From rapidly transforming consumer behaviors to heavily affecting economies around the globe, the Covid-19 pandemic has created a plethora of challenges and continues to have a multi-sector impact on nations and citizens alike.

With the arrival of vaccinations, 2021 seems to bring a new ray of hope for economies worldwide but the fact remains: This year is going to witness the ‘survival of the fittest,’ implying that businesses that turn digital and adapt to the ‘new normal’ are likely to emerge out of the Covid-19 crisis in better position to succeed.

To begin with, cloud computing is arguably going to remain the staple of leading companies. To give a quick run-through, cloud spending grew by 37% in the first quarter of 2020 itself – ushering in a new era of digitization wherein companies look at cloud computing as the most robust way to tide themselves over during the Covid-19 challenge – at this time last year the world had just woken up to the viral effect of the novel Corona virus beyond China. Capitalizing upon the urgency to drive processes remotely and securely, cloud service providers had an unlikely successful year.
Even as total IT spending dropped by 8%, the cloud market grew substantially. Having worked on a number of cloud implementations, I pick the following three key trends in the post-Covid era.

Cost optimization was always a priority before the pandemic. However, disruptions afterward have further elevated its stature in the priority stack. Today, start-ups and enterprises are seeking intelligence to deploy flexible cost models, particularly those in pay-as-you-go services. As expected, the OpEx versus CapEx solutions debate has once again intensified.

In the pursuit of normalization, controlled costing is the first step. With OpEx, businesses can get the total of their costing parameters while achieving scalability with products & services. PwC, in its latest survey, found that 75% of finance decision-makers use OpEx cost modeling and are deferring CapEx for at least another year.

Cloud ecosystems assure total flexibility and scalability in developing and managing key enterprise processes. Using OpEx as a cost model and cloud as a deployment model, enterprises can:

Achieve faster installations, upgrades, and on-demand flexibility. Given the lesser time of approval in OpEx, businesses can leverage frequent product upgrades.
Cloud systems mean negligible maintenance hassles and site visiting. The OpEx model allows for seeking cloud hosting services that cover uninterrupted networking infrastructure and enterprise-grade security.
Entities, both government and private, are likely to upscale their infrastructure capacity in 2021. At the same time, they want to keep costs in control. Therefore, hybrid cloud systems backed by OpEx cost models will set the narrative for data storage and monitoring.

Rise of native clouds – containerization and serverless computing
In order to recover from the pandemic hangover, MSPs – Managed Service Providers, would want to enhance their Customer Experience (CX) quotient while keeping costs in check; exactly what native cloud computing delivers. Native cloud technologies through containerization empower digital transformation strategies for enterprises across the spectrum. Since Azure, AWS and Google Cloud have raised the green flags, at least 60% of service providers will offer containerization on public cloud platforms.

At their core, container management repositories perform workload transportation between multiple verticals such as on-premise, edge, and the cloud. Subsequently, platforms like Kubernetes, that lessen the complexity in container management, should gain explosive acceptance in 2021-22. In addition, serverless computing that was among the top five Platform-as-a-Service (PaaS) cloud services in 2020, is still likely to be a preferred paradigm for multi-cloud developments.

Edge computing gaining the edge
To put it simply, edge computing brings storage and processing closer to the geographic location of data consumption. Besides ensuring faster response times, it saves bandwidth (and infrastructure) while empowering the service providers to serve their customers locally.

There’s no doubt that Edge computing will grow stronger in 2021. Cloud service providers will experiment with new business models beyond humongous data centers and central control of public clouds. Nonetheless, it still seeks the innovation of computing in traditional clouds while enhancing business agility. Edge computing allows enterprises to improvise upon their real-time analytics and make smarter business decisions. Since predictive analysis in CRM and other ERP verticals is growing, edge computing will have a greater role in the process.

Per IDC research, by 2024 25% of organizations will look forward to using cases that integrate edge data with apps already hosted in the cloud. 2021 will also see a series of partnerships between traditional cloud and edge computing service providers. Also, telecom service providers will have a key role in driving these hybrid ecosystems.

Going forward, devices and applications closer to the consumer’s location will play an important role in the larger fabric of the Internet of Things (IoT) and hybrid cloud models.

Opportunity is in the eyes of the beholder
The cloud was already a dominating force. The pandemic only proved that most enterprise processes can be managed remotely if the right cloud implementation is backing them. Therefore, it is not incorrect to believe that cloud service providers are sitting on a gold mine of opportunity.

The managed service provider (MSP) market is extremely competitive and fraught with challenges. MSPs need to offer competitive pricing to make their offerings attractive to customers, but at the same time require the agility to develop and deliver solutions that support the customer journey into the cloud. MSPs also need to meet and exceed service level agreements (SLAs) to maintain their customer base. They also need to avoid vendor lock-in, which may isolate potential customers, simplify their solution stack to streamline management and operations, and ensure their technology is always up to date. Achieving all of this can be impossible without the right foundation in place, which is where software-defined storage (SDS) comes in.

Standardising hardware is the key

SDS is the ideal supporting platform to help MSPs build and deliver solutions and easily manage and operate them. By decoupling hardware and software, SDS allows MSPs to take advantage of their choice of server technology and server architecture. This ensures a vendor-agnostic approach, while at the same time enabling MSPs to standardise on their hardware, using commodity servers, cloud architecture or a combination of the two.

By unifying block, object and file for hypervisors, containers, backup and cloud workloads, the result is a scale-out, resilient and distributed architecture that maximises availability and protects against hardware failure. Essentially, SDS brings significant simplicity into the framework for enhanced predictability in an elastic solution that can scale to thousands of nodes as demand increases, without disrupting service.

The ultimate goal is to establish a fabric that can support a variety of workloads, including virtualisation, containers and backup, and meet today’s data infrastructure challenges through a single domain.

Ideal for MSPs

The backbone of SDS is highly supportive of a multi-tenancy environment and simplifies management of the technology stack that goes with it, regardless of the storage or workloads that are being run. SDS also supports all providers, ensuring there is no vendor lock-in, giving ultimate flexibility in the choice of hardware, development and deployment options.

A single management and presentation layer not only simplifies complexity, it also collapses storage silos into a single management interface to eliminate mass data fragmentation. By deploying a software-defined layer on top of commoditised hardware, across various clusters including virtualised, bare metal, containers and the cloud, a truly agile infrastructure can be created. This also mitigates the risk of technology refreshes, which can be absorbed without creating disruption or downtime.

Virtual disks deliver a utility storage framework on the back end, for granular provisioning of volumes with enterprise storage functionality. This elastic infrastructure eliminates downtime across the spectrum. It also further delivers on agility by automating management of the underlying hardware and infrastructure, removing this from day-to-day administrative tasks.

Focus on customers, not tin

Using SDS, MSPs can solve new infrastructure challenges in a distributed way, enabling seamless cloud integration and adoption, supporting the hybrid cloud journey and allowing for enterprise data protection through data distribution.

SDS provides storage for virtual environments, seamlessly integrates with various container orchestrators, and serves as a single backup storage target, regardless of which backup software solution is in use. This improves efficiency, allowing MSPs to extend their service offerings easily, scale without performance degradation and support their clients’ multi-cloud strategy with persistent, high-availability storage.

MSPs are able to maximise their total cost of ownership, simplicity and scale, which lends itself to multiple use cases. From agile container footprints to micro-services and virtualisation, MSPs are able to drive a single data centre model across regions that provides absolute uptime and high availability. SDS essentially transforms commodity hardware into an elastic, resilient, modern storage solution that allows MSPs to focus on customers and application sets, rather than on the underlying hardware needed to deliver services.

What Does a Java Microservices Developer Do?

A Java Microservices Developer designs, builds, and maintains distributed backend services using Java-based frameworks—most commonly Spring Boot. The role sits at the intersection of software engineering and systems architecture, requiring both hands-on coding ability and an understanding of how individual services fit into a broader platform.

In enterprise environments, this role typically involves collaboration with cross-functional teams including data engineers, middleware teams, and security architects. Developers are expected to produce code that is not only functional but reusable, well-structured, and compliant with organizational architecture and information security standards.

Core Technical Responsibilities

While specifics vary by employer, Java Microservices Developer roles consistently require the following:

• Designing and implementing RESTful services using Java, typically with Spring Boot as the primary framework.
• Building microservice architectures—decomposing monolithic systems into independently deployable services with clear API boundaries.
• Translating technical specifications and design models into production code for new features or system enhancements.
• Writing reusable, well-structured code that follows object-oriented principles and internal coding standards.
• Ensuring deliverables meet methodology and information security requirements, including compliance with architecture review processes.
• Participating in cross-team collaboration, including work with data teams, mid-tier infrastructure teams, and product owners.
• Contributing to special projects and adapting to evolving team needs as assigned.

Required Technical Skills

Java and Spring Boot

Spring Boot is the de facto standard for building microservices in Java. Candidates are expected to understand how to configure Spring Boot applications, expose RESTful endpoints, manage dependencies via Spring’s dependency injection model, and integrate with databases and messaging systems.

Microservice Architecture Principles

Beyond writing code, developers need to understand the architectural patterns that make microservices work in production: service discovery, API gateways, circuit breakers, and inter-service communication via REST or messaging queues. Familiarity with platforms like Kubernetes or Docker is increasingly expected, though it may be implicit rather than listed.

Test-Driven Development and Test Automation

Enterprise Java roles increasingly require experience with the full testing stack:

• JUnit for unit testing
• Mockito for mocking dependencies
• Cucumber for behavior-driven development (BDD) and functional testing
• Mutation testing to validate test suite effectiveness (e.g., using PIT)
• Test-driven development (TDD) as a day-to-day practice, not just a methodology to cite

Strong test coverage is especially important in microservices environments, where a failure in one service can cascade through a system. Employers value developers who treat testing as a first-class concern rather than an afterthought.

Non-Technical Expectations

Technical competency alone is not sufficient for most senior Java microservices roles. Employers consistently call out the following soft skills and professional behaviors:

• Strong written and oral communication—particularly for documenting APIs, writing technical specifications, and communicating status to non-technical stakeholders.
• Planning and organizational skills—the ability to manage multiple workstreams, meet milestones, and flag risks early.
• Compliance orientation—understanding and following IT policies, especially those related to quality, security, and delivery methodology.
• Collaborative mindset—working effectively across data, infrastructure, security, and product teams.

Architecture and Security Awareness

Enterprise microservices developers are expected to understand and apply architecture standards—not just follow them as a checklist. This includes knowing why certain patterns exist (e.g., why sensitive data must be encrypted in transit and at rest, why API versioning matters, why service boundaries should align with business domains).

Information security is increasingly a shared responsibility across development teams rather than solely the domain of a security team. Developers should be familiar with common vulnerability patterns (OWASP Top 10 is a common baseline), secure coding practices, and how to validate inputs across service boundaries.

Career Context: Java Microservices in Enterprise Environments

Roles like this are common at large consulting firms and technology services companies that embed development talent within client organizations. In these environments, developers must balance client-specific delivery expectations with internal methodology standards—a skill in itself.

For developers looking to grow in this space, the most valuable investments are typically:

1. Deepening Spring Boot knowledge, including Spring Cloud for distributed systems patterns
2. Gaining hands-on experience with containerization (Docker) and orchestration (Kubernetes)
3. Practicing TDD and learning mutation testing tools
4. Understanding CI/CD pipelines, since microservices require robust deployment automation
5. Studying domain-driven design (DDD), which informs how microservice boundaries are drawn

About the Original Posting

This article is derived from a Java Microservices Developer job posting attributed to Capgemini, a global technology and consulting firm. The original listing was for a position in Horsham, PA, posted in October 2020. Job requirements and employer details reflect the original posting and may not represent current open roles.

What Is the Continuous Delivery Market?

Continuous Delivery (CD) is the software engineering practice of keeping code in a deployable state and automating the release pipeline so that validated builds can be shipped to production at any time. The tooling and platform ecosystem that supports CD — including pipeline orchestration, artifact management, environment provisioning, and release automation — makes up what analysts categorise as the Continuous Delivery market.

As DevOps adoption accelerated in the late 2010s, organisations across virtually every vertical began investing in CD platforms to shorten release cycles, reduce manual deployment risk, and improve software quality. This demand drove significant commercial activity among both established software vendors and specialist DevOps tool providers.

Key Vendors in the Continuous Delivery Space

The market as of 2019 was served by a broad range of vendors, from large enterprise software companies to focused DevOps specialists. Notable players identified in the research report include:

• Atlassian — Bitbucket Pipelines and integrations with Jira for end-to-end traceability
• IBM — UrbanCode Deploy and broader DevOps portfolio
• XebiaLabs — XL Release and XL Deploy for enterprise release orchestration
• CA Technologies — Release Automation tooling (now part of Broadcom)
• Electric Cloud — ElectricFlow pipeline and release orchestration platform
• Puppet Enterprise — Infrastructure automation underpinning many CD workflows
• Chef Software — Configuration management and compliance automation
• CloudBees — Enterprise Jenkins and CloudBees Core for scalable CD
• Microsoft — Azure DevOps (formerly VSTS) pipelines
• Red Hat — OpenShift pipelines and Ansible automation
• CircleCI — Cloud-native CI/CD platform
• Heroku — Platform-as-a-Service with integrated pipelines
• JetBrains — TeamCity CI/CD server
• Bitrise — Mobile-focused CI/CD
• AppVeyor — Windows-centric CI/CD cloud service
• Shippable — CI/CD pipelines (later acquired by JFrog)
• VMware, Micro Focus, Clarive, Accenture, Wipro, Applariat, Flexagon, Spirent, Infostretch, Kainos

This breadth of vendors reflects how CD tooling spans point solutions (pipeline runners, artifact repositories, deployment tools) as well as integrated platform suites aimed at enterprise-scale release management.

Deployment Types: On-Premises vs. Cloud

The CD market is typically segmented by deployment model:

• On-premises — Self-hosted CD platforms running inside an organisation’s own data centre or private cloud. Preferred by enterprises with strict data sovereignty, compliance, or air-gapped requirements (financial services, government, defence).
• Cloud (SaaS/hosted) — Managed CD platforms delivered as a service. Lower operational overhead, faster onboarding, and elastic scalability make these attractive to startups, mid-market organisations, and teams adopting cloud-native architectures.

By the end of the 2010s, cloud-delivered CD was growing faster than on-premises as organisations shifted workloads to public cloud providers and sought to reduce infrastructure management burden.

Vertical Industry Adoption

CD platforms are not confined to technology companies. The market report identifies adoption across a wide range of industries:

• Banking, Financial Services, and Insurance (BFSI) — High demand driven by pressure to deliver digital banking features rapidly while maintaining regulatory compliance and auditability.
• Telecommunications — Network function virtualisation and OSS/BSS modernisation are accelerating CD adoption among telecoms operators.
• Media and Entertainment — Streaming platforms and digital publishers rely on rapid feature delivery and A/B testing infrastructure.
• Retail and eCommerce — Seasonal peaks and competitive pressure demand continuous feature releases and pricing engine updates.
• Healthcare — Digital health applications, patient portals, and health IT modernisation create growing CD demand, balanced against regulatory constraints (HIPAA, MDR).
• Manufacturing — Industrial IoT and smart factory software increasingly adopt CD practices for firmware and application updates.
• Education — EdTech platforms and student information systems are embracing CD for faster feature iteration.
• Government, Transport and Logistics, Energy and Utilities — Public sector digital transformation programmes and operational technology modernisation are emerging adoption areas.

Regional Market Landscape

The Continuous Delivery market is global, with adoption and investment levels varying significantly by region:

• North America (United States, Canada, Mexico) — The largest and most mature market, driven by a high concentration of technology companies, early DevOps adopters, and mature cloud infrastructure.
• Europe (Germany, UK, France, Italy, Russia, Turkey) — Strong enterprise demand, particularly in financial services and automotive/manufacturing sectors. GDPR compliance requirements influence deployment model choices.
• Asia-Pacific (China, Japan, South Korea, India, Australia, Indonesia, Thailand, Philippines, Malaysia, Vietnam) — The fastest-growing region, driven by digital transformation investment in China and India and expanding cloud infrastructure across Southeast Asia.
• South America (Brazil and others) — Growing adoption among digital-native businesses and financial services firms undergoing modernisation.
• Middle East and Africa (Egypt, GCC Countries) — Emerging market with government-led digital transformation programmes providing a foundation for CD adoption.

Market Growth Drivers

Several structural factors were driving demand for CD platforms as of 2019 and continued to do so into the early 2020s:

• DevOps adoption at enterprise scale — As DevOps matured from an engineering subculture to a mainstream enterprise strategy, investment in the toolchain — including CD platforms — grew correspondingly.
• Cloud-native development — Containerisation (Docker, Kubernetes) and microservices architectures created new requirements for pipeline tooling capable of managing complex multi-service deployments.
• Digital transformation mandates — Board-level pressure to deliver digital products faster made automation of the release pipeline a priority.
• Regulatory compliance and auditability — CD platforms with built-in approval gates, audit trails, and policy enforcement became attractive to regulated industries.
• Talent constraints — Automation of manual deployment steps reduced dependence on scarce operations expertise.

Key Market Challenges

Despite strong growth, the CD market faces ongoing challenges:

• Tool sprawl and integration complexity — Organisations frequently operate multiple overlapping CD tools across teams, creating integration and governance overhead.
• Cultural and organisational resistance — Technology adoption alone does not deliver CD. Process change and organisational alignment remain significant barriers.
• Security integration — Embedding security testing (SAST, DAST, SCA) into pipelines without unacceptable increases in pipeline duration is an ongoing engineering challenge.
• Vendor fragmentation — The large number of competing vendors makes platform selection complex and increases switching costs.

Market Consolidation Trends

Since the original report was published in 2019, the CD market has seen meaningful consolidation. Several vendors listed in the report have been acquired: CA Technologies became part of Broadcom, Shippable was acquired by JFrog, Electric Cloud became CloudBees, and XebiaLabs merged with Digital.ai. This consolidation reflects the market reaching a level of maturity where larger platform players are absorbing point solution specialists to offer broader value chains.

Evaluating a CD Platform: Key Questions

Whether you are selecting a new CD platform or rationalising an existing toolchain, the following questions are worth considering — and align with the type of analysis a market research report in this space would typically address:

• What deployment model (cloud SaaS, self-hosted, hybrid) aligns with your compliance and operational requirements?
• How well does the platform integrate with your existing source control, artifact management, and monitoring stack?
• What approval, audit, and policy enforcement capabilities does the platform provide for regulated environments?
• How does the platform handle multi-cloud, hybrid, or Kubernetes-native deployment targets?
• What is the total cost of ownership, including licensing, infrastructure, and operational staffing?
• What is the vendor’s financial stability and acquisition risk profile?

For current pricing, feature comparisons, and analyst evaluations of specific vendors, consult up-to-date sources such as vendor documentation, Gartner Peer Insights, or G2 — as market conditions and product capabilities change rapidly in this space.

Background: USCIS Embraces DevSecOps

In mid-2017, the U.S. Citizenship and Immigration Services (USCIS) Office of Information Technology signaled a significant shift in its technology acquisition strategy by preparing two separate solicitations for Development, Security, and Operations (DevSecOps) services. The move reflected a broader trend in U.S. federal agencies adopting agile, security-first software delivery methodologies.

DevSecOps integrates information security practices directly into the DevOps software delivery lifecycle, rather than treating security as a late-stage gate or afterthought. This approach aims to produce secure applications faster and more reliably—a priority for a high-volume, mission-critical agency like USCIS.

The Two Solicitations: A Staged Approach

USCIS structured its procurement in two complementary phases, with the first solicitation laying the technical groundwork for the more advanced capabilities requested in the second.

Solicitation One: Cloud Infrastructure and System Enhancement

The first Request for Information (RFI) asked vendors to demonstrate their ability to build and enhance systems in the cloud. This foundational layer focused on establishing a modern, scalable infrastructure using DevSecOps principles—specifically emphasizing agile processes, microservices architecture, CI/CD pipelines, and open-source tooling.

Solicitation Two: Data Science, Machine Learning, and AI

The second RFI built on that cloud foundation by seeking more advanced capabilities, including:

• Deep data science and big data analytics
• Machine learning services
• Artificial intelligence applications

Both solicitations requested that vendors provide specific details of their past performance on similar requirements. Responses to both RFIs were due July 26, 2017.

Core Technical Requirements

A July 12, 2017 notice outlined the mandatory technical practices expected of any vendor awarded work under these contracts. Both future contracts required:

• Agile processes — iterative, sprint-based delivery rather than waterfall development
• Microservices architecture — decomposing applications into independently deployable services
• Continuous Integration/Continuous Delivery (CI/CD) pipelines — automating build, test, and deployment workflows
• Open-source tools — leveraging community-maintained toolchains rather than exclusively proprietary software

Services were intended to be delivered across USCIS’s enterprise and within the broader Department of Homeland Security (DHS) environment, indicating an expectation of scale and interoperability.

USCIS’s Prior DevOps Experience

These solicitations were not USCIS’s first foray into DevOps. The agency had already established a track record with related contracts:

• 360 IT Integrated Solutions RLLP—a joint venture of Qbase LLC, Geocent LLC, and the Newberry Group Inc.—won an Enterprise Acquisition Gateway for Leading Edge Solutions II (EAGLE II) task order in August 2016 for a rapid DevOps implementation. The contract was valued at $4.7 million and was set to end in September 2017.
• Infozen Inc. had held a four-year, $15 million Alliant Small Business task order for transformation integration and configuration services, which concluded in June 2017.

The timing of these new solicitations—coming shortly after both prior contracts concluded or neared their end—suggests USCIS was planning a deliberate transition to a more mature, security-integrated DevSecOps model rather than simply renewing existing arrangements.

Why DevSecOps Matters for Federal Agencies

Federal agencies face unique pressures that make DevSecOps particularly well-suited to their needs:

• Compliance by design: Regulations such as FISMA require continuous security assessment. Embedding security into CI/CD pipelines reduces the compliance burden compared to periodic audits.
• Reduced time-to-delivery: Agile and CI/CD practices allow agencies to release working software incrementally rather than in multi-year waterfall cycles.
• Scalability in the cloud: Cloud infrastructure enables USCIS to handle variable workloads—such as immigration application surges—without over-provisioning fixed data center capacity.
• Auditability: Automated pipelines create reproducible, documented build and deployment processes, supporting federal audit requirements.

Key Takeaways for DevOps Practitioners

The USCIS solicitations from 2017 are an early, concrete example of the federal government codifying DevSecOps requirements into procurement language. Several patterns are worth noting for practitioners working in or selling to government environments:

• Agencies are increasingly specifying CI/CD, microservices, and open-source tooling as baseline requirements—not differentiators.
• Procurement is structured in layered stages: establish infrastructure first, layer advanced analytics and AI on top.
• Past performance on similar DevSecOps engagements is a critical evaluation criterion in federal RFIs.
• Security is expected to be built into the delivery pipeline, not bolted on at the end.

As federal modernization continues to accelerate—driven by mandates from OMB and initiatives like the Federal Cloud Computing Strategy—the pattern established by USCIS in 2017 has become a template repeated across dozens of agencies.