Oh, well, 2020 was a long year, wasn’t it? Thanks (or actually, not at all) to the Covid-19 pandemic, the order of the world has changed, and how! Economies have stagnated, consumers have adapted, and businesses have pivoted. Now, we’re all just learning how to embrace what has changed.

Ever since the nation went into lockdown, millions of professionals in India have had the chance to take some bold calls, the most liberating of which, has been to take a plunge and startup on their own. Be it out of a passion for some, out of having some extra hours in the day from working remotely, or for having figured out a need in the market for the others — when it comes to building a business, taking the early steps right is everything.

However, when it comes to funding, it’s a long haul from the day you start your company to the day you’re able to bring investors in through the front door. For bootstrapped founders, optimising company resources and costs becomes as important as executing things well.

Hence, the need of the hour for such businesses is to realise the importance of technologies like cloud computing in solving their challenges to lay a strong foundation and help them build and scale their business in a highly sustainable way. In this quick article, we’ll double down on how cloud computing becomes a no-brainer to look towards for any founder when starting out.

Typical Challenges Of A Startup Founder
Running a business is tough, and starting a business is even tougher. Startup founders, across the board, unanimously, are overwhelmed with challenges and troubles. From not having industry-specific knowledge and expertise to not knowing how to manage finances, they seem to go through it all. Here are some of the typical challenges faced by a startup founder:

Exponentially Increasing Cost Of Development: If you’re starting out in 2020, there’s an almost one hundred per cent chance you’re building a business which sells products or services over the internet. In which case, as your business grows, you need to keep expanding your app or website to be able to facilitate the uptick in traction. This means more server space, complex compute options, managed databases, you name it. Not hard to guess what all of this translates to higher costs.
Lack Of Robust Infrastructure To Scale Up Offerings: Whether it is out of ignorance, or negligence, a big challenge that startups face during their course is not having a tech infrastructure which can enable them to execute their roadmap. As a result of which, considerable time and money are spent to make things right.
Filtering Good Advice From All The Noise: If you’re a non-tech founder, for you, this could simply be knowing how tech works. And when you get to learn more about it, it can be difficult to cut through the clutter, to filter out good advice from the noise. Which is why it’s always better to follow advice which comes with proof.
Let’s see how using cloud computing can help you steer clear of these challenges, but first, here’s a quick introduction to cloud computing for the uninitiated.

So, What Is Cloud Computing?
While it’s been more than two decades that cloud computing has now been on the technology scene, there’s still a lot of confusion around what it constitutes. Simply put, cloud computing is the delivery of computing services — including servers, storage, databases, networking, software, analytics, and intelligence — over the internet, called here as the cloud, to offer increased flexibility of resources, lower infrastructure costs, and improved the ability to scale.

The Benefits: Why Should Startups Consider Cloud Computing?
Despite data pointing to the business efficiencies, cost-benefits, and competitive advantages it holds, cloud computing hasn’t fully caught up with the startup community. According to a report, businesses that invest in new-age technologies like cloud computing, marketing automation and more, enjoy 53% higher revenue.

Shouldn’t it then be obvious for you to choose cloud as the de-facto infrastructure? Here is a look at some of the tangible benefits Cloud Computing can provide for your startup:

Improves Agility And Speed Of Execution
One of the most apparent benefits of working in a cloud computing environment is this: new development resources are always only a click away, as opposed to having on-site servers and infrastructure, which can sometimes take weeks to provide. Owing to this, there is a dramatic increase in the agility and speed of execution for your business since the cost and time it takes to develop is lowered by a significant margin.

Offers Flexibility According To Your Needs
Cloud helps you eliminate guesswork from your infrastructure capacity needs, while at the same time making it more flexible for you to experiment and make iterative decisions. When you make a decision prior to deployment, you often end up either holding on expensive unused resources or dealing with limited capacity. With cloud computing, these problems go away for good. From dynamic compute power to storage, the cloud offers you complete flexibility in choosing the right amount and type of resources for your stack.

Keeps Development Costs Affordable As You Scale
More than 20% businesses are concerned about the cost of setting-up cloud infrastructure and other resources as opposed to having on-site servers, however, this is just a misconception as cloud computing needs minimum investment to get you started. Moreover, you can pay only for actual usage of resources and increase your investments as you scale your products or offerings.

Provides Enterprise-grade Data Security And Protection
According to RapidScale, 94% of businesses saw an improvement in security after switching to the cloud, and 91% said the cloud makes it easier to meet government compliance requirements. By locating data on reliable servers, providing encryption, and making regular backups and snapshots, the majority of cloud infrastructure providers provide a set of services and technologies which help to protect your company’s data very securely.

How Startups Have Leveraged Cloud Computing Successfully
Now that we’ve addressed the obvious, and not so obvious benefits of cloud computing for startups, let’s look at some testimonials from startups who have leveraged it successfully.

Slack Practices Disaster Recovery Scenarios Through Cloud
In case you haven’t heard the name, Slack is a collaboration tool which provides a messaging platform that integrates with and unifies a wide range of apps and services such as Google Docs, Jira, GitHub, MailChimp, Trello, Stripe, and more.

The ease of provisioning resources in the cloud allows Slack to practice disaster recovery scenarios, which is essential for assuring existing and prospective customers that their information will always be there, when and where they need it.

Moreover, being on cloud immediately addresses their customers’ security concerns because their cloud provider, AWS, publishes service organisation control (SOC) reports, which are based on third-party examinations evaluating how AWS achieves compliance controls and objectives.

Ralali Scales And Grows Exponentially With Cloud
Ralali is an online B2B marketplace in Indonesia. It connects local sellers and buyers, from industrial and maintenance, repair, and operating categories to office supplies, automotive, medical, agriculture, and many others.

Since using cloud services, Ralali’s agent business has been able to grow from 400 agents to over 100,000 agents in a year. Ralali.com has been able to innovate and start new projects in under 3 days, scaling quickly to provide highly available services for its end users.

ShopBack Cuts Infrastructure Costs by 60%
ShopBack is a cashback reward program available across Asia-Pacific with over 5 million members on its platform. It allows online shoppers to receive a small percentage of their purchases on the platform, paid for through affiliate programs by the merchant.

Looking for cost reductions as well as improved scalability and reliability, ShopBack discovered a cloud solution to reduce its infrastructure costs by 60 per cent, increased app/site usage fourfold, and more.

What To Keep In Mind When Choosing A Cloud Solution For Your Startup
With the plethora of tools out there, it can be a tad bit difficult to figure out how to choose the one which is most appropriate for your business. Choosing the right cloud computing is not just important, but paramount to the success of your startup. Here are few things you need to keep in mind when choosing a cloud provider. It should:

Be Robust Enough To Support Your Ambitions
Whether it is building, growing, or scaling, your cloud provider should be able to support you at all stages of your startup’s journey. Given that providing services and infrastructure is only a part of it, your cloud services provider should also be able to offer you resources and community so you can learn from how others have been able to fix the problems you have.

Offer Round-The-Clock Troubleshooting And Support

Another parameter which requires you to make a careful consideration is customer support. If you’d need assistance, and you surely would especially in the young days of your startup, would you be able to get it quickly, and on the channel of your preference?

In some cases, customer support is only provided through chat service or call centre. For the hustle at which startups operate, this might not be the most ideal for you. What you should look for is having a dedicated resource, in addition to having the usual channels. Chances are you still might encounter some constraints on the time and access, so be sure to clear all your queries upfront with regards to the level and form of support you’d be provided with.

Integrate Well With Your Tech Stack

As your startup grows, you’d need more and more tools to empower your teams and various business functions for them to improve productivity, automate tasks, streamline processes, and whatnot. Decisions like tech infrastructure and hosting are some of the most critical ones you’d make in your startup journey, hence, it becomes imperative for you to choose a cloud provider that offers native integration (or through APIs) to other market-leading products.

As a founder, and a business professional, you’d be well versed with the concept of investment vs expense. Investments are what help you grow, expenses are what you’d rather not have on your plate if there was a choice. Cloud is akin to having a solid investment.

To reiterate the point of this article, if you have a good foundation on which you’re trying to build your startup, your chances of success increase tremendously. Otherwise you’d just be the 9/10 that fail despite doing most things right.

H3 Dynamics Eyes Final Close of US$16M Series B Round

Singapore-headquartered H3 Dynamics, a startup that automates remote security and industrial asset inspection using drones, robotics, and AI, was in the process of closing a US$16 million Series B financing round as of June 2019. The round is led by existing investor SPARX Mirai Creation Fund, a Japanese fund backed by Toyota, SMBC, and SPARX Group.

According to Group Founder and CEO Taras Wankewycz, a first closing of US$6 million had already been secured, with the remaining US$10 million in final closing progressing at the time of the report. Existing Series A investors — Capital Management Group (Seychelles) and ACA Investments (Singapore) — also participated in the new round.

“Due diligence is in progress with several corporate VCs of global multi-nationals as well as VCs from Singapore, Europe, and Silicon Valley. We expect to close our Series B round by the end of August, and this will be our final private round.”

— Taras Wankewycz, Group Founder and CEO, H3 Dynamics

What H3 Dynamics Builds

Founded in 2015 by Wankewycz and later joined by Shaun Koo (CTO) and Cher Chuan Lee (VP Engineering), H3 Dynamics is building a combined software and hardware platform designed to automate the full cycle of complex, dangerous, or remote data acquisition and processing. The company does not manufacture drones itself; instead, it integrates with and automates existing drones, partnering with specialist drone makers to deliver specific industrial solutions.

Its platform is built around two core products:

• H3 Zoom — a cloud-based digital micro-services platform that uses machine learning and built-in inspection workflows to convert scanned image data into structured inspection reports.
• DBX — a field-deployable tele-robotics base station for drones, designed for automated scanning of commercial assets in remote or uninhabited locations, and for responsive surveillance at client sites.

H3 Zoom: AI-Powered Inspection Reporting

H3 Zoom applies a proprietary machine learning engine to identify, qualify, and map surface defects across 3D models or 2D blueprints of inspected structures. The platform supports a range of asset types including buildings, ships, and solar photovoltaic (PV) farms. Once analysis is complete, it automatically generates a health-check report formatted to match industry-standard paper reports, which can be downloaded by operators or contractors from anywhere.

According to the company, an initial test involving a building scan in Brazil produced a 1,400-page inspection report within minutes — though this figure comes from H3 Dynamics itself and has not been independently verified.

DBX: Autonomous Drone Operations Without a Pilot

DBX is H3 Dynamics’ tele-robotics base station, designed with a future in mind where human pilots are not required at the point of operation. The system provides automated drone scanning for assets in remote or difficult-to-access locations, as well as a surveillance and security capability for client sites. H3 Zoom and DBX are designed to work together as a closed-loop system — data collected in the field by DBX feeds directly into the H3 Zoom platform for processing and reporting.

Market Focus: Singapore and Beyond

Wankewycz described Singapore as the company’s primary reference market, with immediate commercial opportunities in real estate, maritime, and oil and gas. He cited Singapore’s foreign labour reduction targets, along with worker safety and productivity goals, as driving demand for robotics and automation solutions.

“Singapore has all the ingredients that can make us successful in our first commercial phase. Our core technology blueprint can easily be translated from local use cases to other types of large-scale infrastructure that doesn’t exist in Singapore, such as large hydro-power dams or large-scale solar PV farms — calling for further deployments of our solutions outside Singapore.”

— Taras Wankewycz

The company had already gained traction in the real estate sector with a micro-service focused on high-rise façade inspection, which was intended as the template for a broader suite of inspection services. The long-term ambition is to host the entire infrastructure inspection industry on a single platform, deployable via both pilot-assisted and fully autonomous systems.

Funding History and Recent Milestones

• February 2017: H3 Dynamics raised US$7 million in a Series A round from ACA Partners and Capital Management Group.
• May 2019: The company won the Echelon Asia Summit 2019 grand finale and received S$50,000 in grants from Enterprise Singapore.
• June 2019 (at time of reporting): Series B round at US$16 million, with US$6 million already closed and US$10 million in final closing, expected to complete by end of August 2019.

Growth Plans

Wankewycz indicated that following the Series B close, the company planned to grow its team to scale revenue and expand its product line. He also noted that H3 Dynamics’ data collection ecosystem would expand beyond drones to include other forms of robotics sourced from third-party partners, enabling the platform to support a wider range of industrial use cases.

Source: e27.co (June 2019)

Why Cloud and DevOps Go Hand in Hand

Cloud computing and DevOps are two sides of the same coin. DevOps aims to reduce friction between development and operations so that software changes reach production faster and more reliably. Cloud platforms amplify this by providing on-demand infrastructure provisioning, elastic scaling, and managed services that would otherwise require significant manual work.

Despite the natural synergy, many teams still struggle when combining the two. The most common obstacles are not purely technical—they stem from cultural misalignment, unclear ownership, and poorly defined processes. The five practices below address both dimensions.

1. Train Staff on Both DevOps and Cloud Computing

Most DevOps adoption failures have a people problem at their root, not a tools problem. When engineers and managers do not share a common understanding of DevOps principles—continuous integration, continuous delivery, shared responsibility for reliability—the process breaks down regardless of which cloud platform you use.

Invest in structured training that covers both DevOps methodologies and the specific cloud services your teams use. Training alone is rarely sufficient; pair it with mentoring, hands-on projects, and clear explanations of why specific practices matter. When engineers understand the business rationale behind a practice, adoption follows more naturally than when it is imposed as a mandate.

• Schedule recurring knowledge-sharing sessions (brown bags, internal wikis, post-mortems).
• Identify internal champions who can mentor peers and model good practices.
• Use cloud provider training programs (most major providers offer free foundational courses) to accelerate cloud-specific literacy.

2. Integrate Security from the Start (Shift Left)

Security is one of the most commonly neglected aspects of cloud DevOps, and it is also one of the most consequential. Cloud environments introduce security models that differ significantly from traditional on-premises setups. Identity and access management, secrets handling, network policies, and shared-responsibility boundaries all require deliberate design choices.

Rather than treating security as an audit gate at the end of a release cycle, embed it throughout the pipeline:

• Static analysis and dependency scanning in every pull request.
• Secrets management using dedicated vaults (such as HashiCorp Vault or your cloud provider’s native secrets service) rather than environment variables or config files checked into source control.
• Infrastructure-as-code security scanning to catch misconfigured storage buckets, overly permissive IAM roles, or open security groups before they reach production.
• Automated compliance checks integrated into your CI/CD pipeline.

If your organization’s cloud footprint is significant, consider designating a cloud security engineer or establishing a dedicated security-as-code practice to own these controls across all applications.

3. Choose Flexible, Cloud-Agnostic DevOps Tooling Where Practical

It is tempting to rely exclusively on the native DevOps tooling bundled with a single cloud provider. This approach can accelerate early adoption, but it can also create tight coupling that makes migrations, multi-cloud strategies, or negotiating contract renewals significantly harder.

Where feasible, prefer tools that are portable across environments. CI/CD platforms, container orchestration, monitoring solutions, and infrastructure-as-code frameworks that work across providers give you flexibility without sacrificing capability. Evaluate your toolchain against these questions:

• Can this tool deploy to a second cloud or on-premises environment if needed?
• Does the tool’s configuration live in source control as code, or is it locked inside a proprietary console?
• Is there a viable migration path if the vendor changes pricing or deprecates the service?

Cloud-agnosticism is a spectrum, not a binary choice. Even teams committed to a single provider benefit from keeping deployment manifests and pipeline definitions in a portable format.

4. Establish Governance and Resource Management Early

Cloud platforms make it easy to spin up new services—so easy that organizations frequently accumulate sprawling collections of resources with no clear owner, undocumented dependencies, and runaway costs. This problem tends to emerge during the first year of serious cloud DevOps adoption, when the pace of provisioning outpaces the maturity of governance processes.

Avoid this by establishing governance policies before the sprawl starts:

• Tagging conventions: enforce resource tags (owner, environment, cost center, application) through policy-as-code so every resource is attributable.
• Cost visibility: set up budget alerts and review cloud spend in your regular engineering review cadence, not just in finance.
• Service catalog: define approved infrastructure patterns teams can self-serve, reducing the likelihood of insecure or non-standard resources being created ad hoc.
• Deprecation workflows: build a process for decommissioning unused resources. What gets provisioned easily should be cleaned up easily.

5. Automate Performance Testing in the Pipeline

Performance issues are notorious for remaining hidden until an application reaches production under real load. By that point, users have already experienced the problem, and the reputational and operational cost is high. Automated performance testing, run as part of your CI/CD pipeline, moves performance regressions into the development phase where they are far cheaper to fix.

Practical approaches include:

• Load testing on every release candidate using tools that simulate realistic traffic patterns against a staging environment that mirrors production in configuration.
• Performance budgets: define acceptable latency and throughput thresholds and fail the pipeline automatically if they are breached.
• Continuous profiling in production to capture baselines and detect gradual degradation between releases.
• Chaos engineering experiments to validate that the system behaves gracefully under failure conditions—not just under normal load.

Putting It All Together

No single practice here is sufficient on its own. The organizations that get the most value from cloud DevOps treat it as an ongoing discipline rather than a one-time migration project. Staff capability, security posture, toolchain flexibility, governance, and quality assurance all need to mature in parallel.

Start by auditing where your team currently stands against each of these five areas, identify the highest-risk gaps, and address them incrementally. Continuous improvement—the same principle that underpins DevOps itself—applies equally to the way you practice DevOps in the cloud.

If your team has already adopted continuous integration, automated testing, or infrastructure as code, you are ready to ask the next question: what does a more mature DevOps practice look like? The steps below offer a structured path forward.

What Is DevOps?

DevOps is a set of practices, cultural philosophies, and tooling patterns that break down the traditional silos between software development, QA, and IT operations. By bringing these disciplines into a single, cross-functional team that owns the entire product lifecycle — from commit to production — DevOps enables faster delivery, fewer human errors, better version control, and more efficient use of engineering resources.

Crucially, DevOps is not just a toolchain. It is a combination of people, process, and technology. Introducing a CI/CD pipeline without changing how teams communicate and share ownership will produce only marginal improvements. Genuine DevOps transformation requires cultural change alongside technical investment.

6 Steps to Advance Your DevOps Practice

1. Flatten Team Hierarchies and Establish End-to-End Ownership

One of the most significant obstacles to DevOps maturity is the persistence of vertical, siloed team structures. When developers only see their slice of the codebase and operators only see the infrastructure, no one has the full picture needed to optimize delivery end to end.

Moving toward a flatter organizational model — where cross-functional product teams own a service from development through deployment and monitoring — aligns directly with core DevOps principles. This means giving engineers visibility into production behavior, giving operations teams input into architecture decisions, and holding everyone accountable for the health of the whole system, not just their individual component.

2. Adopt Container-Based Architecture and Microservices

Containers (such as those managed by Docker and orchestrated by Kubernetes) and microservices architectures are natural complements to DevOps. They allow large, monolithic applications to be decomposed into independently deployable services, each owned by a small team that can build, test, and release on its own cadence.

Containers provide consistency between development, staging, and production environments, which eliminates a significant class of environment-related bugs. Microservices make it easier to scale individual components without redeploying the entire application. Together, they increase team autonomy and reduce the coordination overhead that slows delivery in large organizations.

3. Foster Healthy Competition Through Transparent Metrics

Visibility across teams is a powerful accelerant for continuous improvement. When teams can see how they are performing relative to each other — on dimensions like deployment frequency, mean time to recovery (MTTR), change failure rate, and lead time for changes — healthy competition naturally emerges.

This does not mean ranking teams punitively. Rather, it means publishing shared dashboards that make performance data transparent and actionable. Teams that see a peer group deploying twice as frequently will look inward for bottlenecks. This peer visibility is far more motivating than top-down mandates, and it drives organic knowledge-sharing as high-performing teams become a reference point for others.

The four DORA metrics — deployment frequency, lead time for changes, change failure rate, and MTTR — are a widely used starting point for this kind of benchmarking.

4. Expand Automation Across the Entire Pipeline

Speed and scale are core promises of DevOps, and neither is achievable without extensive automation. If your team has automated unit tests and basic CI builds, the next layer of automation worth pursuing typically includes:

• Integration and end-to-end testing — automated test suites that validate behavior across service boundaries.
• Infrastructure provisioning — using tools like Terraform or Ansible to codify and automate environment creation.
• Security scanning — shifting security checks left by embedding SAST, DAST, and dependency vulnerability scanning into the CI pipeline.
• Release and deployment automation — progressive delivery strategies such as blue/green deployments, canary releases, and feature flags.
• Compliance and configuration drift detection — automated checks that ensure infrastructure remains in its desired state.

Beyond the efficiency gains, automation removes repetitive, error-prone manual work from engineers’ plates — work that drains motivation and diverts focus from higher-value problem-solving.

5. Build Fast Feedback Loops at Every Stage

The faster a team learns about a problem, the cheaper it is to fix. This principle applies both to technical feedback (test failures, production alerts, build errors) and to team-level feedback (code reviews, sprint retrospectives, incident post-mortems).

Practically, this means:

• Keeping CI build times short so developers get test results in minutes, not hours.
• Instrumenting production services with meaningful observability (logs, metrics, traces) so issues surface before users report them.
• Running regular retrospectives where teams openly discuss what slowed them down or caused incidents.
• Treating post-mortems as blameless learning exercises rather than exercises in assigning fault.

Fast feedback is not only a technical concern. Managers and leads should also close the loop quickly with individual engineers — acknowledging good work, flagging problems early, and providing context that helps engineers make better decisions independently.

6. Secure Leadership Commitment and Organizational Accountability

DevOps transformations stall most often not because of tooling gaps, but because of insufficient leadership buy-in. If senior leadership treats DevOps as a purely technical initiative owned by engineering, the cultural and organizational changes necessary for it to succeed will not happen.

Effective DevOps at scale requires leaders to:

• Actively fund and protect the time teams need to reduce technical debt and improve internal tooling.
• Remove organizational blockers — such as approval processes or procurement cycles — that create artificial delays in delivery.
• Model the collaborative, blameless culture they want to see in their teams.
• Hold themselves accountable for providing clear priorities, so teams are not constantly pulled in competing directions.

When accountability flows from leadership downward and shared ownership flows across teams, DevOps practices take root and compound over time.

DevOps Is a Journey, Not a Destination

The organizations that get the most from DevOps treat it as a continuous improvement system rather than a one-time implementation project. Each of the six steps above builds on the others: flatter teams communicate faster, automated pipelines make feedback loops tighter, and transparent metrics sustain the accountability that keeps improvement going.

Whatever your current level of DevOps maturity, the next step is always the same — identify your biggest constraint, address it systematically, measure the result, and repeat.