devopsy.kinsta.cloud

Category: Cloud Management

  • CloudBees Unfurls Dual CI/CD Strategy at DevOps World Event

    CloudBees Unfurls Dual CI/CD Strategy at DevOps World Event

    During a DevOps World event, CloudBees took the wraps off the first major update to the open source Jenkins continuous integration/continuous delivery (CI/CD) platform made in the past several years.

    At the same time, the company also unveiled a proprietary DevSecOps platform based on Kubernetes that is optimized for building and deploying cloud-native applications based on portable Tekton pipelines.

    Shawn Ahmed, chief product officer for CloudBees, said the updates to Jenkins make it possible to horizontally scale Jenkins controllers while at the same time ensuring high availability. The latest update also provides a workspace caching mechanism to simplify sharing them across multiple jobs in a way that significantly reduces the amount of compute and storage resources consumed, he added.

    CloudBees also added a Baseline capability to the Jenkins repository to improve startup times without causing build storms.
    Collectively, those capabilities will increase the number of jobs that can be simultaneously executed to improve overall productivity, said Ahmed.

    CloudBees has also added a Pipeline Explorer tool in the cloud-based edition of Jenkins that enables DevOps teams to visually debug and troubleshoot pipeline jobs. That tool will also provide the foundations for self-healing and artificial intelligence (AI) capabilities that CloudBees plans to add to the Jenkins platform later this year and into 2024, added Ahmed. For example, AI tools will surface suggestions on how to fix a problem in a pipeline, he noted.

    The DevSecOps platform, meanwhile, leverages Tekton pipelines to provide DevOps teams with more granular control over how pipelines can be orchestrated, said Ahmed. It also provides access to GitHub Actions-style domain-specific language (DSL), support for feature flagging, security, compliance, pipeline orchestration capabilities, analytics and value stream management (VSM) tools that can be deployed by an internal IT team or accessed via a single or multi-tenant managed cloud service.

    Those built-in capabilities will make it simpler for platform engineering teams to centrally manage building and deployment of cloud-native applications by enabling developers to self-service their own engineering requirements via an internal developer platform (IDP), said Ahmed. The overall goal is to provide a more integrated approach that breaks down software engineering silos that exist in many existing DevOps workflows, said Ahmed.

    Each DevOps team will need to decide for themselves to what degree to move forward using Jenkins to build and deploy applications versus opting for a more modern alternative in the form of the DevSecOps platform. CloudBees, however, is committed to providing plug-ins and integrations across both platforms to enable DevOps teams to protect their investment in existing tooling, noted Ahmed.

    The status of Jenkins X, an open source CI/CD platform based on Kubernetes that CloudBees previously donated to the Cloud Delivery Foundation (CDF), is not immediately clear. Regardless of the approach, however, there is a clear opportunity to revamp DevOps workflows by upgrading Jenkins or switching to a more modern platform such as DevSecOps. The challenge, as always, is determining the pace at which any such transition might be made.

  • Broadcom Survey Surfaces Drive to Consolidate Automation Platforms

    Broadcom Survey Surfaces Drive to Consolidate Automation Platforms

    Broadcom this week published a global survey of 535 IT leaders that found more than three-quarters (78%) are moving to consolidate cloud automation tools and platforms. However, thus far, only 8% of respondents said they had completed that effort.

    Overall, the survey also found more than 81% already have multiple cloud automation solutions in place, and 70% noted this issue had created significant challenges, including increasing time to automate (59%), time to report (52%) and time to remediation (52%) and higher costs (49%). In addition, 46% noted it’s more difficult to troubleshoot IT environments, while 41% noted multiple tools increase compliance risks.

    IT teams also find that having multiple automation tools slows down software delivery (37%) and contributes to the over-provisioning of IT environments (32%).

    Aline Gerew, head of automation for the Agile Operations Division at Broadcom, said the multiple islands of automation that have evolved on various cloud computing platforms now need to be centralized to reduce the current level of friction in the cloud. Those efforts need to start with platforms capable of unifying observability across all the platforms employed, she added.

    The amount of consolidation that any IT organization can implement depends on the amount of political capital they have. In many cases, the applications and associated automation tools running in any given environment have been adopted by a department or business unit that exercises a lot of autonomy regarding IT. The issue that creates is multiple tools and platforms increase the total cost of IT. At a time when many organizations are experiencing economic headwinds, the need to reduce the total cost of IT naturally becomes a more pressing concern.

    Rather than consolidate automation tools and platforms, the simpler option is to deploy an automation framework that is designed to be integrated with the various tools and platforms that are already in place, noted Gerew. That approach enables automation to be applied at much higher levels of scale to reduce costs without forcing every arm of an organization to standardize on the same tools and platform, she noted.

    The survey found that, when it comes to cloud automation, the most important consideration factors are operational costs (62%), performance (53%) and operational efficiency (49%).

    Responsibility for cloud automation will naturally vary from one organization to the next, but the survey noted that 67% of respondents currently have a cloud architect on staff and another 33% are planning to hire one.

    That role is increasingly required as organizations find themselves managing a wide range of cloud computing environments, including software-as-a-service applications (57%), legacy applications that have been lifted into the cloud (56%), new cloud-native applications (46%) and legacy applications that have been refactored for the cloud (41%).

    It’s apparent that cloud computing environments are becoming more complex with each passing day. There may come a day when artificial intelligence (AI) helps reduce the level of complexity; in the meantime, IT organizations need to find ways to streamline the management of cloud computing environments. Today, those environments are made up of applications based on a wide range of increasingly divergent architectures as the rate of application deployments exceeds the retirement of legacy apps.

  • Cisco Aligns With Nutanix on Hybrid Cloud Computing

    Cisco Aligns With Nutanix on Hybrid Cloud Computing

    Cisco and Nutanix this week announced a strategic partnership through which the two companies will collaborate to advance hybrid cloud computing.

    As part of that agreement, Cisco is committing to making AHV virtual machine software from Nutanix available from the edge to the cloud, starting with the Cisco Unified Compute Systems (UCS) rack and, soon after, blade servers.

    Jeremy Foster, senior vice president and general manager of Cisco Compute, said via a software-as-a-service (SaaS) platform, Cisco will be able to centrally manage virtual machines from Nutanix alongside the other major virtual machines it already supports.

    In addition, the partnership will enable Cisco to apply multiple forms of artificial intelligence (AI) across a hybrid cloud computing environment, he added.

    Thomas Cornely, senior vice president of product management for Nutanix, said the goal is to provide IT teams with an opportunity to consolidate infrastructure across a hybrid cloud computing environment. In effect, Nutanix and Cisco are working toward converging the control planes across their entire respective portfolios, he added.

    The goal is to enable IT teams to streamline the number of platforms that need to be supported as part of an effort to reduce the total cost of IT, said Cornely.

    The issue that IT organizations regularly encounter is that each platform requires hiring additional IT personnel to manage. At a time when many organizations are encountering economic headwinds, there is a natural inclination to reduce the number of platforms as the size of the IT staff is reduced. Despite advances in automation, IT labor costs still represent the largest overall segment of any IT budget.

    It’s not clear how aggressively IT teams are consolidating IT infrastructure to reduce costs, but after more than a decade of continuous investments in IT, many organizations are discovering they are supporting a wide range of platforms. During a downturn, however, IT teams tend to more aggressively eliminate “snowflake” platforms that require unique skillsets to manage, noted Cornely.

    In the meantime, IT environments are also becoming more distributed as more workloads move to the network edge. Those workloads are not replacing applications running in on-premises or cloud computing environments, so the overall IT footprint will continue to increase. Given the chronic shortage of IT skills, the only way to effectively manage that IT estate will be to rely more on automation frameworks increasingly infused with AI.

    Each IT organization will need to determine for itself what level of automation to embrace, but Cisco is betting most will opt to rely on a SaaS platform provided by a vendor versus building and maintaining an IT management platform themselves. Regardless, legacy approaches that depend heavily on manual processes will increasingly give way to cloud-based platforms that can more easily manage workloads wherever they happen to be deployed.

    The issue now, as always, is funding the transition to new platforms to bring the total cost of IT back under control and eventually pay for themselves.

  • How Platform Engineering Can Drive Digital Sobriety

    How Platform Engineering Can Drive Digital Sobriety

    If we’re being honest, the “green issue” currently isn’t the priority it needs to be for a lot of companies. At best, they are ticking the box marked ‘sustainability’ and paying lip service to a trendy topic. At worst, they are engaging in nothing more than greenwashing.

    Considering carbon emissions from cloud computing have now overtaken those from commercial aviation, this is disheartening for the IT sector. Unsurprisingly, most of these emissions come from inefficient use of the cloud due to overly complex processes and a lack of centralized oversight over cloud infrastructures. And if “emissions” sounds a bit vague, here’s a translation into dollars–$147 billion was wasted in 2022 in cloud spend.

    So, when it comes to reducing an organization’s cloud carbon footprint, there is clearly a financial incentive. Even for those who don’t believe in individual responsibility or worse, simply don’t care what kind of world we’ll leave future (and some present) humans to live in, there is money to be saved.

    The truth is that companies need to put sustainability first across the whole enterprise, and they need to do it now.

    A New Kind of Business

    Tackling departments one-by-one or singling out individual processes to make them more sustainable is not going to work. What organizations need is to stop thinking of sustainability as an afterthought and start incorporating it in the decision-making process from the get-go, maybe even as part of their very business model.

    This is the sort of business that places its people and the planet above profits. Progressive, modern companies that want to stay in business longer need to invest in their people and take care of the planet instead of chasing endless growth and ever-increasing profit because that, simply put, cannot last.

    As a culture, we’re currently at a turning point–late-stage capitalism is running its course, and more people are realizing that constant growth at the expense of well-being and the planet’s dwindling resources is not sustainable (in all senses of the word).

    For this to work, it’s about looking at business through a new prism.

    Driving Digital Sustainability From the Ground Up

    It’s not too late for businesses to become more sustainable. In fact, it is the best time to make life-saving changes. When it comes to tech specifically, there are a couple of things you can do, starting with two key things that need to change.

    First, cloud waste has been costing companies billions of dollars for years now. Organizations are set to spend nearly $600 billion on the cloud in 2023, but it seems that most people are still in the dark about the real environmental impact of cloud usage. As with most big corporate changes, it’s all about a change of mindset. We need to accelerate awareness and promote digital sobriety to inspire transformation and decision-making with GreenOps on the enterprise level.

    A cloud-first approach has long been the holy grail of IT. However, what we couldn’t anticipate is the sheer volume of resource usage and complexity that comes with it. We simply do not have the planetary resources to support this growth much longer. It’s time to become smarter, leaner and more environmentally conscious by using the “consume better” approach.

    Second, think about the KPIs. Change without success parameters will not work. While organizations have a key role in decreasing global cloud spend, they must have the right tools and references. They need to be able to assess the environmental impact of their digital choices at all decision levels.

    For the IT sector, this is where platform engineering comes into play. An internal developer platform can act as the critical piece that connects DevX, deployments, governance, security and observability.

    With green best practices and cloud carbon footprint visibility at every stage–from the dev deploying a new environment on the cloud to the CFO checking the monthly cloud bill–a platform engineering approach ensures not only organizational but also individual responsibility. When all tools are accessible and processes transparent, nothing gets lost in translation. This means less room for error and cloud waste.

    Ultimately, it’s About Consuming Better and Consuming Less

    Right now, these KPIs will be financially motivated, and rightly so. But there will come a time when progressive organizations will put their environmental impact at the forefront of their mission statement.

    The B-Corp certification, which evaluates companies in terms of their social and environmental performance, grew 63% in 2022. This shows the trend toward moving to a more inclusive and sustainable economy. Partly because it’s in the interest of the businesses’ long-term success and reducing costs, but partly because it is simply the right thing to do.

  • IBM to Provide Hybrid Cloud Service Based on VMware Cloud

    IBM to Provide Hybrid Cloud Service Based on VMware Cloud

    At the VMware Explore 2023 conference this week, IBM announced that it will soon provide a fully managed service based on a streamlined edition of VMware Cloud.

    Brendan Kinkade, vice president for independent software vendors, technology and hybrid cloud partnerships for IBM Global Sales, said VMware is now making available editions of VMware Cloud that are both easier to deploy and manage and, just as importantly, migrate between cloud platforms and on-premises environments as IT teams see fit.

    IBM is committed to using that platform to deliver a managed VMware Cloud service that will span hybrid cloud computing environments aligned to an NIST-validated framework, he added. That approach is critical because it will enable IT teams to apply VMware license credits to any instance of VMware Cloud no matter where it is deployed, noted Kinkade.

    In addition, the streamlined edition of VMware Cloud doesn’t use proprietary application programming interfaces (APIs) to make it simpler to port IT environments to another cloud service or back to an on-premises IT environment whenever necessary, he added.

    At the foundation of the hybrid cloud service will be an instance of a multi-tenant vCloud Director console residing on the IBM Cloud. Through the console, IT teams will be able to work with IBM to co-manage application environments.

    In addition, IBM is providing a managed IBM Cloud Cyber Recovery (ICCR) Service to better secure cloud computing environments.

    It’s not clear how much of IT is now being consumed as a managed service, but the COVID-19 pandemic has certainly increased that number. Many IT organizations are also finding it simpler to rely on a managed services provider (MSP) to manage infrastructure so they can focus more of their time and effort on application development, noted Kinkade.

    MSPs are also in a better position to aggregate all the telemetry data needed to train artificial intelligence (AI) models that will be used to automate workflows, he added.

    Exactly how DevOps workflows will evolve as organizations rely more on external service providers to manage IT infrastructure is, naturally, a work in progress within many organizations. The main challenge is aligning a unique set of continuous delivery (CD) practices for deploying and updating applications with a provider that has already defined its own workflows.

    Nevertheless, given the complexity of those environments, many organizations are not able to hire and retain the IT expertise required to manage it, so the only option may be to rely on an MSP.

    Each IT organization will need to decide whether to rely on an MSP, given the total cost of a service. Many organizations often wind up having a mix of workloads managed by internal IT teams and external service providers. The one thing that is certain is that as the pace at which workloads are being deployed in the cloud increases, many internal IT teams are overwhelmed by a level of complexity that will only increase.

  • VMware Looks to GitOps to Drive Edge Computing

    VMware Looks to GitOps to Drive Edge Computing

    At its VMware Explore 2023 event, VMware today unveiled an orchestration tool, dubbed VMware Edge, that promises to simplify the management of edge computing services at scale.

    At the same time, VMware has launched a Project Keswick initiative through which it will work with customers to define additional use cases for VMware Edge based on zero-trust principles and GitOps workflows for deploying applications. The company also unveiled a VMware Retail Edge platform based on VMware Edge and is planning to add additional offerings aimed at specific vertical industry segments.

    Finally, VMware is making available a managed connectivity service through which it will provide private 4G/5G wireless services.

    VMware Edge Cloud Orchestrator is based on a tool that VMware created to orchestrate the management of its secure access service edge (SASE) platform. That has now been extended to support a wider range of software running on edge computing platforms.

    Sanjay Uppal, senior vice president and general manager of service provider and edge for VMware, said the goal is to streamline the management of software-defined edge computing platforms via a single console. Achieving that goal requires the ability to identify and programmatically manage workloads distributed across a mix of networks, he added.

    VMware is betting that as more workloads are distributed to edge computing platforms, there will be a greater need to centralize the management of workloads running on platforms that are not always easy to physically access. Less clear, however, is to what degree those edge computing platforms will be managed by IT teams versus operational technology (OT) teams that are usually embedded within a department that manages a specific business process.

    However, regardless of who manages those platforms, they will be relying more on GitOps workflows to programmatically provision infrastructure and deploy applications that will need to be regularly updated. In fact, because these platforms are often dispersed across hundreds of physical locations, the need for a pull-based orchestration tool that works asynchronously is critical, said Uppal.

    In the longer term, IT teams should also expect artificial intelligence (AI) capabilities to be applied in a way that makes edge computing self-healing, he added.

    No one can say exactly how many organizations have adopted GitOps to manage the provisioning of both infrastructure and the delivery of applications, but it’s conceivable that edge computing will force the issue. The tricky part will be finding a way to manage those GitOps workflows at the necessary level of scale. Most DevOps teams already struggle with implementing DevOps workflows at scale, so if more workloads are to be distributed across hundreds of edge computing platforms, there will be a much more acute need for automation to consistently deploy, secure and update applications.

    Regardless of approach, however, there may come a day when the number of workloads deployed at the edge far outnumbers the number of workloads deployed in the cloud or in a data center. The challenge and the opportunity now is to get ahead of edge computing issues before they inevitably create a set of management issues that will be more difficult to address after applications have already been deployed.

  • VMware Looks to Streamline Multi-Cloud Computing Management

    VMware Looks to Streamline Multi-Cloud Computing Management

    VMware today integrated its console for managing cloud instances with its VMware Cloud Foundation to streamline the deployment of its software in on-premises IT environments.

    Announced at the VMware Explore 2023 conference, the latest edition of VMware Cloud will make it simpler to manage multi-cloud computing environments by combining VMware Cloud Foundation Software and VMware Cloud Services into a single platform.

    VMware also announced early access to an ESXi life cycle management cloud service for VMware vSphere+ that enables IT teams to centrally manage upgrades across a distributed vCenter environment. Additional updates to vSphere in the upcoming release include doubling GPU capacity per virtual machine.

    Krish Prasad, senior vice president and general manager for cloud infrastructure at VMware, said the goal is to improve the overall pace of innovation;  in addition to deploying workloads in on-premises IT environments, organizations are also deploying workloads on multiple cloud computing services.

    VMware Cloud is being made available in five editions that can either be managed by an internal IT team, an external services provider or by VMware. In addition, a VMware Ransomware Recovery service based on VMware Cloud is also generally available. Following a breach of an on-premises IT environment, VMware Ransomware Recovery will enable organizations to run production workloads in the cloud until forensics are completed. The company also unveiled a technology preview of cybersecure storage that will integrate recovery workflows with native vSAN snapshots and add support for Google Cloud VMware Engine.

    In addition, VMware is adding a managed NSX service delivered via the cloud, dubbed NSX+, that manages instances of the virtual networking software that runs on top of its virtual machine software. There is also now an NSX+ virtual private clouds (VPCs) option that isolates instances of the virtual networking platform.

    Finally, VMware is adding a VMware Cloud with VMware vSAN Max, which will make 8.6 petabytes of disaggregated capacity and 3.6 million IOPS per cluster available on demand later this year.

    VMware appears to be streamlining the number of platforms IT teams need to acquire to support and manage IT infrastructure at a time when more organizations are trying to navigate increasing economic headwinds.

    One way or another, IT teams will need to reduce the cost of IT at a time when IT environments are becoming more complex. VMware is betting that, given its dominance in on-premises IT environments, there will be a natural inclination to deploy more of its software in the cloud to create a more homogenous IT environment that is less complex.

    However, it’s not clear whether organizations are willing to pay extra for the privilege. Many organizations are now supporting multiple classes of virtual machines and associated software despite the fact that each additional platform raises the total cost of IT.

    In the meantime, many IT organizations are also awaiting the outcome of Broadcom’s effort to acquire VMware before deciding how to centralize the management of multi-cloud computing environments.

  • DevOps Download: What to Know About Life in the Cloud(s)

    DevOps Download: What to Know About Life in the Cloud(s)

    According to the 2022 Flexera State of the Cloud Report, 89% of cloud customers now use multiple cloud hosting providers. Nearly nine out of 10 might sound high, but it tracks with the anecdotal evidence we’ve seen. For varied and good reasons, companies are spreading their usage across multiple hyperscalers rather than putting all their eggs in one basket.

    In this article, I’ll take a look at what life in the cloud(s) looks like today. Along the way, I’ll examine the value that companies and their DevOps teams can derive from this approach, the challenges to be aware of, use cases for making the multi-cloud move and more.

    What is Multi-Cloud?

    Multi-cloud is a type of cloud strategy approach where an organization uses computing services from at least two cloud providers to run their applications. Instead of a single-cloud stack, these environments include two or more public or private clouds, or a combination of both. With multi-cloud, you can have an application running on Google Cloud Platform (GCP), another in Amazon Web Services (AWS), and maybe one on premise for hard-to-move applications.

    There are three kinds of cloud setups. Single cloud is when workloads run solely on one environment. Hybrid cloud entails overlapping workloads across multiple clouds, such as operating the same programs on different providers for business continuity purposes. The final setup is planned multi-cloud, which disperses applications and usage across providers along specific lines, like having compute intensive applications with one provider and data analysis applications with another.

    Got a Preference?

    Make no mistake, using multiple cloud providers is more complex than a single host, but as its popularity shows, the benefits can carry more weight. Foremost, that’s because an organization gains the flexibility to create a best of all worlds situation, based on factors like the following:

    • Operational preference: Users may like different features from different providers, and splitting types of use can yield the ideal setup. For instance, a customer may run compute on AWS but want their business intelligence and machine learning on GCP. In this deployment, the front-end app could gather the needed information, then send the data to the other provider for analysis and ML.
    • Regulatory requirements: Certain workloads may require data storage in specific regions, but not all cloud vendors have multiple “regions” in each country. Companies that want to use the cloud can set up a “multi-region” environment by having one region on AWS and a second region on GCP within the same country.
    • Cost savings: Cloud providers offer different savings plans. For a savvy user, structuring a flexible program can take advantage of each to significantly reduce costs. It’s also a great way to avoid the pitfalls of lock-in and can make it easier to go elsewhere should a provider lose your trust.
    • Failsafe Options: Outages happen, so companies needing 24/7 access to apps will sometimes run portions redundantly on two hosts to ensure smooth operations. For example, a retail app may run on GCP and AWS with live failover between them. That way, if one goes down the other can kick in without noticeable downtime.

    Not Without its Challenges

    The benefits to running a multi-cloud setup are clear, but there are some challenges as well. A carefully planned multi-cloud setup can save money, but a careless approach will duplicate operations and cost. It also leaves companies vulnerable to mistakes that can lead to significant overrun, especially for hybrid cloud operations, which can be extremely complex. Specialists must be well versed in FinOps principles and experienced at writing modern applications that can scale and work across regions and clouds, to ensure success in a multicloud approach.

    Coming to Terms

    You’ll undoubtedly come across a lot of new ideas and terminology when researching cloud setups. Here’s a few of the more crucial ones to become familiar with as you plan strategy.

    • Lift and shift: This refers to cloud-to-cloud migration, in other words, taking what you have in one cloud and putting it in another, whether it is private to public or public to public.
    • Move and improve: This usually refers to migrating while making a small change to take advantage of a public cloud feature. For instance, you could be using open source Kubernetes on premise but want to move to a managed version. Eliminating management of Kubernetes would require a minor change but it improves operations greatly.
    • Cloudbursting: On premise offers hard limits to capacity. For companies able to anticipate business peaks, cloudbursting can scale workloads to an on-demand public cloud for a short period. For example, a retailer who operates on premise may cloudburst on Black Friday in order to handle a volume increase.
    • High Availability: The goal of this is to eliminate single points of failure by enabling users to continue working even if one of the IT components that an applications depends upon fails.
    • Disaster Recovery: Clouds offer solutions to help an organization restore critical systems and data after a disaster strikes. Recovery comes in three “heat levels”: Cold is for data backup only, warm restores operations in several hours, hot is for near-instant resumption of cloud operations.

    People and Processes

    The most important considerations for operationalizing multi-cloud are people and processes. Providers pump out new services fast, and not only can it be difficult for staff to keep up, it can be demoralizing when they’re unable to. Allowing time to succeed, fail and learn is key, and larger companies might consider designated specialists for each platform.

    When it comes to processes, management and security are highly customizable, but it requires deep knowledge to get them right. Operating via infrastructure as code rather than ClickOps is a must. The latter is a time consuming approach that requires selecting options in a provider menu and introduces both operational and security risks in the form of configuration drift.

    Life in the Clouds

    Multi-cloud brings strong benefits to DevOps. Organizations can get the right infrastructure balance based on their needs. Distributing workloads can reduce the impact of outages and bolster resiliency. There’s greater opportunity for cost savings, and scaling is simple. Ultimately, multi-cloud operational enhancements can result in more reliable and innovative solutions, which delivers on the mantra of DevOps itself.

  • How New Tech Elevates Release Management’s Quality Standards

    How New Tech Elevates Release Management’s Quality Standards

    Release management is a critical discipline within software development and IT operations that focuses on the planning, scheduling, coordination and deployment of software releases. It includes the procedures, plans and methods employed to guarantee that software updates or items are sent to customers in a secure and effective way. Release management’s main objective is to make it possible for software releases to be delivered reliably and smoothly while causing as little disturbance as possible for the company and its users. This entails overseeing a release’s whole lifespan, from preliminary planning through testing, deployment and post-release support.

    Challenges in Traditional Release Management

    Traditional release management approaches often face several challenges that can hinder the efficient and effective delivery of software releases. These include manual and time-consuming processes, lack of visibility and traceability, complex and fragmented environments, limited collaboration and communication and a lack of effective communication channels and collaboration tools. Manual processes can be time-consuming, error-prone and lead to delays in release cycles. Lack of visibility and traceability can make it difficult to track the status of releases, identify bottlenecks and troubleshoot issues effectively. Fragmented environments can be complex and differ widely from one another, making managing and synchronizing these environments manually challenging and prone to errors.

    Limited collaboration and communication can lead to miscommunication, delays and misunderstandings. Traditional release management can lead to silos between development, operations and other stakeholders, hindering efficient coordination. Inconsistent release practices can lead to variations in processes, documentation and quality standards, making it difficult to establish a standardized and repeatable release process. Lack of automation and continuous integration can slow down the release process, increase the chances of human errors and inhibit the ability to deliver frequent, small and reliable releases. Limited scale and adaptability can be addressed by adopting new technology and modernizing release management practices. Automation, continuous integration, deployment pipelines, collaboration tools and standardized processes can help overcome these hurdles and enable more efficient, reliable and quality-driven release management.

    Benefits of New Technology in Release Management

    Advanced Testing Techniques for Improved Quality Assurance

    1. Enhanced speed and efficiency
    2. Improved interaction and collaboration
    3. Improved stability and quality of software
    4. Reduced risk and downtime

    Using New Technology: Implementation Techniques

    1. Organizational readiness assessment
    2. Choosing the correct technologies and tools
    3. Developing an all-inclusive release management strategy
    4. Embracing the DevOps and Agile principles

    The Impact of New Technology on Release Management Quality

    Automation: Accelerating Release Cycles and Ensuring Consistency

    Automation plays a pivotal role in release management by significantly accelerating release cycles. It reduces manual effort and expedites the delivery of software releases, leading to a faster time-to-market. Automated workflows enforce standardized practices, configurations and environments, resulting in more reliable and predictable releases. Automated testing frameworks and tools enable faster and more comprehensive testing, while continuous integration and automated build processes facilitate seamless integration of code changes. Automation also enables better visibility and traceability, allowing release management teams to track the progress of releases, identify bottlenecks and analyze performance metrics.

    Continuous Integration: Early Detection of Issues and Improved Collaboration

    Continuous integration has revolutionized software development practices by emphasizing early issue detection and enhanced collaboration. By regularly integrating their code, businesses can spot problems early and fix them, decreasing the possibility of significant issues later in the development cycle. Additionally, increased developer collaboration encourages better coordination, communication, and information sharing, which results in a more effective and unified development process.

    Organizations can profit from continuous integration by utilizing automated build processes, extensive test suites and a collaborative development environment. Early problem identification and enhanced teamwork not only lead to better software quality but also enable development teams to build applications more quickly and consistently. Organizations can achieve improved efficiency, productivity and success in the dynamic world of software development by adopting continuous integration as a core practice.

    The Role of Innovation in Breaking Barriers: Future Outlook and Trends

    Machine Learning and Artificial Intelligence in Release Management

    Release management is not an exception to the way that machine learning (ML) and artificial intelligence (AI) are transforming numerous sectors. Technologies based on machine learning and artificial intelligence (ML and AI) provide useful capabilities that can significantly improve release management procedures, increase effectiveness, and promote improved software quality. The function of ML and AI in release management is described in more detail below:

    Automated Testing and Quality Assurance:
    In release management, ML and AI may automate and enhance testing and quality assurance procedures. Intelligent algorithms can examine enormous amounts of data to find trends, anomalies and potential issues in brand-new software releases. To cut down on testing time and effort while maintaining high standards, ML models can be trained to anticipate and prioritize test cases. AI-driven testing solutions can also suggest the right test coverage and offer insights into the effects of code modifications.

    Predictive Analytics for Release Planning
    ML and AI approaches can be used to create prediction models for release planning using past release data, such as metrics, logs and performance statistics. These models are able to predict potential dangers, predict release dates, and allocate resources more efficiently. Release managers may prioritize important tasks, make data-driven decisions and improve the planning process for software releases by employing AI-driven insights.

    Anomaly Detection and Continuous Monitoring
    ML and AI algorithms can continuously monitor the production environment, analyzing real-time data to spot anomalies and potential problems. Release management teams can proactively identify and respond to performance bottlenecks, security breaches, and other key occurrences by putting in place sophisticated monitoring solutions. A faster and more reliable reaction to production issues can be achieved with the use of ML-powered anomaly detection, which can decrease the mean time to detect (MTTD) and mean time to resolve (MTTR).

    Impact Analysis and Risk Assessment for Releases
    ML and AI approaches can be used to evaluate the hazards that may be involved in a release. ML models can estimate the effect of a release on several areas like performance, stability and user experience by assessing historical data, code modifications, dependencies, and environmental factors. Release managers can prepare mitigation methods, make educated decisions, and reduce the likelihood of unforeseen problems throughout the release process thanks to these risk assessment skills.

    Intelligent Release Deployment and Rollback
    ML and AI technology can help with intelligently choosing when to deploy and roll back a release. In order to recommend deployment tactics, machine learning (ML) models can learn from previous deployment experiences, including success rates, user input and mistake patterns. In order to ensure a more dependable and error-resistant deployment process, AI algorithms can track the deployment process, evaluate the system’s health and initiate automated rollbacks if anomalies or severe concerns are discovered.

    In general, ML and AI provide valuable capabilities to release management, boosting testing and quality assurance, streamlining release planning, enabling continuous monitoring, analyzing release risks and simplifying wise deployment decisions. Utilizing these technologies enables businesses to improve software quality, streamline release management procedures, and deliver high-performing applications more effectively and reliably.

    Microservices Architecture and Cloud-Native Technologies
    With the advent of cloud-native technologies and the adoption of microservices architecture, release management has been transformed, enabling organizations to leverage the benefits of scalability, agility, and flexibility. Let’s explore how cloud-native technologies and microservices architecture enhance release management:

    Containerization and Orchestration
    Release management has a solid foundation thanks to cloud-native technologies like containerization (like Docker) and orchestration frameworks (like Kubernetes). Application components are encapsulated in containers, which makes them very portable and independent of the underlying infrastructure. Release management can use containerization to streamline application packaging and distribution while ensuring consistent application deployment across a variety of environments. Frameworks for orchestration allow for automated container deployment, scaling and administration, speeding up release management procedures.

    Scalability and Elasticity
    Applications can use cloud-native technologies’ inherent scalability and elasticity to dynamically modify resources in response to demand. The modular and independent services of the microservices architecture make granular scalability possible. Release management can use these features to scale individual services or components on their own, ensuring optimal resource usage and effective handling of increasing user loads. This adaptability reduces downtime and enhances the application’s general performance during releases.

    Fault Isolation and Resilience
    Failures in one service do not affect the entire system, thanks to the fault isolation and resilience that the microservices architecture fosters. Release management can use this resilience to lessen the impact of any potential issues during releases. It is possible to roll back or replace a specific service if it develops issues without affecting other services. Release management may efficiently manage errors, improve fault tolerance and maintain service availability during the release process by implementing cloud-native technologies and microservices.

    Observability and Monitoring
    The enhanced observability and monitoring capabilities made possible by cloud-native technology allow for release management. Platforms for container orchestration include integrated monitoring and logging capabilities that give information on the efficiency of an application’s use of resources and the state of the system overall. With the use of this information, release management teams can proactively monitor releases, spot abnormalities and quickly resolve problems. Observability and real-time monitoring support the release process by ensuring the dependability and stability of programs.

    Release management greatly benefits from cloud-native technologies and microservice architecture. Organizations can improve their dependability, achieve faster and more frequent releases, achieve scalability, fault isolation, and observability, and produce high-quality software applications by leveraging containerization, orchestration, CI/CD methods and many other technologies. Organizations are better equipped to manage complex release cycles and adjust to the changing needs of the software industry when they adopt these cutting-edge methods.

    Conclusion

    In this article, we have explored new technology’s role in raising the bar for release management quality standards. Organizations may increase communication, optimize processes, and more quickly produce high-quality software by adopting automation, continuous integration and DevOps approaches. The advantages and revolutionary potential of new technology in release management are apparent, notwithstanding the risks and difficulties that may arise. Organizations may promote continuous improvement, adjust to market demands and succeed in today’s changing business environment by tearing down barriers and embracing innovation.

  • Palo Alto Networks Extends CNAPP to CI/CD Platforms

    Palo Alto Networks Extends CNAPP to CI/CD Platforms

    Palo Alto Networks has extended the reach of its cloud-native application protection platform (CNAPP) to include the ability to secure continuous integration/continuous delivery (CI/CD) platforms.

    Daniel Krivelevich, CTO for application security for Prisma Cloud at Palo Alto Networks, said this extension of the Prisma Cloud platform would make it easier to better secure software supply chains as software builds are continuously updated by application development teams.

    Previously, Palo Alto Networks provided the ability to secure runtimes and secrets and scan code for vulnerabilities as it is being developed. This latest extension now adds the ability to secure the CI/CD platforms that drive DevOps workflows, he noted.

    While more organizations than ever are shifting application security responsibility further left toward developers, many of them overlook the need to secure the CI/CD platform itself. Most developers are not cybersecurity experts, so the chances they will miss something that can find its way into a software build are still high. Extending the reach of Prisma Cloud to the CI/CD platform will ensure the build that forms the foundation of the code is free of vulnerabilities when it finds its way into a production environment.

    That’s critical, because cybercriminals are becoming more adept at injecting malware into software supply chains in the hopes of being able to eventually compromise multiple downstream applications. In fact, this issue has prompted governments around the world to hold more organizations legally responsible for the security of the applications they build and deploy.

    There are, of course, multiple approaches to securing software supply chains, but Palo Alto Networks is making a case for an integrated platform that provides a comprehensive approach to securing the entire IT environment. Rather than integrating multiple point products, a CNAPP ultimately reduces the total cost of cybersecurity on an end-to-end basis, noted Krivelevich.

    It’s not clear how quickly organizations are transitioning to CNAPPs, but as that transition occurs, the overall state of application security should improve. One of the issues that has historically plagued application security is no one in an organization has been specifically tasked with ensuring it. Application development teams assumed cybersecurity professionals were allocating funds to it. Cybersecurity teams, however, tended to focus on areas they directly controlled, such as network firewalls. A CNAPP makes it simpler to deploy a cybersecurity framework in a more extensible way.

    Of course, there’s still much work to be done when it comes to prioritizing vulnerability remediation efforts. The truth is developers only have so much time to allocate to developing patches, so the focus needs to be on identifying the vulnerabilities that are the most severe in terms of the amount of damage that might be inflicted. At the very least, however, a CNAPP should provide the means by which the context required to identify those vulnerabilities could be more easily shared.

    One way or another, however, the number of vulnerabilities finding their way into production environments should steadily decline as more focus is put on securing software supply chains.