8 DevOps Trends to be Aware of in 2020

  • Automation will become the major focus
  • Shifting attention from CI Pipelines to DevOps Assembly Lines
  • Rise in Artificial Intelligence (AI), Data Science Boost
  • Concept of “everything as code”
  • Hype in using Server Less Architecture
  • Automation through AI and Data Science
  • More Embedded Security
  • Kubernetes has evolved significantly

According to a collective study, DevOps market generated 2.9 billion in 2017 and the market is expected to reach at $6.6 billion by 2022. DevOps has become a key focus and has shaped the world of software and many experts predict that DevOps is going to be the mainstream and is going to reach its peak at 2020.

Enterprises are not only showing interest in DevOps but are gradually adopting DevOps-related practices and technologies. As per Hackernoon article citing Statista, there was a 7% boost in DevOps adoption from 2017 to 2018. DevOps software market is projected to grow from $2.9 billion in 2017 to $6.6 billion in 2022 (source: estimates from IDC).

DevOps Projected Growth 2019

Fig: Google trend is shown for “DevOps” and a hypothesis of its estimated growth in 2019.
DevOps offers the following benefits:

  • Fast response towards an amendment
  • Offers great speed and makes the security arrangement more agile
  • Establishes a perfect channel of collaboration and communication
  • Fast identification of bugs or vulnerabilities in the code
  • Team can effortlessly put their sole attention on other critical things instead of focusing on security features

Many enterprises are adopting DevOps and there is a boost up to 17% in the year 2018 than what was about 10% in the year 2017 (according to Statista)

Image source: Statista

Predictions of 8 DevOps Trends to be aware of in 2020:

1. Automation will become the major focus

Companies that have already implemented DevOps have seen high efficiency and faster deployments. When it comes to DevOps, DevOps automation is what we talk more about. Zero-touch automation is going to be the upcoming future. Understanding the 6 C’s of the DevOps cycle and to apply automation between these phases is the key, and this is going to be the major objective in 2020.

2. Shifting attention from CI Pipelines to DevOps Assembly Lines

The final goal of DevOps is to improve collaboration between planning and automation of the delivery procedure. It is not just about doing Continuous Integration (CI) but it is all about CD (continuous delivery). Companies are investing extra effort and time into understand about automating their whole software development process. In 2020, the attention is going to shift from Continuous Integration (CI) pipeline to DevOps assembly lines.

Advantages of Assembly Lines:

  • Powerful nested visibility
  • Native integrations
  • Fast on board and scale with “as-code” philosophy
  • Perfect CD (continuous delivery) with interoperability
  • Team-based business intelligence and analytics

3. Rise in Artificial Intelligence (AI), Data Science Boost

Growing number of Artificial Intelligence-driven apps will push data science teams to look for DevOps philosophy in their workflows. DevOps method is expected to be their prominent option in dealing with automated pipelines, maintaining, and testing multiple deployed models in the production chain.

This is going to boost further as data science & development teams move closer for high efficiency in development, deployment & managing AI & ML-driven apps.

4. Concept of “everything as code”

We cannot deny the fact that coding has now become the backbone of the IT sector. Understanding various DevOps tools and automating scripts plays a crucial role in the software development and this is going to dominate in 2020. The future of this industry depends on the technical capabilities of the developers, testers, and people of the operation.

Since, DevOps is all about easing the delivery cycle, there is a need to bring in the code which can be used to increase the software production cycles efficiency. The thought of “everything as code,” is DevOps’s built-in practice and it can be present in the SDLC to create a wave in the DevOps trend 2020. Software Testers are likely to suffer if they do not learn to code and write their test scripts.

5. Hype in using Server Less Architecture

DevOps can be reached to the zenith level with server-less architecture. This is not free of server; however, there is a cloud service which takes care of the complete architecture. This extraordinary architecture allows the software developers to concentrate focus on the “Application Part”. BaaS and FaaS are the two critical aspects of the server less architecture. By employing server-less architecture, you can save time, cut down the costs, and ensure resilient work flow.

6. Automation through AI and Data Science

The main objective of 2020 is zero-touch automation. The continuous increase of Artificial Intelligence and Data Science has become a game-changer. Various apps are fueled with AI, which is pushing DevOps teams to seek automation possibilities to discover prospects within their workflow streams.

7. More Embedded Security

With the exponential growth of security breaches and the bad impacts to the company’s reputation, cyber-security has become business imperative. In 2020, DevOps will rapidly include security.

Recently we have seen a buzz trend of DevSecOps. DevSecOps is all about injecting security first in the app development life cycle, therefore decreasing vulnerabilities and improving business reputation.

The shift to DevSecOps will also bring great collaboration in software development. It will ensure the development processes remains flawless, efficient, and effective.

8. Kubernetes has evolved significantly

Kubernetes has turn out to be the top growing container technology. Globally, technologists and CIO’s have preferred Kubernetes because of its offerings and it is expected to grow by 2020. This year, we saw the adoption of Kubernetes take off as companies of all sizes embraced containers for running cloud-native apps. In 2020, we will start to see container orchestration software replacing several old DevOps functions.

Solution- How can we help you?

Whether it is all about offering software development services or other services, DevOps has become the inevitable part of any organization. By staying up to date with the newest trends, you set your business up to get the enormous benefits from DevOps.

As an industry leader in DevOps Testing Solution, ImpactQA give holistic agile and DevOps adoption services across diverse domain segments, backed by its dedicated DevOps Continuous Testing practice. We implement a robust plan to manage both resources and testing tools in a new environment and to facilitate continuous testing and delivery.

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How IoT and Machine Learning is changing the World?

  • What is Machine Learning?
  • What is the Industrial Internet of Things (IIoT)?
  • How IoT (Internet of Things) and Machine Learning affect our life?
  • Challenges- IoT and Machine Learning
  • Solution

IoT and Machine Learning are getting smarter. Companies are incorporating artificial intelligence (AI)—in specific, machine learning—into their IoT apps. From smart thermostats to wireless sensors, IoT devices are gradually but positively garnering mainstream adoption. Virtual assistants like Siri, Alexa, and Cortana are only making this technology easy to adopt.

The core purpose behind advancement in the IoT space is to help information move smoothly and seamlessly. For as much as we condemn technology, we can all recall a moment when the right message has appeared at the right time, with perfect user experience.

The truth of IoT and Artificial Intelligence – specifically machine learning – is far less sinister. It is shaping the way we live, travel, work, and communicate. In fact, it is shaping our lives smartly and the decisions we make.

The proliferation of smart IoT devices is shaping the future and gives instant access to the information world.

Let’s have a glance at these burning IoT statistics:

  • There are about 17 billion inter-connected devices in the globe as of 2018. With more than 7 Billion of these IoT (internet of things) devices. (Source- IoT Analytics)
  • According to McKinsey Global Institute, each second, 127 new IoT devices connect to the net.
  • The global IoT market is expected to be worth $1.7T in 2019. (Source: CBI Insights)
Worldwide  Iot Active Connection Graph
Worldwide IoT Active Connection Graph

What is Machine Learning?

ML is one of the critical components of AI, where a computer is programmed with the ability to improve its performance. In short, Machine Learning is all about analyzing big data – the automatic extraction of information & using it to make predictions.

Netflix, Amazon, Google, and other E-Commerce platforms use it to bring semantic outcome. It is based on algorithms that analyze the user’s purchasing history to predict their preference. Machine learning is gradually integrating into all verticals, through automation of physical labor, we are improving the connectivity and shaping the future of AI and the IoT.

What is the Industrial Internet of Things (IIoT)?

The Industrial IoT or Industry 4.0 or the 4th industrial revolution are the terms generally used for IoT technology in a business setting. The concept is similar to the consumer IoT; to use wireless networks, a mix of sensors, big data and analytics to optimize industrial processes.

IoT devices provide information and analytics to connect the world of hardware devices and high-speed internet.

We can separate the Industrial IoT into two main categories:

  • Industrial IoT- The Industrial IoT, connects devices and machines in sectors like healthcare, transportation, power generation, etc.
  • Commercial IoT– Commercial IoT sits between industrial IoT and consumer and shares aspects of both.

How IoT (Internet of Things) and Machine Learning affect our life?

IoT and ML are improving the way we live and communicate in our lives. For instance, the AlterEgo headset easily responds to our brainwaves to control appliances and on the other hand, Alexa and Amazon’s Echo enables the voice-activated control of your high-tech smart-house.

This amalgamation of IoT and Machine Learning is changing various industries and the relationships that companies have with their clients. Businesses can easily gather and transform data into valuable information with IoT.

IoT is also transforming business models by helping companies to move from concentrating on products & services to companies that give the best outcomes. By impacting organizations’ business models, the blend of IoT-enabled devices & sensors with ML creates a collaborative world that aligns itself around results & innovation.

Challenges- IoT and Machine Learning

These days’ enterprises are flooded with data that comes from IoT devices and is seeking AI to help manage the devices. It is tough to manage and extract crucial information from these systems than we might expect.

There are aspects to IoT like data storage, connectivity, security, app development, system integration, and even processes that are changing in this space. Another layer of complexity with the Internet of Things has to do with functionality level.

Critical challenges that companies face with IoT and ML are with the application, ease of access, and analysis of IoT data. If you have a set of data from varied sources, you can run some statistical analysis with that data. However, if you want to be proactive to predict events to take future actions, a business needs to learn how to use these technologies.

Many firms are turning to the main cloud platform providers — for instance, Google, Amazon, Microsoft, Alibaba Cloud, or IBM. These companies offer a range of services to store IoT data and prepare it for data analytics, plus to train and run machine-learning models. They also assist in creating graphs, dashboards, and other simple-to-grasp layouts to visualize the information these models generate. Overall, IoT and Machine Learning are combined to provide high visibility and control of the wide range of devices connected to the Internet.

Solutions-How can we help you?

Futurists say ML (Machine Learning) and the Internet of Things (IoT) will transform business profoundly than the digital and industrial revolutions combined.

Are there some kinds of risks? Yes, as with any new technology, we have to accept both the profit and risks that come with mainstream adoption. We can do this with the confidence only when these technologies are tested against several odds.

One of the innovative solutions for seamless operation flow is IoT testing. There will be several other types of testing which require to be considered to cover the comprehensive functionality of IoT devices.

As part of ImpactQA’s Advisory Services, we also provide an implementation plan to help our clients improve time-to-market while keeping their business goals in mind. We use our assessment frameworks (like Chatbot testing framework, RPA Testing framework, etc.), based on industry best standards, focusing on processes, tools, and infrastructure.

Collaborate with our specialists to improve all QA areas – people, processes, tools, and infrastructure across the delivery life-cycle.

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