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5 Ways How DevOps Becomes a Dealmaker in Digital Transformation

The culture of DevOps-ism is a triumph for companies. DevOps has plundered the inefficiencies of the traditional model of software product release. But, there is a key to it. Companies must unlock the true DevOps tenacity by wiring it with its primary stakeholders – People and Process. A recent survey shows that most teams don’t have a flair for DevOps implementation. Another study reveals that around 78 percent of the organizations fail to implement DevOps. So, what makes the difference? Companies must underline and acclimatize the cultural shift, which erupts with DevOps. This culture is predominantly driven by automation to empower resilience, reduce costs and accelerate innovation. The atoms that make up the cultural ecosystem are people and processes. Funny story, most companies that dream of being digital savvy, still carry primitive mind-sets. Some companies have recognized this change. The question remains – are they adept at pulling things together? Are You in the Pre-DevOps Era, Still? It is archaic! Collaboration and innovation, for the most part, is theoretical. The technological proliferation coupled with cut-throat competition has put your company in a hotspot. You feel crippled embracing the disruptive wave of the digital renaissance. Also, you feel threatened by a maverick Independent Software Vendor – who is new to the software sector. If the factors above seem, relevant, it is time to move away from the legacy approach. The idea is simple – streamline and automate your software production – across the enterprise. It is similar to creating assembly lines, which operates parallel, continuous and in real-time. If you consider manufacturing, this concept is more than 150 years old. In software space, we have just realized the noble idea. Where it all started….. The IT industry experienced a radical change due to rapid consumerization and technological disruption. This created a need for companies to be more agile, intuitive and transparent in their service offerings. The digital transformation initiatives are continually pushing the boundaries to deliver convergent experiences that are insightful, social and informative. Further, the millennials who form more than 50 percent part of the overall IT decision makers globally are non-receptive to inefficient technologies and slow processes. They want their employees to work in an innovative business environment with augmented collaboration and intelligent operations. It is essential for the organization to follow an integrated approach for driving digital transformation, integrating cross-functionalities and enabling IT agility. DevOps enables enterprises to design, create, deploy and manage applications with new age software delivery principles. It also helps in creating unmatched competencies for delivering high-quality applications faster and easier; while accelerating innovation. With DevOps, organizations can divide silos facilitating collaboration, communication, and automation with better quality and reduced risk and cost. Below are the five key DevOps factors to implement for improving efficiency and accelerating innovation. 1. Automating Continuous Integration/Continuous Delivery DevOps is not confined to your departments. Nor it is just a deployment of some five-star tools. DevOps is a journey to transform your organization. It is essential to implement and assess a DevOps strategy to realize the dream of software automation. Breaking the silos, connecting isolated teams and wielding a robust interface can become taskmasters. This gets more tedious for larger companies. The initial focus must remain on integrating people in this DevOps model. The idea is to neutralize resistance, infuse confidence, and empower collaboration. Once these ideas become a reality, automation will become the protagonist. The question remains – How automation will be the game changer? This brings the lens on Continuous Integration/ Continuous Delivery (CI/CD). It works as a catalyst in channelizing automation throughout your organization. Historically, software development and delivery have been teeth-grinding. Even the traditional DevOps entails a manual cycle of writing codes, conducting tests, and deploying codes. This brings several pitfalls – multiple touchpoints, non-singular monitoring, increased dependencies on various tools, etc. How to Automate the CI/CD Pipeline? Select an automation server that provides numerous tools and interfaces for automation Select a version control and software development platform to commit codes Pull the codes in the build phase via automation server Compile codes in the build phase for various tasks Execute a series of tests for the compiled codes Release the codes in the staging environment Deploy the codes from the staging server via Docker An automated CI/CD pipeline will mitigate caveats associated with the traditional DevOps. It will result in a single, centralized view of project status, across stages. It drastically brings down the human intervention, moving you towards zero errors. But, is that all simple? Definitely no. It has its own set of challenges. Companies that are maneuvering from waterfall to DevOps, often end up automating wrong processes. How can teams avoid this? Well, have the following checklist handy. The frequency of process/workflow repetitions The time duration of the process Dependencies on people, tools, and technologies Delays resulting due to dependencies Errors in processes, if it is not automated These checklists will provide insights on the bottlenecks. It will help prioritize and automate critical tasks – starting from code compiling, testing to deployment. 2. The Holy Nexus of Cloud and DevOps You don’t buy a superbike to drive it in city traffics. You would prefer wide roads, less traffic to unleash its true speed. Then why do Cloud without DevOps? The combination of Cloud and DevOps is magical. Often, IT managers don’t realize it. Becoming a Cloud first company is not possible without a DevOps first approach. It is a case of the sum being more significant than parts. What is the point of implementing DevOps correctly, when the deployment platform is inefficient? Similarly, a scalable deployment platform loses its charm without fast and continuous software development. Cloud creates a single ecosystem, which provides DevOps with its natural playground. The centralized platform offered by Cloud enables continuous production, testing, and deployment. Most Cloud platforms come with DevOps capabilities of Continuous Integration and Continuous Delivery. This reduces the cost of DevOps in an On-Premise environment. Consider the case of Equifax – a consumer credit reporting company. They store their data on cloud and in-house data centers. In 2018, they released a document on the cyber-attack, which hit them in Sep 2017. Hackers collected around 2.4 million personally identifiable information (PII) of their customers. The company had to announce that they will provide credit file monitoring services to affected customers at no cost. Isn’t it damaging – monetarily and morally? But, what made hackers get access to such sensitive customer information? Well, per the website, there was a vulnerability Apache Struts CVE-2017-5638 to steal the data. Although the company patched this vulnerability in March 2017, it required more profound expertise and smarter process regime. If they had a DevOps strategy to redeploy software with continuous penetration testing more frequently, a cyber-attack could have averted. It is a genuine concern for any CIO to derive the value of cost, agility, security, and automation from their Cloud investment. The most common hurdle to this is the less compatible IT process. There other significant challenges too. Per a recent survey by RightScale, around 58 percent of Cloud users think saving cost is their top priority. Approximately 73 percent of the respondents believe that lack of skill expertise is a significant challenge. More than 70 percent of respondent said that governance and quality is an issue. The report also outlines integration as a challenge when moving from a legacy application to the Cloud. DevOps can standardize the processes and set the right course to leverage Cloud. DevOps in the backend and Cloud in the frontend gives a competitive edge. Cloud works well when your Infrastructure as Code (IaC) is successful. IT teams must write the right scripts and configure it in the application. Manually writing infrastructure scripts can be daunting. DevOps can automate scripts for aligning IT processes to Cloud. 3. Microservices – The Modern Architecture Microservices Without DevOps? Think Again! The sea-changes in consumer preferences have altered companies’ approach to delivering applications. Consumers want results in real-time, unique to their needs. Perhaps, this is why companies such as Netflix and Amazon have lauded the benefits of Microservices. It instills application scalability and drives product release speed. Companies also leverage Microservices to stay nimble and boost their product features. The main aim of Microservices is to shy away from the monolithic application delivery. It breaks down your application components into standalone services (Microservices). These services then must undergo development, testing, and deployment in different environments. The services’ numbers can be in 100s or 1000s. Additionally, teams can use various tools for each service. The resultant will be mammoth tasks coupled with an exponential burden on the operations. The process complexities and time-battle will also be a nightmare. Leveraging Microservices with a waterfall approach will not extract its real benefits. You must de-couple the silo approach to incubate the gems of DevOps – People>Process>Automation. Microservices without DevOps would severely jolt teams productivity. The Quality Assurance teams would experience neck-breaking pressure due to untested codes. They will become bottlenecks, hampering the process efficiencies. DevOps with its capability to trigger continuity will stitch every workflow through automation. 4. Containers –Without DevOps? Consider companies of the size and nature of Netflix that require to update data in real-time and on an on-going basis. They must keep their customers updated with new features and capabilities. This isn’t feasible without Cloud. And, on top of that, releasing multiple changes daily, will be dreadful. Thereby, for smooth product operations, Container Architecture is a must. In such a case, they must daily update their Container Services – multiple times. It entails website maintenance, releasing new services (in different locations) and responding to security threats. Even if you are a small to medium Independent Software Vendor operating in the upper echelons of the technology world, your software product requires a daily upbeat. Your developers will always be on their toes for daily security and patching updates. This a daunting task, isn’t it? DevOps is the savior. DevOps will hold back for your applications that are built in the Cloud. It will set a continuous course of monitoring through automation and ease the pressure of monitoring from developers. Without DevOps, Container Architecture won’t sustain the pressure. 5. Marrying DevOps, Lean IT, and Agile The right mix of DevOps, Lean and Agile amplifies business performance. Agile emphasizes greater collaboration for developing software. Lean focuses on eliminating wastes. DevOps wants to align software development with software delivery. The three work as positives; adding them will only augment the outcome. However, there persists a contradiction in perception towards adopting these three principles. When Agile took strides, the teams said that we already do Lean IT. When DevOps took strides, the teams said that we already do Agile. But, the three principles strive to achieve similar things in different areas of the software lifecycle. Combining DevOps, Lean and Agile can be an uphill task. Especially, for leaders that carry the traditional mindset. Organizations must revive their leadership style to align with modern business practices. The aim must be moving towards a collaborative environment for delivering value to the customers. Companies must focus on implementing a modern communication strategy at the workplace. It is necessary that they address the gaps between IT and the rest of the groups within an organization. They must be proactive in initiating mindful cross-functional relationships, backed by streamlined communications. The software development teams will then work as protagonists in embracing DevOps, Lean and Agile to survive the onslaught of competition. It is also essential to champion each of the above concept. This will ensure that we profit out of each component in the combination. Organizational leadership must relentlessly work to create a seamless workflow, while removing bottlenecks, cutting delays, and eliminating reworks. Companies haven’t yet fathomed the true benefits of DevOps-Agile-Lean combination. It needs time and the team of experts to capitalize on these three principles. Additionally, companies shy away from exploiting the agility and responsiveness of modern delivery architects – Microservices, in particular. This becomes a hindrance in reaping the full potential of the combination. The crux of driving DevOps-Agile-Lean combination is a business-driven approach. Continual feedback backed by the right analytics also plays a crucial role. It facilitates fail-fast, thereby, creating a loop of continuous improvement. Agile offers a robust platform to design software, which is tuned with the market demands. DevOps stitches the process, people and technology, ensuring efficient software delivery. Final Thoughts Adopting DevOps is a promising move. Above, we have depicted in 5 manners how DevOps is your digital transformation dealmaker. However, it can be nerve crunching. It takes patience, expertise, and experience for embodying its purest form. A half-baked DevOps strategy might give you a few immediate results. In the long run, it will deride your teams’ efforts. However, automation is the best way to sail through it.

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ci/cd cloud cloud devops Containers continuous integration continuous-delivery devops Digital Transformation Microservices

An Introduction to Serverless and FaaS (Functions as a Service)

Evolution of Serverless ComputingWe started with building monolithic applications for installing and configuring OS. This was followed by installing application code on every PC to VM’s to meet their user’s demand. It simplified the deployment and management of the servers. Datacenter providers started supporting a virtual machine, but this still required a lot of configuration and setup before being able to deploy the application code.After a few years, Containers came to the rescueDockers made its mark in the era of Containers, which made the deploying of applications easier. They provided a simpler interface to shipping code directly into production. They also made it possible for platform providers to get creative. Platforms could improve the scalability of users’ applications. But what if developers could focus on even less? It can be possible with Serverless Computing. What exactly is “Serverless”?Serverless computing is a cloud computing model which aims to abstract server management and low-level infrastructure decisions away from developers. In this model, the allocation of resources is managed by the cloud provider instead of the application architect, which brings some serious benefits. In other words, serverless aims to do exactly what it sounds like—allow applications to be developed without concerns for implementing, tweaking, or scaling a server.In the below diagram, you can understand that you wrap your Business Logic inside functions. In response to the events, these functions execute on the cloud. All the heavy lifting like Authentication, DB, File storage, Reporting, Scaling will be handled by your Serverless Platform. For Example AWS Lamba, Apache IBM openWhisk.When we say “Serverless Computing,” does it mean no servers involved?The answer is No. Let’s switch our mindset completely. Think about using only functions — no more managing servers. You (Developer) only care about the business logic and leave the rest to the Ops to handle.Functions as a Service (FaaS)It is an amazing concept based on Serverless Computing. It provides means to achieve the Serverless dream allowing developers to execute code in response to events without building out or maintaining a complex infrastructure. What this means is that you can simply upload modular chunks of functionality into the cloud that are executed independently. Sounds simple, right? Well, it is.If you’ve ever written a REST API, you’ll feel right at home. All the services and endpoints you would usually keep in one place are now sliced up into a bunch of tiny snippets, Microservices. The goal is to completely abstract away servers from the developer and only bill based on the number of times the functions have been invoked.Key components of FaaS:Function: Independent unit of the deployment. E.g.: file processing, performing a scheduled taskEvents: Anything that triggers the execution of the function is regarded as an event. E.g.: message publishing, file uploadResources: Refers to the infrastructure or the components used by the function. E.g.: database services, file system servicesQualities of a FaaS / Functions as a ServiceExecute logic in response to events. In this context, all logic (including multiple functions or methods) are grouped into a deployable unit, known as a “Function.”Handle packaging, deployment, scaling transparentlyScale your functions automatically and independently with usageMore time focused on writing code/app specific logic—higher developer velocity.Built-in availability and fault tolerancePay only for used resourcesUse cases for FaaSWeb/Mobile ApplicationsMultimedia processing: The implementation of functions that execute a transformational process in response to a file uploadDatabase changes or change data capture: Auditing or ensuring changes meet quality standardsIoT sensor input messages: The ability to respond to messages and scale in responseStream processing at scale: Processing data within a potentially infinite stream of messagesChatbots: Scaling automatically for peak demandsBatch jobs scheduled tasks: Jobs that require intense parallel computation, IO or network accessSome of the platforms for ServerlessIntroduction to AWS Lambda (Event-driven, Serverless computing platform)Introduced in November 2014, Amazon provides it as part of Amazon Web Services. It is a computing service that runs code in response to events and automatically manages the computing resources required by that code. Some of the features are:Runs Stateless – request-driven code called Lambda functions in Java, NodeJS & PythonTriggered by events (state transitions) in other AWS servicesPay only for the requests served and the compute timeAllows to Focus on business logic, not infrastructureHandles your codes: Capacity, Scaling, Monitoring and Logging, Fault Tolerance, and Security PatchingSample code on writing your first lambda function:This code demonstrates simple-cron-job written in NodeJS which makes HTTP POST Request for every 1 minute to some external service.For detail tutorial, you can read on https://parall.ax/blog/view/3202/tutorial- serverless-scheduled-tasksOutput: Makes a POST call for every minute. The function that is firing POST request is actually running on AWS Lambda (Serverless Platform).Conclusion: In conclusion, serverless platforms today are useful for tasks requiring high-throughput rather than very low latency. It also helps to complete individual requests in a relatively short time window. But the road to serverless can get challenging depending on the use case. And like any new technology innovations, serverless architectures will continue to evolve to become a well-established standard.References: https://blog.cloudability.com/serverless-computing-101/ https://www.doc.ic.ac.uk/~rbc/papers/fse-serverless-17.pdf https://blog.g2crowd.com/blog/trends/digital-platforms/2018-dp/serverless-computing/ https://www.manning.com/books/serverless-applications-with-node-js

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Aziro (formerly MSys Technologies) 2019 Tech Predictions: Smart Storage, Cloud’s Bull Run, Ubiquitous DevOps, and Glass-Box AI

2019 brings us to the second-last leg of this decade. From the last few years, IT professionals have been propagating rhetoric. They state that the technology landscape is seeing a revolutionary change. But, most of the “REVOLUTIONARY” changes, has, over the time lost their gullibility. Thanks to the awe-inspiring technologies like AI, Robotics, and upcoming 5G networks most tech pundits consider this decade to be a game changer in the technology sector.As we make headway into 2019, the internet is bombarded with numerous tech prophecies. Aziro (formerly MSys Technologies) presents to you the 2019 tech predictions based on our Storage, Cloud, DevOps and digital transformation expertise.1. Software Defined Storage (SDS)Definitely, 2019 looks promising for Software Defined Storage. It’ll be driven by changes in Autonomous Storage, Object Storage, Self-Managed DRaaS and NVMes. But, SDS will also be required to push the envelope to acclimatize and evolve. Let’s understand why so.1.1 Autonomous Storage to Garner MomentumBacked by users’ demand, we’ll witness the growth of self-healing storage in 2019. Here, Artificial Intelligence powered by intelligent algorithms will play a pivotal role. Consequently, companies will strive to ensure uninterrupted application performance, round the clock.1.2 Self-Managed Disaster Recovery as a Service (DRaaS) will be ProminentSelf-Managed DRaaS reduces human interference and proactively recovers business-critical data. It then duplicates the data in the Cloud. This brings relief during an unforeseen event. Ultimately, it cuts costs. In 2019, this’ll strike chords with enterprises, globally, and we’ll witness DRaaS gaining prominence.1.3 The Pendulum will Swing Back to Object Storage as a Service (STaaS)Object Storage makes a perfect case for cost-effective storage. Its flat structure creates a scale-out architecture and induces Cloud compatibility. It also assigns unique Metadata and ID for each object within storage. This accelerates the data retrieval and recovery process. Thus, in 2019, we expect companies to embrace Object Storage to support their Big data needs.1.4 NMVes Adoption to Register TractionIn 2019, Software Defined Storage will accelerate the adoption rate of NVMes. It rubs off glitches associated with traditional storage to ensure smooth data migration while adopting NVMes. With SDS, enterprises need not worry about the ‘Rip and Replace’ hardware procedure. We’ll see vendors design storage platforms that append to NVMes protocol. For 2019, NMVes growth will mostly be led by FC-NVME and NVMe-oF.2. Hyperconverged Infrastructure (HCI)In 2019, HCI will remain the trump card to create a multi-layer infrastructure with centralized management. We’ll see more companies utilize HCI to deploy applications quickly. This’ll circle around a policy-based and data-centric architecture.3. Hybridconverged Infrastructure will Mark its FootprintHybridconverged Infrastructure (HCI.2) comes with all the features of its big brother – Hyperconverged Infrastructure (HCI.1). But, one extended functionality makes the latter smarter. Unlike HCI.1, it allows connecting with an external host. This’ll help HCI.2 mark its footprint in 2019.4. VirtualizationIn 2019, Virtualization’s growth will be centered around Software Defined Data Centers and Containers.4.1 ContainersContainer technology is ace in the hole to deliver promises of multi-cloud – cost efficacy, operational simplicity, and team productivity. Per IDC, 76 percent of users’ leverage containers for mission-critical applications.4.1.1 Persistent Storage will be a Key ConcernIn 2019, Containers’ users will envision a cloud-ready persistent storage platform with flash arrays. They’ll expect their storage service providers to implement synchronous mirroring, CDP – continuous data protection and auto-tiering.4.1.2 Kubernetes Explosion is ImminentThe upcoming Kubernetes version is rumored to include a pre-defined configuration template. If true, it’ll enable an easier Kubernetes deployment and use. This year, we are also expecting a higher number of Kubernetes and containers synchronization. This’ll make Kubernetes’ security a burgeoning concern. So, in 2019, we should expect stringent security protocols around Kubernetes deployment. It can be multi-step authentication or encryption at the cluster level.4.1.3 Istio to Ease Kubernetes Deployment HeadacheIstio is an open source service mesh. It addresses the Microservices’ application deployment challenges like failure recovery, load balancing, rate limiting, A/B testing, and canary testing. In 2019, companies might combine Istio and Kubernetes. This can facilitate a smooth Container orchestration, resulting in an effortless application and data migration.4.2 Software Defined Data CentersMore companies will embark on their journey to Multi-Cloud and Hybrid-Cloud. They’ll expect a seamless migration of existing applications to a heterogeneous Cloud environment. As a result, SDDC will undergo a strategic bent to accommodate the new Cloud requirements.In 2019, companies will start cobbling DevOps and SDDC. The pursuit of DevOps in SDDC will be to instigate a revamp of COBIT and ITIL practice. Frankly, without wielding DevOps, cloud-based SDDC will remain in a vacuum.5. DevOpsIn 2019, companies will implement a programmatic DevOps approach to accelerate the development and deployment of software products. Per this survey, DevOps enabled 46x code deployment. It also skyrocketed the deploy lead time by 2556x. This year, AI/ML, Automation, and FaaS will orchestrate changes to DevOps.5.1 DevOps Practice Will Experience a Spur with AI/MLIn 2019, AI/ML centric applications will experience an upsurge. Data science teams will leverage DevOps to unify complex operations across the application lifecycle. They’ll also look to automate the workflow pipeline – to rebuild, retest and redeploy, concurrently.5.2 DevOps will Add Value to Functions as a Service (FaaS)Functions as a Service aims to achieve serverless architecture. It leads to a hassle-free application development without perturbing companies to handle the monolithic REST server. It is like a panacea moment for developers.Hitherto, FaaS hasn’t achieved a full-fledged status. Although FaaS is inherently scalable, selecting wrong user cases will increase the bills. Thus, in 2019, we’ll see companies leveraging DevOps to fathom productive user cases and bring down costs drastically.5.3 Automation will be the Mainstream in DevOpsManual DevOps is time-consuming, less efficient, and error-prone. As a result, in 2019, CI/CD automation will become central in the DevOps practice. Consequently, Infrastructure as a Code to be in the driving seat.6. Cloud’s Bull Run to ContinueIn 2019, organizations will reimagine the use of Cloud. There will be a new class of ‘born-in-cloud’ start-ups, that will extract more value by intelligent Cloud operations. This will be centered around Multi-Cloud, Cloud Interoperability, and High Performance Computing. More companies will look to establish a Cloud Center of Excellence (CoE). Per RightScale survey, 57 percent of enterprises already have a Cloud Center of Excellence.6.1 Companies will Drift from “One-Cloud Approach.”In 2018, companies realized that having a ‘One-Cloud Approach’ encumbers their competitiveness. In 2019, Cloud leadership teams will bask upon the Hybrid-Cloud Architecture. Hybrid-Cloud will be the new normal within Cloud Computing in 2019.6.2 Cloud Interoperability will be a Major ConcernIn 2019, companies will start addressing the issues of interoperability by standardizing Cloud architecture. The use of the Application Programming Interface (APIs) will also accelerate. APIs will be the key to instill the capability of language neutrality, which augments system portability.6.3 High Performance Computing (HPC) will Get its Place on CloudIndustries such as Finance, Deep Learning, Semiconductors or Genomics are facing the brunt of competition. They’ll envision to deliver high-end compute-intensive applications with high performance. To entice such industries, Cloud providers will start imparting HPC capabilities in their platform. We’ll also witness large scale automation in Cloud.7. Artificial IntelligenceFor 2019 AI/ML will come out of the research and development model to be widely implemented in organizations. Customer engagements, infrastructure optimization, and Glass-Box AI, will be in the forefront.7.1 AI to Revive Customer EngagementsBusinesses (startups or enterprise) will leverage AI/ML to enable a rich end-user experience. Per Adobe, enterprises using AI will more than double in 2019. Tech and non-tech companies, alike, will strive to offer personalized services leveraging Natural Language Processing. The focus will remain to create a cognitive customer persona to generate tangible business impacts.7.2 AI for Infrastructure OptimizationIn 2019, there will a spur in the development of AI embedded monitoring tools. This’ll help companies to create a nimble infrastructure to respond to the changing workload. With such AI-driven machines, they’ll aim to cut down the infrastructure latency, infuse robustness in applications, enhance performances, and amplify outputs.7.3 Glass-Box AI will be crucial in Retail, Finance, and HealthcareThis is where Explainable AI will play its role. Glass-Box AI will create key customers’ insights with underlying methods, errors or biases. In this way, retailers don’t necessarily follow every suggestion. They can sort out responses that fit rights in that present scenario. The bottom-line will be to avoid customer altercations and bring out fairness in the process.

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Micro-Services and Containers – Overview and Benefits

The worldwide technology community is acutely focused on the Digital Transformation Era of the day. This focus has spiked an unprecedented demand in highly competent Digital Transformation Services from IT service providers. This article gives you an in-depth understanding of some key application containerization best practices, which will give you a clear perspective on the basic requirement for any robust Digital Transformation services and solutions. A Precursor On Digital Transformation And Containerization Digital transformation and containerization; let us see how two seemingly orthogonal ideas concur. Just as a precursor, we see people everywhere glued to their screens. People are experiencing and interacting with the world through the screens of their gadgets. In many countries, over 90 percent of people have access to and are using mobile phones, tabs, laptops, and other smart screen devices. The digital world is providing people with open, fast, and transparent access to the services and products. With so many people on highly available digital fabric, with digital identities, it has become imperative for businesses to provide services in the digital world. This drives digital transformation. Thus, we have witnessed rise in the container service providers globally. Since 2013, the growth & adoption of container technologies has been exponential and continues to explode with no hint of slowing down. CET (Cloud-Enabling technologies) which includes Virtualization, Containers, and Private PaaS is expected to grow at a CAGR of 8.84 percent during the period 2017-2021. Containers market hold a significant portion of market revenue, which promotes the upward revenue growth trajectory, given some of the adoption trends. With over $40B revenue projections for the year 2020, the adoption of containers has become a prime focus area for enterprise customers. Let us glance at the digital transformation journey with application containerization. Today’s Challenges With the advent of e-commerce and other web-applications, users have the following expectations from the service: The service should always be ON – up and running It should be accessible from anywhere It must be responsive (reasonably fast) It should work seamlessly with different form factors (screen sizes) without any change in user experience Ever changing technological landscape is varying at a rapid pace. New technologies, new competitors emerge quickly. Responding to these challenges needs agility. Along with the changes in technology, there are changes in compliance, rules, and regulations. This puts additional pressure on businesses to respond quickly. Most companies have monolith applications or set of such applications that are currently servicing the customers. Such applications run as a significant process consuming many resources. Although at times monolith applications give a good performance, they suffer from drawbacks such as: Lack Of Agility Increased Costs Less Flexibility Or Adaptability Lack Of Elasticity Transitioning To Micro-Services Before we jump into transitioning to micro-services, let us understand that micro-services is an architectural style that structures an application as a collection of loosely coupled small services, which implement business capabilities. The micro-service architecture enables the continuous delivery/deployment of large, complex applications. In other words, micro-services architectural style is an approach to developing a single application as a suite of small autonomous services, each running in its own process and communicating with lightweight mechanisms, often an HTTP(S) resource API, which is modeled around a business domain. Some of the benefits of micro-services include: 1. Likely to consume fewer resources Unlike monolithic applications, only those micro-services, that see demand, need to be scaled. In monolith applications, most of the modules have to be scaled up. Because few services may have to be scaled up, fewer resources are likely to be consumed most of the time. 2. Scalable yet elastic Micro-services can be scaled out as the need be. Over a server farm, micro-services could be scaled out. When there is drop in demand, those services could be turned off or reduced. Due to smaller footprint, more services could be accommodated. If not all the services see demand at the same time, a smaller set of resources could be used for more scalable and elastic services. 3. More adaptable Change in the business environment or rules and regulations make it necessary to tweak software. If policy engines were available as micro-service, other services do not get affected. Such micro-service could be separately updated or tweaked. It can be separately tested. Thus, micro-service based systems are more adaptable. 4. Isolation In most cases, changes in a micro-service do not affect other micro-services, provided there are well-designed interfaces between them. Thus, there is isolation between the services. Each service may use a different technology. Isolation reduces or eliminates the impact of technology or design choice. 4 Key Uses of Application Containerization ontainers provide a convenient way to implement micro-services. Virtualization is being used over last decade to achieve some of the goals discussed above and for better hardware utilization. Virtualization adds 30 percent overhead. Hypervisors that allow running virtual machines on hardware add to this significant overhead. Container overheads are minimal and can provide even better resource utilization. Containers run on a machine for most optimal performance and resource utilization. If the machine fails all the containers running on that machine, get impacted. Container orchestration & automation engine software such as Kubernetes address this single point of failure (SPOF). Deploying containers on server farms To handle a variety of failures and to provide always ON system, the containers must be deployed on a server farm. Software such as Kubernetes provides the ability to provide scalability, elasticity, load balancing of the containers over the farm. Containerization can help the digital transformation journey by creating a scalable, elastic, adaptable, and quick deployment of micro-services to align with the rapidly changing business needs. They can help to respond to disruptive technologies and rapidly changing business environment to meet today’s challenges.

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Decoding the Self-Healing Kubernetes: Step by Step

PrologueBusiness application that fails to operate 24/7 would be considered inefficient in the market. The idea is that applications run uninterrupted irrespective of a technical glitch, feature update, or a natural disaster. In today’s heterogeneous environment where infrastructure is intricately layered, a continuous workflow of application is possible via self-healing.Kubernetes, which is a container orchestration tool, facilitates the smooth working of the application by abstracting machines physically. Moreover, the pods and containers in Kubernetes can self-heal.Captain America asked Bruce Banner in Avengers to get angry to transform into ‘The Hulk’. Bruce replied, “That’s my secret Captain. I’m always angry.”You must have understood the analogy here. Let’s simplify – Kubernetes will self-heal organically, whenever the system is affected.Kubernetes’s self-healing property ensures that the clusters always function at the optimal state. Kubernetes can self-detect two types of object – podstatus and containerstatus. Kubernetes’s orchestration capabilities can monitor and replace unhealthy container as per the desired configuration. Likewise, Kubernetes can fix pods, which are the smallest units encompassing single or multiple containers.The three container states include1. Waiting – created but not running. A container, which is in a waiting stage, will still run operations like pulling images or applying secrets, etc. To check the Waiting pod status, use the below command. kubectl describe pod [POD_NAME] Along with this state, a message and reason about the state are displayed to provide more information.... State: Waiting Reason: ErrImagePull ... 2. Running Pods – containers that are running without issues. The following command is executed before the pod enters the Running state.postStartRunning pods will display the time of the entrance of the container.... State: Running Started: Wed, 30 Jan 2019 16:46:38 +0530 ... 3. Terminated Pods – container, which fails or completes its execution; stands terminated. The following command is executed before the pod is moved to Terminated.prestopTerminated pods will display the time of the entrance of the container.... State: Terminated Reason: Completed Exit Code: 0 Started: Wed, 30 Jan 2019 11:45:26 +0530 Finished: Wed, 30 Jan 2019 11:45:26 +0530 ... Kubernetes’ self-healing Concepts – pod’s phase, probes, and restart policy.The pod phase in Kubernetes offers insight into the pod’s placement. We can havePending Pods – created but not runningRunning Pods – runs all the containersSucceeded Pods – successfully completed container lifecycleFailed Pods – minimum one container failed and all container terminatedUnknown PodsKubernetes execute liveliness and readiness probes for the Pods to check if they function as per the desired state. The liveliness probe will check a container for its running status. If a container fails the probe, Kubernetes will terminate it and create a new container in accordance with the restart policy. The readiness probe will check a container for its service request serving capabilities. If a container fails the probe, then Kubernetes will remove the IP address of the related pod.Liveliness probe example. apiVersion: v1 kind: Pod metadata: labels: test: liveness name: liveness-http spec: containers: - args: - /server image: k8s.gcr.io/liveness livenessProbe: httpGet: # when "host" is not defined, "PodIP" will be used # host: my-host # when "scheme" is not defined, "HTTP" scheme will be used. Only "HTTP" and "HTTPS" are allowed # scheme: HTTPS path: /healthz port: 8080 httpHeaders: - name: X-Custom-Header value: Awesome initialDelaySeconds: 15 timeoutSeconds: 1 name: liveness The probes includeExecAction – to execute commands in containers.TCPSocketAction – to implement a TCP check w.r.t to the IP address of a container.HTTPGetAction – to implement a HTTP Get check w.r.t to the IP address of a container.Each probe gives one of three results:Success: The Container passed the diagnostic.Failure: The Container failed the diagnostic.Unknown: The diagnostic failed, so no action should be taken.Demo description of Self-Healing Kubernetes – Example 1We need to set the code replication to trigger the self-healing capability of Kubernetes.Let’s see an example of the Nginx file. apiVersion: apps/v1 kind: Deployment metadata: name: nginx-deployment-sample spec: selector: matchLabels: app: nginx replicas:4 template: metadata: labels: app: nginx spec: containers: - name: nginx image: nginx:1.14.2 ports: - containerPort: 80 In the above code, we see that the total number of pods across the cluster must be 4.Let’s now deploy the file.kubectl apply nginx-deployment-sampleLet’s list the pods, usingkubectl get pods -l app=nginxHere is the output.NAME READY STATUS RESTARTS AGE nginx-deployment-test-83586599-r299i 1/1 Running 0 5s nginx-deployment-test-83586599-f299h 1/1 Running 0 5s nginx-deployment-test-83586599-a534k 1/1 Running 0 5s nginx-deployment-test-83586599-v389d 1/1 Running 0 5s As you see above, we have created 4 pods.Let’s delete one of the pods.kubectl delete nginx-deployment-test-83586599-r299iThe pod is now deleted. We get the following outputpod "deployment nginx-deployment-test-83586599-r299i" deletedNow again, list the pods.kubectl get pods -l app=nginxWe get the following output.NAME READY STATUS RESTARTS AGE nginx-deployment-test-83586599-u992j 1/1 Running 0 5s nginx-deployment-test-83586599-f299h 1/1 Running 0 5s nginx-deployment-test-83586599-a534k 1/1 Running 0 5s nginx-deployment-test-83586599-v389d 1/1 Running 0 5s We have 4 pods again, despite deleting one.Kubernetes has self-healed to create a new node and maintain the count to 4.Demo description of Self-Healing Kubernetes – Example 2Get pod details$ kubectl get pods -o wideGet first nginx pod and delete it – one of the nginx pods should be in ‘Terminating’ status$ NGINX_POD=$(kubectl get pods -l app=nginx --output=jsonpath="{.items[0].metadata.name}") $ kubectl delete pod $NGINX_POD; kubectl get pods -l app=nginx -o wide $ sleep 10 Get pod details – one nginx pod should be freshly started$ kubectl get pods -l app=nginx -o wideGet deployement details and check the events for recent changes$ kubectl describe deployment nginx-deploymentHalt one of the nodes (node2) $ vagrant halt node2 $ sleep 30 Get node details – node2 Status=NotReady$ kubectl get nodesGet pod details – everything looks fine – you need to wait 5 minutes$ kubectl get pods -o widePod will not be evicted until it is 5 minutes old – (see Tolerations in ‘describe pod’ ). It prevents Kubernetes to spin up the new containers when it is not necessary$ NGINX_POD=$(kubectl get pods -l app=nginx --output=jsonpath="{.items[0].metadata.name}") $ kubectl describe pod $NGINX_POD | grep -A1 Tolerations Sleeping for 5 minutes$ sleep 300Get pods details – Status=Unknown/NodeLost and new container was started$ kubectl get pods -o wideGet deployment details – again AVAILABLE=3/3$ kubectl get deployments -o widePower on the node2 node $ vagrant up node2 $ sleep 70 Get node details – node2 should be Ready again$ kubectl get nodesGet pods details – ‘Unknown’ pods were removed$ kubectl get pods -o wideSource: GitHub. Author: Petr RuzickaConclusionKubernetes can self-heal applications and containers, but what about healing itself when the nodes are down? For Kubernetes to continue self-healing, it needs a dedicated set of infrastructure, with access to self-healing nodes all the time. The infrastructure must be driven by automation and powered by predictive analytics to preempt and fix issues beforehand. The bottom line is that at any given point in time, the infrastructure nodes should maintain the required count for uninterrupted services.Reference: kubernetes.io, GitHub

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