. It has moved developers to a DevOps environment with the idea of continuous delivery and innovation deeply ingrained within their processes. The result? Bing deploys thousands of services 20 times a week and pushes out 4000 individual changes every week. The continuous effort by the team to deliver has made Bing the second largest search engine in the world.

While adopting a DevOps culture is essential for a company to thrive, it is also crucial that they have the right architecture and systems in place to complement their principle of continuous delivery and innovation. That’s where microservices is now playing a massive role.

Micro-services and Their Role in DevOps Organization:

For a long time, companies relied on a monolithic architecture to build their application. As monolithic applications are built as a single unit, even a small change in a single element made it necessary to build a completely new version of the application. 

With more and more companies moving towards DevOps, such a monolithic architecture makes it difficult to implement changes rapidly. The need for greater agility gave rise to a new type of architecture -enter microservices. 

With Microservices, an application is built on small, independent components that are independently deployable. Although independent, these components communicate with each other via RESTful APIs. So, even if a single piece of code has to be changed in a single element, the developer does not have to build a new version of the whole product. They can simply make the changes to the individual components without affecting the entire application, making the deployment efficient and faster. 

For companies that have adopted the DevOps culture, developing applications with microservices has several benefits that include:

  • Easy rectification of errors: When a component fails the test or requires changes, it is easy to isolate and fix. This makes it easier for companies to fix errors quickly without affecting the users of other services.
  • Better collaboration: Unlike a monolithic architecture where the different teams focus only on specific functions such as UX, UI, server, etc, a microservices architecture encourages a cross-functional way of working. 
  • Decentralized governance: Monolithic architecture uses a centralized database, while microservices use a decentralized method of governance, wherein each service manages its database. This makes it easier for developers to produce tools that also can be used by others to solve specific issues.

A key trend accelerating the adoption of Microservices in such scenarios is Containerization. Containerization allows code for specific elements to be carved out, packaged with all the relevant dependencies, and then run on any infrastructure. These applications can be deployed faster and can be made secure. The applications are extremely portable and adaptable to run on different environments. 

Companies like Amazon and Netflix have shifted to microservices to scale their business and improve customer satisfaction. 

Product companies aiming to become customer-centric and delight with continuous improvement in the product may find it essential to adopt a DevOps mindset married to a transition to the microservices architecture

Of course, it will take some time to transition product development. Teething problems are bound to arise, including duplication of efforts due to the distributed deployment system. However, given the larger picture and the potential benefits, it’s a wise move for product companies to make. 

How offshore development has changed with DevOps?

How Offshore Development has Changed With DevOps?

Offshore software development has never been easy. Neither has DevOps. Although both offer a distinct set of advantages to organizations, trying to do them together could be challenging. In addition to creating a culture of collaboration, new tools have to be adopted. Yet, many large global organizations have successfully built DevOps capabilities across time zones, while meeting requirements 24×7 – within time and budget. 

Here’s how Offshore Development has Changed with DevOps:

  1. The Improvement in Product Quality: Quality management has always been a basic requirement of software development, and also a popular way to control development costs. But with offshore development, quality management gained a reputation for being rigid and imbalanced. Offshore teams had a tough time balancing quality and costs. The perception grew that they could only focus on one aspect while overlooking the other. However, DevOps brings in a way for offshore development teams to drive quality and costs simultaneously. Since there is more collaboration between teams, bugs are identified quickly – which improves quality, and there is less rework – which reduces the associated costs. 
  2. The Stress on Culture: Offshore development teams have often focused on the tools and technologies needed to drive outcomes. However, with the advent of DevOps, there is a ton of business culture aspects to consider. When DevOps comes into the picture, it’s not just about tooling; teams have to work together and collaborate to drive the intended DevOps outcomes. Rather than looking at culture as a nice-to-have feature, offshore development teams have started to look at it as a core competency that lays the foundation of an efficient software development practice. 
  3. Accelerated time-to-Market: Since the dawn of offshore development, teams have been following the sun; once early analysis and design are complete, documentation is sent to remote developers to start coding and testing. However, what DevOps does, is turn all of this on its head; by seeking greater collaboration between teams, it helps them release software in bite-sized sprints – so teams can get more frequent visibility and feedback. Such an approach builds faster feedback loops, accelerates the velocity at which a company can test hypotheses about what the client wants – without wasted time and effort – and brings products to market sooner. 
  4. The Elimination of Hand-offs: Offshore development has also always been about hand-offs. When one person (or team) is done with a piece of work, a key milestone is achieved, and he/she then notifies the other to start working. However, what DevOps does is just the exact opposite. It enables different teams to work on aspects of software development in tandem, while greatly reducing the number of handoffs or delays. Teams do not have to waste time waiting for a “go-ahead” to start working; instead, they drive continuous collaboration through the entire development life cycle, keep track of tasks across coding, unit testing, build scripts, configuration scripts and avoid passing work back and forth. 
  5. The Growth of Analytical Dashboards: For offshore teams having a tough time getting visibility into project status, DevOps drives the use of analytical dashboards. These dashboards often serve the purpose of providing a single source of truth across the complete organization, while giving real-time updates on project status, issues, challenges, and improvement opportunities. Teams that leverage these tools find themselves resolving issues faster while making the entire process of offshore development far more effective.
  6. Handling out-of-Scope Requests: Offshore teams have always found it difficult to handle out-of-scope requests and cater to emergency patch-up works which come out of their schedule. This is mainly due to the differences in time zone. However, with DevOps, the project’s scope is clearly defined through several iterations of communication between the internal team and the offshore team. Any out-of-scope request can be accommodated, based on the availability of resources, as can urgent jobs which need immediate attention.  

Improve Software Development Outcomes: 

When the world embraced the offshore development model, the productivity gains and cost savings stimulated technological innovation for years to come. While offshoring helped businesses achieve their market and customer goals – quickly and more efficiently, it also paved the way for the adoption of methodologies and approaches to produce software more efficiently and effectively. 

DevOps is one such transformation, that is helping offshore teams break departmental siloes, and drive a cultural shift towards efficient software delivery. The changes range from dramatically improving software quality to accelerating time-to-market, eliminating wasteful hand-offs, to offering real-time visibility into product status while seamlessly handling out-of-scope requests. The impact of DevOps on offshoring has been phenomenal, and the approach will continue to boost offshore development outcomes for years to come.

5 Point Guide to Devops Strategy

The 5 Point Guide For A Successful DevOps Strategy

As the requirement for high-quality software in short time frames and restricted budgets increases, developers are looking for approaches that make building software a lot faster and more efficient. DevOps greatly helps in improving the software product delivery process; by bridging the gap between the development and operations teams, DevOps facilitates greater communication and collaboration, and improves service delivery, while reducing errors and improving quality. According to the State of Agile report, 58% of organizations embrace DevOps to accelerate delivery speed.

Tools for a successful DevOps Strategy

DevOps creates a stable operating environment and enables rapid software delivery through quick development cycles – all while optimizing resources and costs. However, before you embark on the DevOps journey, it is important to understand that since DevOps integrates people, processes, and tools together, more than tools and technology, it requires a focus on people and organizational change. Begin by driving an enterprise-wide movement – right from the top-level management down to the entry-level staff – and ensure everyone is informed of the value DevOps brings to the organization before integrating them together into cross-functional teams.

Next, selecting the right tools is critical to the success of your DevOps strategy; make sure the tools you select work with the cloud, support network, and IT resources and comply with the necessary security and governance requirements. Here’s your 5-point guide for developing a successful DevOps strategy and the tools you would need to drive sufficient value:

  1. Understand your Requirements: Although this would seem a logical first step, many organizations often make the DevOps plunge in haste, without sufficient planning. Start by understanding the solution patterns of the applications you plan to build. Consider all important aspects of software development including security, performance, testing, and monitoring — basically all of the core details. Use tools like Pencil, a robust prototyping platform, to gather requirements and create mockups. With hundreds of built-in shape collections, you can simplify drawing operations and enable easy GUI prototyping.
  2. Define your DevOps Process: Implementing a DevOps strategy might be the ideal thing to do, but understanding what processes you want to employ and what end result you are looking to achieve is equally important. Since DevOps processes differ from organization to organization, it is important to understand which traditional approaches to development and operations to let go of as you move to DevOps. Tools like GitHub can enable you to improve development efficiency and enjoy flexible deployment options, centralized permissions, innumerable integrations and more. GitHub allows you to host and review code, manage projects, and build quality software – moving ideas forward and learning all along the way.
  3. Fuel Collaboration: Collaboration is a key element of any DevOps strategy. It is only through continuous collaboration that you can develop and review code and stay abreast with all the happenings. With frequent and efficient collaboration, you can efficiently share workloads, enable frequent reviews, be informed of every update, resolve simple conflicts with ease, and improve the quality of your code. Collaboration tools like Jira and Asana enable you to plan and manage tasks with your team across the software development lifecycle. While Jira allows team members to effectively plan and distribute tasks, prioritize and discuss team’s work, and build and release great software together, Asana allows project leaders to assign responsibilities throughout the project; you can prioritize tasks, assign timelines, view individual dashboards and communicate on project goals.
  4. Enable Automated Testing: When developing a DevOps strategy, it is important to enable automated testing. Automated test scripts speed up the process of testing, and also improve the quality of your software by testing it thoroughly at each stage. By leveraging real-world data, they reflect production-level loads and identify issues in time. DevOps-friendly tools like Selenium are ideal for enabling automated testing. Since Selenium supports multiple operating systems and browsers, you can write test scripts in various languages including Java, Python, Ruby and more and can also extend test capability using additional test libraries.
  5. Continuously Monitor Performance: To get the most out of your DevOps strategy, measuring and monitoring performance is key. Given the fact that there will be hundreds of services and processes running in your DevOps environment, all of which cannot be monitored, the identification of the key metrics you want to track is vital. Tools like Jenkins can be used to continuously monitor your development cycles, deployment accuracy, system vulnerabilities, server health, and application performance. By quickly identifying problems, it enables you to integrate project changes more easily and deliver a functional product more quickly.

Improve Service Delivery

Implementing a DevOps strategy is not just about building high-quality software faster; it’s about driving a cultural shift across the organization to improve development processes and make it more efficient. Making the most of a switch to DevOps requires you to start with a new outlook, along with the use of new tools and new processes. By using the right tools at every stage, you can accelerate the product development process, meet time-to-market deadlines, and begin your journey towards improved service delivery and optimized costs.

Watch Out for these 8 DevOps mistakes

Watch Out for these DevOps Mistakes

The past few years have witnessed the meteoric rise of DevOps in the software development landscape. The conversation is now shifting from “What is DevOps” to “How can I adopt DevOps”. That said, the Puppet’s State of DevOps Report stated that high performing DevOps teams could deploy code 100 times faster, fail three times less and recover 24 times faster than the low performing teams. This suggests that DevOps, like with every other change in the organization, can be beneficial only when done right. In the haste to jump on the DevOps bandwagon, organizations can forget that DevOps is not merely a practice but is a culture change – a culture that breeds success based on collaboration. While DevOps is about collaboration between teams, continuous development, testing and deployment, key mistakes can lead to DevOps failure. Here’s a look at some common DevOps mistakes and how to avoid them.

  1. Oversimplification:
    DevOps is a complex methodology. In order to implement DevOps, organizations often go on a DevOps Engineer hiring spree or create a new, often isolated, DevOps department to manage the DevOps framework and strategy. This unnecessarily adds new processes, often lengthy and complicated. Instead of creating a separate DevOps department, organizations must focus on optimizing their processes to create operational products leveraging the right set of resources. For successful DevOps implementation, organizations must manage the DevOps frameworks, leveraging operational experts and other resources that will manage DevOps related tasks such as resource management, budgeting, goals and progress tracking.
    DevOps demands a cultural overhaul and organizations should consider a phased and measured transition to DevOps implementation by training and educating employees on these new processes and have the right frameworks in place to enable careful collaboration.
  2. Rigid DevOps processes:
    While compliance with core DevOps tenets is essential for DevOps success, organizations have to proactively make intelligent adjustments in response to enterprise demands. Organizations thus have to ensure that while the main DevOps pillars remain stable during DevOps implementation, they make the internal adjustments that are needed in internal benchmarking of the expected outcomes. Instrumenting codebases in a granular manner and making them more partitioned gives more flexibility and gives DevOps teams the power to backtrack and identify the root cause of diversion in the event of failed outcomes. However, all adjustments have to be made while remaining within the boundaries defined by DevOps.
  3. Not using purposeful automation:
    DevOps needs organizations to adopt purposeful automation – automation that is not done in silos like change management or incident management. For DevOps, you must adopt automation across the complete development lifecycle. This includes continuous delivery, continuous integration, and deployment for velocity and quality outcomes. Purposeful end-to-end automation is essential for DevOps success. Hence organizations must look at complete automation of the CI and CD pipeline. At the same time, organizations need to keep their eyes open to identify opportunities for automation across processes and functions. This helps to reduce the need for manual handoffs for difficult integrations that need additional management and also in multiple format deployments.
  4. Favoring feature-based development over trunk-based development:
    Both feature-based development and trunk-based development are collaborative workflows. However, feature-based development, a development style that provides individual features their isolated sandboxes, adds to DevOps complexity. As DevOps automates many aspects of the code between development and production environments, keeping different conceptual flavors around the codebase makes DevOps more complex. Trunk-based development, on the other hand, allows developers to work in a coherent and single version of the codebase and alleviates this problem by giving developers the capability to manage features through selective deployments instead of through version control.
  5. Poor test environments:
    For DevOps success, organizations have to keep the test and production environments separate from one another. However, test environments must resemble the production infrastructure as close as possible. DevOps means that testing starts early in the development process. This means ensuring that test environments are set up in different hosting and provider accounts than what you use in production. Testing teams also have to simulate the production environment as closely as possible as applications perform differently on local machines and during production.
  6. Incorrect architecture evaluation:
    DevOps needs the right architectural support. The idea of DevOps is to reduce the time spent on deploying applications. Even when automated, if deployment takes longer than usual there is no value in the automation. Thus, DevOps teams have to pay close attention to the architecture. Ensure that the architecture is loosely coupled to give developers the freedom and flexibility to deploy parts of the system independently so that the system does not break.
  7. Incorrect incident management:
    Even in the event of an imperfect process, DevOps teams must have robust incident management processes in place. Incident management has to be a proactive and ongoing process. This means that having a documented incident management process is imperative to define incident responses. For example, a total downtime event will have a different response workflow in comparison to a minor latency blip. The failure to do so can lead to missed timelines and avoidable project delays.
  8. Incorrect metrics to measure project success:
    DevOps brings the promise of faster delivery. However, if that acceleration comes at the cost of quality then the DevOps program is a failure. Organizations looking at deploying DevOps thus must use the right metrics to understand progress and project success. Therefore, it is essential to consider metrics that align velocity with throughput success. Focusing on the right metrics is also important to drive intelligent automation decisions.

To drive, develop, and sustain DevOps success, organizations must focus on not just driving collaboration across teams but also on shifting the teams’ mindset culturally. With a learning mindset, failure is leveraged as an opportunity to learn and further evolve the processes to ensure DevOps success.

Understanding The Terminology – CI and CD in DevOps

The path to building cutting-edge software solutions is often paved with several obstacles. Disjointed functioning of various development teams often results in long release cycles. This not only results in a poor quality product but also adds to the overall cost of development. For organizations looking to set themselves apart from the competition, it has become essential to embrace the world of DevOps and enable frequent delivery of good-quality software.

The Growth of DevOps

Conventional software development and delivery methods are rapidly becoming obsolete. Since the software development process is a long and complex one, the process requires teams to collaborate and innovate with each passing day. Models evolved -first it was Waterfall, then Agile, and now it’s DevOps – in order to meet the dynamic demands of the industry, and growing expectations of the tech-savvy user, the software development landscape is undergoing constant change. Today, DevOps is being seen as the most efficient method for software development. According to the recently released 2017 State of DevOps Report, high performing organizations that effectively utilize DevOps principles achieve 46x more frequent software deployments than their competitors, 96x faster recovery from failures, and 440x faster lead time for changes. There seems little room for doubt any longer about the impact of DevOps.

DevOps aims at integrating the development and operations teams to enable rapid software delivery. By fuelling better communications and collaboration, it helps to shorten development cycles, increase deployment frequency, and meet business needs in the best possible manner. Using DevOps, software organizations can reduce development complexity, detect and resolve issues faster, and continuously deliver high-quality, innovative software. The two pillars of successful DevOps practice are continuous integration and continuous delivery. So, what are these terms? What do they mean? And how do they help in meeting the growing demands of the software product industry? Let’s find out!

Continuous Integration

Definition: Continuous Integration (CI) aims at integrating the work products of individual developers into a central repository early and frequently. When done several times a day, CI ensures early detection of integration bugs. This, in turn, results in better collaboration between teams, and eventually a better-quality product.

Goal: The goal of CI is to make the process of integration a simple, easily-repeatable, and everyday development task to reduce overall build costs and reveal defects early in the cycle. It gets developers to carry out integration sooner and more frequently, rather than at one shot in the end. Since in practice, a developer will often discover integration challenges between new and existing code only at the time of integration, if done early and often, conflicts will be easier to identify and less costly to solve.

Process: With CI, developers frequently integrate their code into a common repository. Rather than building features in isolation and submitting each of them at the end of the cycle, they continuously build software work products several times on any given day. Every time the code is inputted, the system starts the compilation process, runs unit tests and other quality-related checks as needed.

Dependencies: CI relies heavily on test suites and an automated test execution. When done correctly, it enables developers to perform frequent and iterative builds, and deal with bugs early in the lifecycle.

Continuous Delivery

Definition: Continuous Delivery (CD) aims to automate the software delivery process to enable easy and assured deployments into production —at any time. By using an automatic or manual trigger, CD ensures the frequent release of bug-free software into the production environment and hence into the hands of the customers.

Goal: The main goal of CD is to produce software in short cycles so that new features and changes can be quickly, safely, and reliably released at any time. Since CD involves automating each of the steps for build delivery, it minimizes the friction points that are inherent in the deployment or release processes and ensures safe code release can be done at any moment.

Process: CD executes a progressive set of test suites against every build and alerts the development team in case of a failure, which then rectifies it. In situations where there are no issues, CD conducts tests in a sequential manner. The end result is a build that is deployable and verifiable in an actual production environment.

Dependencies: Since CD aims at building, testing, and releasing software quickly and frequently, it depends on an automated system that helps the development team to automate the testing and deployment processes. This is to ensure the code is always in a deployable state.

CI/CD for Continued Success

Software development involves a high degree of complexity that requires teams to embrace new and modern development methodologies in order to meet the needs of business and end-users alike. DevOps focuses on the continuous delivery of software through the adoption of agile, lean practices. The pillars of DevOps, CI, and CD, improve collaboration between operations and development teams and enable the delivery of high-quality software for continued success. RightScale estimates that over 84% of organizations have adopted some aspect of DevOps principles -it’s time you do too. As DevOps pundit Jez Humble rightly says, DevOps is not a goal, but a never-ending process of continual improvement”.

How to use between agile and Devops?

Agile? DevOps? What’s The Difference And Do You Have To Choose Between Them?

Any roles involved in a project that do not directly contribute toward the goal of putting valuable software in the hands of users as quickly as possible should be carefully considered.” – Stein Inge Morisbak

Does anyone remember the days when the Waterfall model was still around and widely adopted by the enterprises? Over the years most developers have stories of how they realized that it wasn’t giving the best results, that it was slow and inflexible as it followed a sequential process. Fast forward a few years and the principles of Kanban and scrum methodology organically evolved and gave rise to the Agile approach to software development –and we were all on board in a flash. Suddenly, software development teams were able to shift from longer development cycles to shorter sprints, fast releases, and multiple iterations.

But the evolution was not over, as we now know. As Agile shone a spotlight on releasing fast and often, enterprises started loving the opportunity to be more flexible and to speedily incorporate the feedback of their customers. However, this also revealed some drawbacks with the Agile approach. Though the development cycle was faster, there was a lack of collaboration between the developers and the operations team and this was adversely impacting the release and the customer experience.

This gave rise to the new methodology of DevOps which focused on better communication among development, testing, business, and the operations team to provide faster and more efficient development.

So now software development organizations face a choice –should they be Agile? Or do DevOps? Or perhaps somehow both? Let’s look at both approaches more closely, starting with filling in the essential backstory.

The Agile Approach Explained

Software Development approaches like the Waterfall model took several months for completion, where the customers would not be able to see the product until the end of the development cycle. On the other hand, the Agile approach is broken down into sprints or iterations which are shorter in duration during which certain predetermined features can be developed and delivered. There are multiple iterations and after every iteration, the software team can deliver a working product. The features and enhancements are planned and delivered for every succeeding iteration after discussions (negotiations?) between the business and the development teams.
In other words, Agile is focused on iterative development, where the requirements and solutions are developed because of collaboration between cross-functional and self-organizing software teams.

What is DevOps?

This is the age of Cloud and SaaS products. That being the case, DevOps can be defined as a set of practices enabling automation of processes between the software development and the IT teams for building, testing, and deploying the software in a faster and more efficient manner. DevOps is based on cross-functional collaboration and involves automation and monitoring right from the integration, testing, releasing, and deployment along with the management of infrastructure.

In short, DevOps helps in improving collaboration and productivity by integrating the developers and the operations team. Typically, DevOps calls for an integrated team comprising developers, system administrators, and testers. Often, Testers turned into DevOps engineers are assigned the end-to-end responsibility of managing the application software. This may involve everything from gathering requirements to development, deployment, and gathering user feedback to implementing the final changes.

How do they compare (or contrast)?

  • Creating and deployment of software:
    Agile is purely a software development process. That means, the development of software is an inherent part of the agile methodology. Whereas Devops can deploy software which may have being developed using other methodologies, based on either Agile or non-agile approaches.
  • Planning and documentation:
    The Agile method is based on developing new versions and updates during regular sprints (a time frame decided by the team members). Besides, daily informal meetings are key to the Agile approach, where team members are encouraged to share progress, set goals, and ask for assistance if required. To that extent, the emphasis on documentation is less.
    On the other hand, DevOps teams may not have daily or regular meetings but plenty of documentation is required for proper communication across the teams for effective deployment of the software.
  • Scheduling activities and team size:
    Agile is based on working in short and pre-agreed sprints. Traditionally sprints can last for a week to 1 month or so at the extreme. The team sizes are also relatively smaller as they can work faster with fewer individuals working on the effort.
    DevOps can comprise of several teams using different models such as Kanban, Waterfall model, or scrum where all of them are required to come together for discussing regarding software deployment. These teams could be larger and are by design much more cross-functional.
  • Speed and risk:
    Agile releases, while frequent, are significantly less than what DevOps teams aim for. There are DevOps products out there that release versions with new features multiple times in an HOUR! The application framework and structure in Agile approach needs to be solid to incorporate the rapid changes. As the iterative process involves regular changes to the architecture, it’s necessary to be aware of every change related to the risks to ensure quick and speedy delivery. This is true of DevOps also, but the risk of breaking previous iterations is far greater in DevOps as the releases are much more frequent and follow much faster on the heels of one another than in the Agile approach.

Conclusion

DevOps is a reimagining of the way in which the software needs to be configured and deployed. It adds a new dimension to the sharp end of the value chain of software development i.e the delivery to the customers. There is some talk about that that DevOps will replace Agile, but our view is that DevOps complements Agile by streamlining deployment to enable faster, more effective, and super-efficient delivery to the end users. That’s a worthy goal –so why choose between the two!

devops and CI

Achieving Assured Quality in DevOps With Continuous Testing

DevOps has finally ushered in the era of greater collaboration between teams. Organizations today realize that they can no longer work in siloes. To achieve the required speed of delivery, all invested in the software delivery process, the developers, the operations, business teams, and the QA and testing teams have to function as one consolidated and harmonious unit. DevOps provides organizations this new IT model and enables teams to become cross-functional and innovation focused. The conviction that DevOps helps organizations respond and adapt to market changes faster, shrinks product delivery timelines, and helps to deliver high-quality software products is reflected in the DevOps adoption figures. According to the Puppet State of DevOps Report, in 2016, 76% of the survey respondents adopted DevOps practices, up from 66% in 2015.

One of the hallmarks of the DevOps methodology is an increased emphasis on testing. The approach has shifted from the traditional method of adding incremental tests for each functionality at the end of each development cycle. The accepted way now is to take a top-down approach to mitigate both functional and non-functional requirements. To achieve this DevOps demands a greater testing emphasis on test coverage and automation. Testing in DevOps also has to start early in the development process to enable the DevOps methodology of Continuous Integration and Continuous Delivery.

The Role of Testing in Continuous Delivery and Continuous Integration:

In order to deliver on the quality needs, DevOps demands that testing is integrated into the software development and delivery process and acts as a key driver of DevOps initiatives. Here, individual developers work to create code for features or for performance improvements and then have to integrate it with the unchanged team code. A unit test has to follow this exercise to ensure that the team code is functioning as desired. Once this process is complete, this consolidated code is delivered to the common integration area where all the working code components are assembled for Continuous Integration. Continuous Integration ensures that the code in production is well integrated at all levels and is functioning without error and is delivering on the desired functionalities.

Once this stage is complete, the code is delivered to the QA team along with the complete test data to start the Continuous Delivery stage. Here the QA runs its own suites of performance and functional tests on the complete application in its own production-like environment. DevOps demands that Continuous Integration should lead to Continuous Delivery in a steady and seamless manner so that the final code is always ready for testing. The need is to ensure that the application reaches the right environment continuously and can be tested continuously.

Using the staging environment, the Operations teams too have to run their own series of tests such as system stability tests, acceptance tests, and smoke tests, before the application is delivered to the production environment. All test data and scripts for previously conducted application and performance tests have to be provided to the operations teams so that ops can run its own tests comprehensively and conveniently. Only when this process is complete, the application is delivered to production. In Production, the operations team has to monitor that the application performance is optimal and the environment is stable by employing tools that enable end-to-end Continuous Monitoring.

If we look at the DevOps process closely we can see that while the aim is faster code delivery, the focus is even more on developing error free, ready for integration and delivery code by ensuring that the code is presented in the right state and to the right environment every time. DevOps identifies that the only way to achieve this is by having a laser sharp focus on testing along with making it an integrated part of the development methodology. In a DevOps environment, testing early, fast and often becomes the enabler of fast releases. This means that any failure in the development process is identified immediately and prompt corrective action can be taken by the invested stakeholders. Teams can fail fast and also recover quickly – and that is how to ensure Quality in DevOps.

automate testing for devops

The Big Challenges in Automating Your Testing for DevOps

To stay ahead of the market organizations have to deliver a high-quality product in the least possible time. For this, organizations have had to fundamentally change their development methodologies as well as their testing practices. These shifts have prompted all the stakeholders of product development to work more closely and in tandem with one another. DevOps is one such development methodology that takes a more holistic approach to software development by bringing software developers, testers, and operations together to improve collaboration and to deliver a quality product at light speed.

Clearly, the role of QA and testing have been redefined in the DevOps environment. DevOps is heavily focused on the ‘fail fast, fail often’ mandate propelled by the ‘test first’ concept. Testing, thus, becomes continuous and exhaustive and hence demands greater levels of automation. But just how easy is it to automate testing in DevOps?

DevOps makes testers an important part of the development team to develop new features, implement changes and enhancements, along with testing the changes made in the production software. While on the outset this arrangement looks fairly simple to achieve, there can be some challenges that first need to be addressed to automate testing in a DevOps environment. In fact, Quali’s 2016 survey on the challenges of implementing DevOps states that 13% of those surveyed feel that implementing test automation poses a barrier to successful DevOps implementation. In this blog, we take a look at some changes that create challenges in automating testing for DevOps.

  1. The New-age Testing Team
    The DevOps environment needs testing teams to change pragmatically to accommodate accelerated testing – not always easy to achieve. These teams, instead of being in the back end now have to co-exist with the other development stakeholders in DevOps. Along with being focused on the end-user, testing teams in DevOps also have to be aware of the business goals and objectives and have to have the ability to understand how each requirement impacts another and be in a position to identify and iterate cross-project dependencies. So along with being able to understand user stories and define acceptance criteria’s, they also need to have better communication, and analytical and collaboration skills. This allows them to clarify intent and also provide sound advice on taking calculated risks.
  2. The Process Change
    DevOps demands greater integration of development and testing teams. This also means that the testing and QA team has to work closely with product owners and business experts and also understand the working of the business systems being tested. Even testing teams need to develop a Product Lifecycle Management mindset by first unlearning the standard SDLC process. DevOps testing teams also need to assign an architect to select the right testing tools, determine best practices for continuous integration and integrate the test automation suite with the build deployment tool for centralized execution and reporting. There, thus, has to be a ‘one team’ mentality across the invested teams – a significant change in the “way we work”.
  3. The Pace of Change
    DevOps also focuses heavily on the speed of development and deployment. This places a lot of emphasis on increasing test coverage, iterating detailed traceability requirements and ensuring that the team does not miss testing of critical functions in the light of rapidly changing requirements. Test plans in DevOps thus need to be more fluid and have to be carefully prioritized to adapt to these uncertainties that arise from changing requirements and tight timelines. Test Automation also takes time to develop. At the blistering pace set by the DevOps team how is the automation to be completed?
  4. Unified Reporting and Collaboration
    Test automation in DevOps demands consolidated timely reports to provide actionable insights to foster collaboration in cross-functional teams. Testing teams also need to ensure that they introduce intelligence into the existing test automation set up. This is to proactively address scalability challenges that may slow down testing speed. Analytics and intelligence can also play a key role in implementing intelligent regression models and establishing automation priorities. This is essential to test what is needed, and only what is needed, in the interest of time. Ensuring easy maintainability of the automation architecture has always been a priority but it may now become necessary to have a central repository of code-to-test cases for easier test case traceability. Prevailing test practices are not necessarily tuned to this level of reporting and analysis and this is a significant challenge to overcome.
  5. Testing Tools Selection and Management.
    Traditional testing tools may be misfits in a DevOps environment. Some testing tools can be used only once the software is built, thus failing the whole purpose of DevOps. Some testing tools can only be employed once the system has evolved and is more settled. DevOps testing teams thus, need to use those tools that help them explore the software still being built. They must test in a manner that is unscripted and fluid.

The test automation tools DevOps needs can link user stories to test cases, provide a holistic requirement view, keep a record of testing results and test data, have REST API’s, help manage test cycles and create and execute test cases real-time, and provide detailed reporting and analytics.

Testing teams in a DevOps environment are critically important. They need to work with an enhanced degree of speed and transparency and they must root out all inefficiencies that impede the automation process. Automation is key to their success but as we have outlined, there are some significant challenges to overcome in getting Automation right in DevOps. Stay tuned for future posts where we reveal just how these challenges can be addressed in the DevOps environment.

What-should-startups-look-for-while-choosing-their-technology-stack

What should startups look for while choosing their technology stack?

Look at any business today and you will find a compelling dependence on technology. Today, technology also forms the core of any successful startup. When it comes to startups, it has sometimes been seen that while entrepreneurs focus on building the front end of their business, the job of choosing the right product technology stack features low on the priority list…almost as an afterthought.

The right choice of technology stack for product development contributes greatly to the efficiency and smooth running of a start-up. Ensuring that the right technologies are being leveraged ensures that you release on time. At the same time, given the overwhelming number of technology options, this can be a tough decision to make as well.

Many non-technical founders tend to depend on developer opinion when choosing a technology stack. This sometimes can backfire as developers can be biased towards particular technologies depending on their proficiency and comfort level. They also might assess the technology based on its technical merits rather than on the business requirements. Technology options need to be evaluated more objectively and here we take a look at some business considerations that need to be made before choosing a technology stack for building the product that will define your startup.

Usability

One of the primary considerations before making a technology selection is to first identify how and for what the technology will be used. The usage aspect heavily influences a technology decision as a technology that works perfectly for developing an eCommerce website might not necessarily be best suited for an enterprise mobile application. ‘Purpose’, thus, ranks the highest when selecting a technology. The technology stack has to be such that it fulfills the requirement demands and helps in establishing the business.

UI and UX Focus

The consumer of today goes by the principle of ‘don’t make me think’. Having high-end user experiences thus becomes of paramount importance. Simple, intuitive and intelligent user interfaces that facilitate a seamless user experience are a must. Technology choices have to be made such that they act as enablers of usability and allow the application users to be consistently productive in their work.

Talent Availability
You might want to choose the next hot technology on the block but if you cannot find the talent to work with this technology then all you’ll be stuck! This, for startups, can be a big financial drain. For example, finding developer talent to create a chat server with Erlang may prove harder than finding developers proficient in Java, Ruby or Python. Leveraging mainstream technologies that are open source and opting for a development methodology such as Agile or DevOps with a heavy testing focus is a good idea. This will give your startup the advantage of getting to market faster, rapidly shipping code and getting the desired features to the users at the earliest.

Technology Maturity
Startups need to look at the maturity of the technology before selecting a particular technology to ensure that the technology is built to last. Programming languages such as Ruby are relatively recent but have gone through several iterations and has now achieved language maturity. Mature technologies also give startups the benefit of a mature tools ecosystem that allows bug tracking, code analysis, facilitate continuous development and continuous integration etc. all of which make development faster and easier.

When looking at technology maturity, it is also essential to assess how easily you can build and share solutions built on the technology stack. Leveraging a technology that has great third party packages or ready to use, community generated code or a complete suite of easy to use and build solutions, or automated testing capabilities helps in not only attracting more developers but also helps in making development quicker and convenient.

Technology Dependencies

All it takes is one weak link to bring down a large fortress. Take the case of the Heartbleed bug which was caused because of the OpenSSL component in the library. When this bug was introduced, every technology that leveraged this widely used cryptographic library was affected. This just goes to show that when making a technology choice you have to ensure that the primary and secondary technologies are robust and secure and that their dependencies can be managed easily. So if for example, you are looking at Ruby on Rails, you should know that Rails (the Framework) is the secondary technology since it relies on Ruby (the primary technology) and that Ruby will also have its own set of dependencies. To leverage the two well you need to know the risks of both.

Scalability and Accessibility
Technology choices should support the demands of a growing business. The technology that a startup chooses thus has to allow for adding more users over time, add new functionalities or services, allow iterations, and enable integration with higher technologies. These days, looking at technologies that support a Service Oriented Architecture or SOA, gives more scope for extensibility to a startup by accommodating changes and iterations according to the needs or the market or product evolution demands.
Along with this, startups also have to ensure that the technology choice that they make allows for greater accessibility and security to allow business users access the product or service anytime anywhere.

Community Support
Community support might not rank highly in the startup technology choices priority list, but it probably should. Why? Simply because, as a startup, you can do with all the help that you can get. Along with this, a strong developer network and back-end support emerge as crucial resources when you are exploring the technology to either solve a problem or add new functionalities.

When evaluating technology options, startups also need to consider the maintenance needs of the technology, its compatibility capabilities, and security levels. Choosing the right technology is an imperative for the success of any startup. Startup entrepreneurs thus need to tick the right boxes when it comes to making the technology choice if they want to enable their startup to maximize their chances of success.

Categories