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Shift Left Security: Upgrade DevOps Automation Services And Kubernetes For 4 Phases of Container Lifecycle

Even with automation processes in place, DevOps tests can take an inordinate amount of time to execute. Also, Kubernetes has grown into a de facto container orchestration system in the modern digital landscape. This implies that the number and variety of tests will only grow considerably as containerized projects scale, resulting in significant SDLC inefficiencies. With the pace being a priority feature for DevOps automation services and Kubernetes both, the increasingly complex projects cannot do with existing test performance. A ray of hope comes in the form of “shifting the test automation to the left in SDLC”. Shift Left encourages early testing where the testing strategy is essentially preponed in the development process. Moreover, with DevSecOps gaining popularity in mainstream IT business, the concept of “shifting left” is beneficial for Kubernetes and the overall CI/CD security as well. In this blog, we will take a look at Shift Left Testing Automation and understand its performance and security implications for DevOps automation services and Kubernetes. Shift Left Testing Shift left testing is a technique for speeding up software testing and making development easier by bringing the testing process forward in the development cycle. It is done by the DevOps team to ensure application security at the earliest phases of the development lifecycle, as part of a DevSecOps organizational pattern. Shift left testing focuses on integration. We can find out integration concerns earlier by moving integration testing as early as possible. This will aid in resolving integration concerns in the early stages, when architectural changes may be made. This, like other DevOps methods, encourages flexibility and allows the project team to scale their efforts to increase productivity. Embracing the Shift Left Testing approach Bugs can occur in any code. Depending on the error type, bugs might be minor (low risk) or major (high risk). It is always important to find the bugs earlier, as it allows development teams to fix software quickly and avoid lengthy end-of-phase testing. Better Code Quality: In Shift right testing all bugs are fixed at once. In contrast to this shift left uses an approach to detect the bug in the early stage that improves communication between testing and development teams. Cost-effective: Detecting bugs early saves time and money on the project. This can be helpful to launch a product on time. Better Testing Collaboration: Shift-left strategies take advantage of “automation” regularly. It enables them to do continuous testing to save time. Secure Codebase: Shift-left security encourages more security testing throughout the development period, which enhances test coverage. Teams can write code keeping security in mind from the beginning of a project, avoiding haphazard and awkward fixes later on. Shortened market time: Overall, shift-left security has the potential to improve delivery speed. Developers will have less wait time and there will be fewer bottlenecks when releasing new features thanks to improved security workflows and automation. Ensure that their shift-left strategies are contemporary and capable of dealing with today’s application testing performance concerns, organizations can also benefit from their security features. Understanding Shift Left Security for DevOps and K8s Security testing has traditionally been carried out at the end of the development cycle. This was a major from a debugging point of view, requiring teams to untangle multiple factors at once. As a result, this increased the risk of releasing software that lacked necessary security features. Shifting security left aims to build software with security best practices built-in, as well as to detect and resolve any security concerns and vulnerabilities as early as feasible in the development process. Moreover, Kubernetes security is more vulnerable to threat actors as they are constantly looking for exploiting overlooked bugs. Shift left allows the security to be embedded into every aspect of the container life cycle i.e. – “Develop,” “Distribute,” “Deploy,” and “Runtime.” Here’s how Shift left work with these four phases: Develop: Security can be introduced early in the application lifecycle with cloud-native tools. You can detect and respond to compliance issues and misconfigurations early by conducting security testing. Distribute: While using third-party runtime images, open-source software, this phase gets more challenging. Here, artifacts or container images require continuous automated inspection and update to prevent the risk. Deploy: Continuous validation of candidate workload properties, secure workload observability capabilities, and real-time logging of accessible data enables when security is integrated throughout the development and distribution phases. Runtime: Policy enforcement and resource restriction features must be included in cloud-native systems from the start. When workloads are incorporated into higher application lifecycle stages in a cloud-native environment, the runtime resource limits for workloads often limit visibility. Breaking down the cloud-native environment into small layers of interconnected components to address this difficulty is advisable. Conclusion A software flaw can cause a huge economic disruption, a massive data breach, or a cyber-attack. The ‘Shift Left’ concept resulted in a significant change for the overall ‘Testing’ role. Previously, the only focus of Testing was simply on ‘Defect Detection,’ but now the goal is to detect the bugs in the early stages to reduce the complexity at the end. Also, we all know that cyber-attacks will continue, but early and frequent testing can help detect vulnerabilities in software and build stronger resilience. For all the unforeseen disruptions to come, Shift Left is the direction one cannot deter from.

Aziro Marketing

CI/CD security devops devops automation

Site Reliability Engineering (SRE) 101 with DevOps vs SRE

Consider the scenario belowAn Independent Software Provider (ISV) developed a financial application for a global investment firm that serves global conglomerates, leading central banks, asset managers, broking firms, and governmental bodies. The development strategy for the application encompassed a thought through DevOps plan with cutting-edge agile tools. This has ensured zero downtime deployment at maximum productivity. The app now handles financial transactions in real-time at an enormous scale, while safeguarding sensitive customer data and facilitating uninterrupted workflow. One unfortunate day, the application crashed, and this investment firm suffered a severe backlash (monetarily and morally) from its customers.Here is the backstory – application’s workflow exchange had crossed its transactional threshold limit, and lack of responsive remedial action crippled the infrastructure. The intelligent automation brought forth by DevOps was confined mainly to the development and deployment environment. The IT operations, thus, remained susceptible to challenges.Decoupling DevOps and RunOps – The Genesis of Site Reliability Engineering (SRE)A decade or two ago, companies operated with a legacy IT mindset. IT operations consisted mostly of administrative jobs without automation. This was the time when the code writing, application testing, and deploying was done manually. Somewhere around 2008-2010, automation started getting prominence. Now Dev and Ops worked concurrently towards continuous integration and continuous deployment – backed by the agile software movement. The production team was mainly in charge of the runtime environment. However, they lacked skillsets to manage IT operations, which resulted in application instability, as depicted in the scenario above.Thus, DevOps and RunOps were decoupled, paving the way for SRE – a preventive technique to infuse stability in the IT operations.“Site Reliability Engineering is the practice and a cultural shift towards creating a robust IT operation process that would instill stability, high performance, and scalability to the production environment.”Software-First Approach: Brain Stem of SRE“SRE is what happens when you ask a software engineer to design an operations team,” Benjamin Treynor Sloss, Google. This means an SRE function is run by IT operational specialists who code. These specialist engineers implement a software-first approach to automate IT operations and preempt failures. They apply cutting edge software practices to integrated Dev and Ops on a single platform, and execute test codes across the continuous environment. Therefore, they carry advanced software skills, including DNS Configuration, remediating server, network, and infrastructure problems, and fixing application glitches.The software approach codifies every aspect of IT operations to build resiliency within infrastructure and applications. Thus, changes are managed via version control tools and checked for issues leveraging test frameworks, while following the principle of observability.The Principle of Error BudgetSRE engineers verify the code quality of changes in the application by asking the development team to produce evidence via automated test results. SRE managers can fix Service Level Objectives (SLOs) to gauge the performance of changes in the application. They should set a threshold for permissible minimum application downtime, also known as Error Budget. If a downtime during any changes in the application is within the scale of the Error Budget, then SRE teams can approve it. If not, then the changes should be rolled back for improvements to fall within the Error Budget formula.Error Budgets tend to bring balance between SRE and application development by mitigating risks. An Error Budget is unaffected until the system availability will fall within the SLO. The Error Budget can always be adjusted by managing the SLOs or enhancing the IT operability. The ultimate goal remains application reliability and scalability.Calculating Error BudgetA simple formula to calculate Error Budget is (System Availability Percentage) minus (SLO Benchmark Percentage). Please refer to the System Availability Calculator below.Illustration.Suppose the system availability is 95%. And, your SLO threshold is 80%.Error Budget: 95%-80%= 15%AvailabilitySLA/SLO TargetError BudgetError Budget per Month (30 days)Error Budget per Quarter (90 days)95%80%15%108 hours324 hoursError Budget/month: 108 hours. (At 5% downtime, per day downtime hours is 1.2 hours. Therefore for 15% it is 1.2*3 = 3.6. So for 30 days it will be 30*3.6 = 108 hours)Error Budget/quarter: 108*3 = 324 hours.Quick Trivia – Breaking monolithic applications lets us derive SLOs at a granular level.Cultural Shift: A Right Step towards Reliability and ScalabilityPopular SRE engagement models such as Kitchen Sink, a.k.a. “Everything SRE” – a dedicated SRE team, Infrastructure – a backend managed services or Embedded – tagging SRE engineer with developer/s, require additional hiring. These models tend to build dedicated teams that lead to a ‘Silo’ SRE environment. The problem with the Silo environment is that it promotes a hands-off approach, which results in a lack of standardization and co-ordination between teams. So, a sensible approach is shelving off a project-oriented mindset and allowing SRE to grow organically within the whole organization. It starts by apprising the teams of customer principles and instilling a data-driven method for ensuring application reliability and scalability.Organizations must identify a change agent who would create and promote a culture of maximum system availability. He / She can champion this change by practicing the principle of observability, where monitoring is a subset. Observability essentially requires engineering teams to be vigilant of common and complex problems hindering the attendance of reliability and scalability in the application. See the principles of observability below.The principle of observability follows a cyclical approach, which ensures maximum application uptime.Step Zero – Unlocking Potential of Pyramid of ObservabilityStep zero is making employees aware of end-to-end product detail – technical and functional. Until an operational specialist knows what to observe, the subsequent steps in the pyramid of observability remain futile.Also, remember that this culture shift isn’t achievable overnight – it will be successful when practiced sincerely over a few months.DevOps vs. SREPeople often confuse SRE with DevOps. DevOps and SRE are complementary practices to drive quality in the software development process and maintain application stability.Let’s analyze four key the fundamental difference between DevOps and SRE.ParameterDevOpsSREMonitoring vs. RemediationDevOps typically deals with the pre-failure situation. It ensures conditions that do not lead to system downtime.SRE deals with the post-failure situation. It needs to have a postmortem for root cause analysis. The main aim is to ensure maximum uptime and weed out failures for long term reliability.Role in Software Development Life Cycle (SDCL)DevOps is primarily concerned with the efficient development and effective delivery of software products. It must ensure Zero Down Time Deployment (ZDD). It also requires to identify blind spots within infrastructure and application.SRE is managing IT operations efficiently once the application is deployed. It must ensure maximum application uptime and stability within the production environment.Speed and Cost of Incremental ChangeDevOps is all about rolling out new updates/features, faster release cycle, quicker deployment and continuous integration, and continuous development. The cost of achieving all this isn’t of significance.SRE is all about instilling resilience and robustness in the new updates/features. However, it expects small changes at frequent intervals. This gives a larger room to measure those changes and adopt corrective measures in case of a possible failure. The bottom line is efficient testing and remediation to bring down the cost of failure.Key MeasurementsDevOps’ measurement plan revolves around CI/CD. It tends to measure process improvements and workflow productivity to maintain a quality feedback loop.SRE regulates IT operations with some specific parameters like Service Level Indicators (SLIs) and Service Level Objectives (SLOs).Conclusion – SRE Teams as Value CenterA software product is expected to deliver uninterrupted services. The ideal and optimal condition is maximum uptime with 24/7 service availability. This requires unmatched reliability and ultra-scalability.Therefore, the right mindset will be to treat SRE teams as a value center, which carries a combination of customer-facing skills and sharp technical acumen. Lastly, for SRE to be successful, it is necessary to create SLI driven SLOs, augment capabilities around cloud infrastructure, a smooth inter-team co-ordination, and thrust Automation and AI within IT operations.

Aziro Marketing

devops Site Reliability Engineering SRE

Test Automation 2022: DevOps Automation Strategies Need Better Focus On Environment and Configuration Management

With the advent of DevOps, even the once cumbersome task of deployment is now quite automatic with something as easily manageable as a Jenkins file. It’s is the fact of our times that the DevOps pipelines have made the entire development process faster, easier, and better. Gone are the days when developers are stumped by issues in different OS, browsers, or locales. However, the testers still sometimes struggle to find issues reported by a particular user in a particular locale or OS. There are certain environmental and configurational anomalies that still feel excluded from the comfort of Automation that DevOps was intended for in the first place. The question arises, how we bring Environment and Configuration Management under the garb of automation in a way that they don’t disrupt the existing DevOps pipeline, but enhance it.The Ecosystem for Automation and SoftwareSoftware is ubiquitous. Users are now, more than ever, aware of their dependency on the digital landscape thriving on sophisticated applications highly scalable digital services. With the growth of SaaS (Software-as-a-Service) and IaaS (Infrastructure-as-a-Service), many users now use low-code development platforms to create software that meets their absolute needs with details. These all are firm and positive steps towards optimal and efficient Automation. A major challenge that now the DevOps teams are facing is to monitor at surface level as well as deeper levels in their different corresponding environments. The only way to not be stumped by these kinds of anomalies is to fix them before they catch us off-guard.Automating the process of testing in different environments is now becoming an essential part of the development process. Unit testing, integration testing, load testing, alpha/beta testing, user acceptance testing are different testing processes, each aimed at different goals. The complexity of those systems could be minimal. But while simulating for pre-production or production environments, the complexities would be higher. Tracking of servers, resources, credentials become easy with proper configuration management, which comprises of the below steps:Identify the system-wide configuration needs for each environment.Control the changes in the configuration. For example, the database to connect may be upgraded down the lane. Hence, all the details concerning connecting with the database should be changed. This should be tracked continuously.Audit the configuration of the systems to ensure that they are compliant with the regulations and validations.Let us now see how one can practically implement such complex automation for their Environments and Configuration?Codifying Environment and Configuration ManagementAll the configuration parameters can be compiled into a file, like a properties file, for example, that can automatically build and configure an environment. Thus, proper configuration management in DevOps can give birth to:Infrastructure-as-a-code (IaaC): An infrastructure can be anything, from load balancers to databases. IaaC allows developers to build, edit and distribute the environment (as containers in an extension), ensuring the proper working state of the infrastructure, is ready for development and testing. Below is a sample code to configure an AWS EC2 instance:2. Configuration-as-a-code (CaaC): Configure the infrastructure and its environment can now be put into a file and managed in a repository. For example, the Configuration as Code plugin in Jenkins allows configuring the required configurations of any infrastructure in a YAML file.At the basic level, the different servers for the different environments for testing and development can hold different properties files that can be appropriately picked up by the Jenkins pipeline and deployed accordingly.Talking about these automating techniques begs the next question: “Are these automated?” Of course, yes. The market provides many tools that can automate environment and configuration management like:Ansible automates infrastructure configuration, deployment, and cloud provisioning with the IaaC model, using playbooks. A playbook is a YAML file with the steps of the configuration and deployment which is executed with the Ansible execution engine.Puppet can be used to configure, deploy, and run servers and automate the deployment of the applications, along with remediating operation and security risks.CFEngine helps in provisioning and managing software deployment, mainly heavy computer systems, embedded systems.ConclusionThe digital environment and the complex configurations are both equally essential for a healthy and productive DevOps pipeline. Especially when it comes to testing, both these aspects hold the potential to drastically choke up or relieve the bandwidths for the testing teams. Having a way to automate the Environment and Configuration Management is not just time saving but a highly encouraging step towards the modernization of DevOps automation that the digital world needs today.

Aziro Marketing

Configuration Management devops devops automation

3 Major Requirements For Synergizing DevOps Automation Services and Low-Code

Flexible load-balancing, multi-layer security, impeccable data operations, or multi-point monitoring – DevOps automation has made all this possible. The software deliveries have accelerated, and legacy systems have grown to be more automation-friendly thanks to CI/CD. What organizations are now becoming increasingly interested in is the benefits of Low-code solutions. Been amongst the buzzwords for quite some time now, Low-code is now finding its way into mainstream software development and digital business processes. One might thank the recent disruption caused in the last two years for this, or maybe just the way things are accelerated in the digital world. Either way, Low-code, and DevOps seems like a partnership everyone can benefit from. While DevOps automation services have already found their ground in the digital transformation landscape, the appeal for low-code majorly lies in its scope for complex innovations with faster results. Such space is essential for the contemporary customer needs and modernization of complex business processes. No wonder Gartner too predicted in their recent report for the low-code to almost triple in its utilities. Therefore, it is essential to understand how ready our DevOps machinery is for Low-code, especially in terms of three major concerns in today’s digital ecosystem: Scalability Data Management and Security We will go through these concerns one by one and discuss the current status in DevOps pipelines and the need for Low-code implementation. 1. Scalable Infrastructure for High-Performing Low-Code Although low-code platforms are there to encourage scalable workload scalability, the complexity in the variable workloads for different industrial and business-specific needs might attract unnecessary manual intervention throughout the application development and delivery pipelines. Integrating the low-code platforms with the specialized DevOps pipelines would require architectural support to streamline the operations and accelerate the deployments. Such cutting-edge infrastructure is not completely absent in modern-day DevOps, but one needs the right expertise to explore and exploit it. The key ingredient that would bring the right flavor for low-code solutions would be the configuration management automation that DevOps services now offer. Tools like Chef, Openstack, Google Compute Engine, etc. can provide the architectural and configurational support that the DevOps teams would require to work with Low-code platforms. Once the required configuration management for provisioning, discovery, and governance are in place, DevOps pipelines and Low-code solutions can easily achieve the scalability standards required for the globally spread services and complex customer demands. 2. Smart Storage for Easy Low-Code Data Management Productive Low-code automation would require efficient data management for customized workloads and role-based operations. This requires a robust storage infrastructure with required accessibility and analytics features that would work well with the low-code platforms. DevOps pipelines have already evolved to work with technologies like Software-Defined Storage, cloud storage, and container storage for such data management requirements. Moreover, tools like Dockers, Kubernetes, and AWS resources are also now offerings support for better storage integration and management whether remote or on-premise as per the business needs. With the required scalability and data management capabilities already in place, the only major concern that can make or break the deal for Low-code is Security. 3. Secure Operations for the Low-Code Tools SaaS and PaaS solutions are already joining hands with low-code tools and technologies. DevOps teams are keenly working with pre-built templates that can be easily customized for scalability and data management needs. However, the security aspect of the Low-Code and DevOps engagement is still fuelling the skepticism around it. Integrating external tools and APIs with the existing DevOps pipelines may go either way as far as security is concerned. Vulnerabilities in monitoring, network management, and data transactions can be cruelly exploited by cyberattackers as we saw in many security incidents across the globe last year. So, what remedies are available in existing DevOps that can encourage more business leaders to adapt and explore the benefits of Low-code with DevOps automation services. The answer lies in a rather popular DevOps specialization known as DevSecOps. DevSecOps has the in-built CI/CD security and features like shift-left and continuous testing that offer the required attack protection and threat intelligence. There are tools for interactive security testing, cloud security assessment, secret management, and secure infrastructure as code. Expertise in tools like Veracode, Dockscan, and HashiCorp Vault can offer the security assurance one would need to introduce low-code capabilities in their DevOps ecosystem. Moreover, the latest OAuth/2 models, TLS1.2 protocols, and HMAC standards are also there to provide an external security layer. Conclusion Products and offerings across the global industries have now aligned themselves for the vast benefits of digital innovation. Low-code is a fairly new player in this game where DevOps already happens to be a fan favorite. With customer demands getting more nuanced, focusing on low-code will offer the required time and space for futuristic innovations. With the above-mentioned concerns properly addressed, Low-code solutions can easily work in synergy with DevOps and provide the business leaders the modern-day digital transformation that their business needs.

Aziro Marketing

devops devops automation Low-Code

What Are DevOps Services and How Do They Impact the Engineering Team?

Nowadays, development teams are under pressure to deliver high-quality software products without compromising performance, security, and reliability. Thus, several organizations have increasingly adopted DevOps to meet this demand. According to Puppet’s 2023 State of DevOps Report, 69% of organizations practicing DevOps reported improved software delivery performance, while high-performing teams deploy code 208 times more frequently than their lower-performing counterparts. These numbers highlight the significance of adopting DevOps practices, especially for engineering teams to build scalable and reliable software. Therefore, in this blog, we will dive into DevOps services and their impact on the engineering teams. An Introduction to DevOps Service DevOps Service refers to tools, practices, and culture philosophies that automate the collaboration between software development and operations teams. It aims to deliver faster software releases, enhance code quality, and improve collaboration. In addition, several DevOps companies can also attain both speed and reliability in the software development life cycle (SDLC) process by collaborating with software development and IT operations teams. Also, there are several ways to implement DevOps service, including Continuous Integration/Continuous Deployment (CI/CD), infrastructure as code (IaC), version control systems, cloud resource management, cloud infrastructure management, and configuration management. By eliminating workflow bottlenecks and enhancing continuous and real-time collaboration, DevOps services enable engineering teams to release more reliable and high-quality code at a higher velocity. Advantages of Adopting DevOps Services for the Engineering Team Implementing DevOps service transforms how engineering teams develop, deploy, and maintain software products. Also, it reduces the gap between development and operation teams to deploy faster software releases, improve reliability, and enhance collaboration. Enhanced Productivity and Collaboration DevOps supports collaboration between software development, IT operations, and QA teams. Although traditional software development methodologies separate these teams, they work independently, which causes software product delays and confusion. DevOps practices eliminate all these barriers by providing various tools, objectives, and processes. Engineering teams can easily coordinate workflows with monitoring tools, CI/CD pipelines, and integrated communication platforms. Tasks like software deployments, code reviews, and performance testing are aligned through an associated process. Consequently, it results in streamlined decision-making, reduced development cycles, and maximized overall productivity. Accelerated Software Deployment DevOps services enable engineering teams to enhance software release speed with continuous integration and continuous delivery (CI/CD) pipelines. Automated build, test, and software deployment processes minimize the time between code commits and software releases. It ensures that engineering teams can respond to market demands and customer feedback faster than before. Also, faster software deployments can lead to higher business agility and competitive advantage. According to the 2023 State of DevOps Report, elite-performing DevOps teams deploy code 973 times more frequently than low performers, with 6570 times faster lead times from commit to deployment. This allows organizations to easily acknowledge security concerns and customer needs faster than companies relying on traditional software development methodologies. Enhanced Code Quality Improved code quality builds reliable, scalable, and secure software products. DevOps practices incorporate continuous integration tools, automated testing, and code analysis to ensure that every code change meets quality standards before it reaches software deployment. By integrating QA testing directly into CI/CD pipelines, engineering teams can analyze and resolve early development bugs, performance bottlenecks, and security risks. Some interconnected methods, such as peer code reviews, collaborative development practices, and static code analysis, enhance code consistency. This leads to more effective codebases, reduced debugging sessions, and more predictable software behavior in development. Advanced Data Privacy DevOps services enhance data privacy by integrating security protocols and security compliance directly into the software development and deployment pipeline. This methodology is referred to as DevSecOps. Several security-oriented automation tools manage code security reviews, vulnerability scans, and code security reviews at every stage of the deployment process. DevOps practices such as Infrastructure as Code (IaC) tools also help implement secure configurations, and encryption protocols ensure that data is protected in transit and at rest. DevOps supports secret managers and key vaults to store sensitive information, such as tokens, passwords, and keys. By embedding security into DevOps, engineering teams can easily analyze potential vulnerabilities, minimizing the risk of data breaches. Furthermore, it helps gain organizational trust and reduces reputational and financial risks. Enhanced Scalability and Seamless Flexibility DevOps services offer the engineering teams flexibility and scalability, which is required to adapt software applications and infrastructure. Using DevOps practices like Infrastructure as Code (IaC), cloud-native deployments, and containerization, engineering teams can easily provision and scale resources on demand without a hands-on approach. Some prominent container and orchestration platforms, such as Kubernetes, can simplify distributed systems management by automating scaling, deployment, and recovery. In addition, operational flexibility ensures that systems remain highly available, even during major product rollouts and heavy load conditions. Engineering teams can test some new features in isolated environments and later respond to system incidents with high availability. To Wrap Up In conclusion, DevOps services have been a game-changer for all the engineering teams striving to deliver high-quality software products. With the culture of collaboration, continuous improvement, and automation, DevOps helps shorten development cycles and improve the quality of the code. Improved productivity, faster software deployment, robust security practices, and scalability. It enhances operational efficiency and strengthens the team’s ability to adapt quickly to market demands, with benefits like increased productivity, faster deployment, scalability, and security practices. As several businesses continue to adopt DevOps, the engineering teams can always take advantage of it. Consequently, it will ensure software products’ reliable, secure, and scalable delivery. Frequently Asked Questions (FAQs) Q. What are the seven different phases of DevOps? Ans: DevOps has seven phases, including continuous development, integration, testing, monitoring, feedback, deployment, and operations.

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