DevOps is what has powered the accelerating progress of technology in the recent years. DevOps offers us a portal into the future, where software technology is always up to date, everything loads in a blink of an eye, and you will never again have to face another app failure. How is this possible? Close team communication, rapid feedback, and the automation of key processes enable DevOps teams to constantly innovate, making the traditional IT look excruciatingly slow and cumbersome. Today’s software companies now stand before the following choice: “Adopt DevOps or die slowly.”
Thanks to agency.howtotoken.com for support in creating this topic (First platform with proven ICO contractors)
But before we go any further, let’s clarify the notion of what DevOps actually is. DevOps is a holistic approach to software delivery that unifies software development (Dev) and software operations (Ops). It involves automation at all stages of software engineering and much shorter development cycles. One of the most famous examples of successful DevOps adoption is Netflix — it has been able to manage rapid growth due to ubiquitous automation, including the automation of failures (a tool called “Chaos Monkey” regularly tests the stability of Netflix applications by randomly shutting down server instances).
That being said, DevOps still has a few issues — mostly related to automation processes, insufficient infrastructure, and a lack of computational power. Fortunately, there are a number of noteworthy projects that address certain DevOps challenges with the help of tokenized infrastructure marketplaces, automation GRIDs, and artificial intelligence. In this article we will describe them in detail and compare them to the non-blockchain solutions.
DevOps vs. Traditional IT: Feel the Difference
The benefits or DevOps adoption include 50% less time spent on handling security problems, a 24x faster recovery rate from failures, and a 3x lower change failure rate. Also, today’s most adaptive and fast-growing tech companies are using DevOps to function close to the “speed of need.” They get rapid feedback on their products and meet newly arising demands with minimum delay.
How exactly is DevOps different from the traditional IT model, which was used to create the majority of existing websites?
Dedicated cross-functional teams
Any DevOps-oriented company consists of dedicated cross-functional teams instead of skill-centric silos — separate departments without sufficient communication. In a traditional IT environment, three or four silos work consequently on a new feature, sometimes sending it back to the previous one. DevOps teams, however, are self-sufficient. The teams consist of developers, testers, operators, and business analysts who are focused on one application. Such a cross-functional team would work on a new feature without passing the buck to someone else and saying “it’s not our job.” The work is done when it is ready to deploy. As a result, no time is wasted on hand-offs. According to the ¼–2–20 rule, every 25% reduction in cycle time doubles the productivity and cuts operating expenses by 20%.
Small, frequently delivered batches
DevOps works with small batches, which are delivered as frequently as possible — instead of big releases several times a year. From a DevOps perspective, big batches are too risky, too complex, and too difficult to coordinate, while small batches can be easily tested with the necessary level of thoroughness. If anything goes wrong, the issue can be fixed promptly and easily. In addition to this, small, frequent releases allow DevOps organizations be more responsive to their customers’ needs.
DevOps culture appreciates automation, and this allows the team to handle creative tasks instead of routine ones. A build is automatically created and tested for each piece of code, and (if it passes the tests) it is sent through the pipeline and delivered to consumers. It should be noted that total automation is usually not necessary. The automation level depends on the processes and pain points of each team, and over-automation can lead to suboptimal results. To reach the perfect balance, each team should evaluate its needs, define the bottlenecks, and set priorities — unfortunately, there are no universal schemes that cater to all needs.
Challenges of DevOps Adoption
If DevOps is such a beneficial approach that leads to a competitive advantage, why isn’t it accepted by everyone? It has been around for several years already, first appearing in 2010, but in 2018 the situation is as follows: only 30% of software companies have declared a full (17%) or almost full (13%) introduction of DevOps, and only 22% have just started the transition to this approach.
The most important problem is, of course, the massive mentality shift of the entire company — from management to entry-level employees. It is the reason why it is hard to initiate the introduction of DevOps and why it is even harder to complete it successfully. Development and operations teams in most businesses try to achieve opposite objectives: the former is encouraged to innovate, while the latter is incentivized to maintain uptime and continuity. To eliminate hostility and bring them together is no easy task. That is why company management should support the transformation to DevOps by introducing collaboration-oriented objectives and promoting cross-functional training. It will help Dev and Ops see beyond their usual scope of responsibility and realize that they all play on the same team.
What is Stopping DevOps from Taking Over the Industry?
Apart from a corporate culture shift, DevOps adoption is impeded by inevitable utilitarian problems related to infrastructure, synchronization, and automation processes. According to the survey carried out by sandbox specialist Quali, the top barriers that impede the introduction of DevOps are company culture (14%), testing automation challenges (13%), legacy infrastructure (12%), application complexity (11%), and budget limits (11%).
Testing automation is one of DevOps cornerstones: it makes continuous integration possible and saves the team’s time so they can focus on more creative work. Testing is meant to check if a piece of code works as intended and whether or not it meets all the technical or business requirements. There is a wide variety of testing types, and that is why manual testing will inevitably become a bottleneck in the context of fast DevOps flow. Though testing automation requires extra effort, it is definitely worth the cost. This is especially true for such applications as FinTech solutions or e-commerce websites — even the smallest downtime can cause a significant loss of profits.
A common problem with automated testing is that it may prove excessively time-consuming when run on local infrastructure with limited resources. Sometimes you may even have to run automated tests in the evening to get the results the next day, or even wait until weekend. Such low speeds are unacceptable for swift DevOps processes, but few companies can afford to build a powerful on-premises infrastructure.
Issues with legacy infrastructure is one more reason why many companies resist DevOps. Fast development, which is characteristic for this approach, is mostly based on microservices architecture — completely different from the traditional one. Moving to microservices entails a sharp workload increase, and in most cases legacy infrastructure requires costly upgrades.
Another infrastructure problem lies with the integration of DevOps tools with the existing IT systems — it rarely goes smoothly, because there are too many changes involved. For example, Dev and Ops teams usually employ different tools and metrics, but in order to achieve the true DevOps efficiency they must be integrated and unified — since there will be a single cross-functional team.
The optimal environment for DevOps is the Cloud, and the reasons are obvious: it provides the necessary scale, optimal speed, and maximum flexibility, all of which cannot be usually achieved within the on-premise limits. Cloud computing gives developers more control over the components and decreases wait times. Aside from that, a cloud environment enables DevOps teams to create self-service methods for provisioning infrastructure — it means that they do not have to wait for resources to be provisioned. But transitioning to the Cloud is not always possible: according to this survey, 44% of applications running in on-premise environments are deemed too complex to be moved to cloud environments.
Automation Solutions Comes to the Rescue of Enterprises
There are several automation solutions created to address some of the aforementioned problems of DevOps adoption. Plutora and Kovair are meant for enterprises that want to introduce DevOps despite the large and messy legacy systems.
Plutora is a cloud platform with a set of enterprise-level SaaS tools: Plutora Test, Plutora Environments, Plutora Release and Plutora Analytics. They can be customized to meet the needs of any software engineering methodology (Waterfall, Agile, DevOps).
- Plutora Test is a robust enterprise-ready tool that ensures proper test coverage, provides complete test management, and centralizes all test assets and metrics in a single cloud-based repository, offering a real-time view of testing activities.
- Plutora Analytics aggregates all data (related to release, quality, deployment, etc.) and provides insightful analytics and rich visualization. It can be used for digital transformation monitoring, continuous improvement, and informed decision-making.
- Plutora Environments is meant for the comprehensive management of test environments: it features a self-service booking engine that allows one to streamline testing and eliminate resource conflicts.
- Plutora Release is another powerful tool that facilitates the release management of complex enterprise applications. It automatically synchronizes with the tools of the delivery team and allows for the centralized management of release pipelines. Plutora Release tracks system dependencies within and across projects, and it provides valuable data insights for workflow optimization.The failure risk is reduced thanks to extensive reporting and analytics.
Though Plutora is a highly effective platform, it is not a universal solution. It is created for large enterprises in order to disentangle their extremely complex processes and systems. Unfortunately, small-scale companies cannot afford the subscription prices of Plutora and have to look for cheaper options.
Kovair Intelligent DevOps
Kovair Intelligent DevOps is a desktop enterprise-scale solution that facilitates the transition to DevOps culture and policies. Kovair’s solution is meant to unite and synchronize automation tools, thus streamlining the DevOps flow and eliminating process disruptions.
The major advantage of Kovair Intelligent DevOps is that it connects automation tools to a central integration hub, so that tool data could be moved across the system. It also ensures real-time visibility and insightful analytics, which can be used for prompt decision-making.
Kovair Intelligent DevOps facilitates the following tasks:
- Collaboration between automation tools in real time
- Continuous planning
- Cross-tool traceability
- Implementation of test strategy for continuous testing
- Continuous integration: the build is automatically triggered as soon as code check-in is completed successfully
- Continuous delivery due to test automation script execution
- Continuous monitoring of release quality
- Continuous delivery via tracking release pipeline
However, this solution is only meant to integrate DevOps tools — each company should evaluate the available tools and choose what is best for their own purposes. But as long as the right automation solutions are found, Kovair’s platform creates a truly seamless tool ecosystem.
Blockchain-Based DevOps Platforms
A number of crypto projects have emerged to satisfy the industry’s increasing demand for affordable computational resources and infrastructure. They utilize different technologies, but have one thing in common: tokens that incentivize community growth and serve as a reward for using resources.
Being one of the most promising decentralized DevOps platforms, Buddy addresses the infrastructure problem by offering access to two automation GRIDS. Trusted, high-availability private automation GRIDs and shared automation GRIDs can perform time-intensive and computation-intensive automated actions, or even whole pipelines. As a result, DevOps teams do their work with maximum efficiency (and without worrying about infrastructure availability). It is also important that Buddy supports complex enterprise-scale applications, multi-cloud workflows, and hybrid environments.
Buddy users can create pipelines using the supported automation actions. Currently, there are 80 actions, but more will appear soon thanks to Buddy’s marketplace, which was created to encourage community growth and support talented developers. Third-party developers are allowed to submit their own automation actions to Buddy’s ecosystem and offer them up for sale or for free.
Private Automation GRID is a network of Buddy instances that form auto-scalable, on-demand infrastructure for the automation of DevOps processes. Users can run Buddy instances wherever they consider suitable: on their own physical infrastructure, in a private cloud, or on IaaS servers. Buddy can also use trusted GRIDs provided by its partners or SaaS-integrations (Google Cloud, Amazon Web Services, etc.). Depending on the load, Buddy automatically creates new instances and removes them when they are no longer needed.
Shared Automation GRID is used in cases when trusted infrastructure is not necessary. Time-intensive and computation-intensive tasks can be given to a network of Buddy instances that have the available resources. Users who run these instances will get a BUD token for each computed unit. This GRID cannot be used for core development, but rather for testing (tests run by hundreds of Buddy instances take much less time) or other tasks that do not require a high trust level — for example, performance monitoring or availability monitoring.
DevOps engineers can also remove development bottlenecks with the help of Buddy’s Sandboxes, which allows it to run applications or websites in disposable environments directly from Git repositories. Sandboxes do not require any physical servers or VMs.
Buddy supports integration with the following ecosystems: Github, Bitbucket, GitLab, Slack, DigitalOcean, Vultr, AWS, Google Cloud, Microsoft Azure, and many others. It also has a built-in Git that users may choose to base their projects on.
Ethereum-based BUD Token is meant to serve as a basis of a decentralized economy and to create positive feedback loops in Buddy ecosystem. Without tokenization the platform would lack economic incentives for GRID participation, because fiat payments are too slow and inefficient to power community growth.
Fetch.ai is a blockchain-based project that presents the Smart Ledger — a next generation distributed ledger technology. It powers a digital world where autonomous software agents can sell their data or idle resources for Fetch tokens. DevOps teams can obviously benefit from such a marketplace: it will be a convenient way to buy computational resources for testing, monitoring, or other DevOps time-intensive tasks. From a DevOps perspective, it is somewhat similar to the above-mentioned Buddy Shared Automation GRID, but there is less human intervention.
How else can this technology be used? To put it briefly, data can sell itself in Fetch’s digital world. IoT devices can sell information that can prove useful to other agents: for example, the use of a vehicle’s windshield wiper can be relayed by a software agent as the source of weather information. An idle computer can perform testing tasks or run other computations for a remote customer. Besides that, it is possible to plug legacy data into Fetch and make it a marketable asset.
The Fetch network is likely to expand and gain massive computational power over time, and its agents will consequently get new data insights. Thanks to the machine-learning technology integrated into the Fetch system, the network is able to create its own valuable knowledge. Ultimately, trusted digital agents will be able to replace human middlemen and build entirely new industries. Data and infrastructure won’t be as dependable on humans as they are today — they will create new markets and sell themselves autonomously.
Fetch tokens will be used as the internal currency for all transactions and operations within the network. They will also serve as a refundable deposit for certain actions to ensure security and prevent undesirable behavior.
The Golem project also addresses the potential of idle computer resources, creating yet another decentralized marketplace with Ethereum-based tokens. The Golem network is a global supercomputer that combines its users’ available resources, and apparently DevOps teams can effectively use it to run intensive, automated tasks. However, the reliability and availability of such resources are questionable: will home computers (even a large number of them, combined together) be as reliable as the trusted cloud infrastructure that Buddy has?
Participants of the Golem network — both humans and applications — can request or sell machine cycles. Those who share their resources, be that a PC or a huge data center, get paid instantly by the requestors in Golem Network Tokens (abbreviated as GNT). The necessary level of security is provided with the help of sandbox environments, where computations are completely isolated from host systems.
In addition to this, the Golem ecosystem can be used by software developers for the creation, deployment, distribution, and monetization of applications. Golem provides the Application Registry and Transaction Framework to facilitate these activities.
Currently, Golem is still in beta, as its creators are focused on making it more robust and flexible. They also plan to add a variety of tools for developers and software companies in order to make Golem a viable alternative to cloud providers.
We’ve created an infographic to better explain this idea to you:
Most of the projects mentioned in this article — both non-crypto platforms and blockchain-based ones — address the dire need of computational resources, which is bound to get worse in the years to come. Although traditional cloud providers seem quite efficient in providing infrastructure and computing power, decentralized solutions are more promising in terms of community engagement and independence. As soon as they gain enough traction, they will begin to develop and grow in their own ways, attracting talented developers who will add new features and possibilities. Artificial intelligence, machine learning, and other cutting-edge technologies will fuel their further advancement — and one day we will be surprised to discover that the future has already arrived.
But the most significant thing about blockchain-based platforms is that they allow virtually anyone take part in this marketplace and earn tokens by selling idle resources. It means that decentralized platforms can potentially leverage all the existing computational power of the Earth, should the need arise.
About the author:
Kirill Shilov — Founder of Geekforge.io and Howtotoken.com. Interviewing the top 10,000 worldwide experts who reveal the biggest issues on the way to technological singularity. Join my #10kqachallenge: GeekForge Formula.