Cloud computing has been a sole bastion of private enterprises for the last decade or so. Not anymore. Government organisations in India and world-over have now started to venture into cloud computing in a big way, as well. Be it hosting, computing, storage, innovative e-Services or PaaS solutions, governments worldwide have started to involve and adapt themselves to cloud related technologies as part of their digital transformation. The reasons – infinite computing power, storage, security, scalability, speed and resilience.

Gartner predicts governments’ cloud spending worldwide to grow at a CAGR of nearly 17.7 per cent through 2021 and sees a two-fold rise in the public cloud adoption of governments in this period.

So, why is there a sudden push to cloud by government organisations and agencies in India and world-over?
The traditional reason everyone can think of is cost. ‘Pay-as-you-go’ model propagated by public cloud providers could have been the clincher, we all think. May be not. Let us analyse this. If the business objectives of any government could not have been thoroughly addressed by deploying their systems to the cloud, they would not have ventured into cloud in the first place. After-all governments are in the business of satisfying citizens’ needs and if that does not get accomplished securely and successfully, governments would not have turned to cloud in such vast numbers this year, regardless of the cost savings they can achieve.

So, what are the security, compliance and performance barriers that are being taken out in cloud environments, for the governments to feel safe to move to the cloud now than ever-before?

Cloud security and compliance:
Cloud security and data security in particular was a primary barrier. The major confidence-booster for governments in this regard, is the security measures that have improved tremendously in the public cloud arena. Matured techno-concepts such as private subnets, network access control lists, Web-application firewalls, reverse proxies, data encryption at rest and motion, have helped to secure the computing and storage resources of governments. Compliance standards such as FedRAMP, HIPAA, GDPR, GxP, HITRUST, ISO, SOX, PCI that are facilitated and adopted by cloud providers and cloud system integrators have helped the governments to assess the security readiness of their cloud systems in order to thwart attacks from hackers.

Local data storage:
Local data storage and related data security was another key barrier. Governments world-over wanted their citizens’ data to be stored in public clouds within their own borders. That means all the public cloud providers needed to have at least one data center in each country. They are working towards this, but this will take some time. So, for now, at least governments are looking at storing data within their regions (like APAC AWS/Azure Regions for India) and nearby availability zones, so that data does not go far from their home.

Scaling and availability:
The third major barrier was the scaling and availability of the compute and storage servers. When government systems and applications are processing millions of citizen records, the ability for the systems to scale and accommodate these high-volume requests become a critical criterion for success. With the advent of “autoscaling” feature almost all the public cloud providers are able to address the high-volume problem successfully nowadays.

Cloud compute and storage systems, aided by a technology called containerisation could now dynamically deploy additional “live” parallel compute/storage systems within seconds of anticipating such loads, in order to cater to the additional citizen demands instantly. These systems can also shut themselves off automatically, when the sudden surge in demand from citizens reduces. The “Pay-as-you-go” model also helps here as the governments are charged only for the usage of these additional systems from the time, they come alive until the time they shutdown automatically as part of the autoscaling.

In summary, we see that all the potential issues the government faced in hosting systems, applications, computing and storing data in cloud have been addressed to a point that governments world-over are comfortable moving to cloud. The additional comfort of decoupling all government systems from each other and also from other private enterprises, within the same cloud deployment, by way of the security technologies mentioned above helps from a risk mitigation standpoint for all the stakeholders. Hence it is not a surprise to see even the local and state governments moving their latest technology systems involving IoT, prediction analysis, AI/ML based data engineering, Robotic Process Automation, and blockchain to the public cloud, along with their national governments.

The Cloud Native Computing Foundation has gained another graduate project. Accepted into the CNCF in 2018, storage project Rook is now mature enough to fall into one category with cloud native bedrocks Kubernetes and Prometheus.

Rook was originally developed at Upbound and looks to supply users with Kubernetes Operators for all sorts of storage providers to facilitate automated storage management. It is today maintained by a variety of companies ranging from Red Hat to Suse.

Kong portfolio gets new nervous system
API gateway provider Kong has used its house conference Kong Summit to announce its new connectivity platform Kong Konnect. The still in beta service is supposed to connect the Kong portfolio, and aims to “accelerates the journey to microservices, secures and governs APIs and services, and it allows developers to rapidly design, publish and consume APIs and services”[sic].

Konnect is made up of a runtime manager to spin up API gateways, Kubernetes Ingress, and service mesh runtimes, a service hub listing an organisation’s services, a developer portal, to govern service access, a vitals section for monitoring service health, and the Insomnia API Designer for changing interfaces.

Docker turns up the volume of collaboration and security
Containerisation tech company Docker has announced some enhancements for subscribers of their Team and Pro tiers. Docker Hub for example now comes with vulnerability scanning, so that users are notified about potential security issues when pushing to the image repository. Scan results are also said to soon make their way into Docker Dashboard.

Other plans for the coming months include ways to share contexts with team members, ignore updates to Docker Desktop, and enhanced support for Desktop and Hub.

Elixir 1.11 now available
Elixir, a programming language for the Erlang VM, has recently received a major update and is now available in version 1.11. Once upgraded, developers can profit from tighter Erlang integration, compiler checks for data constructors and application boundaries, built-in datetime formatting, and other calendar enhancements.

Sumo Logic sprinkles some more insight onto Continuous Intelligence Platform
Data analytics provider Sumo Logic this week introduced Software Development Optimization (SDO) to its Continuous Intelligence Platform. The new addition is meant to help teams visualise log data and analyse the information available to provide users with a solid basis for process optimisation amongst other things. Initial integrations include Jira, GitHub, Jenkins, Bitbucket, PagerDutie, and OpsGenie, though Sumo Logic promises easy extensibility for tools like Azure DevOps, GitLab, and CircleCI.

Sonatype intros Advanced Development Pack
Software development lifecycle management tool provider Sonatype has added a new set of developer-focused enhancements to its Nexus Lifecycle product. The so-called Advanced Development Pack mainly includes some dependency management tools to support software developers with component upgrades, help them to choose secure open source components, and warn about supply chain attacks.

Open Source Crosses the Enterprise Tipping Point

A few years before 2017, open source was widely regarded as the unglamorous, low-cost alternative to proprietary software. Enterprises tolerated it primarily to cut licensing spend. By 2016, that perception had been completely overturned. Open source had become the de facto standard across nearly every layer of the enterprise stack — from operating systems and databases to container runtimes and cloud platforms. Cost had become almost an afterthought; innovation was now the primary driver.

A market study conducted by North Bridge and Black Duck, titled Future of Open Source, captured the scale of the shift: approximately 90% of surveyed organisations reported that open source improved efficiency, interoperability, and innovation. More strikingly, adoption of open source for production environments outpaced proprietary software for the first time, with more than 55% of respondents leveraging open-source software (OSS) for production infrastructure.

Heading into 2017, the question was no longer whether enterprises would adopt open source — it was how fast and how deeply. Four areas stood out as particularly significant.

OpenStack and the Private Cloud Momentum

OpenStack had already established itself as an enterprise-grade framework for building private and hybrid clouds. An independent study commissioned by SUSE found that 81% of senior IT professionals were planning to move to — or were already running — OpenStack-based private cloud infrastructure. Many Fortune 100 companies had moved OpenStack into production.

The appeal went beyond cost savings. A proprietary cloud platform is expensive to build, license, and maintain. OpenStack offered flexibility and agility without vendor lock-in, giving enterprises the freedom to compose infrastructure from commodity hardware and open APIs. Crucially, OpenStack provided self-service developer access, enabling teams to provision resources on demand rather than waiting weeks for infrastructure tickets to be resolved.

Analysts noted at the time that OpenStack’s value was not primarily tied to server consolidation or virtualisation — it was about enabling a broader cultural shift toward developer agility and faster delivery cycles. As cloud became the foundation on which future business initiatives would run, the choice of cloud platform would have far-reaching consequences for every digital transformation project undertaken in 2017 and beyond.

Open Source at the Core of Digital Transformation

Digital transformation presented CIOs with an acute challenge: environments were heterogeneous, data volumes were exploding, and the pace of change demanded platforms that could scale, adapt, and interoperate across vendor boundaries. Open source addressed all three requirements simultaneously.

Technologies such as the Internet of Things (IoT) and the converging stack of social, mobile, analytics, and cloud (SMAC) were generating unprecedented data diversity — in volume, variety, and velocity. The fragmented ecosystem of devices, protocols, and standards made open, community-driven platforms particularly attractive. Proprietary solutions, by contrast, risked creating new silos that would hinder rather than accelerate transformation.

Perhaps the clearest indicator of open source’s centrality was this: virtually every organisation at the leading edge of digital business was already relying on open-source platforms and tooling at scale. The velocity of innovation delivered by open-source communities — Linux kernel releases, container ecosystem advances, database engine improvements — was outpacing what any single vendor could deliver alone.

Software-Defined Data Centers Built on Open Source

Research from IDC around this period indicated that 85% of surveyed enterprises globally viewed open source as the realistic or preferred approach to migrating toward software-defined infrastructure (SDI). IDC specifically flagged vendor lock-in as a critical risk to avoid, recommending open-source deployments as a mitigation strategy.

Linux adoption in data centers was growing steadily year over year, and the reason was straightforward: the core requirements of SDI — efficiency, scalability, and reliability at minimal capital investment — mapped directly onto what open-source platforms delivered. Enterprises running open-source infrastructure could build, deploy, and update applications faster, with less risk of being stranded on a vendor’s end-of-life roadmap.

Software-defined storage (SDS) was a particular bright spot. Open SDS solutions offered near-unlimited horizontal scalability without requiring a full platform refresh or disruption to running workloads — a meaningful advantage over proprietary storage arrays that demanded expensive forklift upgrades. The goal of true zero-downtime operations in software-defined environments was increasingly achievable through open-source tooling.

Open Source as the Foundation of Enterprise DevOps

By 2017, software had become a direct determinant of business performance. The ability to develop, test, deliver, and maintain applications quickly and reliably was no longer a concern limited to technology teams — it was a board-level priority. DevOps practices and containerisation technologies were the primary levers for increasing release frequency and improving application quality.

Enterprises attempting to operationalise DevOps ran into a consistent problem: replicating production environments for testing was costly and complex. Teams struggled to isolate test workloads from live systems. Open-source container technologies — with Docker being the most prominent example — addressed this directly by enabling lightweight, reproducible environments that could be spun up and torn down on demand.

Industry analysts in 2017 pointed to a converging architecture: microservices running inside containers, hosted on open and scalable cloud infrastructure, as the trajectory for enterprise application delivery. OpenStack-based clouds were viewed as a natural complement to this model because the same open infrastructure could be reused across container lifecycle events — creation, scaling, teardown — without proprietary constraints.

The flexibility and interoperability of open-source platforms meant DevOps teams could standardise toolchains across development, staging, and production — reducing the “works on my machine” class of failures that had historically slowed delivery cycles.

Looking Back: Did 2017 Deliver on the Promise?

From the vantage point of hindsight, 2017 did mark a genuine inflection point for enterprise open source. Kubernetes graduated from Google’s internal tooling to become the dominant container orchestration standard, the Cloud Native Computing Foundation (CNCF) expanded rapidly, and major cloud providers deepened their open-source contributions and managed service offerings. The predictions made in early 2017 — about containers, cloud-native infrastructure, and DevOps toolchains — proved directionally accurate, even if OpenStack’s long-term dominance in the private cloud market was later challenged by managed Kubernetes offerings.

What 2017 confirmed, beyond any remaining doubt, was that open source had moved from a cost-reduction strategy to an innovation imperative. Enterprises that had not yet built open-source competency were not just paying more — they were falling behind.