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
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.
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.
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.
Latest posts by Editor (see all)
- May Roundup @ Botmetric: Deeper AWS Cost Analysis and Continuous Security - May 31, 2017
- What is NoOps, Is it Agile Ops? - May 25, 2017
- Why Botmetric Chose InfluxDB — A Real-Time Metrics Data Store That Works - May 18, 2017