The State of DevOps in 2017

Editor’s Note: This is a guest blog post authored by Nate Vickery, a business technology expert.

As we witness the technological “Big Bang,” the demand for new applications and new software will expand. This is nothing new, because every time humanity has leaped forward with new technologies, so has the demand for new products. DevOps has arrived in the time of need, giving a solution to the demand for new software and offering a way into the future with new ways of collaboration and development of software processes.

However, in 2016, humanity saw DevOps in a typical way humanity views something new – the “Let’s poke it with a stick, and see what happens” kind of way. Every time a new opportunity is seen on the horizon, humanity is skeptical. Nevertheless, DevOps offers a new perspective that is perceived as positive by enterprises, which are already starting to implement some of the ideas DevOps has to offer. 2017 will be an interesting year for DevOps and software development in general.

Alternative or Evolution

People see DevOps as an alternative to agile software development. Experts argue about whether we should abandon a system that has been proven effective and has been around for over a decade and switch to a more innovative method. After all, we are creatures of habit – it’s always a challenge to move from what you got used to, to something different. However, the need for DevOps came to life from agile software development’s popularity and its tendencies to provide more software releases.

Agile methodology signifies a change in the way of thinking and practice that leads to organizational change. DevOps emphasizes the importance of organizational change and improved collaboration between departments for achieving goals. Instead of an alternative, DevOps should be seen as the next step in agile development as it improves the practices of agile methodology and brings something new to the process.

Increased Popularity

Enterprises are already experimenting with DevOps practices. DevOps practices ensure notably shorter time to market, better product quality, reliable releases, and improved customer satisfaction. Also, they allow you to build the right product by fast experimentation and improved productivity and efficiency. But those are not the only things that DevOps brings to the table. The popularity of DevOps will continue to rise as its innovative methods are being used more often.

We can already see microservices being used more and more for developing continuously deployed systems. And the possibilities of software containers are driving enterprises crazy. Serverless systems that have the potential to change how companies develop software and applications that are built into the kernel itself are truly capturing the attention of everyone in the industry. Large enterprises will undeniably adopt DevOps even more in 2017.

More Useful Tools

We have seen various tools similar to DevOps in the past few years, like Docker – for containerization, Vagrant- visualization platform, Puppet – Infrastructure as Code, and Jenkins – for continuous integration. Docker, for example, is an open source project, and many companies like Microsoft and IBM have already announced support or partnership with Docker in the future.

There are plenty more tools available, like:

  • Code review and Verizon control tools
  • Build status tools
  • Test and result tools that determine performance
  • Artifact repository and application pre-deployment staging tools
  • Release automation tools
  • Infrastructure as Code tools
  • Application performance monitoring tools

DevOps supply a wide variety of tools – from biometric authentication tools to Code development tools. It seems that enterprises see the potential in the development and usage of these tools, and are willing to offer even more support. Therefore, we can expect that most, if not all, of those tools will become improved and more sophisticated in 2017.

More Collaboration and Consolidation

With DevOps comes a new way of organizing business structure. Managers have been interested in improving cross-department communication in more than one way. DevOps introduces a necessity for collaboration and consolidation between all aspects of an organization and mutual aid between developers, SQA testers, security testers, and every other staff member of the IT sector.

This culture has a positive effect on efficiency and progress of software life-cycle and software delivery. Since there has been positive feedback on this culture, the management team will most likely try to implement this method on a company-wide scale. After all, it is perceived as well-organized and profitable.

Concluding

DevOps is a clipping from “software development” and “information technology operations.” DevOps aims to establish an environment and culture where developing, testing and releasing software can happen frequently, rapidly and more reliably. As mentioned, it emphasizes collaboration between software developers and other IT professionals. So far, it has proved to be an amazing method with a potential to push the technology even further. It is safe to assume that 2017 will be the most exciting year for DevOps progress and development. Let’s wait and see how the events unfold.

-END-

Guest Blogger’s Profile:

Nate Vickery is a business technology expert mostly focused on future trends applicable to SMB and startup marketing and management processes. He has also been blogging in the past few years about before mentioned topics on various leading sites and communities. In the little free time left, Nate edits a business oriented website – Bizzmarkblog.com.

Top Five DevOps to NoOps Trends to Watch in 2017 and Beyond

2017 will be an exciting year for DevOps engineers. The astounding rise of containers, microservice architectures, and proliferation of machine intelligence is helping them solve their everyday problems. To this end, Ops & Automation is much simpler now. And with the fast-moving innovation paradigm that has set in over the years, the Ops community has seen the operational tasks evolving from traditional operations to new age DevOps. Primarily to suffice the need for more  agility and productivity. But with the rise of machine intelligence, another new trend is treading currently: DevOps to NoOps.

In the words of Botmetric CEO Vijay Rayapati, “NoOps is a logical progression of DevOps with the philosophy: Humans should solve new problems and the Machines should solve known problems!”

Vijay adds, “NoOps is an era of using intelligent automation for your operational tasks so you can eliminate the need for humans to manage operations, save precious engineering time, and solve known problems. As machines can make decisions on known problems and can provide diagnostic information for the new problems to reduce the operational overhead for engineers.”

Here’re the top five DevOps to NoOps adoption trends that every cloud engineer should know:

1. Serverless Programming: This programming and deployment paradigm will significantly eliminate the DevOps requirement for provisioning and configuration management. The cloud world will only see a growth trajectory for NoOps movement as all cloud vendors mature their serverless offerings.

2. Containerization: The containers like Docker will further abstract the dependencies and resource sharing between different components by leveraging cluster management and orchestration solutions like Kubernetes, Mesos, ECS, Nomad, etc. to provide a common view of underlying infrastructure.

3. Microservices Architecture: It will help engineers and companies to decouple the complexity of monolithic systems into small yet manageable components handling specific responsibility. As containerization becomes standard way of deploying components in the cloud, it will see rapid adoption.

4. Intelligent and Unified Operations: Static tooling with (no intelligence) is slowly growing on to the engineers and getting on their nerves To this end, there has been a  rise in the use of machine intelligence, and increased adoption of deep learning. Consequently, the industry will see more adoption of dynamic tooling that can ultimately help them in day-to-day operations.

5. Self Healing and Auto Remediation: Earlier, DevOps world was limited to build, deployment and provisioning while the day-to-day operations were handled in a manual or semi-automated fashion. Now it’s about time, engineers embrace NoOps where machines can resolve known, repetitive problems and engineers can solve new problems.

To delve further deep into DevOps to NoOps trends, read the post by Botmetric CEO Vijay Rayapati, where Vijay will throw light on the details of all the five trends shaping the cloud world in 2017 and beyond.

Which other technologies do you think will trend this year in the cloud arena? Do drop in your thoughts in the comment section below or tweet to us at @BotmetricHQ.

Editor’s Note: This exclusive blog post is an adaption of the original article, The 2017 Cloud Trends: DevOps to NoOps, penned by Botmetric CEO Vijay Rayapati.

Cloud Computing in 2017: An Op-Ed From the Cloud Geeks

Digital transformation has changed the way organizations work, and so has the cloud. Following along the lines of VMWare’s Ex CEO Paul Martiz, cloud geeks across the globe have been saying it loud now ‘Cloud Computing in 2017 is about how you do computing, not where you do computing.’

Forrester, in one of its recent report, says, “Cloud computing will continue to disrupt traditional computing models at least through 2020. Starting in 2017, large enterprises will move to cloud in a big way, and that will supercharge the market. We predict that the influx of enterprise dollars will push the global public cloud market to $236 billion in 2020, up from $146 billion in 2017.”

While these numbers are enough to validate that ‘Cloud is the New Black,’ it also sends out clear signals that it is imperative to take the right measure and shove in the right strokes to get the most from your cloud computing in 2017.

The Way Forward

In 2016, we saw that many enterprises failed to achieve success with cloud computing, especially public cloud. For the reason that they failed to develop a cloud strategy rooted in the definition and delivery of IT services linked to business outcomes. More so, they missed out leveraging the real benefits of elasticity feature that a cloud offers. They purchased instances in bulk to handle peak demands, like how they did with on-premise IT infra, and then turned a blind eye towards idle resources that could be optimized easily.

They also overlooked the fact that ‘anything and everything’ on the cloud can be codified and APIs can be made use of to automate the tasks on the cloud completely. Essentially, to go the NoOps way while on the cloud.

So, 2017 is the year where you put these in perspective and introspect how you can align these in your cloud strategy so that IT are seamlessly linked to business outcomes. Here’re few tips from our tech geeks on what to focus in the cloud for 2017:

1.Implement cost governance as a discipline:

Every business has its own ideas on how best to determine cloud ROI. However, they will have to think beyond Capex and Opex to get the cloud economics right. Our cloud geeks say that to get maximum ROI of your cloud, the first step is to establish the right policies, and closely monitor as well as regulate the resource usage every day. By bringing in a discipline with the right policies and budgeting, you can easily govern the costs. Plus, automating the tasks to monitor and streamline the cloud spend continuously will definitely help bring down the TCO.

2. Focus more on compliance:

There’s a myth that has remained with many companies even today — public or hybrid cloud present compliance challenges, unlike private clouds where control and customization are much easier. With the increase in the adoption of cloud, things have changed. Increasingly cloud service providers are open to dialogues when it comes to SLA, and also provide services that comply with PCI DSS, HIPAA, and other regulatory requirements. Another block that many of our customers are concerned is noncompliance due data’s location. It is simple. Locate your data, and during an audit, justify its location along with the measures that are in place to protect it.   

3. Automate security:

While compliance and assuaging DDoS attacks plays a major role in cloud security, an API-driven strategy that puts all things in the right place at the right time also plays an equally important role. Automation is the future. And to get there, APIs are the keys to unlock the door. By automating security, it helps you code in the practices that make your data comply with your company’s security policy, identify vulnerabilities on running instances, and further fix those vulnerabilities in split seconds.

4. Take a note of Security of Things (SoT):

In this age of IoT, many are skeptical about the security of these connected devices talking on the cloud. At the end of the line how much ever a technology advances to help protect our networks and devices, security is ultimately a shared responsibility on the cloud. To know more, read the Botmetric blog on ‘Bridging the Cloud Security Gaps: With Freedom Comes Greater Responsibility.’ 

5. Go serverless:

Serverless architectures have already taken the cloud computing by the storm. With the amount of interest leading cloud services providers  are showing, especially AWS, Azure, Google, and IBM, it will be the theme of 2017. So, DevOps teams need to be hands-on in choosing the right services and be nimble. One observation we made during 2016 was that there is a common misconception in the DevOps community that going serverless is NoOps. It is not! DevOps team still need test, deploy, log and monitor the code.

6. Leverage Microservices:

Microservices are currently playing a key role in cloud computing, and they will continue to do so. Thanks to container technologies such as Docker, Rocket, and LXD — portability of code (microservice) across multiple environments is seamless. More so, deploying and managing containerized applications are now easier. Above all, these microservices along with the container technology will help developers autoscale and easily handle the load.

7. Use Machine Learning in IT Operations:

Machine learning, and its subset Deep Learning, is now no more restricted to just the Big Data applications. It is slowly seeping into the walls of DevOps sitting on the cloud to help them improvise IT operations. Especially to minimize human intervention. More so, applying machine intelligence to problem-solving will be a norm very soon. For instance, it will come in handy to fix the alerts flood & monitoring fatigue caused by a company’s operational management systems in this 24*7 uptime world. Read this Botmetric blog Assuage Alert Fatigue Mess with DevOps Intelligence to know how machine intelligence can help solve this issue.

8. Use Robotic Process Automation (RPA):

Even though this technology is in a quiet nascent stage now, it has made its footprints felt in the cloud computing. From our observation, 2017 will be the year, it will be used voraciously by many cloud management and SaaS products, where in they will offer data-driven ‘Bots’ that can automatically capture and interpret existing data, manipulate it, and trigger responses and do more intelligently and smartly. In short: Gear-up yourself to embrace this gen-next of deep learning.

9. Embrace NoOps:

While RPA, machine learning, automating security, etc. are making strides towards efficient cloud computing, NoOps will be the next wave of efficient cloud computing in 2017. Soon automating all the operations will be the norm. Building cloud as a code, with just the Dev team and investing Ops team into development efforts & innovation, will be the way forward. Are you game?

Cloud Computing in 2017: The State of Cloud Providers

AWS Cloud

In 2006, AWS created the first wave of cloud computing. A decade later, AWS has again created the second wave. Apart from the fact that it is currently operating at an $11 Billion USD, it has also announced 50+ services. This is helping change the landscape of enterprise cloud computing. As an AWS Technical partner, here’re few tips from team Botmetric that you can take into account in 2017:

1. Use Lambda@Edge to deliver a low latency UX for customized web applications, and more so, run code at CloudFront edge locations without provisioning or managing servers.

2. Integrate Blox, the new open source scheduler for Amazon EC2 container service.

3. Leverage AWS CodeBuild and AWS Elastic Beanstalk without fail.

4. Buy Convertible RIs and leverage Regional Benefit to get the most out of EC2s.

5. Use new features available in S3 Storage. For instance: Object Tagging, S3 Analytics, Storage Class Analysis, S3 Inventory, and S3 CloudWatch Metrics.

Microsoft Azure

According to a leading survey, Microsoft Azure accounts to 28.4% of the global IaaS ecosystem and is quickly catching up with AWS in the race to tap this growing market. With its growing portfolio of services (with support for machine learning, DevTest Labs, Active Directory, Log Analytics, BotService, etc.) and continued patronage among Microsoft aficionados, the Azure PaaS is also gaining ground, especially among enterprises.  

Google Cloud Platform

With Google accelerating its move to cloud data warehousing and machine learning, it is also up for the race with AWS and Azure stealing 16.5% share of them from the IaaS market.

To Wrap Up

At Botmetric, we talk about cloud computing and DevOps everyday.  Not just with a bunch of clients, but with other cloud geeks in the ecosystem too, closely observing the industry trends and practical challenges cloud engineers face every day. To this end, we have developed a close-knit collaboration with other partners and seek to make cloud management a breeze for all — using automation. Hence this write-up. And we hope that we have thrown some light on the trends that will reign the cloud computing in 2017. Let us know if we have missed on something here. Plus, do share your views and thoughts on the state of cloud computing in 2017 on Twitter, Facebook, & LinkedIn.