TSG Training

Day: 31 January 2022

  • Bringing AI, Data Science, And DevOps Together To Produce Practical, Business Focused Outcomes

    Every company across every industry wants to find more efficient ways of operating. Advances in technology over recent years have innovated and improved business processes and outcomes exponentially, but there is still more that can be done.
    There is a careful balance between adopting new solutions and not overspending on proprietary options.
    Open-source solutions are a low cost and agnostic way of accelerating businesses, and bringing them together can be a practical option for many.
    Artificial Intelligence (AI) has boomed over the last few years, and businesses of all shapes and sizes are now utilising this technology to reach their goals. AI is commonly used for banking services, product recommendations, and digital assistants, and when created properly, these solutions can be very successful.
    One of the biggest challenges with deploying AI in a business is ensuring it stays supportable and operational over time. Combining AI with data science and DevOps can produce more practical outcomes and lead to improved success. However, implementing these aspects together requires careful planning, skills, and effort.

    Aligning Development Approaches

    Almost all cloud services now use DevOps as their standard for development. It puts an emphasis on automated processes and focuses on creating a culture that encourages collaboration across all teams.
    Applications using DevOps are well supported through instrumentation, platform, and processes. It forces teams to look at the infrastructure required for supporting the application and if any tools can help automate this.
    Generally speaking, AI projects use their own development methodologies. Similarly to DevOps methodologies, these use practices and principles from real-world projects to lead the development to success. This approach is individual to data science projects and unique because small iterations are made frequently to refine the data.
    The intention behind this kind of methodology is to align the AI development alongside the business needs. This process usually has little interaction with operational teams and does not focus on the product release. DevOps teams today are usually unfamiliar with the way data science projects are developed.
    Both AI development and DevOps are separate methodologies with one goal in common: to get the application into development. By bridging the gaps and aligning these differing approaches, businesses can produce more practical and focused outcomes to meet their goals.
    AI projects must incorporate some of the deployment and operational methods used in DevOps, and DevOps projects can benefit from AI developments automation and release processes.

    Integrating AI, Data Science, And DevOps

    Bringing these methodologies together could potentially streamline and stabilise a business’s release process. Bridging the gaps between AI and DevOps is not always easy, and there are a few things to consider when looking to integrate these methods.

    • The AI development process relies heavily on experimenting with different iterations of models. This can take up a lot of time for each model to be tested and trained properly. Create a separate workflow that accommodates the timelines for model builds and the testing cycle.
    • When teams are developing for AI and data science projects, put a focus on adopting practices and processes which allow evolution and a model lifecycle. The key aspect here should be delivering value over time as opposed to a one-time creation of a model.
    • DevOps is known for integrating development, release, business, and operational knowledge into a single solution. It is critical that AI is represented and included throughout this process.
    • Appropriate metrics must be used to inform the models that are being updated and deployed. AI offers many benefits to metrics in application solutions and should be integrated appropriately. This technology can be used to define accuracy metrics and then track these throughout the process. Business metrics should be tracked to capture the impact the model has on operations. Furthermore, data metrics must be monitored to keep an eye on model performance.

    Automating Model Pipelines And End-To-End Data

    The AI model pipeline connects all the correct processes, tools, and data elements together. This brings another level of complexity to DevOps methodologies because although one of the pillars of DevOps is automation, automating the complete pipeline is a huge challenge when it comes to integration.
    In the AI pipeline, workstreams are often divided up into different teams, and every step is intricate and detailed. Automating the entire pipeline might be troublesome because of the various tools, requirements, and even languages involved.
    Development teams should identify the processes which can easily be automated. Data analysis workstreams can use scripts to move and validate data and report on the quality of the data and consistencies. When it comes to the release process, the AI pipeline can be integrated for seamless deployment. Operational and performance metrics should be automated with capture and store model inputs and outputs and subsequent model retraining cycles.

    Trained And Experienced Teams

    AI, data science, and DevOps processes are only as good as the team using them. Before you consider bringing these elements together and reaping the benefits, you need to ensure your team is trained and experienced enough for the task.
    At TSG Training, we offer training solutions for both AI and DevOps to help your business make the most of its technologies. Our BCS Foundation Course In AI is perfect for those who are new to Artificial Intelligence. Software developers wanting to build AI applications can benefit from our Designing and Implementing an Azure AI Solution training course.
    If AI skills are already ripe in your business, then your team could benefit from DevOps training. Our SAFe DevOps Certification course takes a deep dive into the world of DevOps and the competencies needed for these projects.
    For a full introduction to the principles and practices of the methodology, the SRE Foundation course could be a good option. Our classes are available either online or in classroom learning and include lifetime support from a dedicated tutor. For more information, contact TSG Training today.

  • 10 Reasons Why Every Business Needs A DevOps Strategy

    DevOps works to combine software development and IT operations to successfully deliver new applications. Almost every company can benefit from becoming more DevOps driven, and now is the time for businesses to focus on staying competitive and cyber secure.
    An effective DevOps strategy encourages collaboration and ownership during the software development process, resulting in reduced time to market, lower failure rates, and less time spent on invaluable tasks. With our DevOps training courses, we have worked with many businesses and have seen the benefits they’ve had through a DevOps strategy and here are the ten more popular reasons why every business needs to adopt a DevOps strategy.

    ·Deliver Real-Time Responses To Threats And Opportunities

    Developers are having to compete with tighter windows for time-to-market than ever before. On top of this is the need to respond to cyber threats immediately, with many attackers targeting cybersecurity monitoring platforms. It is obvious that IT processes need to deliver responses to threats in real-time, and DevOps can help with this.
    With a DevOps approach, software development and updates can be completed faster than the competition, bringing new customer opportunities. Any company that is willing to embrace DevOps will improve their strength against competitors and handle threats and opportunities immediately.

    ·Improve Traceability, Visibility, And Scale In IT Operations

    DevOps brings consistency to the development lifecycle and cuts down on the risk of code changes impacting production. Poorly planned IT changes cause the majority of unplanned outages, and DevOps can protect against this. With DevOps strategies in place, your IT operations will improve their traceability, visibility, and scale.

    ·Speed Up Application Cycle Times

    Software lifecycles can be made significantly faster with a DevOps approach. This leads to a faster time to market, improved customer service, and lower development costs. Some of the key pillars of DevOps are collaboration and automation, which help speed up processes.

    ·Reduce Bugs Before Release

    With a DevOps approach, software is tested and analysed at every stage. This helps to catch bugs and faults in the code which could otherwise go undetected until after release. There are so many benefits to using DevOps to reduce code bugs, such as cutting down the cost of customer service, eliminating the need for code patches, and avoiding swapping out applications entirely.
    The various iterations of a DevOps approach mean that issues can be removed from a codebase quickly and easily before they become a real concern.

    ·Quantify Financial Contributions Over Time

    With some investments in software development, it is nearly impossible to track and quantify their return and success. Breaking down DevOps strategies means it is possible to produce a roadmap to value which is driven by metrics and quantifies financial contributions.
    When you can accurately understand your financial-based metrics, you can optimise staff, decrease expenses, and increase sales.

    ·Improve Collaboration Across Teams

    DevOps is all about collaboration and encouraging communication among all teams in the company. Development, IT operations, sales, finance, and management will all be on the same page when a DevOps strategy is in place. This approach can close the gap between different departments, which can help to avoid costly mistakes.
    For example, finance teams may need to understand the average cost variances of software under development, and knowing this information can show the direct impact it has on business profitability.

    ·Monitor KPIs and Risk-Based Metrics

    Organisations that use DevOps can better monitor their KPIs and risk-based metrics, gaining improved visibility to the true causes of risks to revenue. Far too often, businesses lose sales, customers, and accounts because sales and service teams are not aware of a problem right away.
    DevOps can help businesses alert all teams to key pricing, quoting, and revenue metrics, which could potentially retain customers, highlight a product issue or rescue a sale.

    ·Eliminate Roadblocks To Connected, Smart Products

    One of the biggest uses of DevOps is to create smart, connected products across all industries. Applications that are connected, smart, and deliver product-as-a-service revenue are in extremely high demand.
    Developing these products is not always easy, but DevOps can help to eliminate some of the most common roadblocks that engineers find along the way.

    ·Fuel New Product Ideas And Drive Revenue Growth

    With a DevOps strategy, product teams are able to see more growth opportunities for every customer experience. These kinds of insights can fuel ideas for new products or features and ultimately drive revenue growth. DevOps gives manufacturing, engineering, sales, and marketing one unified customer viewpoint.
    This gives everyone in the organisation the insights they require to come up with new, innovative opportunities and expand product offerings.

    ·Increase Customer Loyalty And Value

    Utilising a DevOps framework can help to improve customer loyalty and increase Customer Lifetime Value (CLV). In addition to this, DevOps can provide businesses with the chance to digitally reinvent themselves. The trend for DevOps leaders going forward is service-oriented products and touchless sales, which are in high demand among consumers.
    The DevOps framework allows delivery of a complete customer experience with automated customer transactions and support.
    Many businesses struggle with a backlog of IT projects, and teams are lacking the time to get these done. Traditional waterfall methods for development are not quick enough to handle the pace, scale, and complexity of today’s demands. DevOps can solve these problems and bring many benefits to businesses of all shapes and sizes.
    If you are considering adopting a DevOps strategy for your organisation, your first port of call should be ensuring all team members are appropriately trained. At TSG Training, we offer DevOps training courses to help businesses adopt this framework for themselves.
    Our DevOps Foundation Certification Training course is an excellent introduction to the DevOps framework, with an emphasis on the collaboration, communication, integration, and automation of the methodology.
    For a complete overview of the principles and practices which enable DevOps development processes, try out SRE Foundation (SREF) course. For more information on our DevOps training options, contact our team.

  • Do Software Engineers Need To Know DevOps Too?

    There are many different people that make up a development team and so many job roles involved in the release of a software product. Generally, DevOps training and knowledge was reserved for developers and dedicated DevOps engineers, but now other professionals are increasingly needing to know the methodology.
    Software engineers are the latest profession to be thrown into the world of DevOps and for good reason.
    Almost every software engineering role is now requiring applicants to have DevOps experience and knowledge. These engineers are no longer just building the applications in question, but they are responsible for continuous integration, maintenance, and deployment.
    The understanding of DevOps methodology has to start with Continuous Integration, Continuous Delivery and Continuous Deployment, or CI/CD.

    What Is Continuous Integration (CI)?

    CI refers to the practice of integrating code changes from various contributors into an application automatically. In most developments, there are various engineers and developers merging their code into the master every single day.
    CI ensures there are automated checks in place to keep the code in a good working state. Prior to integrating new codes to the master, code formatters, unit tests, and code linters should be run.
    CI pipelines work to automate this whole process instead of having to rely on developers to use these tools manually. Using Continuous Integration pipelines, you can prevent bad code from being integrated into the application.
    A CI pipeline should be very fast, which requires pipeline jobs to be run alongside one another with a fast test suite. As well as timely, CI pipelines must also be extremely reliable. If a section of code is broken, software engineers must be on hand to resolve it immediately because one build failure will block all new merge requests from completing.
    With a successful CI pipeline set up, development teams can commit to the master branch every day, sometimes even multiple times a day if necessary. It eliminates the need for lengthy feature branches waiting to eventually be merged together.

    What Is Continuous Delivery And Continuous Deployment (CD)?

    CD stands for Continuous Delivery and Continuous Deployment, but these two terms do have some slight differences to be aware of. Continuous Delivery is the result of creating a build with a CI pipeline, and it happens naturally in the process. The build artefact becomes a working version of the application, which can then be deployed to a specific environment.
    With this strategy, an application is ready to be deployed at any time. Software engineers can then choose when they deploy, whether that be daily, weekly, or monthly. With Continuous Delivery, the software is ready to deploy at any time, but manual interaction is needed to start the deployment process.
    With Continuous Deployment, the process is taken one step further, and the deployment process is automated with the CI pipeline. This means that the deployment process will start without human interaction as soon as the new code is merged with the master branch.
    With CD, software developers can see their working code in production right after merging. With automated checks in place in the CI pipeline, any failed code will be blocked and prevented from being released to production.
    Organisations can choose between Continuous Delivery and Continuous Deployment, and the right option for your applications will depend on your team and processes. The goal for both strategies is to deliver software products to customers as frequently and quickly as possible.
    Both these options take away a lot of the risk of human error, as even with a continuous delivery method, the application should have the ability to be deployed with a single button.

    Deployment Strategies For DevOps

    With a CI/CD pipeline, software engineers are required to be very involved in the DevOps process. There are various deployment strategies that can be used:

    • Canary Deployment

    With this strategy, the first release of a new software version is delivered only to a small subset of users. This gives software engineers the opportunity to ensure the changes are functioning properly for these users. Once satisfied, the update can be rolled out to all users. Canary deployment is generally considered a cautious option for code release as changes are applied gradually.

    ·Blue/Green Deployment

    Blue/green deployment is a popular method for software engineers, and it involves using two production environments. One is actively used for the productions and has the most up to date versions of the software. The second has no traffic sent to it and is essentially on standby.
    When the new application is deployed, it is done so to the standby environment, and then all traffic is routed here. The old production environment will now become the standby environment and receives no traffic. With this method, it is easy to roll back releases if necessary.

    ·Rolling Blue/Green Deployment

    Similar to blue/green deployment is rolling blue/green deployment. This is often used when multiple instances of the software are running simultaneously in the same environment. This could be the case if you have four nodes used for production, and then you swap out the first one with another, which is running an updated version of the software.
    You would then have three nodes with the old application and one with the new, and you continue this process until all nodes are running the latest version.
    Because of the rolling nature of this deployment, it is less risky than other options; however, it is also more time-consuming for a full release.
    Ultimately, it is clear that software engineers need to know DevOps in the same way that software developers do. Entire teams should be knowledgeable about CI/CD practices and approaches and understand how to use these appropriately.
    Keeping software engineers in the loop with DevOps will increase productivity and cut back on application errors. We offer a range of DevOps training courses to help software engineers and developers stay up to date with the methodology.
    Choose from our SAFe DevOps Certification, DevOps Foundation Certification Training, or SRE Foundation (SREF). For advice and guidance on the best course for you or your team, contact us today.

  • Key Steps For Transforming Your DevOps Team Into A DevSecOps Force

    For years, businesses have been focusing on building and investing in a powerful DevOps team. These teams are well-oiled machines for deploying new applications and ensuring they go off without a hitch.
    Now, the world is changing once again, and companies are looking to transform their DevOps teams into DevSecOps forces.
    The security of enterprises has been under the microscope for the last year, and cybercriminals are becoming more complex and finding new opportunities to attack. This has put more pressure on software teams to ensure their code is as secure as possible in order to reduce the risk to themselves and their customers. If you’re looking to increase security, transforming your DevOps team into a DevSecOps force can be a fantastic starting point.

    What Is DevSecOps?

    DevSecOps is a term that we are seeing more and more frequently, and it stands for development, security, and operations. It is a business approach to automation, culture, and application design, where security is a key consideration throughout the entire lifecycle.
    This approach is beginning to overtake traditional DevOps strategies, and there are some key differences to be aware of. DevOps focuses solely on development and operation teams within the process, but in today’s climate, IT security needs to be integrated into this approach.
    The role of IT security has often been considered a standalone responsibility, isolated to one team who get involved during the final development stages. With a DevOps approach, development cycles are rapid and frequent, and dated security practices can potentially impact the entire project.
    DevSecOps has come about as a method to combat this and emphasise the importance of focusing on security at every stage of the DevOps process.

    How To Transform A DevOps Team To A DevSecOps Force?

    If your team have been working with a DevOps approach, you might be considering incorporating security into this mix. Here are a few key steps to transform your DevOps team into a DevSecOps force:

    Secure Your Pipeline Configuration

    The more resources a pipeline has access to, the higher the increase of a security problem arising. This could be proprietary code, databases, or something else entirely, and a Continuous Integration and Continuous Deployment (CI/CD) approach are necessary for ensuring security. Adopting a CI/CD configuration for your pipeline will lessen the risk of security breaches.
    Begin by securely storing any methods or secrets you have for connecting your pipeline to third-party services and pipelines. Encrypted-at-rest variables are a popular option for this kind of security, as are ‘contexts’ features.
    Contexts can provide access to specific variables across the pipeline and restrict to specific team members if necessary.
     
    For sensitive information such as code signing keys, you need an extra layer of security. Store these in encrypted files and keep the decryption key in your contexts or variables. Some systems allow for codes to be injected from another secure system when they are needed instead of decrypting within the CI/CD pipeline. This setup makes it even more challenging for sensitive information to be leaked or breached.

    Analyse Code And Git History

    Having the ability to look through complete project history at the touch of a button using git is so important during the development stages. However, this also leaves sensitive information within the git history, which is an area that cybercriminals are commonly attacking.
    There are various tools available that can help your teams to identify secrets that are now in the codebase and can be deactivated in the git history. These development tools can also work to scan through your git and code history for sensitive data that might have been placed in the repository previously.
    After ensuring your git history doesn’t contain any secrets or access points, the next stage is ensuring the current revision of the application doesn’t have any vulnerable aspects. Appropriate security testing must be used to look through the software and highlight any issues before you proceed to deployment.
    Dynamic Application Security Testing (DAST) techniques are a reliable option for this as they can create a copy of your production environment within your CI pipeline to scan every executable.

    Put A Security Policy In Place

    Checking every single security aspect from known vulnerabilities is simply not an option. Some will be specific to your business and must be implemented as security policies. For most organisations, these exist as either manual or automated compliance checks.
    Manual tasks such as ensuring onboarding and offboarding processes are synced, and reviewing account access settings, should be performed on a regular basis.
    Some security tasks are very easy to automate, and there are many third-party services that can code rules which work to your unique CI pipeline. Some applications provide options for proving compliance with the relevant regulations governing your data. In the event of a mismatch, your build will fail on security grounds.
    The most valuable asset to any development is the security research team. They know your application inside and out and are constantly working on them. Provide your team with a specific process for reporting any security issues as they arise, and set specific timelines for resolving these. Make it as easy as possible for staff to report problems and celebrate those that do.
    Transforming your DevOps team to a DevSecOps force will bring many benefits to your business, but your operation will only be as strong as your team’s knowledge.
    At TSG Training, we provide various training courses for DevOps and security. Our SAFe DevOps Certification course is a popular option for businesses that want to enhance their team’s knowledge of DevOps competencies.
    For team members with limited DevOps experience, our DevOps Foundation Certification Training is a perfect choice. It is a complete introduction to the methodology and emphasises the importance of communication, collaboration, integration, and automation in application development.
    If you are unsure of the right training approach for you and your team, speak with our experts at TSG Training today.