It is critical to stay current with industry trends in order to solve problems in a dynamic business ecosystem. From DevSecOps to low-code apps, software development trends change as quickly as technology itself. Here, I will categorize trends across following technology disciplines.

1. Software Engineering/Development
2. Cloud Computing
3. Data
4. Architecture
5. Integration
6. Automation
7. Data Science, AI, ML
8. IoT
9. BlockChain
10. AR/VR
11. Cyber Security

Software Engineering/Development

• Scale up of Low-code, No-Code Platforms
  • Appian
  • Zoho Creator
  • Mendix
  • Salesforce LowCode platform
  • Microsoft Power Apps
• DevSecOps tools/techniques continues to strengthen
  • Cloud based Pipeline-as-a-service
  • Observability and Metrics will become mainstream to evaluate effectiveness.
• Microfrontends coupled with Event driven microservices
• Micro frontends for mobile
• Native App Development still dominant approach.
• PWA - Progressive Web Apps are on the rise.
• Increased emphasis on UI/UX
• Design Thinking

Cloud Computing

• Hybrid Cloud emerging as standard for regulated industries
  • Amazon EKS Anywhere, GCP Anthos, Azure Arc making hybrid seamless.
• Exponential adoption of Serverless computing
• Multi-Cloud paradigms
• Infrastructure-as-code enhancements(AWS CDK etc)
• Tailored Industry Cloud Enclaves(FinTech Cloud, HealthCare Cloud, LifeSciences Cloud etc.)
• Customers and Hyper-scalers are thinking sustainability
• Edge Computing critical for time sensitive compute.
• Increase PaaS offering form hyper-scalers.
• Kubernetes emerges as Defacto for containerized apps.
• Vendor Agnostic CASB, CWPP, CSPM platforms.

Data

• Domain Driven Data Fabric(ex: R&D, Marketing, Sales, Supplychain)
• Data Mesh & principles (domain data ownership, data as a product, self-serve data platform and computational federated governance.)
• Data Virtualization and unified interfacing.
• Datalake storage + Snowflake is a game changer
• Privacy, Trust by design and in-depth.
• Composable data and analytics
• Power of graph data enabling(Knowledge Graph)
• Data and Analytics evolve as core business function in the quest of new digital business models.
• Organization(large and medium) are realizing importance of streamlines data governance and management process and move in that direction.
  • Explosion of data focused platforms like Collibra, Immuta, atlan.
• Data Cataloging and assetification
• Metadata management becoming more and more important
• Data Observability
• Unified Data Infrastructure helping organization do gap analysis.
• Convergence of Data Engineering and AI/ML.
• Organization, practitioners debating on Data Stack being bundled or unbundled - Differentiating needs will be the tie breaker.
• Edge compute of data will gain more prominence for latency sensitive workloads.
• DataOps function for every product platform should be.
• Self service BI
• Purpose fit, polyglot databases are still justified.
• New paradigms are inevitable…

Architecture

• Micro, nano event driven services lead the way
• API Economies
• Composable Enterprise
• Packages Business Solutions
• Reusable Capabilities
• Cloud First is a Norm
• Service Mesh
• Favor matured managed platforms instead of re-inventing the wheel.
• ZERO-TRUST Architecture practices
• *-as-a-service thinking.
• Product vs Project thinking.
• Data parity between environments with techniques like anonymization etc.

Integration

• API-first mindset and API-led connectivity
• API Technology: REST, gRPC, and GraphQL will co-exist
• Low-code, No-code integration capabilities will accelerate.
• “Hybrid <*>” will force organization to think about hybrid integration platform(HIP)(ex: Mulesoft, Boomi, iPaaS etc.)
• More demand for real-time data as business models evolve.
• Self healing integration and processes.
• Self-service APIs(POssible after matured data capabilities)

Automation

• Organization will embark on the journey od Hyperautomation by integrating all its facets( Robotic process automation (RPA), process mining, chatbots, low-code workflow platforms, artificial intelligence, machine learning, and intelligent document processing)
• Scout platforms pave path for more automation capabilities(Ex: Sorroco)
• Ill informed enterprises use automation to treat bad business process(re-imagining business processes).
• Low-code, No-code will make strides in this segment as well.
• Semantic automation(Automation of AI steroids)
• Centralized view on automation will bring governance on investments.
• Organization focus on citizen development considering labour, skill shortage.

Data Science, AI, ML

• Deepfakes, generative AI, and synthetic data
• AutoML and No-Code AI will pave path for self service AI
• Tensor Flow will continue to rule
• AI to masses will continue - AI for Development and testing etc.
• Multi-modal learning
• Tiny ML to revolutionize edge use-cases.
• Democratization of AI knowledge, tools and experiences.
• Governance of AI usage(The Algorithmic Accountability Act)
• New business models around NLP (ex: GPT)
• Accelerated development of purpose fir, differentiating platforms
• Organization to emphasize on clean data for accurate AI outcomes & scaling.

IoT

• 5G
• Digital twins grow up
• Edge Computing is and will be mainstream where necessary.
• Standards, guardrails, reusable capabilities will emerge and drive.
  • Protocols
  • Security
• Burst in wearable devices
• Software defined networking (SDN) is an enabler.
• Cloud Providers will ship more simplified managed services around IoT.
• Every industry and function will rush to find its next IoT use-case.

BlockChain

• Progresses beyond crypto currencies
• Tokenization and NFT’s will take world by storm
• Web3 is a long term game
• Business models harnessing the power of “proof-of-stake”
• Smart contracts for real-world applications.
• Blockchain will need to turn green
• Blockchain and IoT integration
• Blockchain for governance, compliance and regulations.
• Blockchain-as-a-service business models and services.
• Standards, guardrails, reusable capabilities continue to emerge.
  • Protocols
  • Security
• ERP(Enterprise Resource Planning) to NRP (Network Resource Planning)

AR/VR

• IoT and 5G capabilities will accelerate AR/VR business models/use-cases.
• Apple ARKIT, Android ARCORE - More neutral platforms will emerge like mobile app technologies.
• AR/VR wearables
• Metaverse
• Covid has accelerated the need for AR/VR for every industry.(Manufacturing, Education, Healthcare, Retail, Remote “Anything” services, Automotive)
• AR Hardware & LiDAR
• AI + Edge Compute + Next gen chips will take wearable experience more natural.
• Standards, guardrails, reusable capabilities continue to emerge.
  • Protocols
  • Security

Cyber Security

• Vulnerability Disclosure Programs
• Architectures adopting Zero Trust principles
• Adoption of SASE
• AI to power cyber needs
• Organization will put special focus on Product security vs IT Security
• Blockchain based Self-sovereign data and digital personal identity
• SSO and MFA adoption will rise.
• Cloud IAM and centralized entitlements management(ex: Sailpoint, Keycloak)
• Data privacy and Trust will serve as foundational pillars
• Software Bill of Materials
• Policy-as-a-Code
• Data-Residency-as-a-Service
• interactive application security testing (IAST)

Cheers and Happy Building 🤘

Avinash Erupaka

I am a technology leader, with experience driving all aspects of technology transformation, from strategy to future state architecture. For last 10 years I worked for major corporations building B2B, B2C & internal platforms. I worked in the capacity of a senior dev, tech lead, Platform architect with hand-on experience driving technology strategy enabling business strategy. My expertise is in disciplines like distributed cloud Architectures, Data engineering and analytics, web and mobile application development, IoT, automation, security by design , agile - devsecops practices. I love managing teams and solving complex problems. I love tech, teaching, traveling, and fitness level boxing. I have proficiency using tools like React.js, Redux, Bootstrap, Material Design for the front end. Node.js, Scala, Clojure and Java for the back end. I leverage AWS, GCP, AZURE, OCI cloud platforms and I am a Multi Cloud Certified Architect. Opinions are my own and not the views of my employer.