Category: DevOps Practice

  • How Automation Enables Remote Work

    How Automation Enables Remote Work

    In recent years, the world has witnessed a significant shift towards remote working, largely driven by global events such as the COVID-19 pandemic. This transformation has necessitated the adoption of new tools and strategies, with automation emerging as a key enabler of effective remote work.

    So, what does automation mean in this context? Well, it’s the use of technology to carry out tasks with minimal human intervention. It’s a powerful tool that can streamline processes, boost efficiency and cut down on errors, making it an invaluable resource for companies navigating the complexities of remote work.

    The Rise of Remote Work

    According to McKinsey, a whopping 58% of Americans now have the opportunity to work from home (WFH) at least one day per week. And 35% have the opportunity to WFH for the totality of their work responsibilities.

    This shift has brought numerous benefits to both employers and employees. For employees, it means more flexibility, less commuting and a better work-life balance. For employers, it broadens the talent pool, cuts overhead costs and can even boost productivity. However, remote working also presents unique challenges, such as:

    ● Communication Barriers: In a remote work setup, maintaining clear and effective communication can be a challenge. Without face-to-face interactions, messages can be misunderstood or overlooked. This can lead to confusion, mistakes and a lack of cohesion within the team.

    ● Difficulty in Tracking Productivity: When employees are working from different locations, it can be difficult for managers to monitor their productivity. Traditional methods of tracking work, such as observing employees’ work hours, are not effective in a remote work setup.

    ● Maintaining Team Cohesion: Building and maintaining a strong team culture can be more challenging when employees are working remotely. Without regular in-person interactions, employees may feel isolated and disconnected from the team.

    ● Cybersecurity Concerns: Remote work often involves using personal devices and home networks, which may not have the same level of security as office networks. This can expose companies to increased cybersecurity risks.

    The Role of Automation in Remote Working

    Now, let’s delve into the ways automation plays a pivotal role in remote work.

    Automation and Communication
    In a remote work setup, effective communication is paramount. Automation tools such as Slack and Microsoft Teams facilitate better communication by automating tasks like scheduling meetings, sending reminders and translating messages.

    These tools can also automate the process of organizing and archiving conversations, making it easier to retrieve information when needed. Additionally, they can automate the process of updating team members about project changes or important announcements. These features ensure that all team members are on the same page, enhancing collaboration, reducing the chances of miscommunication and ultimately leading to a more cohesive and efficient team.

    Automation and Human Resources
    Automation in human resources (HR) is a game-changer in remote work settings. HR automation software can streamline recruitment, automating resume sorting, interview scheduling and follow-up emails. It can also enhance onboarding, automating welcome emails and account setups.

    Performance management can be improved with automated feedback collection and goal tracking. Furthermore, e-learning platforms can automate training assignments, progress tracking and certification issuance. This ensures a consistent, efficient and effective HR process regardless of location, enhancing the remote work experience.

    Automation and Project Management
    Project management can be a challenge in remote teams due to the lack of face-to-face interaction. Automation tools like Asana and Trello simplify this process by automating task assignments, tracking progress and generating reports.

    These tools can also automate the process of setting deadlines, sending reminders for upcoming tasks and notifying team members about changes in project plans. This allows managers to keep track of projects in real time, ensures that deadlines are met and helps in identifying potential issues early on, making project management more efficient and effective.

    Automation and Employee Monitoring
    Monitoring employee productivity and performance is crucial in a remote work setup. Automation tools like Time Doctor and Toggl track time spent on tasks, providing valuable insights into productivity.

    These tools can automate the process of generating productivity reports, tracking breaks and even monitoring website and app usage. This data can be used to identify bottlenecks, improve processes and ultimately increase productivity. It also allows managers to provide constructive feedback and tailor their management strategies to individual employees’ work habits.

    Automation and Cybersecurity
    Cybersecurity is a critical concern in remote work setups, which often involve multiple devices and networks. Automation plays a key role in maintaining security by detecting threats, installing updates and performing backups. Cybersecurity tools can automate the process of scanning for viruses, blocking malicious websites and encrypting data.

    They can also automate the process of updating security protocols and alerting users about potential security threats. This ensures that data remains secure, protecting companies from potential security breaches and giving employees peace of mind to focus on their work.

    Final Thoughts

    Automation plays a crucial role in enabling effective remote work. By increasing efficiency, reducing errors and saving costs, automation not only makes remote work possible but also profitable. As the future of work continues to evolve, we should expect to see more and more of the remote working processes being handled by automation tools.

  • Five Great DevOps Job Opportunities

    Five Great DevOps Job Opportunities

    DevOps.com is now providing a weekly DevOps jobs report through which opportunities for DevOps professionals will be highlighted to better serve our audience.

    Our goal in these challenging economic times is to make it easier for DevOps professionals to advance their careers.

    Of course, the pool of available DevOps talent is still relatively constrained, so when one DevOps professional takes on a new role it tends to create an opportunity for others.

    The five job postings shared this week are selected based on the company looking to hire, the vertical industry segment and, naturally, the pay scale being offered.

    We’re also committed to providing additional insights into the state of the DevOps job market. In the meantime, for your consideration:

    Indeed.com

    PEAR Health Labs
    Remote
    DevOps Manager
    $150,000 to $175,000

    Dice.com

    SR Partners
    Dallas, Texas
    DevOps Architect
    $140,000 to $160,000

    SimplyHired

    Reynolds & Reynolds
    Tallahassee, Florida
    Senior Software Architect
    $106,000 to $135,000

    LinkedIn

    Genesys
    Oakdale, Connecticut
    Senior Software Engineer: DevOps
    $93,600 to $194,400

    CareerBuilder.com

    Patterned Learning AI
    Remote
    DevOps Engineer
    $60,000 to $70,000

  • Integral Makes Generative AI Code Review Tool Open Source

    Integral Makes Generative AI Code Review Tool Open Source

    Integral this week launched an open source Robin AI project that leverages OpenAI’s generative pre-trained transformer (GPT) platform to review code changes and provide constructive feedback.

    Integral is a data analytics platform used by health care providers. The company originally developed Robin AI using a set of Bash scripts to create a generative artificial intelligence (AI) tool to assist its internal development team.

    Integral CTO John Kuhn said Robin AI is essentially a bot that functions like a coach for developers. It first reviews code and then surfaces optimization suggestions that developers can instantly apply, said Kuhn. It’s up to each developer to decide whether to accept those suggestions, but Integral is already using it to, for example, make sure all the code being written is human readable, he added.

    Robin AI currently works best on JavaScript code repositories, but can be applied to any codebase residing in a Git repository. Integral has also already developed a GitHub Actions script.

    In addition, as an open source project, Robin AI can be integrated with any number of generative AI platforms that might be built using more domain-specific large language models (LLMs), noted Kuhn.

    Most developers are already using AI tools such as GitHub Copilot to write better code. Robin AI is now extending generative AI capabilities to the code review process as part of an effort to improve the quality of the code being written. In effect, it provides a means to surface common mistakes developers make and enables them to fix those before they are discovered by a colleague.

    It’s not clear how much application development will be driven by AI, but Kuhn said he believes it’s only a matter time before the entire software engineering process is automated. As those advances are made, the cost of building applications will effectively drop to zero, he added.

    Of course, not everyone in the application development community agrees with that assessment. But one thing that is clear is that generative AI capabilities will soon be pervasive. In fact, the next frontier will arguably involve integrating generative AI platforms with frameworks that make it possible to automatically apply suggestions and recommendations made by generative AI platforms across an entire enterprise IT environment.

    In the meantime, DevOps teams should be evaluating generative AI technologies in terms of the capabilities they can provide today and their future potential. Many of the manual tasks that conspire to make application development and deployment tedious will become increasingly automated. DevOps teams committed to ruthlessly automating as many processes as possible will naturally be at the forefront of adoption. The challenge and the opportunity lies in determining whether AI platforms can be trusted or if a human must always be in the loop to ensure there are no unexpected outcomes.

    After all, while AI can be applied to automate deployments, it’s not quite as clear whether they can be rolled back if a mistake is made.

  • How to Empower DevSecOps in a Complex Multi-Cloud Landscape

    How to Empower DevSecOps in a Complex Multi-Cloud Landscape

    Organizations are embracing cloud-based application delivery for speed of delivery and scale. However, the proliferation of multi-cloud systems to access and maximize the cloud’s capabilities is driving complexity in IT environments. Many organizations do not consider how multi-cloud adoption is expanding their attack surface—and the risk is growing: The 2023 CrowdStrike Global Threat Report found cloud exploitation cases grew by 95% year-over-year and cases involving threat actors targeting cloud environments were up 288% from a year prior.

    The expansion of cloud infrastructure and services has increased the pressure on organizations to protect assets within their multi-cloud environments. To alleviate this burden, more businesses are turning to DevSecOps, a practice that incorporates security at an earlier point in the development life cycle. This practice of shifting left helps improve the quality and reduces risk of applications, as well as makes the delivery of these applications more efficient since any potential issues are found earlier in the development process.

    DevSecOps is being adopted rapidly by organizations today to address the expanding array of threats and increasingly sophisticated attacks targeting multi-cloud environments. However, securing the cloud can be tricky due to its dynamic nature and multi-cloud makes shift left security even more complex. For DevSecOps to truly be effective, here are three things that organizations should consider doing.

    1. Strive for Complete Visibility in a Multi-Cloud Environment

    It is important that DevSecOps teams have a comprehensive understanding of their multi-cloud environment. Without it, they will not be able to identify a variety of security risks including vulnerabilities, privileged credentials, misconfigurations and other threats that may leave their organization’s cloud assets vulnerable.

    The best way to get full visibility across multi-cloud environments is through a cloud security posture management (CSPM) tool. With a CSPM tool, DevSecOps teams can identify misconfigurations and proactively detect threats. In addition, DevSecOps teams should also use a cloud infrastructure entitlement management tool (CIEM) to manage identities across all of their cloud infrastructure resources. The primary goal of a CIEM tool is to mitigate the risk that comes from the unintentional and unchecked granting of excessive permissions of user credentials.

    2. Visibility and Compliance Do Not Guarantee Security

    Organizations need to develop a comprehensive security strategy to mitigate issues within the development process. This may include implementing tools, automation and standards to enable developers to follow the desired security behavior. These approaches reduce developer friction, as well as diminish the likelihood that unsafe or default configurations will be used. Historically, DevOps teams have pushed back on integrating security since their concern is that it slows down the development lifecycle. However, DevSecOps is gaining traction in recent years because organizations are realizing integrating security sooner in the development lifecycle is more efficient than reactively patching problems as they arise.

    A tool that DevSecOps teams should look to leverage is cloud workload protection (CWP) because it offers breach protection for workloads, containers and Kubernetes, while enabling them to continue to build, run and secure applications with speed and confidence.

    3. Create Consistency With Security Tools

    Ideally, organizations should opt for a single platform that consolidates capabilities such as CSPM, CWP and CIEM. The reason for consolidation is to eliminate security gaps from having multiple security solutions. As a result, DevSecOps teams should turn to cloud-native application protection platform (CNAPP) tools to create more consistency within the multi-cloud environment.

    Securing multi-cloud environments can be complex. By empowering DevSecOps teams using these best practices, organizations will be able to move faster than today’s adversaries and have the agility to quickly adapt to present and future cybersecurity challenges in their multi-cloud environments.

  • How to Avoid Risk When Using Multiple Low-Code Platforms

    How to Avoid Risk When Using Multiple Low-Code Platforms

    Organizations are still increasing their use of low-code/no-code (LCNC). But this adoption isn’t always consolidated around one tool—frequently, multiple low-code/no-code platforms are used under the same roof. In fact, Gartner predicts that by 2024, 75% of large enterprises will be using at least four low-code development tools for both IT application development and citizen development initiatives.

    Utilizing multiple low-code/no-code platforms simultaneously introduces some security concerns. This is partially due to a lack of standard policies to govern different platforms in the same way. Low-code platforms are often incompatible with traditional IT security processes, like vulnerability scanning, manual code reviews and runtime security monitoring. Organizations going all-in on citizen development need safe ways to use low-code/no-code platforms. So, how can they safely enable this innovation without hindering productivity?

    I recently met with Michael Bargury, CTO and co-founder, Zenity, about securing LCNC systems. Bargury, who oversees the OWASP Low-Code Top Ten list, has significant insight into both the benefits and drawbacks of low-code/no-code platforms. Below, we’ll review the potential risks of using multiple low-code platforms and consider ways to mitigate these concerns.

    Why Companies Have Multiple Low-Code Platforms

    Interest in low-code has been rising, and low-code/no-code adoption continues to accelerate across enterprises. According to Bargury, large enterprises often don’t get a choice in the matter—low-code tools are arising organically, and it’s challenging to keep a lid on their proliferation.

    One way this occurs is that low-code becomes embedded into the SaaS platforms everyone already uses. Software platforms integral to business operations, like Salesforce, Microsoft Office and ServiceNow, have arguably mutated into low-code platforms, making them more like cloud providers than SaaS vendors, said Bargury.

    The other way low-code platforms emerge is through bottom-up transitions, says Bargury. This could be a specific knowledge worker working in a subset of the business to automate a domain-specific operation or integrate various tools. Then, there are the platforms, like OutSystems, Mendix or Mulesoft that specifically target professional developers.

    Organizations going all-in on citizen development may build a center of excellence and focus efforts on a single platform. And low-code platforms targeting developers will sometimes encourage more consolidation. Yet, “different platforms solve different use cases better,” explained Bargury. As a result, you will usually have a few converging in the same enterprises.

    Potential Security Concerns of Multiple Low-Code Platforms

    The emergence of low-code is similar to the bring your own device (BYOD) movement. IT and security leaders fought to avoid it at one point, but nowadays, everyone does it. So, what are the security implications if low-code becomes similarly ubiquitous? Well, no matter how it’s generated, low-code-bred programs are still applications susceptible to the same logical problems. And unfortunately, compared to your typical traditional code development life cycle, low-code development is fraught with discrepancies, says Bargury.

    Immature CI/CD Pipelines

    Some platforms do not offer the kind of mature CI/CD process one would expect from a software development platform. For example, there may be no way to create tests or separate your environments. Since there’s no coherent and consistent way to push code from development into production, you lack a way to apply secure development across platforms. “You don’t have a way to ensure every piece of software is up to your standards,” said Bargury.

    Opaque Underyling Codebases

    In traditional software development, you apply your own security reviews to ensure applications don’t contain risks. This includes shift-left scanning, security gates, manual reviews to catch mistakes early on and runtime scanning to catch unknown vulnerabilities in production. But there aren’t always parallels in low-code development. Low-code solutions typically have their own way of doing things with fewer standards, and they avoid exposing the underlying code and Git, said Bargury.

    Lack of Visibility

    As such, with low-code obfuscation, you lose a degree of visibility into how an application runs. Logs may be insufficient or wholly inaccessible. It’s also tricky—or at times impossible—to set up runtime monitoring, let alone scan various platforms. This means that low-code users can’t leverage powerful observability tools to identify errors and remediate security holes.

    Lack of Unified Policies

    Finally, establishing common authorization and permissions across multiple low-code development platforms is another hurdle. Since low-code vendors have their proprietary building blocks, you’re unable to leverage something like OPA or Kyverno to create and unify policies. Lacking shared policies across tools makes it challenging to verify that best practices have been implemented, says Bargury.

    How to Secure Multi-LCNC

    Low-code can grant much creative potential. But, knowing the above risks, what should IT be doing to reduce risks around low-code—especially when using multiple platforms? Well, Bargury shared several steps to help cybersecurity leaders start safely addressing the emergence of increasingly low-code capabilities.

    1. Take low-code development under the application security umbrella. First, low-code must be brought under the security umbrella, if it isn’t already. “It should be part of their mandate,” said Bargury. Shift the responsibility to professionals well-trained in resolving threats.
    2. Understand your surface area. As a basic security tenant, you can’t secure what you don’t know. Thus, Bargury recommends increasing your visibility into each low-code platform by collecting logs when possible and centralizing your analysis.
    3. Create automated guardrails. Next, it’s critical to identify your risks and set guardrails for your low-code users—especially when citizen development is involved. The OWASP framework provides a good overview of common risks and mitigation advice across robotic process automation (RPA), integration and low-code. In general, it’s important to design permissions with the rule of least privilege in mind. This can help reduce the chance of vulnerabilities like LCNC-SEC-03: Data Leakage and Unexpected Consequences and LCNC-SEC-01: Account Impersonation.
    4. Address gaps within the development life cycle (SDLC). Lastly, low-code platforms often provide the building blocks to secure applications, but it’s still up to you to ensure they are safely used. Cybersecurity teams should continually audit the low-code SDLC to ensure holes don’t persist.

    You’re Responsible for Securing Low-Code Development

    Low-code development platforms aren’t 100% safe from harm. It’s not out of the question for hackers to abuse low-code platforms and turn them against their owners. For example, Microsoft’s Detection and Response Team (DART) reported how a hacker group used entry to a low-code tool to remain hidden within an organization for six months, using credential stuffing to access an administrative account. By creating automations, they were able to use internal discovery tools and exfiltrate secrets and data that could have been used for privilege escalation.

    As you can see, there are legitimate concerns for low-code, especially at scale. However, security responsibility is not always that transparent. To date, there isn’t an equivalent of a shared cloud responsibility model in the realm of low-code development. As such, at the end of the day, you need to take the reins to own the applications that you build and ensure everything is secure.

  • Google Calls Microsoft Azure Anti-Competitive ¦ Gen-Z Can’t Email

    Google Calls Microsoft Azure Anti-Competitive ¦ Gen-Z Can’t Email

    Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

    This week: Google complains to the FTC about Microsoft market abuses, and new graduates don’t know how to office. (more…)

  • Noname Security Looks to Shift API Security Testing Left

    Noname Security Looks to Shift API Security Testing Left

    Noname Security today made generally available an update to a tool for testing application programming interface (API) security that promises to make it easier for DevOps teams to ensure APIs are secure.

    Filip Verloy, a field CTO for Noname Security, said Active Testing V2 is purposely designed to make it simpler to integrate API testing within a larger DevSecOps workflow.

    Version 2 of Active Testing, for example, provides additional integrations with continuous integration/continuous deployment (CI/CD) platforms along with automated API discovery tools.

    Other capabilities included in the latest release are tools to automate API response inspection, troubleshooting, classification and vulnerability discovery.

    Finally, Noname Security has also added support for GraphQL-based APIs alongside REST APIs.

    In total, there are now more than 160 API security tests that can be employed on an API testing tool that Noname Security developed to enable it to build Active Testing, said Verloy. In effect, Active Testing is an extension of that core API testing tool, he noted.

    The biggest issue DevSecOps teams encounter when testing API security is that most legacy tools are not designed to provide any visibility into the business logic used to construct APIs. As such, there is a need for API security tools that can be easily integrated within DevSecOps workflows to discover issues before APIs are exposed in a production environment, he noted.

    While a lot of progress has been made toward securing software supply chains, APIs have generally not received enough attention. Developers typically create APIs, but they don’t typically assume responsibility for managing and securing them. As the number of APIs within organizations continues to proliferate, there is a growing need to centralize API management and security.

    Historically, developers have assumed that cybersecurity teams were making sure APIs are secure. Cybersecurity teams, conversely, assumed that the developers that created APIs would be responsible for securing them. DevSecOps best practices make it possible to now extend responsibility for security further left toward developers in a way that enables cybersecurity teams to define the policies and controls that should be used, noted Verloy.

    It may a while before every organization masters the all the nuances of DevSecOps, but as pending legislation that requires organizations to better secure software supply chains becomes law it’s only a matter of time before organizations revisit API security—if they have not done so already.

    In the meantime, cybercriminals have already discovered that insecure APIs provide a convenient mechanism for exfiltrating data that they can then sell or hold for ransom. The number of rogue and zombie APIs that are unknown or that have been forgotten has become a major cybersecurity issue. Ideally, DevSecOps teams would not only test the security of APIs before they are deployed but would also address a significant amount of technical API security debt that has already accumulated.

    One way or another, API security is going to become a significant issue in the weeks and months ahead. The issue now is how to address it before it gets any worse.

  • System Initiative Employs Modeling to Reinvent DevOps

    System Initiative Employs Modeling to Reinvent DevOps

    System Initiative (SI) today made available in private beta a platform that creates simulations of IT environments. The platform leverages a built-in framework to generate the code needed to update an application environment.

    Fresh from raising $18 million in funding, SI CEO Adam Jacob said the ultimate goal is to provide a level of abstraction for DevOps environment that eliminates much of the complexity that creates bottlenecks in DevOps workflows.

    For all intents and purposes, DevOps is fundamentally broken; there are too many manual processes that need to be performed, he added. The SI platform represents an ambitious effort to reimagine how DevOps processes are constructed and maintained, said Jacob.

    At the core of that effort are models of IT environments created by the SI platform that are accessed via visual interface. The automation framework built into the platform then uses the relationships between models to infer configuration dynamically and then automatically generate TypeScript code that a DevOps team can apply to automate a task.

    Feedback loops are also provided in real time to provide insight into the viability of a configuration and eliminate the need for no state files to track and no ‘plan’ versus ‘apply’ stages.

    As more organizations realize how dependent they are on software to drive digital processes, many of them are looking to improve the productivity of developers and the DevOps teams that support them. After a wave of initial progress, many DevOps teams find themselves supporting DevOps workflows using custom code that varies widely in quality. SI is making a case for a digital twin platform that generates a set of code that can be applied more consistently, rather than relying on a DevOps engineer to write code.

    Ultimately, the goal is to launch a new DevOps era to eliminate most of the silos that slow down application development and deployment, noted Jacob. In fact, one of the reasons few organizations today fully automated DevOps across the application development and deployment process is that it’s simply too difficult to achieve using legacy tools and DevOps platforms, he added.

    A recent survey conducted by the Continuous Delivery Foundation (CDF), for example, found only 22% of respondents are using CI and CD approaches to automate all building, testing and deployment of code in a production environment. Instead, many organizations are using a combination of DevOps and waterfall processes to manage application development and deployment.

    It’s not clear how many organizations are willing to fundamentally change the way they have implemented DevOps. But at a time when more organizations are moving to centralize the management of DevOps, many of them are evaluating their options, at the very least. The issue, of course, is that multiple DevOps teams within the same organization have committed to disparate platforms. Enticing them to centralize on a common platform will require not just a compelling technical advantage but also a significant amount of political capital.

  • Choosing the Right Software Deployment Tools

    Choosing the Right Software Deployment Tools

    Imagine this scenario: After investing countless hours in developing your software, it is finally ready for deployment. Now, you must select the appropriate software deployment tools to guarantee a seamless release.

    This article will guide you through the concept of software deployment and discuss various tools that cater to different needs—from dedicated deployment tools to comprehensive CI/CD pipeline solutions and GitOps approaches. By understanding these categories and their benefits, you’ll be well-prepared to make an informed decision on which tool is the best fit for your organization’s needs.

    What is Software Deployment?

    Software deployment plays a crucial role in the software development life cycle. It involves packaging, distributing and installing an application on target systems or environments, aiming to make your software accessible and usable for end-users seamlessly.

    In today’s fast-paced world, companies must be able to deliver applications rapidly and reliably. A well-planned software deployment strategy ensures that new features reach users promptly while minimizing downtime and errors during updates.

    What to Look For in a Software Deployment Tool

    When selecting the ideal software deployment tool, consider the following factors:

    • Automation: The tool should automate complex software deployments, making the deployment process faster and more efficient.
    • Continuous deployment: Continuous deployment tools allow you to deploy software repeatedly, ensuring consistent deployments. Choose a tool that automates release management and integrates automated builds throughout the development process.
    • Scalability: The tool should be capable of handling large-scale deployments and distributing software across multiple servers. Opt for a tool that enables applications to deploy to multiple servers simultaneously.
    • Integration: The tool should integrate with version control and other third-party tools, making the deployment process seamless. Look for a tool that integrates with modern DevOps processes and connects automated builds to configuration management.

    Full CI/CD Tools

    Bamboo

    Bamboo by Atlassian is a robust tool that integrates seamlessly with other Atlassian products, such as Jira and Bitbucket.

    It offers first-class support for multiple languages and platforms while providing built-in deployment projects for smooth releases.

    GitLab CI/CD

    GitLab CI/CD, an integral part of GitLab, simplifies pipeline management using YAML configuration files stored within your project repository.

    This approach enables easy collaboration among team members while ensuring consistent build environments across all stages of development.

    Codefresh

    Codefresh is a cloud-native solution designed specifically for Kubernetes deployments, It provides a modern interface to manage pipelines visually, along with advanced real-time debugging capabilities.

    Dedicated Deployment Tools

    Jenkins

    Jenkins was originally conceived as a continuous integration (CI) tool, but many organizations use it mainly for deployment. It is an open source automation server that provides support for building and deploying software projects, as well as to schedule and run tasks at regular intervals. Learn more about Jenkins in this in-depth blog post.

    Harness

    Harness is an intelligent software delivery platform that simplifies deployments through automation and machine learning. Their continuous delivery-as-a-service (CDaaS) approach helps you deploy faster while minimizing risks and errors.

    AWS CodeDeploy

    If you’re using Amazon Web Services (AWS), AWS CodeDeploy might be a perfect fit for your needs. This completely managed service automates code deployments to any instance or serverless Lambda function in AWS, guaranteeing consistent results every time.

    Spinnaker

    An open source project backed by Netflix and Google, Spinnaker offers powerful multi-cloud continuous delivery capabilities for deploying applications at scale across various cloud providers like AWS, GCP, Azure, Kubernetes clusters, etc.

    GitOps Tools

    Argo CD

    Argo CD is a declarative, Kubernetes-native continuous delivery tool that uses Git repositories as the source of truth for application definitions. It simplifies rollbacks, provides audit trails and enforces consistency across environments.

    Flux CD

    Flux CD, another Kubernetes-focused option, automates deployments by monitoring your code repository for changes and applying them to your cluster accordingly. Bonus: It supports multi-tenancy and integrates with Helm charts.

    Weave GitOps Core

    Lastly, Weave GitOps Core offers an open source foundation for managing Kubernetes applications using the power of GitOps workflows. This versatile tool can be extended to fit various use cases while maintaining simplicity in its core functionality.

    Conclusion

    There are many software deployment tools available that can help automate the software delivery process, reduce errors and improve collaboration between development and operations teams. From open source tools like Jenkins to cloud-native solutions like AWS CodeDeploy, each tool has its own strengths and features that make it suitable for different use cases.

    When selecting a software deployment tool, it is important to consider factors such as compatibility, automation, scalability, security, monitoring, deployment environment compatibility, integration with existing tools and support and documentation. By carefully evaluating these factors and choosing the right tool for your specific needs, you can ensure that your software deployment process is efficient, reliable and successful.

    Image Source: Freepik

  • Developers’ Role in Protecting Privacy

    Developers’ Role in Protecting Privacy

    We live in a world where we always expect things to happen seamlessly. Every time somebody walks into a café and signs in to the free WiFi and opens their Instagram or TikTok to stay up-to-date with trends and friends or retrieves a discount from a retailer by joining their newsletter circulation, rarely do they stop to think about how that convenience and value is derived.

    Technology is the key enabler working away in the background, and developers and DevOps teams are making that happen. Underneath the slick interfaces of the apps and websites that provide these highly efficient and personalized experiences is a complex machine that relies on data to fuel it, built by developers and delivered by DevOps teams.

    In many ways, data is a two-way exchange, and those end-users that are aware of this give and take appear to be happy with how the relationship works.

    Indeed, several surveys in recent years suggested that the majority of consumers are happy to share their data with companies if it improves their experience. Furthermore, a significant minority are still comfortable if they have no control over who sees their data, there is no clarity around how data is stored and used, even if the organization in question has a poor reputation for data privacy.

    The Privacy Balancing Act

    So, if most people already accept data trade-offs in some shape or form, should developers still care about building applications and solutions that guarantee data privacy?

    The short answer is yes, but as developers, that involves a tricky balancing act.

    Although sharing data has become commonplace in exchange for benefits and value, consumers are becoming more aware of privacy issues. Take the EU’s General Data Protection Regulations (GDPR) as an example. Over the past five years, awareness has more than doubled in notable European markets such as the UK, Spain, Germany, the Netherlands and France.

    Meanwhile, there is also commercial pressure, as employers rely on developers to innovate to remain profitable. At the same time, customers expect brands to be responsible with their data, and failure to do so at the expense of trying to commercialize a new application could be detrimental. Indeed, while the pandemic may have ushered in significant changes and altered consumers’ attitudes toward data privacy, end users remain unwavering about the importance of security.

    Maintaining this balancing act is becoming increasingly complex to achieve. However, the question of data privacy is becoming a key business priority, and that means developers have a big opportunity to show their commercial value to their organizations. Indeed, companies cannot afford to get the balance wrong, and developers are central to creating the perfect formula.

    In fact, the privacy conundrum has been around for a long time.

    When the internet was created, privacy was not considered an issue because all content accessed online was deemed to be public. Nothing was encrypted; the introduction of email complicated things, not least because anybody on the internet could, theoretically, intercept personal data and read private messages.

    This prompted the emergence of the cypherpunks, a group of cryptographers who began to contemplate what the future of digital privacy might and should look like. They started to create the tools they believed the world needed to safeguard data privacy–today, their mission is carried on by developers who value user privacy.

    Why Developers Need to Be Familiar With FHE

    However, securing the transmission of data is not enough, as many breaches still occur because data isn’t encrypted during processing.

    So, in a world where more and more data needs to be shared to deliver the sort of experiences consumers expect, is it inevitable that privacy and security will be compromised as the volume of data exchanges grows? Not necessarily.

    Fully homomorphic encryption (FHE) offers a solution, allowing developers to build applications and run services without needing to see or secure the underlying data. This is because FHE enables data to be processed blindly without having to decrypt it at any stage. FHE offers a way for developers to maintain that all-important balancing act between maintaining privacy and offering value to both business and customer.

    In FHE, to guarantee a user’s data privacy, all data is encrypted by the user with their own secret key. Users of a particular service, such as an online medical portal, will use a secret key to send their encrypted data to a server where blind processing takes place. The result is also encrypted and sent back, the user again using their secret key to decrypt the information.

    What this means is that, because data is encrypted end-to-end, the company providing the service can do so in a way that keeps the same customer experience, even though they cannot see the data that is being shared and sent back. From a security perspective, this is also critical. Governments, attackers and service providers cannot see the exchanged information because they do not possess the key–they also cannot break it, as the encryption used in FHE can resist attempts made even by powerful quantum computers.

    Privacy can also be protected during larger-scale data exchanges that underpin collaboration between organizations and nation-states on numerous strategic programs, with each contributor able to add their value knowing that their intellectual property and sensitive information is not compromised.

    Looking ahead, if developers can embed FHE into their practices on a broad scale, then a key milestone for privacy is within reach. Rather than being viewed as an objective relating to digital interactions, privacy can be treated as a naturally occurring by-product of every application, piece of software and service that the developer community creates.