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  • Automation in DevOps: Advancements, Platforms and Examples

    Automation in DevOps: Advancements, Platforms and Examples

    Automation is the backbone of DevOps. By facilitating seamless integration and continuous delivery, it revolutionizes the ways organizations deliver software, products and services. When applied correctly, automation can significantly enhance productivity, reduce time-to-market, improve software quality and minimize the risk of human error.

    A range of automation tools support these goals, each tailored to a specific aspect of the software development life cycle (SDLC).

    From code integration to testing and deployment, these tools optimize processes and enable the rapid and reliable release of software. In this article, we will explore the role of automation in the DevOps landscape.

    The Importance of Automation in DevOps

    Automation in DevOps is the process of designing, developing and deploying software and systems with minimal human intervention. The goal is to streamline the software development life cycle from design, development and testing to deployment and management.

    Automation provides several benefits:

    1. Speed and efficiency: Automation enables quick development and deployment of software, which results in faster delivery of features and fixes to customers.
    2. Reliability: Automated systems are less prone to human error, resulting in more reliable code deployment and management.
    3. Consistency: Automation guarantees that routine tasks are performed the same way every time, ensuring consistent results.
    4. Reduced cost: Automation eliminates the need for manual intervention in routine tasks, leading to a reduction in operating costs.
    5. Increased productivity: By taking over routine tasks, automation frees up the team to focus on more critical, high-level tasks.

    Automation in DevOps: An Overview

    Automation in DevOps encapsulates various stages, from development and testing to integration, deployment, and monitoring. The process is often referred to as a DevOps pipeline, a set of practices aimed at reducing development times and improving software quality.

    ● Development: Automation begins at the development phase with tools for source control (like Git), which help developers manage and track code changes.
    ● Integration: The next step is continuous integration, where tools like Jenkins automate the build process, allowing teams to identify issues early in the development life cycle.
    ● Testing: Automated testing tools (like Selenium) streamline the testing process, ensuring that the code is error-free and ready for deployment.
    ● Deployment: Continuous deployment tools (like Kubernetes) automate the deployment process, providing fast, consistent and repeatable deployments.
    ● Documenting: Technical documentation is automated with tools like Scriversi to ensure updated, error-free documentation through each version and release.
    ● Monitoring: Finally, automated monitoring tools (like Prometheus) offer real-time insights into the application’s performance, facilitating proactive troubleshooting.

    Automation’s main objective is to minimize manual intervention, thus reducing the risk of errors, improving efficiency and fostering a culture of shared responsibility.

    Examples of Automation in DevOps

    1. Continuous Integration/Continuous Deployment (CI/CD): CI/CD is a critical element of DevOps automation. With CI, developers merge their changes back to the main branch as often as possible. The CI/CD server automatically builds and tests every change. For example, Jenkins, a popular open source automation server, allows developers to automate various stages of their build pipeline.

    2. Infrastructure-as-Code (IaC): This practice involves managing and provisioning computing infrastructure with machine-readable script files rather than physical hardware configuration or interactive configuration tools. For instance, Terraform, an open source IaC software tool, provides a consistent CLI workflow to manage hundreds of cloud services.

    3. Configuration Management: This is the process of maintaining a system’s configuration in a known, consistent state. For example, Ansible, a configuration management tool, helps to automate software provisioning, configuration management and application deployment.

    4. Monitoring and Logging: Automated monitoring and logging systems gather data on how software and hardware are performing and alert the team to any problems. One example is Prometheus, a popular open source monitoring and alerting toolkit.

    5. Technical Documentation: Proper documentation is crucial in the software development process. Yet, it is often overlooked or not updated frequently due to time constraints or the tedious nature of the work. When automated, it simplifies and automates the process of creating and maintaining technical documents.

    Final Thoughts

    In the world of DevOps, automation is not a luxury but a necessity. By automating repetitive and error-prone tasks, teams can focus on what they do best: creating innovative solutions that meet customer needs. From CI/CD, IaC and configuration management to monitoring and logging, automation simplifies the software development process, reduces human error and enhances speed and efficiency. Tools like Jenkins, Terraform, Ansible, Prometheus and Scriversi support this trend, providing various automation capabilities that make the DevOps approach more efficient and effective.

  • 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

  • Technological Breakthroughs in Hurricane Forecasting

    Technological Breakthroughs in Hurricane Forecasting

    The 2023 Atlantic hurricane season marks a transformative era in tropical forecasting, driven by the remarkable progress in machine learning and big data analysis. It’s a rapidly evolving field, where technology and meteorology intersect to better prepare the public for the formidable forces of Mother Nature.

    NOAA’s 2023 Atlantic Hurricane Season Forecast

    The National Oceanic and Atmospheric Administration (NOAA) projects that this year’s Atlantic hurricane season will produce 12 to 17 named storms, with five to nine major (Category 3+) hurricanes. NOAA expresses 70% confidence in these ranges, bolstered by its evolving technology.

    Leveraging Technological Innovations for Advanced Hurricane Forecasting and Resilience
    A summary infographic showing hurricane season probability and numbers of named storms predicted from NOAA’s 2023 Atlantic Hurricane Season Outlook. (Image credit: NOAA)

    Upcoming Upgrades: Supercomputing System Expansion

    The recent implementation of the Probabilistic Storm Surge model improves storm surge forecasting for the U.S. mainland, Puerto Rico and the U.S. Virgin Islands. The model provides forecasters with a range of potential flooding scenarios, enhancing community preparedness. 

    NOAA plans to implement several more upgrades this summer, including a 20% expansion of its operational supercomputing system’s capacity. This enhancement will enable NOAA to run more complex forecast models, leading to more accurate predictions.

    In late June, the Hurricane Analysis and Forecast System (HAFS) becomes operational. Running in tandem with the current Hurricane Weather Research and Forecast Model System, HAFS is projected to show a 10-15% improvement in track forecasts over existing models.

    HAFS represents a significant leap forward in the integration of machine learning algorithms and sophisticated data analysis techniques. By leveraging state-of-the-art computational models and assimilating an extensive array of meteorological data, HAFS has the potential to unlock new insights into the behavior and trajectory of tropical cyclones. This fusion of technology and meteorology is projected to surpass the capabilities of existing models.

    Harnessing Machine Learning for Advanced Forecasting

    The core strength of HAFS lies in its ability to process vast amounts of atmospheric and oceanic data, utilizing advanced machine learning algorithms to identify patterns and correlations. These algorithms can discern intricate relationships between various meteorological variables, such as sea surface temperatures, atmospheric pressure, and wind patterns, enabling more precise forecasting. By comprehensively analyzing historical storm data and incorporating real-time observations, HAFS can generate forecasts with higher accuracy and longer lead times.

    HAFS also harnesses the power of high-performance computing, allowing for faster and more complex simulations. This computational prowess enables the system to simulate a multitude of possible scenarios, accounting for various atmospheric conditions and factors that influence hurricane behavior. The ability to run multiple simulations and generate ensemble forecasts enhances the robustness of predictions and provides forecasters with a comprehensive range of possibilities.

    Innovative Technologies: Drones, Saildrones, Underwater Gliders, and Sounding Balloons

    Innovative technologies like small aircraft drone systems, additional Saildrones, underwater gliders, and WindBorne global sounding balloons will contribute to advancing knowledge and improving hurricane forecast accuracy. 

    Small aircraft drone systems offer a unique vantage point for data collection in the lower atmosphere, enabling meteorologists to gather critical information on temperature, humidity, wind patterns, and other atmospheric variables. These drones are equipped with advanced sensors and instruments, allowing them to navigate through hurricane environments and provide valuable real-time data that can significantly improve forecast models.

    Saildrones, alternatively, are autonomous surface vehicles equipped with an array of meteorological and oceanographic sensors. They harness wind and solar energy for propulsion, enabling them to traverse vast oceanic regions and collect crucial data on sea surface temperatures, ocean currents, and other parameters relevant to hurricane formation and intensification. By expanding the fleet of Saildrones, scientists can enhance their observational capabilities and obtain a more comprehensive understanding of the complex interactions between the ocean and the atmosphere during hurricane events.

    Underwater gliders, equipped with sensors and instruments, offer a unique perspective beneath the ocean’s surface. These autonomous vehicles can collect data on temperature, salinity, and ocean currents, providing valuable insights into the oceanic conditions that influence hurricane development and intensity. By combining data from underwater gliders with other observational platforms, scientists can gain a more holistic understanding of the underlying processes that fuel tropical cyclones.

    WindBorne global sounding balloons ascend to the upper levels of the atmosphere, collecting data on temperature, humidity, and wind patterns. This information is vital for initializing and validating numerical models used in hurricane forecasting, enhancing the accuracy of predictions.

    Leveraging Technological Innovations for Advanced Hurricane Forecasting and Resilience
    NOAA GOES satellite captures Hurricane Ian as it made landfall on the barrier island of Cayo Costa in southwest Florida on September 28, 2022.

    Improving El Niño & La Niña Forecasts

    The Tropical Atmosphere Ocean buoy array is undergoing modernization and upgrades, bolstering the accuracy of El Niño and La Niña forecasts. These climate patterns have significant impacts on hurricane activity, and accurate predictions of their behavior are crucial for understanding the overall climate system. 

    By modernizing and enhancing the buoy array, scientists can gather more precise data on oceanic and atmospheric conditions associated with El Niño and La Niña, leading to more accurate long-range hurricane forecasts.

    New tools and upgrades have also been introduced for more precise hurricane analysis and forecasting. The National Hurricane Center has expanded its Tropical Weather Outlook graphic forecast range to seven days from five. To give communities more time to prepare, the Weather Prediction Center has also extended the Excessive Rainfall Outlook by two days.

    Leveraging Technological Innovations for Advanced Hurricane Forecasting and Resilience
    A summary graphic showing an alphabetical list of the 2023 Atlantic tropical cyclone names as selected by the World Meteorological Organization. The official start of the Atlantic hurricane season is June 1 and runs through November 30. (Image credit: NOAA)

    Bolstering Resilience Against Future Hurricanes

    The integration of these innovative technologies and the modernization of existing observational systems expands observational capabilities both in the atmosphere and the ocean to track and monitor storms. The evolution of forecasting techniques holds promise for even greater resilience against future hurricanes, showcasing the remarkable impact of technological advancements in safeguarding coastal communities.

  • How Embedded Analytics Can Transform Future Businesses

    How Embedded Analytics Can Transform Future Businesses

    It’s no secret that big tech companies like Google, Amazon and Netflix are not only leveraging data but also delivering embedded analytics and insights as a standard functionality of their software, services, applications and toolkits. The analytics appear to consumers as recommendations, usage habits and other helpful information. Such insights not only help consumers extract the most value out of the product they are using but also help providers understand how they can provide better services. Businesses that embed analytics to provide a differentiated user experience also have a direct impact on engagement and revenue.

    Have you considered how embedded analytics could differentiate your company’s own software and hardware products? Let’s understand how embedded analytics can help transform technology businesses:

    1. Analytics are expected and welcomed in your products

    By embedding analytics into existing enterprise software and applications, users can drill down into real-time and context-aware data (for example: How busy a location will be at various times of the day) and can benefit from faster data-driven decision-making without worrying about application compatibility. Commonly, software applications provide in-app analytics to delight and serve their customers, while hardware companies can provide helpful stats on a web portal or app.

    2. Embedded analytics is easier than ever today

    Cloud technology has completely disrupted tech-enabled industries. It’s easier than ever for software, apps and hardware to connect to a data repository to save logs that are a rich source of analytics. The invention of the S3 bucket and object store has made it fairly cheap to keep log data. Finally, the transition to platform-as-a-service (PaaS) and software-as-a-service (SaaS) has fundamentally added an “easy button” to tracking consumption patterns and resource utilization.

    3. Embedded analytics helps design better products and services

    Embedded analytics can give businesses more insight into application telemetry (how customers use the data, how they engage with the product) and provide insights into the challenges they face from a usability standpoint. Providers can use advanced analytics to quickly iterate, draw patterns and make predictions, troubleshoot customer challenges, discover new avenues to monetize, detect and mitigate security threats or create entirely new features and applications that put customers on a faster path to improved application experience and better decision-making.

    4. Embedded analytics increases operational efficiencies

    The tech industry is transitioning from traditional monolithic architectures where applications are self-contained to microservices architectures where different components are spun up as needed via API calls. By embedding analytics directly into developer tools, businesses can manage resources without sacrificing availability or performance. Companies can allocate and optimize resources dynamically and understand peaks and valleys in consumption. Businesses must be able to leverage historical and real-time data to build predictive models to proactively identify and mitigate issues with individual components of the application before the customer experiences a problem.

    Embedding Analytics in Your Application

    Before you start embedding analytics in your application, it’s important to choose the right database foundation, as this will support current needs and future goals. Below are the top capabilities that should be standard features in analytics databases:

    1. Handles massive data volumes: The database must scale easily and efficiently with minimal cost using massive parallel processing. Today’s scale might be terabytes, tomorrow it might be petabytes and so on.

    2. Enables speedy data analytics: Speed is a key factor in a positive user experience. Users want instant insights because they don’t like waiting for results. The database should be capable of optimizing load and query performance so that analytics is both timely and relevant.

    3. Embeds machine learning: Machine learning algorithms are critical for predictive analytics. A platform that can embed ML and iteratively learn from new data can make a big difference and add a whole new level of intelligence.

    4. Features native integrations: The more time developers spend figuring out tools and integrations, the less time is spent innovating. The platform must ideally have out-of-the-box integrations with popular applications, data sources (on-premises, cloud, multi-cloud or hybrid), ETL, and visualization tools (e.g., Microstrategy, Looker, Power BI, Qlik, Tableau). It should be flexible enough to support user-defined functions for things that don’t have native integration.

    5. Encourages self-service: The database should make it easy for data scientists to leverage tools and programming languages they already know such as R, Java, C/C++, Python and SQL. Data scientists will also appreciate a platform that has built-in functions for a wide range of analytics (such as geospatial, time-series, event-series, real-time, machine learning, text analytics, pattern matching and regression) and delivers the tools to spot trends, uncover anomalies and anticipate the unexpected.

    6. Supports highly advanced analytics: Many platforms can analyze single tables or do a simple look-up but few have the power to analyze dozens of tables, hundreds of data types, dimensions and attributes from numerous sources over several years of history.

    7. Unified: The database should be able to streamline everything right from data ingestion to exploration to production until delivery. Users should be able to analyze data in its place to always have a single source of truth.

    It’s not hard to visualize that the most disruptive companies of the future will be the ones that harness data as a core asset and embed analytics in their products and services. Embedding analytics requires the right database foundation; to get to the right foundation, IT teams need to cut through the noise and study the fine print. With the proper database, the future is yours to create.

  • How Does That Stack Up?

    How Does That Stack Up?

    There’s an entire class of successful innovations made up of things that people didn’t realize they needed. Things that were an obstacle they found a way around and didn’t think about until the innovation showed them an easier way. Think of things like virtualization (hardware was the bottleneck, but “That’s just the way it is,” until it wasn’t) or web monster shopping sites (“They don’t have that in the stores; I guess I’ll live without,” until you could order the weirdest or smallest things from the likes of eBay and Amazon).

    My rule here is that I only talk about products and services if I use them and find value in them. And even then, I try to do it sparingly. But in the spirit of the innovation story you just read, I’m going to point you at one of the coolest new websites on the net. I don’t know the company; have not done business with them, couldn’t even name a principal. But I have spent a surprising amount of time on their site, both in the Feed section and Browsing Stacks.

    The site is Stackshare.io, and the reason I think it is so innovative is what and who it is aimed at: Listing companies’ DevOps stack and offering advice on different parts of the DevOps stack.

    The Browse Stacks section is for presenting what other organizations are doing, so you can get good ideas for your own stack. But the developers of the site appear to have recognized the other useful aspect of this information: Matching organizations to prospective employees based on technologies. You can go look and see that Company X is using GitLab, for example, and that can then influence your job search.

    The Feed section is just a running discussion that uses categories to ask questions or offer insight and advice about decisions a given organization came to—so, “Chose X over Y” is actually a standard subheading for posts, as is “Need advice on Z” or “Recommends A”. It makes for great reading, and no doubt while reading through, you’ll have some advice to offer one of the “Looking for advice” posts.

    The Stackshare.io participants seem to range in size from startup to massive, and that is one of the things I hope they change as they grow—the options for looking at DevOps stacks are “Popular” and “Trending”. We all want more filters than that—organization size, number of apps, stuff like that—to help us zero in on environments that are similar to our own. My little company does not have the needs that Facebook does. And while it’s true that some startups use more tools in their toolchain than Facebook, you get the idea.

    Another issue I had with Stackshare.io’s site (that I fully understand, but still wish could be different) is forced registration/login to see some data. It’s not even particularly sensitive data—I know what ELK and Azure Data Services are, so putting the definition/description behind a registration page/login is kind of silly. But every free site needs data to pay the bills, and I suppose I’m glad it is info that’s also available elsewhere that is behind a reg wall.

    The company offers APIs for integration to your site/tool and private company instances of StackShare to help you manage one of my other gripes—the five (or fifty!) different DevOps stacks many organizations have allowed to develop in-house.

    So if you are job hunting, Stackshare.io can help you find companies doing what you would like to do or know you’re good at. If you are an organization trying to improve or set up a new toolchain (which is how I found the site), it has a lot of information to digest, though not all of it is easily accessible at this point. Either way, keep kicking it and keep an eye out for tools that do the job, no matter where you are looking.

  • Implementing DevOps Goes Beyond Technology

    Implementing DevOps Goes Beyond Technology

    The implementation of DevOps is primarily toward a change of process. All you need is to break down the feed store and bring in the competing individual inducements to acquire the actual benefits from DevOps. Regarding the change of process, it will either be embraced by those who are making the change and succeed, or it will get rejected and eventually fail.

    The hardest part of successful DevOps is not the implementation of technology but much beyond it. It is understood that without technology, you can hardly enforce the DevOps culture. The technology side is all about automation, focusing on the infrastructure in the form of codes and establishing the pipeline process.

    A survey found that among more than 2,000 of the IT industry executives, 54% of the respondents believed they had no access to self-service infrastructure; instead, they take some ticket-based approach toward infrastructure delivery. This also impacts productivity and increases time to market. The survey noted that only 23% of the experts said that infrastructures could be delivered in less than 24 hours. However, some 33% said it takes up to a month to give, while 26% responded it takes one month or more to do so. 

    Speaking in terms of technological perspective, we’re well aware of the fact that DevOps targets to achieve complete automation and integration, but practical implementation is not entirely possible. Establishing new aspects has been a great struggle, even if it is related to replace specific traditional methods with some new ones.

    Mentioned below are the best answer to why implementing DevOps goes beyond technology. Let’s discuss them one by one. 

    Lack of Proper Vision

    Without having a proper definition of the issue or solution, it becomes challenging to form a vision. Therefore, when experts become familiar with the process, they begin to follow a specific path to manage things in the correct order. Even though at some point they become stuck in the circle, too.

    With time, it becomes difficult to get out of this vague circle, be more responsive to current situations and discover new methods for betterment all at the same time.

    Without having a proper plan, it becomes not tricky but merely impossible to achieve some productive output. The lack of vision makes it challenging for the project owners to design a clear-cut plan when it comes to deciding milestones and deliverables.

    The industry experts find it a bit risky because there are honestly few people who possess skills and expertise in this domain when compared to the number of tools present in the market. This also gives rise to confusion, which ultimately leads to an increase in the risk factor.

    Cultural Defies

    Another significant challenge is the removal of traditional methods and to adopt new ones. Undoubtedly, people are more comfortable when they follow conventional techniques as long as the outcome is useful toward the end of the day.

    However, if the outcome is not what you’ve desired, or if you start realizing that your job requires various manual interventions, then it would be good to understand that this can hinder your overall productivity and leads to adverse effects in the long term.

    Absence of Tool Knowledge

    Previously, DevOps has introduced the principles of continuous deployment, testing and collaborative reporting. But, since most of the people prefer to continue working with traditional tools, adapting to the functionalities of the latest tools becomes a difficult job. This happens more when it comes to getting a hold on the changes made to the architecture based on cloud and on-premises during the entire process.

    Lack of tool knowledge leads to organizations making poor choices of tools.

    Risk Analysis

    It is challenging to alter old methods and techniques and get them replaced by the latest ones. While implementing DevOps, when it comes to risk analysis, business experts design their dashboards by scaling hundreds of different reports. It is based on calculations and most of the time, it is quite easy to start but hard to climb. It happens when things are being put into action. The workers face troubles in keeping up with the pace. Therefore, adopting the latest methodology involves risks to a significant extent.

    Ways to Minimize These Challenges

    After doing research, I have come up with six best ways to minimize these issues and increase your chances of DevOps success. Let’s discuss them.

    Boost Up Productivity

    As mentioned above, no proper vision is a severe issue, and it also leads to poor and low levels of productivity. With new IT services coming in the market, people will understand the need for shaping their vision. It is crucial because only then they’ll be able to compete in the marketplace. DevOps comes with specific tools ranging from automation to monitoring. These tools can boost up the functions of an organization. An organization can unlock benefits from these automated tools so their developers can have a lighter load. This reduces time on deployment and by default, errors and mistakes are reduced too, which results in more productivity.

    Encourage Diversity

    DevOps successfully brings people together from different backgrounds and with different skillsets, and it delivers the results when this diversity is embraced. Having diversity in a DevOps team leads to higher productivity. This is extremely important with the rise of full-stack developers and the need for every individual to possess a variety of skills.

    Learn From Mistakes

    In the slow-moving model of working, people get afraid to accept they’ve made a mistake or even share any lessons they’ve learned while committing an error because it’ll directly affect their career. In the DevOps world, it is believed that by sharing those experiences, you are encouraging innovation. DevOps often calls for identifying mistakes and ask everyone to consider it as a learning opportunity, instead of an issue to be blamed. The perfect approach is to embrace mistakes and make improvements.

    Review Security Practices

    Security is essential in DevOps implementation. If the developers fail to enforce proper security practices, then they’re solely responsible for the effects afterward. By implementing automated tools or software security services early in the development cycle, teams can test the code throughout their software development process. Also, developers must ensure the presence of security elements while they deliver software timely.

    Focus On the Usage of New Tools 

    The introduction of new tools has speed up the adoption rate of DevOps, and now it has become vital to ensure that these tools are correctly integrated within the existing infrastructure and meet all the security levels. But, much focus should be on the team rather than on devices because workers are the essential faction in the shift of DevOps.

    Educating and Training the Staff

    This area needs serious attention. It is crucial to conduct weekly seminars and training sessions to educate the employers on new methods and tools they might be using in the development process and prepare them for new challenges. This will not just boost up worker’s knowledge but will also foster DevOps success.

    Final Thoughts

    Successful DevOps implementation is not an overnight project. The entire process requires advocacy, time, effort and strong leadership in a way that is compatible with your organization’s goals and objectives. Prepare yourself for achieving DevOps success by overcoming the challenges and hurdles that were made by the people that came before you.

    — Farwa Sajjad

  • Synack: DevSecOps Being Accelerated by Cultural Shifts

    Synack: DevSecOps Being Accelerated by Cultural Shifts

    The 2020 State of Compliance and Security Testing Report from cybersecurity testing platform vendor Synack claims that some of the world’s largest organizations are encountering a significant cultural shift within their development teams, and that bodes well for those seeking to build DevSecOps teams. For the report, Synack surveyed leaders from more than 300 organizations representing a number of industries and verticals, including technology, government, health care, information technology and financial services. 

    According to the report, a large percentage of organizations and institutions are moving toward a rigorous, continuous testing model to ensure compliance. As part of this shift, organizations are utilizing crowdsourced security testing to achieve regulatory compliance and real security, with adoption expected to increase four-fold in 2020.

    Perhaps those companies are being driven by numerous new regulations on the horizon, including the  California Consumer Privacy Act (CCPA), PCI  DSS 4.0, New York’s SHIELD Act and  other proposed data compliance regulations. Or perhaps the shift toward continuous crowdsourced security testing is being driven by the failures some organizations have encountered with traditional security testing methods, which were performed less frequently and failed to keep up with the CI/CD (continuous integration/continuous delivery) pipelines that many organizations have embraced. 

    Simply put, Agile and DevOps application development and delivery methodologies were poorly served by the traditional, siloed security testing methodologies of the past. A realization that has driven many organizations to embrace the DevSecOps model, in which cybersecurity becomes part of the overall team, having equal standing with both development and operations team members. 

    Organizations pushing ahead with the DevSecOps model quickly realized that security toolsets and team member interactions must change to be successful. Synack’s research bears that out, and the report offers that the adoption of continuous security testing platforms is expected to increase by 4X in 2020.

    “The rapid embrace of crowdsourced security testing has happened because it is proven to work better than traditional security testing methods and addresses the ever-growing talent gap within organizations,” said Synack CTO and co-founder Mark Kuhr. 

    The report found security testing is becoming part of an organization’s normal routine, rather than a once-a-year check of the box focused only on compliance. According to the report, 44% of the organizations and institutions surveyed perform security tests on a monthly or weekly basis, suggesting that they are moving toward a continuous model, which is further enabled by crowdsourced solutions.

    The report also revealed that some 63% of organizations commonly use external vendors to identify and reduce vulnerabilities. However, 52% experience unwanted cost and complexity due to overlap in functionality from using multiple security vendors. Those two data points demonstrate that simplification provided by leveraging a single security testing platform could deliver savings. Synack claims crowdsourced security testing solutions provide 147% higher ROI than a typical pen test and can decrease the burden of testing on organizations by reducing the signal-noise ratio. 

    “This shift toward continuous crowdsourced security testing will allow organizations and institutions to have the best of both worlds by procuring technology that offers efficient and effective results while fulfilling best practice standards such as NIST 800-53 to meet compliance objectives,” said Kuhr.

    “Although we are seeing a move toward a 24/7, 365 security culture at organizations in a wide variety of industries and geographies, there is still ample room for improvement,” said Aisling MacRunnels, Synack’s CMO. “Our survey found that on average, most security tests are lasting just 20 hours. As the number of cyber incidents continues to increase, it will be imperative for decision-makers to implement security testing solutions on a continuous basis with 1500-2000 hours of testing a year.”

    Those increased testing requirements will ultimately become the foundation to build a DevSecOps culture in most any organization bound by compliance regulations.

    — Frank Ohlhorst

  • Developers Are Gaining Clout, and We Need to Pay Attention

    Developers Are Gaining Clout, and We Need to Pay Attention

    I’ve been watching the ascent of developers for quite some time. A few years ago, I wrote an open letter to developers in which I noted their power and collective influence over the direction of technology across industries. As creators of our digital future, developers hold incredible power—and with that power comes great responsibility.

    Developers now directly influence technology decisions within their organizations. They have achieved widespread recognition for their expertise and, as such, have frequently acquired a broader role in their company’s digital trajectory.

    While developers have always been first and foremost in feature and functionality development at the Cloud Foundry Foundation, we’re starting to see this approach bubble to the surface across the business landscape and in other open source communities. Cloud-native technologies often focus on operators, but it’s just as important to empower developers.

    If our goal is, as it should be, to enable developers to be more productive and give them the freedom to create more applications to production as quickly as possible, a developer’s workflow needs to be seamless and intuitive.

    Developers Need Widespread Support

    The long-tail impact of developers gaining a seat at the table and influencing technology decisions is a positive shift that demands widespread support. It’s critical that we recognize the important role developers play today and give them accompanying responsibilities to meet our common goals.

    Think about who is creating the software that’s changing how organizations operate and interact with customers: It’s the developers. Developers, above anyone else, know the technologies that make them most productive and impactful. Putting them in the driver’s seat is paramount because we all benefit when they are given space and time to be as productive as possible.

    Enterprises of all shapes and sizes are taking notice and shifting strategies as a result. Indeed, a significant majority of organizations are empowering developers with the freedom to choose the tools they use. In our most recent research, we found that 59% of respondents said their company is giving development teams more authority to choose their tools.

    Perceptions Are Evolving

    It’s no coincidence that this change is happening when software development becomes more critical for companies across all industries. Organizations realize the biggest hurdle to improving application development productivity is culture. More than a third (37%) of survey respondents feel that way today. We’ve been tracking this sentiment since 2016 and only a quarter of respondents felt that way then.

    Just three years ago, 39% of respondents said technology was the biggest hurdle for their organizations to overcome. That number has dropped to 29% today.

    That’s quite the inverse from 2016, and it indicates the levels at which software development is becoming a greater priority for businesses. As such, it’s increasingly common for organizations to give developers resources and influence to shape the direction of their business.

    Let’s not become complacent. We all need to double down on giving developers the best possible experience. It’s the developers who are driving transformational change in our organizations. The more power we give them to do so, the better off we will be as a result.

    — Abby Kearns

  • Got a DevOps Tool? Take Part in Our Annual DevOps Tools Survey

    Got a DevOps Tool? Take Part in Our Annual DevOps Tools Survey

    The DevOps tools market is growing at a fast clip, with market values ranging from $8 billion to $12 billion worldwide by 2022, depending on which analyst you trust most. That growth is due in large part to the number of vendors entering the DevOps space, offering a bevy of tools designed specifically for addressing the need for organizations to bring applications to market faster while improving quality and securely.

    The market is growing so fast, in fact, that it’s getting difficult for us (and, I’m sure, you) to keep up with all the new players out there. That’s why we’ve put together a tools survey that we hope tools vendors will take part in. Our goal is to create a comprehensive directory that developers, IT operations and executives can use to discover the right tool for their DevOps toolchain.

    The survey is also going to be used to help us recognize the top vendors in each category through our annual DevOps Tools Awards. And that, my friends, is a big deal.

    The DevOps Tools Survey breaks tools into categories based on their utility as they relate to building applications. The categories are: creating, assuring, assembling, securing, delivering, running and analyzing. Organizations can submit up to three tools to be included in the directory.

    Want to be a part of the action and get your tool listed? Simply click on this link to get started.  The process takes only about 10 minutes max, and will give us the information we need to get your tool included. It costs nothing to be included in the directory, and enhanced listings are available as well.

    So don’t wait! The deadline for submissions is Sept. 15.

    — Charlene O’Hanlon

  • source{d} Delivers Enterprise Edition of SDLC Platform

    source{d} Delivers Enterprise Edition of SDLC Platform

    source{d} has made available an enterprise edition of its software development lifecycle (SDLC) platform that includes visualization and analytics tools along with additional management capabilities. A free community edition of the core source{d} platform, which is stripped of most of the enterprise-class tools, also is now available in beta.

    Company CEO Eiso Kant said the enterprise edition of source{d} provides the additional tools enterprise IT organizations require to employ the platform as the equivalent of a business intelligence (BI) application for managing DevOps processes.

    The tools can launch queries against a big data repository based on the Apache Spark in-memory analytics engine running on a Kubernetes cluster, which can be populated with actual data or metadata pulled from multiple DevOps tools and platforms. That capability enables IT leaders to then query data that has been joined together in a way that surfaces actionable intelligence, said Kant.

    source{d} Enterprise achieves that goal by including Apache Superset, an open source business intelligence web application. The platform also can be extended to support SQL queries launched from other BI tools and project management applications. The enterprise edition also provides access to advanced queries and user-defined functions to address tasks such as code duplication analysis or identity matching.

    Finally, source{d} Enterprise provides authentication integration with LDAP and OpenID to limit who can edit or view queries, data sources, charts and dashboards.

    Longer-term, source{d} plans to leverage predictive analytics and machine learning algorithms more aggressively as the amount of SDLC data that gets collected by enterprise IT organizations increases.

    Kant said many enterprise IT organizations have tried and failed to build the equivalent of source{d} platform mainly because bringing together and then maintaining all the required technologies often becomes too complex an undertaking. Those efforts also have been confined largely to managing processes such as bug fixes versus including all the BI tools needed to manage software development in a way business and IT leaders can align technology initiatives to specific business goals, he said, noting the source{d} approach brings together enabling technologies such as Spark and Kubernetes to enable IT organizations to deploy an SLDC platform on-premises or in a public cloud.

    As software development increasingly grows more complex, the days when it could be managed efficiently through a project management application alone have come to an end. At the same time, more organizations realize their success ultimately comes down to how consistently they can deliver a high-quality application experience. For all the hype surrounding digital business process transformation, the core tenet is that most organizations are indeed becoming software companies. As such, they need to borrow many of the SDLC processes that successful software companies employ routinely. The only real difference is they don’t need to develop those processes from the ground up when more turnkey SDLC platforms are emerging.

    — Mike Vizard