DEV Community: Komal-J-Prabhakar

Making the Right Choices with Infrastructure as Code

Komal-J-Prabhakar — Wed, 17 Aug 2022 10:47:00 +0000

Virtualization is in full swing, prompting businesses to step up the ultimate digital transformation. Companies today perform hundreds of deployments into production per day. Look at this article by Hubspot describing their feat of 300 deployments per day. An increase in deployments has made it important for enterprises to have automated infrastructure scaling. This is brought about by Infrastructure as code that enables you to treat your infrastructure as you treat your application code.

What is Infrastructure as Code?

Infrastructure as code (IaC) enables automated provisioning and de-provisioning of an IT infrastructure with the use of a high-level descriptive code language. It enables organizations to build, deploy and scale cloud applications faster with lesser security risks and reduced costs. Thereby eliminating the dependency on developers to manually provision and manage servers, database connections, operating systems, storage, and other elements of infrastructure, every time new software or code is created.

Source: Statista

Why do we need Infrastructure as Code?

For an all-success journey of code from the developers’ environment to the production environment, we need a consistent infrastructure configuration throughout. The best practice says that our test environment and dev environment need to mimic the production environment.

Let’s understand it with an example. Suppose we are building an application on cloud, let’s say public cloud. In this particular scenario, I am considering my application is built on Kubernetes, thus it’s a Kubernetes application stack. For this purpose let’s take a VM which carries a legacy application. Now to connect all of them, we need a VPC (Virtual Private Cloud). And now we have a basic infrastructure put in place.

Looking forward to testing the application, we all know that the Test environment must mimic the Dev environment.

This is critical as no matter how well an application is designed, it would break if the environment is different. While building we have definitely documented every aspect of the infrastructure, but does that happen always? Picture this, what if any modifications are left out in the documentation? It’s simple, the application won’t perform.
Imagine, you’re adding a new section to the application that makes the customer experience seamless. To make it happen, we open a communication port on our firewalls and servers of the proprietary protocol and in the process create a change ticket. And you didn’t document it. Well, eventually while auditing, this open port will be brought to question regarding its nature and the reason behind it. On the surface, it doesn’t look like a huge issue, however, if you look through it you need to reason all the time spent by the Security team in tracking the origin of the open port. Had this little thing been documented, you’re not just saving time for unwarranted trouble but you’re also ensuring nothing gets unnoticed. And unnecessary wastage of time.

To solve the problem, this is where we bring Infrastructure as code into picture. There are basically two approaches to bring about this:

Imperative Approach
Declarative Approach

Imperative Approach

Also known as the Procedural approach.

In this, we dive into specifics, defining step-by-step to develop a certain state of the infrastructure. Now, this approach is chosen quite instinctively by developers. The reason is the control it gives over defining the state and other aspects of every single element of the infrastructure.

Advantages:

With the power of cloud tools, the definition becomes even more highly customizable.
Makes it easier for the administrative staff to understand every inch of detail pertaining to the code developed.
That enables them to leverage configuration scripts that are already developed and have been put in place.

Disadvantages:

The level of customization and specificity involved in building it makes it a tad difficult to break it or scale it. Basically, developers have to again create custom scripts for every section for either teardown or scale-up.
It’s time-consuming, both in the sense of creation and after-creation changes/modifications.
If the imperative script is run multiple times we end up having several environments. Suppose, it fails at any step, we have to create custom scripts to teardown completely.

Declarative Approach

Also known as the Functional Approach.

This becomes the most preferred option for the majority of tech teams as it involves only defining the final state of the infrastructure, and the rest is handled by an IaC tool like Terraform. Some popular choice configuration management tools are Puppet, Chef, etc.

These tools enable spinning up a VM or container and installing & managing the different resources by bringing in necessary changes in their configurations.

In this approach, we define the resources of all our infrastructure elements. In reference to our above example, we will define the Kubernetes resources, VM resources, and VPC resources.

Advantages:

No matter how many times the script runs, every single result will be exactly how we defined it.
What simplifies even further is that they are managed with simple config maps. This essentially means we can bring alterations, add or customize changes like defining a host, subdomain, etc.
It is easier to have principles like one-click teardown. This enables us to scale infrastructure without the need for custom scripts.

Disadvantages:

The prime downside to this method is that it requires the expertise of a skilled administrator. They usually specialize in their preferred solution.

Example to understand the difference between Imperative and Declarative Approach of Infrastructure as Code

This can be analogous to finding a route by GPS or following turn-by-turn directions. If you’re thinking how — then understand how both of these methods work. For GPS, you feed your final destination details, and it automatically maps for you the shortest route with low traffic. Whereas the turn-by-turn instructions are created on the basis of personal experience. To understand why a certain route was taken by GPS, we need the knowledge of an expert. For understanding the turn-by-turn instructions you either need the person who gave them to you or maybe refer to the description provided in the document. Here, GPS is symbolic of the Declarative approach and turn-by-turn directions is the Imperative approach.

Benefits of Infrastructure as Code in DevOps

Faster Time to Market

Manually building infrastructure on cloud can be time-consuming and error-prone.
Codifying it entirely ensures automated provisioning and de-provisioning of IT Infrastructure. Also makes it easier to scale.
Less Configuration Drift
Through the version control system, every change, and every detail gets documented.
It makes it easier to mirror the Dev environment, test environment, and Production environment.

Reduces Churn

If not done through a tool, they get delegated to a few skilled engineers.
In this case, if they leave the organization it becomes a tedious task to recreate everything.
With infrastructure being treated as code, and automated, it enables the organization to retain the provisioning intelligence.

Improved ROI

Through IaC tools we can leverage the power of cloud computing that allows us to have a consumption-based cost structure.

Reusability

By codifying every document, it becomes quite convenient to automate the provisioning of legacy infrastructure. This otherwise would have required us to go through a time-consuming process like pulling a ticket.

Best Practices of Infrastructure as Code

Preferring an Immutable Infrastructure Approach over a Mutable Infrastructure Approach

An important aspect to consider while automating Infrastructure is to choose between having an immutable infrastructure or a mutable infrastructure.

What is Mutable infrastructure?

Going by the literal meaning of the word “Mutable” is changeable. So, here we are able to introduce changes/modifications to the infrastructure that is originally provisioned. This level of flexibility looks nice on the surface but considering it practically might make you think otherwise. Why?

It undermines the key feature of IaC of maintaining consistency across environments
Makes it harder for infrastructure version tracking

What is immutable infrastructure?

The exact opposite of mutable infrastructure. The infrastructure that has been originally provisioned cannot be changed or modified. If you want to implement changes, you have to spin an entirely new infrastructure and replace it. This might sound time-consuming and cumbersome but it’s not. With the help of cloud tools — especially IaC tools, spinning up new environments is easier and faster. This option is much more feasible and secure as compared to mutable infrastructure.

The reasons why teams prefer it:

It prevents configuration drift across various environments.
It makes it easier to roll back to any previous versions

Version Control for Infrastructure

In line with the above point of easier rollback, we need a version-control system to store the data of every IaC file. This helps in keeping track of all changes, which further helps team members to work on the latest version. This is similar to how developers record the detail in application source code. In addition to that, it can be referred to in the future to understand the evolution of the current infrastructure version.

Following Modular IaC Rules

It is totally possible to define all the resources or aspects of infrastructure in a single IaC file. To define the type of Operating system to be installed, the category of user accounts to be configured, the applications to install, the networking policies that are needed to be applied, and so on and so forth.

Just because it can be done, it’s not an effective approach to be followed. If we break down these details and define them in separate files or modules, life gets simpler! The teams can easily execute custom changes to specific elements and not everywhere.

To understand better, suppose there are two servers that need to have similar operating systems to be installed but different user accounts. In this usecase, different modules come in handy to implement custom changes.

Treat Infrastructure as Code as an Application Code.

At the end of the day, IaC is a Code that essentially means we can apply the rules of continuous integration, testing, and deployment. We can say that we are putting into the DevOps cycle. Ensuring errorless codes because an error in the IaC file can cost us a fortune.

Therefore, IaC scanning can be incorporated into the CI/CD pipeline which ensures:

Compliance regulation
No database password or a secret credential exists in the code

Secret Management is Vital

To configure certain resources IaC tools do require access to sensitive information like passwords, encryption keys, etc. Including the secrets in the IaC definitions might look like the easiest way but this is the riskiest thing you’ll ever do. If anyone manages to access the IaC file, they can read this sensitive data.

In view of security, we need to use a secret manager. We have in-built secret management in some IaC tools like Chef-vault of Chef. Preferring a third-party manager like AWS Secret Manager in conjunction with IaC tools is also a wise choice. Thus, secrets can be accessed when required and stay protected from getting exposed.

Managing the Lifecycle of Infrastructure as Code

Infrastructure as code aligns with the DevOps approach, one can otherwise phrase it as “empowers DevOps.” It enables faster deployment with reduced costs and enhanced security. Throughout its implementation, we need exceptional observability and monitoring. A minor error can result in a major liability.

When we are able to treat infrastructure with the same quality as we work with our application code, a lot of changes can be brought in simultaneously documenting every bit. If built with CI/CD pipeline, the code gets subjected to automated continuous testing like comprehensive CI scanning, unit testing, etc. As the software development progress through the pipeline, different team members can integrate custom updates, which is usually the case with changing client requirements. This again gets tested and integrated with the source code, resulting in an updated errorless version of the IaC.

Wrapping Up…

Infrastructure as Code injects efficiency and agility into our product release cycle. The agile practices of Digital Transformation are impossible to imagine without bringing in IaC.
Quick & easier tracking of infrastructure changes and the ease of integrating with CI/CD pipelines, make it vital for building scalable infrastructure. By adopting an enterprise-wide approach to automation, we are not just managing IT processes, but the entire system, teams, and organization.

Managing Spot Instances

Komal-J-Prabhakar — Wed, 03 Aug 2022 10:27:00 +0000

According to a recent survey, the worldwide public cloud computing market has been projected to reach $495 billion by end of 2022.

The present-day cloud technologies turn out to be a vital factor in driving innovation and business growth. However, jumping onto the bandwagon of cloud users without planning for cloud cost optimization makes it an expensive affair.

Proceeding further, we will be discussing one such method of cloud cost reduction. That is the use of spot instances. The major public cloud service providers Amazon Web Services (AWS), Microsoft Azure, and Google Cloud all offer spot instances. But let’s understand “what are spot instances?”

What are Spot instances?

Spot instances are the unused cloud computing capacity that is available at steep discounts compared to the on-demand instances and reserved instances.
The cloud service pricing model is divided into the following three categories:

On-demand Instances - This is the pay-as-you-go model, where you pay in terms of computing power used per hour or second. Here you get the flexibility of increasing or decreasing the resources as per your operational requirements. There are no long-term commitments or upfront charges.
Reserved Instances - These costs slightly lesser than on-demand instances. They are what you consider for a longer period. Say 3 years or 5 years, this is when your entire cloud infrastructure runs on a daily basis. These are the long-term commitments where you get to pay a bigger sum upfront. They cost 40-50% lesser than on-demand instances, the pricing also depends on the cloud service provider.
Spot Instances - As discussed earlier these are offered at steep discounts, i.e., even lesser than reserved instances. But there’s a catch, these do not have any fixed prices, and customers/users have to bid on the unused capacity of the cloud provider’s data center. Now, these prices vary as they are adjusted across the availability zones based on market demand and the biggest consideration is that - this spare capacity can be taken away almost instantaneously!

Spot Instances on AWS

The Spot instances in AWS use the unutilized EC2 (Elastic Compute Cloud) instance facilitating them in optimizing their cloud costs. These unused EC2 instances have a variable price in the AWS Spot Market depending on the supply and demand of these instances.
The pricing of spot instances on AWS is done on an hourly basis and is known as the spot price.
Considering the demand and availability of spot instances, AWS determines the auction price (spot price) for each instance type in their respective availability zone.

The Working of AWS Spot Instances

To begin with, the user needs to create a spot instance request. The request includes the following data - quantity of instances, the type of spot instances, the availability zone, and the maximum bid.
When the maximum bid exceeds the auction price, with all conditions of the spot instance request met, Amazon launches the unused EC2 instances. However, if the bid doesn’t exceed, Amazon waits till all the conditions are met to process the request, or the user may cancel the request.
But the work doesn’t end here, the spot instances launched would stay only up to the time the maximum bid of the user exceeds the spot price. The very moment when the prices change, the allotted instances get terminated. Or it can even get terminated if the requested capacity is unavailable. A point to be noted is that the user can start or stop an instance manually. Furthermore, if an instance gets terminated the user can open a new request, and again if all conditions are met the EC2 instances are launched.

[ A Good Read: Guide to Creating Spot Instance Request on AWS ]

How do AWS Spot Instances help Businesses?

Cost Saving

The biggest benefit of using spot instances is quite obvious, the cost-benefit. It costs less than the on-demand and reserved instances. In this particular case study on Lenskart, an effective 80% reduction in overall cloud costs is achieved by leveraging Spot Instances.

Flexibility for Experimentation and Growth

Voost specializes in developing a digital asset management platform for professional cryptocurrency traders and businesses. Their creation ‘Pastel’ ( SaaS Platform ) required connecting with global exchanges to collect large volumes of data. This enables users to view their distributed crypto assets in one place without visiting the exchange. However, being a startup with limited resources, building this infrastructure on on-demand instances made it an expensive affair. This is where they thought of leveraging spot instances, which saved them around 90% in cost over on-demand instances. (reference)

Summing up the benefits from the above case:

No more waiting for approvals or incurring any higher costs while giving shape to your ideas. We can act quicker on our ideas, and test them directly with customers without any delays.
Spot instances are an effective solution, when not sure whether you need extra resources for certain experimental projects.
It gives a choice to businesses for investing in what is critical, and what is required, preventing wastage.

Improved DevOps Productivity

The principles of DevOps promise faster deliverability of products and services. This holds true when the right amount of automation is implemented in the CI/CD pipeline.
It helps in streamlining the DevOps lifecycle by reducing the friction surrounding the testing and release processes, enabling a smoother assembly line.

Challenges of Spot Instances

Transient Nature

The spot instances in AWS are with us till the time -

The current price exceeds our maximum bid of the spot instances
Or the requested capacity becomes unavailable The moment either of the conditions becomes true, the spot instances are terminated immediately. Any applications working on them get interrupted, and we possibly lose a lot of data in the process.

The possible solution is to automate these processes through a platform, whereby all the operations continuing on the AWS spot instances are saved and the very moment spot instances are withdrawn, the platform automatically switches the work to on-demand instances. Thereby balancing the costs and business processes seamlessly.

Multi-Cloud Adoption

Enterprises today are adopting multi-cloud services. It is obvious that different cloud services have different methods of allotting spot instances. Although we are diversifying our resources, at times it becomes a cumbersome process to shuffle the workload among all these variations.
Bringing automation to this is going to solve half of our woes. A hybrid cloud deployment platform that creates a secure virtual environment, and helps us in building a safe passage for our product following the compliances simplifies the product journey.

Choosing the right combination of Instances

The right combination of instances is the blend of spot instances, on-demand instances, and reserved instances for optimal application performance. To be able to know, what part of an application’s service can be compromised (that can be made to work in spot instances), and which parts are critical. For this information, we need to have a good understanding of what our customers want, and this can be achieved by storing data in dashboards format.
A practical solution will be an intuitive platform that stores all metrics in a proper dashboard fashion, and accordingly ensures and allots different instances for optimal resource utilization. Now, businesses are no more busy looking after infrastructure requirements, they can direct their focus toward the core business operations.

Conclusion

The market is very competitive. Businesses are facing steep competition in the form of innovation, agility, and better customer service. This is where spot instances help in filling these competitive gaps. Choosing the right jobs like data analysis, background processing, batch jobs, and other optional tasks can not only bring down our costs but successfully supplement the overall performance of an application.
The foundational pillars of a successful business are proper cost optimization, faster deliverability, and better customer experience. Bringing in this modularity requires a lot of human hours but when considered through an intuitive platform, complexities are reduced to a great extent. Businesses are in for a long marathon and if the right decisions are taken in terms of implementing automation, we are enhancing its lifespan by manifolds.

Top 5 Challenges of CI/CD Pipeline

Komal-J-Prabhakar — Wed, 29 Jun 2022 16:55:56 +0000

Today every company aspires to have an accelerated product cycle. Not just to let things stay in the form of ideas, but to formulate them into new product features, and make them accessible to the audience. Or maybe schedule updates on time, before the errors completely drive off the customer/user.

Gone are the days when different parts of code had to be manually integrated and tested, and yet there were still too many errors. Organizations are embracing methodologies that implement CI/CD pipelines.

What is CI/CD Pipeline?
Continuous Integration
Continuous Deployment
Continuous Deployment
Most Commonly Observed Challenges in the CI/CD Pipeline Implementation

Service Performance Issues
Need for Orchestration in Software Development Lifecycle
Being Data-driven
Overcoming Security and Compliance Issues
Implementing Platform Engineering Practices

Final Verdict

What is CI/CD Pipeline?

CI/CD is a software engineering approach to inject automation into the software development cycle. From integrating the codes in the repositories, feeding them into the pipeline, to subjecting them through a string of tests, to ensure it’s error free. This process demands both the development and operations teams to work together, to enable faster deliverability of the product.
Breaking the pipeline into three parts:
Continuous Integration- This is the part where codes from their repositories are integrated and put in a centralized location(build).

Continuous Delivery

In this step, the built code is subjected to various performance, security, and usability tests. Once the code passes through all these tests with a clear report, this can be deployed with a trigger or button. Though, Deployment requires human intervention.

Continuous Deployment

This is when the code passes all the tests, and after an all-clear report, it is deployed straight into the production environment without human intervention. Note, consider the step when you are totally confident about test reports.

Continuous Deployment

Most Commonly Observed Challenges in the CI/CD Pipeline Implementation

Service Performance Issues

Although CI/CD solves the issues that accompany code integration, it still doesn’t solve the purpose from the business aspect. Elaborating further, automation helps us by converting manual tasks into programmatic tasks, where every new code stored in the repository is integrated with the existing code following certain tests.

However, the important question here is, how are the errors addressed by the delivery teams? These errors are nothing but the inconvenience faced by the end-user if not fixed. Faster-to-market model is not limited to delivering any feature or functionality faster but extends beyond accessibility to encompassing service quality.

It always becomes a challenge to the engineering teams, where the tests are conducted in simulated environments, they are ‘symbolic’ to user experience but do not provide us with the actual user experience data.

A possible solution would be to store the reports of recurring red flags, pay attention to the high change failure rates, and hold a risk-averse attitude while managing CI/CD responsibilities. These approaches are instrumental in maintaining service quality.

Need for Orchestration in Software Development Lifecycle

CI processes are highly automated. To put it simply, the CI/CD pipelines do automate many processes, yet they still require manual inputs at every step. Though the integration of codes is automated, there is human intervention before the CI artifacts are available for conducting further tests. Some manual work is also required before qualifying any software as bug-free.

For the engineering teams to bring better strategies for enhanced user experience, it is essential for them not to get stuck with these manual tasks. Rather than spending their time plugging gaps between the automated processes, if we introduce orchestrated workflows in SDLC, they can be freed from tedious tasks and focus on the business's core objectives.

Being Data-driven

As much as important it is to bridge the gap between the different automation processes and break siloes among different engineering teams, it is also essential to make information accessible to every stakeholder. The CI/CD pipeline should be built with the motive of pulling information across different systems and making them accessible to everyone, thereby helping in decision-making.

Implementing data as a part of the pipeline, where from the device of the developer through the entire process of the pipeline, the report made at every step needs to be considered. This increases the chances of the overall success rate of better deliverability.

Overcoming Security and Compliance Issues

Referring to this recent report by Statista, the average cost of a data breach worldwide is estimated at $ 3.86 Million. In addition to that, nearly 51% of organizations are paying a hefty ransom after a ransomware attack.

This brings us to the point that the majority of organizations are either not prioritizing security or are very inefficient in incorporating security into their software development process.
If you remember in the year 2021 when hackers gained access to one of the servers of Jenkins, through the deprecated Confluence service, to install a cryptocurrency miner. (reference)
Security is an important aspect in every stage of development. DevOps has evolved to become DevSecOps, where everything is the same but now every stage of development includes Security. Incorporating security features in the CI/CD pipeline ensures protection against any form of data breach.

This article will be a good read if you want to know “how to construct a devsecops pipeline?”

Implementing Platform Engineering Practices

The evolution of Platform Engineering came as a solution to address complex issues like resource coordination, service discovery, container orchestration, and usage reporting. Similarly, when dealing with CI/CD pipelines, they need to be built in a way that gives a comprehensive 360-degree view of the pipelines.
This is when you are deploying a new update, a proper synopsis should be made to understand how far the update is effective in delivering a better experience or is it working as a regression to the existing model.

Summing up all…

With all that being said, to simplify CI/CD implementation it can be hugely beneficial if we bring into the picture an intuitive platform. To support us with features like comprehensive observability, an easy user-friendly dashboard containing all the monitoring reports, history, and analytical reports for better flow of information across all departments.

It literally takes a village for smooth performance deliverability in CI/CD Pipelines. As truly as a DevOps approach is defined, any form of siloes present in working on the Software development life cycle can hugely impact the promises of better service deliverability.

Why application containerization is important?

Komal-J-Prabhakar — Wed, 15 Jun 2022 05:37:05 +0000

Organizations today are gearing up to redesign their infrastructure and development approaches. It’s a continuous process of rethinking, unlearning, and relearning - different approaches. With the prevalence of application-specific business transformation, the technology teams are constantly on their toes for bringing regular upgrades to their software models.

According to this report, 19% of respondents of the Global Survey believe that Containerization is already playing a strategic role in driving their business growth.

Instagram was first launched in the year 2010 as an IOS app, and in April 2012 it was launched for Android users. Then, we have LinkedIn which was first established as a website, and then when it started gaining momentum, it launched its app both for IOS and Android (2015) to increase its reach and enhance the mobile experience.

In the above cases, we see that every product that’s ever made is worked on constantly to make it accessible and democratic on all platforms. And what reduces our time in this process is when we follow the “Write Once and Run Anywhere” Philosophy with the codes written. Working on these lines is where application containerization comes into the picture. Although we can also say that application containerization is an alternate form of virtualization, but is lighter and more flexible.

What is Application Containerization?

Containerization is the process of creating a packaged unit (container) consisting of an application and its dependencies like files, libraries, and configuration files; making it an independent executable unit. Basically, a ‘container’ is an application with its own runtime environment, allowing the application to run reliably in multiple computing environments - as they partition a shared operating system.

Containerized applications are becoming an increasingly essential reason for adopting the cloud native development model. Comparing containers and virtual machines we see - VMs contain a guest OS i.e., possess a virtual copy of hardware needed by the OS to run, plus the application and its dependencies; whereas Containers virtualize the OS (which is mostly Linux or Windows) which means they only have an application and its dependencies, and can be easily run by leveraging the resources of the host OS.
This makes containers lightweight and portable, making them the most viable alternative for developers to address application management issues. In addition to that, working on the upgrades of applications individually and making them better than before.

If we look at it from a business perspective, we have a lot of areas to talk about - the ways it helps in keeping the business nimble in the dynamic market. Let’s discuss each of them briefly.

Benefits of Application Containerization

Modernizing Legacy Application
Building Cloud Native Enterprise Application
Enabling Data Centers to Work with Cloud Services
Faster Deliverability
Enhanced Security
Improved Technology Team Satisfaction

Modernizing Legacy Applications

Legacy Applications are often monolithic applications. What makes legacy applications undesirable for modern business scaling is the fact that they are difficult and expensive to update and scale.
This difficulty can be cited to its architectural complexities. In monolithic architecture, all the components are shipped and integrated together, whereby if one component is facing performance challenges, the entire application is scaled up - only to fix the issue of that one particular demanding component. This is a clear scene of waste of resources - both time and money.
If the entire architecture is composed of containers containing a single application, developing and scaling it as per requirements, gives us a lot more flexibility in efficient usage of resources.

Building Cloud Native Enterprise Application

What are cloud native applications?

These are built with discrete, reusable single-function components known as microservices. And they are so designed that they can easily be integrated into any cloud environment. These are built to operate only on cloud, and are structured to be scalable and platform agnostic.

Why cloud native applications?

The reason behind this concept is to meet the demands of improved application performance, and add flexibility and extensibility. Some more advantages to look forward to -

Compared to monolithic applications, these are easier to manage and iterative improvisations can be brought in through Agile and DevOps processes.
Being composed of microservices gives the flexibility to propose newer updates - the addition of newer functionalities incrementally. Improvements are incorporated non-intrusively, causing absolutely no disruption of the end-user experience.
Scaling up and down is so much easier with the elastic infrastructure of the cloud architecture.
Rolling out new updates for a single function without disrupting the performance of other applications is very much possible.

Though these offer many advantages, managing them can be challenging and cumbersome. Their maintenance demands a robust DevOps Pipeline with additional tool sets, replacing all traditional monitoring systems.

Enabling Data Centers to Work with Cloud Services

It is the central facility of an Enterprise’s IT operations. The upkeep of the security of the data center is essential to ensure the continuity of business operations. When enterprises migrate their workloads to cloud data centers, they don’t have to worry about their maintenance. Cloud service providers take responsibility for its upkeep and offer shared access to virtualized computing resources.

Advantages of Cloud Data Centers

Reduced Capital Expenditures As we can pay on an as-needed basis, also we have a variety of subscription models suiting our specific needs.
Efficient Use of Resources With Public Cloud Services offering shared access, individual enterprises don’t have to build and maintain resources of computing and storage, to support them at occasional peak user-traffic periods.
Managed Cloud Services The cloud providers assume the responsibility of maintaining the cloud environments and also guaranteeing the security of critical resources.
Global Network of Data Centers Major Cloud Service Providers have their data centers located across multiple regions and continents. Enabling customers to have an even data processing experience, also allows them to meet all the security and compliance requirements of their customers, irrespective of their geographic location.
Rapid deployment and scalability Either facilitating new updates or scaling an existing application to meet higher demands, the cloud makes it possible in a fraction of the time utilized in doing so in on-premise data centers.

Faster Deliverability

When the individual performance of containers is measured, monitored, and scaled individually; we are avoiding disruptions in the end-user experience. Moreover, when they are treated separately, we can achieve the desired scale of certain services as per our requirements.

Enhanced Security

When all the functionalities are separated from each other through different containers, and they are running in their respective self-contained environments, this adds an additional layer of security. To simplify it, even if any one container’s security is compromised, other containers are safe from any possible intrusion. On top of that, the containers are even separated from the host operating system and interact minimally with the host’s computing resources, making the deployment of applications inherently more secure.

Improved Technology Team Satisfaction

When every new update created or new code written can be easily made accessible to the customers, without disrupting the entire application, or affecting other functionalities, it gives the team more time and encourages the innovation flow.

Conclusion

Though containerization application gives us a lot of advantages over traditional monolithic architecture, its implementation comes with a lot of challenges.

The designing and maintenance of templates for container creation. In the long run, when container adoption expands beyond simple or regular use cases, these templates become the roadmap for simplified implementation.
Expansion of Governance Model Oftentimes, it’s seen that the application layers are shared among different containers - on one hand, it implies an efficient usage of resources but on the other, it makes the containers vulnerable to interferences and security breaches.
Choosing the right open-source container orchestration platform The container orchestrator is at the forefront of setup and management of a containerized application. If not chosen wisely, every deployment will be slow and might encounter errors.
Integration with DevOps Environment The maintenance of these containers takes place through the DevOps methodology. Incorporating it into the DevOps lifecycle requires knowledge and skill.

Container orchestrator is a necessity when dealing with a containerized application. It simplifies the handling and management of containers by automating the steps of installation, scaling, and even assisting in rolling out new features and any bug fixes.
The popular choice for this has always been Kubernetes. If we list down reasons, these would be commonly heard -

fully open-source
complete granular control over scaling of each container
and lastly but the most prominent feature is
supports load balancing and self-healing. However, the complexity and distributed nature of Kubernetes, make the manageability tough. An intuitive platform offering seamless manageability of Kubernetes clusters looks quite convincing when looking forward to an automated work environment. Not just enabling smooth delivery and maintenance of containerized applications but even helping in building custom automation specific to your business needs.

Have a look at this Kubernetes Cheatsheet

With big tech giants like Twitter, Netflix, and Amazon adopting them, it shouldn’t be seen as a distinction of big tech giants, but it should be seen as an example of how it helps in scaling and expanding infrastructure.

SRE vs. DevOps - What's the Difference and their Interrelation

Komal-J-Prabhakar — Fri, 27 May 2022 05:20:07 +0000

The software development life cycle has come a long way - from a non-overlapping development model - the Waterfall Model to an iterative development model like Agile and DevOps. It’s interesting to notice that before the beginning of the DevOps movement (~2007-2008), SRE was born at Google (2003), to build the reliability and resiliency of the entire Google Infrastructure. Google in its SRE book, described how the collaborative efforts of DevOps engineers, SRE, and other engineers like Application Security engineers are vital for maintaining a product like Gmail.

Looking at the above example, it is safe to say that our growing dependency on applications, is what has propelled the widescale adoption of DevOps and SRE. Whether it’s to streamline our business functionalities or launch an app that simplifies our life, we need reliable and scalable systems at every step.

What is DevOps?

DevOps defines a software development approach with a shift in organizational culture towards agility, automation, and collaboration. It aims at eliminating siloes and bridging the gaps between the different departments of development and operations.
In this process, the code development goes through iterative steps of - Continuous Development, Continuous Integration, Continuous Testing, Continuous Feedback, Continuous Monitoring, Continuous Deployment, and Continuous Operations. Also popularly known as ‘7Cs of DevOps Lifecycle.’

What is SRE?

Site Reliability Engineering or SRE plays a more comprehensive role in streamlining the end-user experience and is more concerned with incorporating software development practices into IT operations.
To put it simply, the SRE concept says that if a developer handles the task of IT operations, what are the places where automation can be brought into the picture. This means it expects to use automation as a means to fix many of the problems arising while managing applications in production.
SRE uses three service level agreements to measure the application performance -

Service level agreements (SLAs) - to define the appropriate reliability, performance, and latency of the application, as desired by the end-user.
Service level objectives (SLOs) - The target goals set by the SRE team to meet the expectations of SLAs.
Service level indicators (SLIs) - to measure specific metrics (like system latency, system throughput, lead time, mean time to restore (MTTR), development frequency, and availability error rate) to conform to the SLOs.

Similarities between SRE and DevOps

Both methodologies are focused on monitoring production and ensuring the operations management works as smoothly as expected.
One of their fundamental principles is breaking siloes. It aims at bringing all the stakeholders (Dev team + Ops team) in the application development together. Believe in the model of ‘shared responsibility’ and ‘shared ownership.’
Their common goal is to simplify the operations in the distributed system.

Differences and Interrelation between SRE and DevOps

Development and Implementation

DevOps focuses on building the core of the product. The core is why the product is developed in the first place. It works on the aspect of customer requirements - the different needs and specifications. Taking an agile approach to software development with the continuous process of build, test, and deployment.
SRE teams narrow their focus around the fact of whether the core is really implemented. Whether the product is meeting the expectations of the customer. It monitors the metrics of the application performance and gives feedback to the DevOps team, about the direction of changes that need to be implemented.

Nature of Skills

The DevOps team is more experimental in nature. They write codes and test them constantly for bugs, or may be adding new features. They develop the core design of the product, give shape to it, and push it to production.
The SRE team on the other hand is investigative in nature. They constantly monitor the concerned metrics and give feedback on the possible lines of improvement. They are concerned more with the experience of the end-user. They perform an analysis of every problem, to see its frequency, and find ways of automating the repetitive operations.
Their goal is to find ways to innovate in recurring instances of bugs.

Automation

Be it DevOps or SRE the sole purpose of their existence can be distinguished by the fact, that they both aim at automating manual processes. It's not about just saving time in terms of doing tasks, but extends beyond the fact that anything done manually is prone to errors.
When it comes to automation in DevOps, it means automating deployment (tasks and new features). However, automation in SRE is automating redundancy. They convert the manual tasks into programmatic tasks to keep the tech stacks up and running.

Goal

Every set of tasks ever assigned has a goal associated with it. The goal of DevOps is to develop a template to drive activities towards collaboration. And SRE team focuses on formulating prescriptive measures to enhance the reliability of every deployed application.

Conclusion

Both SRE and DevOps have a shared goal of breaking siloed workflow, bringing automation to recurring manual tasks, and incorporating constant monitoring. Some prime areas where they face challenges are:

CI/CD pipeline management: Implementing different automated tests at different stages of pipelines to ensure errorless codes.
Monitoring and Alerting: The core function is to help us in increasing the reliability of our applications. Gaining 360-degree visibility into the system will help in diagnosing the health of services and gaining vital analytics.
Incident Management: To understand the cause of service failures, the severity of a bug, or even to get alerted immediately when any requests start failing requires prompt communication.

Platforms enabling managed Microservices and managed Kubernetes help us in maintaining the lifecycle of applications, by addressing the above-mentioned challenges. Looking at the data on managed services market size, a projection of $ 274 billion by 2026, shows their potential in simplifying the manageability of applications.

With the global tech giants like Google, Amazon, and Netflix pioneering the adoption of DevOps and SRE, their ROI has grown in leaps and bounds. Furthermore, looking at their never-down robust infrastructure, it is evident that these methodologies are here for the long run.
Do give a look here! An insightful article on DevSecOps best practices.

Everything about Blue Green Deployment Strategy!

Komal-J-Prabhakar — Fri, 06 May 2022 08:13:30 +0000

Back in 2005, two developers named - Daniel Terhorst-North and Jez Humble were tackling issues with their Ecommerce Website. They were disappointed with the fact that even with a good testing system, the errors are still being detected at much later stages of production. Following this, they performed a detailed root cause analysis, the results of which showed a significant difference in the conditions of testing and production environment, and these differences resulted in frequent failures.

Very unconventional for their time, yet they created a new environment running parallel to the existing production environment. That means instead of over-writing on their older version, they had a similar new production environment to deploy new codes and further experiments. The plan was to route the traffic to the new environment where new codes are deployed, to gain accurate real-world end-user insights on their updates. Thereby putting an end to the failures that slipped due to the differences between testing and production environments.

Following the subsequent success, they coined this strategy as “Blue Green Deployment Strategy.”

Requirements before executing Blue Green Deployment Strategy

Two identical environments must be available
It is to be made certain that the new code can be run alongside the existing code, as they will be running at the same time in the production environment.
A load balancer to route the traffic. Two identical platforms are created - Blue environment and Green environment. The blue environment holds the existing version and the green environment holds the newer update (or as per your convenience, there is no rule as such, this is just for naming convention).

Steps Involved in Blue Green Deployment Strategy

The Blue Green Deployment Strategy can be broken down into four steps:

Step 1: Setting up a Load Balancer

Now when we have two environments, we want to direct the traffic to the green environment, where we have deployed our new update. For that to happen we need a load balancer, though it can be done through a DNS record exchange, but it’s not much preferred as DNS propagation is not instantaneous.
If a load balancer and router are used, for switching traffic between two instances, there will be absolutely no requirement to change the DNS records, the load balancer will point to the same DNS records, but the traffic is now routed to the green environment.
With the use of a load balancer, we have full control over the users’ channel, which implies that we can switch them back to the older/existing version, i.e., in our case we have placed it in the blue instance instantaneously, in case of any failure in the green instance.

Step 2: To Execute the Update

After our green instance is ready, we move it to production and run it simultaneously with the existing code. The load balancer effectively drives the traffic, from blue to green. This complete transaction is very unnoticeable to the users.

Step 3: To Monitor the Environment

As the traffic is routed to the new green instance, the DevOps engineers get a narrow frame of time to conduct a smoke test on the new instance. This is to ensure that all aspects of the new instance are working fine. This is a crucial step, in order to figure out any present errors, before it is experienced on a wide scale.

Step 4: Deployment or Rollback

This is the time when any error is found during the smoke test, the users are redirected to the older version or blue instance immediately. In some cases, errors are identified only after the application is live for some time, therefore, even after a successful smoke test, the devops engineers monitor the entire transaction to understand and find the bugs or any other issues.
If all is well with the new green instance, it becomes our blue instance for our next update.

Benefits of Blue Green Deployment Strategy

Pleasant Customer Experience

This is quite possible when we have a load balancer to securely reroute the traffic to the older/existing version without committing any change to the DNS records (in the case where the new instance shows errors). The routing action is so swift that it doesn’t show any downtime to the customers/users.

Instantaneous Rollbacks

It’s as simple as pressing undo, without any adverse consequences. When the routing action swiftly diverts users in no time, it’s easier to roll out new updates for experimentation and also immediate roll back in case of any error or failure.

No more waiting for Maintenance Windows

Earlier DevOps engineers had to wait and keep a track of days when the traffic was down, to conduct the scheduled downtimes, in order to deploy certain updates. These scheduled downtime events incurred a significant amount of loss.

Testing Parity

Results are accurate when the conditions provided are real, or the environment where the newer updates are deployed experiences the same kind of stress as a production environment. The inherent equivalence between the two instances - blue & green, makes it the perfect choice to perform disaster recovery practices.
As compared to Canary Deployment, a small piece of the production environment is used, and a tiny amount of traffic is routed to test the update. Though it’s a profitable approach, with limited conditions impacted on the new update, we cannot establish the complete picture of the update when it’s finally deployed and made accessible to everyone.

Challenges of Blue Green Deployment Strategy

Failed User Transaction

During the initial switch to the green instance or the newly deployed instance, some users would be forced to log out of the application, or in some cases, the services can go down. If the new update is not working, and a switch back to the older environment is required, then the users logged into the green environment might face sudden blocking in services.
These issues can be counteracted with the use of advanced load balancers, which usually work by slowing down the incoming traffic instead of force diverting all the users out of their current sessions or waiting for the users to become inactive.

A Rise in Infrastructure Costs

Enterprises require to maintain an infrastructure that is double the size of their application to perform the Blue Green Deployment Strategy. Making this strategy a good choice, only if our application is not so hardware intensive. An ideal solution, in this case, would be the use of an elastic infrastructure that can help in absorbing the costs.

Compatibility of Codes

When both the existing code and the new updated code are supposed to work parallelly in the production environment, it is of utmost importance to ensure that both of them are consistent in every aspect. For example, if the new software requires some change in the database like adding a new field or column, which is different from the existing code, will make it difficult for us to switch the traffic between the two instances, as it will make the entire process incompatible.

Conclusion

Although the Blue Green deployment strategy involves cost, it is one of the most reliable approaches when it comes to checking the status of an application. This is ideal when our environments are consistent between releases and have our user sessions reliable across multiple new releases.
What’s helpful to notice is that the ever-growing need of adopting complex models like the Blue Green deployment strategy has created a new space for sophisticated services like Managed DevSecOps. They ensure the end-to-end execution of a faster-to-market model by

cost optimization
better uniformity between the new codes and existing codes
comprehensive observability of end-to-end traffic flow
security of the production environment, and much more that is involved in these processes.

The changing demands result in changing trends and being part of it, is what keeps any business afloat. The only way to sustain this dynamic market is to create our very own space, which is created as a result of a satisfied customer base.

The Value of Continuous Delivery

Komal-J-Prabhakar — Mon, 02 May 2022 05:38:32 +0000

Why Continuous Delivery?

From the start of every project, and throughout, every developer looks forward to the day, when the software or the related update will be finally released.
The wait is even more fruitful if the released code is devoid of any errors. That means making the code pass through a ceremonial load of tests, ensuring the code is free of bugs.

This has led to an evolution in the software development mechanism from the Waterfall Model toward continuity, through the methodologies like Agile and DevOps. Today we see a black and white difference (if the above models are compared), the Waterfall Model had non-overlapping steps, to now Agile and DevOps model is defined as an overlapping iterative process of SDLC.

The continuous model implies the frequent and predictable release of quality products. If relied upon a pipeline on daily basis, for the entire development cycle, the risks surrounding the release of applications or their scheduled updates are drastically reduced; as it is easier to notice errors and resolve them quickly. Thereby, making the pipeline robust and product releases smoother.

Continuous delivery encapsulates continuous integration, continuous testing, constant monitoring, and pipeline analytics; while emphasizing continuous delivery, we are aiming at making our tech teams responsive to changing market trends. It’s not just an exclusive practice seen or performed in “Unicorn” companies, tech companies, or large enterprises; this can also and should be performed or adopted by the small-scale startups too.

To support the above statement, we will be looking at some business cases, discussing the benefits and the ways Continuous Delivery can be implemented.

Top Business Benefits of Continuous Delivery

Improves Deliverability Speed

When it comes to outplaying your competitors in the market, the best way is to increase your responsiveness toward market trends. For that, the supposed application updates should be scheduled at proper intervals, or maybe new software should be released faster, and these can be easily facilitated with automated software delivery pipelines. With a faster time-to-market, businesses can claim a position in this very competitive Tech space.

Quality has always been the defining factor for any organization to truly win. When we say “speed,” we mean faster delivery of the highest quality.

Faster rollouts of erroneous code would be like targeting a suicidal speed, drowning all the efforts by the negative reviews from customers.

Enhanced Productivity

Better productivity is a sign of growth and is a byproduct of happy teams. Happier teams mean more engagement, which creates space for innovation. The happiness index can be made high if the amount of tedious tasks is reduced.

The tedious tasks can be like filling bug reports or conducting tests and repeating the entire process of development, etc. When tasks like these are automated, and all the errors found, get documented in an appropriate format, helping the dev team in recognition and subsequently, code is renewed, the entire process of unit testing, code review, and integration testing happens in an automated pipeline - the problem is just solved with least possible time invested.

Supports Sustainability

Businesses are in for long marathons. Staying ahead is very tiring. To stay ahead, we need to bring ample differentiation in our products, to make them stand out better. In addition to that, we need to ensure that every release is devoid of any possible errors.

Easier said than done!
What makes the above-mentioned points a reality, requires people to work 24/7. But if automation is implemented in repetitive tasks, the workload gets substantially reduced. Moreover, financially speaking, it always costs less, if something is done through machines rather than personnel.
Furthermore, with all that said and done, continuous delivery empowers businesses with flexibility and makes it easier to focus on the core objectives of the business.

Challenges while shifting to Continuous Delivery

Although continuous delivery is the right thing to do, designing resilient continuous delivery pipelines is no piece of cake!
Constructing these pipelines involves a huge deal of technical processes, operational culture, and organizational thinking, which can look daunting in the initial stages.

Low Budget

Creating continuous delivery pipelines requires the best players of the dev team. Companies, especially startups, find it difficult to allocate the senior engineers to the development of these pipelines, in order to keep their other priorities running.
Treating it as a side project, and involving the junior team won’t be of much help, where anyway it would again require the attention of senior engineers.
Not much surprise, though for better long-term results/growth, we need to start focusing on the building blocks, or the vital requirements that can help in this.
The only solution can be is to develop a plan and allocate funds appropriately, wherein the team can produce a continuous delivery pipeline MVP (minimum viable product) that can be scaled throughout your organization.

Forward Thinkers

Suppose the CD pipelines are in action, automation is in place, yet we do often see the apprehensive team players, and their need to conduct manual checks after all the steps are performed. This obviously seems like we have housed the wrong people, the teams should fearlessly and confidently change gears with the changing times.
In situations like these, it throws light on the fact of lack of training. The training should be such as to instill the fact that it’s easier to do the right thing, and hard to do the wrong things.

Lack of Priority

The near-sighted businesses classify designing these pipelines as an expense. From conceptualization to action, these pipelines are not an easy feat, they require a considerable amount of time, and also manpower.
No product owner would ever say, to stop the line of work and start working on pipelines, it may sound appropriate in the present times, but pushing it to the backlog would significantly reduce the chances of survival of business in the long term.

Conclusion

All these above challenges are not really a big hurdle. The market seems to have multiple options. We have certain Managed Microservice and Managed Kubernetes service providers, handling the end-to-end installation of customized CI/CD pipelines, offering support to various source code languages, having an interactive UI interface, and offering comprehensive visibility of all the steps running in pipelines - makes it easier to adopt them. Also, some solid security checks like - automated CI checks at every step, and an option to override the CI checks and allow effective troubleshooting.
Enterprises today, need to step up their game and shouldn’t have apprehensions about embracing progressive software development models. It’s not about where the business is today but where it’s planning to reach tomorrow. To move forward, it’s really important to adopt the current changes and react better and faster to the change.

A Comprehensive Guide to DevOps Lifecycle

Komal-J-Prabhakar — Wed, 20 Apr 2022 07:36:24 +0000

Recently, we are seeing a growing inclination of enterprises to adopt DevOps practices.
If we refer to this report, the global DevOps Platform market size is estimated to grow up to USD 26,370 million by 2028, from USD 6,737.6 million in 2021, which looks like a CAGR of 20.7% during 2022-2028.
Let’s have a brief introduction to Devops and understand the devops lifecycle.
DevOps can be defined as a cultural approach towards a collaborative atmosphere around the dev team and IT team. It is an amalgamation of philosophies, practices, and tools that enhance the organization’s efficiency in the deliverability of products and services, i.e., faster time to market.
So, how is it actually helping in faster software delivery?

Increases agility
Reduces manual effort
Efficient cross-functional team collaboration
Continuous innovation
Minimal defects (which is obvious when Dev and IT teams work in tandem)

To understand how devops practices make this possible, let’s understand the lifecycle of devops.

What is DevOps Lifecycle?

The DevOps lifecycle is an iterative process of automated software development, integration, testing, deployment, and monitoring. The DevOps approach is all about continuous experimentation and learning, followed by continuous improvements. These continuous improvements are what you see as new updates in your everyday software applications updates.

So a simple answer to - “What is DevOps lifecycle?”- is all the processes that ensure end-to-end optimization of the entire software development lifecycle, facilitating faster deliverability.

Decoding the Lifecycle of DevOps

Moving forward from “What is DevOps lifecycle?” to “What are the different stages that constitute the lifecycle of devops?”
From planning to monitoring, the entire process has been divided into 7 different stages. Any stage or phase, out of these 7 stages, can iterate multiple times throughout the project until it is finished or conforms to our requirements.
The following are the devops lifecycle phases:

Continuous Development
Continuous Integration
Continuous Testing
Continuous Feedback
Continuous Monitoring
Continuous Deployment
Continuous Operations

Continuous Development

This is the very first phase of the devops lifecycle where the objectives of a project are mapped, based on which the entire software development process is envisioned. Here, the DevOps team primarily focuses on the planning and coding part of the project, in which depending upon the business needs, the developers start coding the source code for the application.

The most popular language choices used for coding applications are JavaScript, C/C++, Ruby, and Python. Though we don’t really require any tool for coding but maintaining the codes is vital. We see a plethora of version control tools available such as GIT, TFS, GitLab, Subversion, Mercurial, Jira, BitBucket, and many more. This process of maintaining the source code is known as Source Code Management (SCM). Furthermore, these codes can be packaged into .exe files with the use of tools like Garden, Maven, and similar other tools.

Continuous Integration

The source code goes through multiple modifications, as it is a continuous process of review and the changes are implemented frequently. Therefore, this phase is also known as the Code Integration phase and is the most crucial in the entire lifecycle of devops. The new codes having additional functionalities are built and integrated into the existing code.
The new code generated and integrated with the existing code is made to pass through different stages of unit testing, code review, and integration testing, which finally leads to compilation, and packaging. This process of continuous integration also helps in reflecting the changes, the end-users would possibly experience with the updated code. Moreover, this is also the stage where developers plan the tests required in the later stages of the devops lifecycle.
There are various tools that are used in the procuring of the updated code and structuring it into .exe format. To name a few - Jenkin, Bamboo, GitLab, CI, and many more. Among them, Jenkin is an open-source tool, used widely to automate these builds and tests.

Continuous Testing

Some developers may prefer this step of the devops lifecycle, prior to Continuous Integration. In this phase, the Quality Analysts test the code constantly for bugs and errors, and upon discovery of any, it is sent back to the Continuous Integration phase for appropriate modifications.

These tests are automated, where a test environment is simulated with the use of Docker Containers. These automated tests not only save us time and effort but also reports generated from them, simplify the analysis of failed test cases. Thereby, reducing the provisioning and maintenance costs of test environments.
Following these automated tests, the code is then passed through the UAT process or User Assessment Testing process; qualifying this, the resultant code is simpler and bug-free.

There are different devops tools used for continuous testing - JUnit, Selenium, TestNG, and TestSigma. Selenium is an open-source automation testing tool, a popular choice, as it seamlessly supports multiple platforms and browsers. We do have a unified AI-driven test automation platform, TestSigma, that eliminates the technical complexities of automated tests through artificial intelligence.

Continuous Feedback

In this phase of devops lifecycle, the continuous improvements implemented to the code during the continuous integration and continuous testing, are analyzed. The developers measure and analyze the outcome of all the modifications implemented into the code.

It is the stage in the lifecycle of devops where the users/customers who tested the code, give their feedback as per their experience and expectations. The feedback received is assessed promptly and the modifications recommended are again implemented into the code. A positive response from the customers paves way for the release of a new version or update of the software application.

Continuous Monitoring

This phase in the lifecycle of devops, looks forward to the major participation of the IT team. The developers record data of the application usage and constantly monitor each functionality. The most common errors that are resolved by the developers are - “Server not reachable,” “Memory Down,” etc.

Through continuous monitoring, we can sustain the availability of services of an application by determining the threats and root causes of recurring system failures.
The role of the IT team seems vital, as they supervise the entire user activity for any unusual behavior and trace the presence of bugs.

Some popular DevOps tools used in this are - NewRelic, Sensu, ELK Stack, Splunk, and Nagios. These tools help in empowering the IT teams in monitoring the performance of the system, the production server, and subsequently the application.
If any major issue is observed, then the application is made to rerun all the earlier stages of the devops lifecycle.

Continuous Deployment

Though conventionally this step occurs before the continuous monitoring, the developers ensure that this step remains active throughout the lifecycle of devops, especially after our application is live and starts receiving traffic.

In this phase, the finalized tested code is deployed to the production server. The key process in this stage of the devops lifecycle is Configuration Management, which ensures accurate deployment of the codes. Essentially, configuration management is responsible for maintaining the consistency of the application in terms of performance and functioning, right from the release of codes to the servers - to scheduling the updates, whilst ensuring the configurations are kept consistent throughout.

Some popular devops tools used for Configuration Management are - Ansible, Puppet, and Chef. Containerisation tools like Vagrant, are also used in achieving continuous deployment through configuration management. Vagrant is known for developing coherence between different environments - from the development and testing of code to staging and production. Likewise, the devops teams use Docker for achieving scalability of continuous deployment. The benefit of these containerization tools is that they help in nullifying the production failures and also system errors by replicating and packaging the software couplings from the phases of development, testing, and staging. Ultimately the application runs smoothly on any device.

Continuous Operation

The last phase in the lifecycle of devops, and the shortest and least complicated of all stages. The purpose of this process is to automate the release of the application and its subsequent updates. This is one of the crucial phases in the devops lifecycle as it aims at eliminating planned downtime. A planned downtime refers to the time when the servers are offline for releasing updates. This downtime is equated to a loss, as the customers won’t be able to use it. With the automation of these processes, continuous operation boosts the uptime of the application. The tools like Kubernetes and Docker, container orchestrators, are most commonly used in this phase, to simplify the steps in the build, test, and deployment of applications to multiple environments.

Conclusion

We have reached the end of this discussion, from understanding “What is DevOps lifecycle?” to going into detail about the 7Cs of the DevOps lifecycle with their commonly preferred tools. The key objective behind learning the lifecycle of devops, is to be able to identify the steps involved in the development, and how we can maintain the continuity and optimize automation. This entire approach is all about the collaborative efforts of the developers, testers, and operations teams, and the elimination of siloed structure of working, working in a way where the software gets delivered quickly.
To make this process even simpler, we have a lot of platforms available in the market, supporting a wide range of integrations of these devops tools, plus supporting a variety of source code languages. The devops culture is new, but it is here to stay for a very long time. With its aim at delivering the highest quality standards to your software, it is about time for businesses to focus on keep rolling new updates with zero downtime and zero errors.

An Introduction to Canary Deployment Strategy

Komal-J-Prabhakar — Wed, 13 Apr 2022 09:16:12 +0000

Is Continuous Integration enough for testing?

With Continuous Integration, every code from developers’ workstations gets incorporated into a shared repository or a central repository, after which with automated build and tests, these codes are checked and are merged. What we notice here is that these are synthetic tests, in simpler words, the scripts on the basis of which these tests happen only emulate user experience. They cannot help the IT team understand the actual end-user experience. This also doesn’t give insights on device resources and health state, which can also affect the application performance.

Understanding “Canary” of Canary Deployment.

Before diving into the fact of - how Canary Deployment helps us in understanding the actual end-user experience, let’s begin our discussion by learning the significance of its name. Well, if somewhere your mind is comparing it with “Canary birds,” then you’re on the right track!
In British Mining History, these humble birds were used as “toxic gas detectors.” While mining for coals, if there is any way emission of toxic gasses like Carbon Monoxide, Nitrogen dioxide, etc, these birds alerted the miners about its presence as these birds are more sensitive to airborne toxins as compared to human beings. Similarly, the DevOps Engineers perform a canary deployment analysis of their code in CI/CD pipeline to gauge any possible errors present. However, here the figurative canaries are a small set of users, who will experience all the glitches present in the update.

Let’s define Canary Deployment!

Canary deployment is a process or technique of controlled rolling of a software update to a small batch of users, before making it available to everyone. Thereby, reducing the chances of widescale faulty user experience. When the update is examined and feedback is taken, this feedback is again applied and then released on a larger scale.

Steps Involved in Canary Deployment Strategy

To keep our customers happy and engaged, it's important to roll out new updates from time to time. Not ignoring the fact that every new change introduced, might have an error or two attached to it, we need a Canary Release Deployment analysis before releasing it to all our customers.

With the level of competition in the market, any bug left unattended is going to attract customers’ displeasure and might cause a good loss of the Company’s reputation.
Starting off by understanding the basic structure of the canary deployment strategy. We can elucidate it under the following headings:

Creation
Analysis
Roll-out/Roll-back

Creation

To begin with, we need to create a canary infrastructure where our newest update gets deployed. Now, we need to direct a small amount of traffic to this newly created canary instance. Well, the rest would be still continuing with the older version of our software model.

Analysis

Now, it's showtime for our DevOps team! Here they need to constantly monitor the performance insights received - data collected from network traffic monitors, synthetic transaction monitors, and all possible resources linked to the canary instance. After the very awaited data gets collected, the DevOps teams then start comparing it with the baseline version’s data.

Roll-out/Roll-back

After the analysis is done, it's time to think over the results of the comparative data, and whether rolling out a new feature is a good decision, or is it better to stick back to our baseline state and roll back the update.

Well, then how are we benefitted?

Zero Production Downtime

You know it when there’s small traffic, and the canary instance is not performing as expected, you can simply reroute them to your baseline version. When the engineers are conducting all sorts of tests at this point, they can easily pinpoint the source of error, and can effectively fix it, or roll back the entire update and prepare for a new one.

Cost-Efficient - Friendly with smaller Infrastructure

The goal of Canary Release Deployment analysis is to drive a tiny amount of your customers to the newly created canary instance - where the new update is deployed. This means you’re using a little extra of your infrastructure to facilitate the entire process. In addition to that, if we compare it with the blue-green deployment strategy, it requires an entire application hosting environment for deploying the new application. As compared to blue-green deployment, we don’t really have to put in our efforts in operating and maintaining the environment, in canary deployment, it's easier to enable and/or disable any particular feature based on any criteria.

Room for Constant Innovation

The flexibility of testing new features with a small subset of users, and being able to receive end-user experience immediately, is what motivates the dev team to bring in constant improvements/updates. We can increase the load of the canary instance up to 100% and can keep track of the production stability of the enrolled features.

Do we have any Limitations?

Well, everything has limitations. What’s important for us is to understand how to counteract them.

Time-consuming and Prone to Errors

Enterprises executing canary deployment strategy, perform the deployments in a siloed fashion. Then a DevOps Engineer is assigned to collect the data and analyze it manually. This is quite time-consuming as it is not scalable and hinders rapid deployments in CI/CD processes. There might be some cases where the analysis might go wrong and we might roll back a good update or roll forward a wrong one.

On-Premise Applications are difficult to update

Canary Deployment looks like an appropriate and quite a possible approach when it comes to applications present in Cloud. It is something to think about - when the applications are installed on personal devices. Even then, we can have a way around it by setting up an auto-update environment for end-users.

Implementations might require some skill!

We are focusing right now is on the flexibility it offers to test different versions of our application, but we should also bring our attention to managing the databases associated with all these instances. For performing a proper canary deployment and to be able to compare the old version with the new one, we need to modify the schema of the database to support more than one version of the application. Thereby, allowing the old and new versions to run simultaneously.

Wrapping up…

With an increasing interest of Enterprises to perform canary deployment analysis, it is to note that we need to counteract the limitations and make processes smoother. We need some good continuous delivery solution providers or Managed Kubernetes orchestrators to automate certain functionalities to keep errors at bay, and also integrate security at every stage of development.

An Introduction to Canary Deployment

Komal-J-Prabhakar — Wed, 13 Apr 2022 08:38:43 +0000

Is Continuous Integration enough for testing?

Understanding “Canary” of Canary Deployment.

Let’s define Canary Deployment!

Steps Involved in Canary Deployment Strategy

Creation
Analysis
Roll-out/Roll-back

Source

Creation
To begin with, we need to create a canary infrastructure where our newest update gets deployed. Now, we need to direct a small amount of traffic to this newly created canary instance. Well, the rest would be still continuing with the older version of our software model.

Analysis
Now, it's showtime for our DevOps team! Here they need to constantly monitor the performance insights received - data collected from network traffic monitors, synthetic transaction monitors, and all possible resources linked to the canary instance. After the very awaited data gets collected, the DevOps teams then start comparing it with the baseline version’s data.

Roll-out/Roll-back
After the analysis is done, it's time to think over the results of the comparative data, and whether rolling out a new feature is a good decision, or is it better to stick back to our baseline state and roll back the update.

Well, then how are we benefitted?

Zero Production Downtime
You know it when there’s small traffic, and the canary instance is not performing as expected, you can simply reroute them to your baseline version. When the engineers are conducting all sorts of tests at this point, they can easily pinpoint the source of error, and can effectively fix it, or roll back the entire update and prepare for a new one.

Cost-Efficient - Friendly with smaller Infrastructure
The goal of Canary Release Deployment analysis is to drive a tiny amount of your customers to the newly created canary instance - where the new update is deployed. This means you’re using a little extra of your infrastructure to facilitate the entire process. In addition to that, if we compare it with the blue-green deployment strategy, it requires an entire application hosting environment for deploying the new application. As compared to blue-green deployment, we don’t really have to put in our efforts in operating and maintaining the environment, in canary deployment, it's easier to enable and/or disable any particular feature based on any criteria.

Room for Constant Innovation
The flexibility of testing new features with a small subset of users, and being able to receive end-user experience immediately, is what motivates the dev team to bring in constant improvements/updates. We can increase the load of the canary instance up to 100% and can keep track of the production stability of the enrolled features.

Do we have any Limitations?

Well, everything has limitations. What’s important for us is to understand how to counteract them.

Time-consuming and Prone to Errors
Enterprises executing canary deployment strategy, perform the deployments in a siloed fashion. Then a DevOps Engineer is assigned to collect the data and analyze it manually. This is quite time-consuming as it is not scalable and hinders rapid deployments in CI/CD processes. There might be some cases where the analysis might go wrong and we might roll back a good update or roll forward a wrong one.

On-Premise Applications are difficult to update
Canary Deployment looks like an appropriate and quite a possible approach when it comes to applications present in Cloud. It is something to think about - when the applications are installed on personal devices. Even then, we can have a way around it by setting up an auto-update environment for end-users.

Implementations might require some skill!
We are focusing right now is on the flexibility it offers to test different versions of our application, but we should also bring our attention to managing the databases associated with all these instances. For performing a proper canary deployment and to be able to compare the old version with the new one, we need to modify the schema of the database to support more than one version of the application. Thereby, allowing the old and new versions to run simultaneously.

Wrapping up…

SOA vs. Microservices Architecture - The Much-Hyped Debate!

Komal-J-Prabhakar — Wed, 01 Dec 2021 10:46:08 +0000

The debate of “which is the right kind of software architecture?” has always been in the air. As a consequence, we do harbor doubts when it comes to picking sides or making decisions.

This blog is going to brush up on the basics surrounding SOA and Microservices Architecture.
Before we begin discussing the similarities and differences between SOA and Microservices Architecture, let us first understand -

What is SOA?
What is Microservices Architecture?
Advantages of Microservices
How are they similar and different at the same time?

What is SOA or Service-Oriented Architecture?

SOA or Service Oriented Architecture is a software architectural style that defines a way to reuse software components or services using a service interface that uses a common language network. A service is a self-contained unit of a software functionality or set of functionalities that contains code and data integrations to carry out specific tasks. These tasks could be - signing into a website, processing an application form, or checking a customer’s credit/rewards.
The reusability of these services or software components is possible because the service interface provides loose coupling between them, i.e., we can call any one of them, as it is not dependent on the pattern of integration implemented underneath.
This feature is both a risk and a benefit. It is because they have shared access to the ESB (enterprise service bus), and if an issue arises in one service, the other connected services would also get affected.

Different Service Types are:

Functional services	Deals with business services or business applications.
Enterprise services	Helps in implementing functionality.
Application services	Used to develop and deploy apps
Infrastructure services	Instrumental for backend processes

SOA, which emerged in the late 1990s, proved to be a turning point in the evolutionary stages of software development, as it facilitated connectivity between a monolithic application to a data or functionality of another system. Before its origin, developers had to recreate point-to-point integration in each new project.

What is Microservices Architecture?

Microservices architecture can be called a variant of the SOA, but the game-changer difference is that these are independent services or codes. Yes, in the case of microservices these are loosely coupled services that can be developed, deployed, and maintained “independently.”

Microservices communicate via APIs (application programming interfaces) to create individual applications performing a specific business function(s). These are agile, scalable, and resilient, created using programming languages like JAVA and Python.

To sum up, Microservices or Microservice Architecture is a cloud-native architectural approach, where each application is composed of loosely coupled services that are independently scalable, and deployable. Microservices are containerized to make these independent services portable.

Advantages of Microservices

Autonomy	As the microservices are independently deployable, it enables continuous improvement and faster app updates.
Independently Scalable	We can scale individual components/services of an application rather than scaling them entirely.
Reduced Downtime	When the fault can be easily isolated, the critical application can keep running even when one of its modules fails.
Easy Maintenance	As the codes are separated and can be independently deployed and scaled, it means the codebases are smaller and can be handled by small individual teams.

After discussing the advantages of Microservices, let’s move further to discuss the similarities we observe between SOA and Microservices.

Both prefer the agile approach for software development
Both architectural styles can be scalable to meet the speed of demanding operational data.
Both break large and complex applications into smaller codes or services.

Differences between SOA and Microservices Architecture

Basis	Service-oriented Architecture	Microservice Architecture
Scope	It has an enterprise approach.	It has an application approach.
Reusability	Reusability and component sharing increase scalability and efficiency.	Reusing at runtime causes real-time dependencies. Here the components reuse the code by copying and data duplications to improve coupling.
Synchronous calls	Reusable services are available across the enterprise using synchronous protocols like RESTful APIs.	An asynchronous pattern of interaction is preferred, such as event sourcing. A subscribe model is used to enable a microservices component to stay updated on the changes happening to the data in another component.
Data Duplication	Here data is directly altered at its primary source, thereby eliminating the need of maintaining complex data synchronization patterns.	Each microservice component has local access to all the data to ensure its independence from others. This implies duplication of code for its reusability which results in complex data synchronization patterns.
Communication	Share a common communication mechanism called Enterprise Service Bus(ESB).	Each microservice is developed independently and has its own communication protocol.
Interoperability	Use heterogeneous messaging protocols such as SOAP (Simple Object Access Protocol) and AMQP (Advanced Messaging Queuing Protocol)	Use lightweight messaging protocols like HTTP/REST (Representational State Transfers) and JMS (Java Messaging Service).
Governance	Shared resources ensure the implementation of common data governance standards across all services.	The independent nature does not enable consistent data governance across all services, providing greater flexibility for collaboration.
Storage	A single data storage layer is shared by all applications shared by all services within an application.	A microservice will dedicate a server or database for data storage for any service that needs it.

Conclusion

Both are indeed equally instrumental in contributing towards the continuous integration and continuous development of applications. In the end, it depends upon the nature of your business needs to successfully implement the right architectural style.

Anyhow Today, Microservices architecture is the epicenter of modern DevOps/DevSecOps/Cloud practices. Even though microservices give the right kind of flexibility, yet we do face certain complexities related to its design (defining a specific responsibility), security threats (increased risk due to its deployment across multi-cloud environments), and when it comes to testing, each microservice needs to be tested independently. To make all these processes seamless, we need the right microservices orchestration tools like BuildPiper, as it offers some state-of-the-art features like 360-degree observability, comprehensive CI checks configuration, end-to-end delivery automation, and so much more!

With reduced management overheads, reduced failures, and robust access and control, enterprises can direct their focus on the core issues of their business.

Challenges of Hybrid Cloud Computing

Komal-J-Prabhakar — Wed, 03 Nov 2021 12:25:40 +0000

The value of the global cloud market was at $52 billion in the year 2020 and is expected to reach approximately $145 billion in 2026, says Statista. If this enormous evaluation has piqued your interest, then let’s dive deep into the discussion of hybrid cloud management.

What is Hybrid Cloud?

To understand more about hybrid cloud architecture, let’s start with the basics.

Hybrid Cloud is an architectural style connecting public and private clouds, enabling orchestration, management, and application portability between them for creating a flexible optimal cloud environment for running enterprises’ compute workloads.

Hybrid Cloud Management enables businesses,

To combine some best-of-breed cloud management platforms and multi-cloud functionalities.
To connect multiple computers through a network and orchestrate processes with the help of automation.
With a customized optimal cloud computing environment for each workload, with a well-designed cloud management strategy.
To shift the workload freely between the public and private clouds.

How does Hybrid Cloud Work?

Traditional Hybrid Cloud Architecture and Functioning

It started with transforming some portions of the company’s on-premises data center into private cloud infrastructure and then connected it to the public cloud environment, hosted by off-premises Cloud Providers ( IBM Cloud, AWS, Google Cloud Services). This integration was possible by using sophisticated enterprise middleware like Red Hat OpenStack. It unified the management tools to monitor, allocate and manage the resources from a central console.

The traditional cloud management platform served various purposes:

Security and Regulations Compliant

Scalability and Resilience

Adoption of new technology

Enhances Legacy applications

VMware migration

Resource optimization and cost savings

Modern Hybrid Cloud Architecture

Not resembling the traditional cloud management platform, modern hybrid clouds do not need a vast network of APIs for the deployment of information and can run on the same OS in every IT environment and a single unified platform.

Hybrid Cloud Architecture is more focused on supporting the portability of workloads across all cloud environments and automation of deployments of those workloads to the best cloud environment. It focuses less on physical connectivity.

Benefits of Hybrid Cloud Management


Greater Infrastructure Efficiency:	Companies can avoid more of the technical debt of on-premises infrastructure by migrating legacy applications faster.
Regulatory Compliance and Security:	It facilitates the use of best-of-breed cloud security and regulatory compliance technologies.
Overall business acceleration:	faster response to customer feedback and delivery of applications suiting clients' requirements.

Challenges of Hybrid Cloud Management

Migration (from public or private cloud services to hybrid cloud services)	· The process is a time-consuming and resource-intensive process · The process involves integrating different specific cloud management brands and providers, and their native or proprietary features and components.
Governance	· Standardization of processes will be more complex in the management of hybrid cloud system that incorporates multiple systems
Network Infrastructure	· One of the key focal points for hybrid cloud management is network latency · It needs to account for bandwidth needs, management of private and public clouds, the locations of branch networks, and the requirements for each application.
Security	· A highly coordinated effort to meet both security and compliance requirements is required while using identity and access management across private and public clouds
Compliance	· The companies need to make sure the providers they use have the necessary certifications and policies that comply with the appropriate regulations applicable to their workloads and data.

Conclusion

Businesses need to be clear about the business requirements of their enterprise while using hybrid cloud management. Adopting hybrid cloud environments does provide better control and flexibility, but the process is often met with hurdles such as complexities in the form of integration, management, monitoring, security, or governance. To tackle these challenges, you need a hybrid cloud management service provider. OpsTree Solutions & OpsTree Labs has a highly specialized proficiency in dealing with DevSecOps Engineering and Technology transformation.

It offers services such as,

Cloud Ops and Migration
DevSecOps
Container Operations
SRE and App Services
DevOps services

By leveraging these services businesses can extensively focus on greater ROI, reduced time to market, and enhanced business growth.

Click here to know more about OpsTree and its services!