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Deployment Automation will minimise operational tasks of the DevSecOps pipeline ensuring security and compliance with 24*7 Managed Services with SRE Principles.Kubernetes Advisory Services and deployment strategies for progressive delivery and scalable infrastructure from CNCF trusted Kubernetes Certified Services Provider (KCSP)
Deployment and Scaling of day-to-day Automation to facilitate DevOps speed to market and application elasticity.
Networking, compute, and storage management on behalf of workloads allows developers to focus on applications.
Continuous health checks, restart containers that fail or have stalled and making services available to users while running.
The architecture allows infinite flexibility, ability to scale virtually to meet changing needs and increase deployment velocity.
Persistent storage with portability for stateful application running on production additionally expanding scalability, and consistency.
Cloud-Native Storage Solutions and its Key Features
Managed services with observability for optimizing operations and enhancing resource efficiency.
Ensure automated and secure deployments and maintain cloud-native visibility.
An end-to-end guide to deploying and developing a hyperledger fabric cluster.
Manage containerized workloads and automate application deployment at scale.
Federated Kubernetes Deployment for Modern Applications
Google Services (GKE)
Resource efficiency, automated operations, scalability, flexibility and accelerate time to market.
Amazon EKS
Amazon VPC for isolation, Elastic Load Balancing, IAM for authentication and Amazon ECR for container images.
Azure Service (AKS)
Elastic provisioning, faster development cycle, Accelerate containerized app development and security-driven solutions.
Your technology partner for cloud-native and enterprise transformation.
Enterprise Technology
Banking and Finance Sector
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Education
Transportation
Retail
Enterprise AI
Big Data Engineering
XAI
DevOps
Agentic AI Systems
Data Science
RESET
Why do enterprise AI programmes stall? Because teams are asked to build AI on broken context, scattered data and unclear ownership. They struggle not because AI is hard, but because their data is not...
What is the real problem with agentic AI? Broken business context. It is not intelligence, access or automation: models are capable, data is plentiful and workflows are everywhere. Agents must know...
What is a private LLM council? It is an AI assistant in which several role-specific models debate a question, critique each other and hand a chairman model a decision space rather than a single...
How do you sustain an open-source data platform on private cloud? By maturing three capabilities together: operational reliability across the whole data journey, specialist co-managed support for the...
Should an AI agent be allowed to fix your data platform? Not at first. AI-assisted site reliability engineering is good at the part of an incident that consumes the most specialist time: gathering...
Can you adopt Apache Iceberg without leaving Hadoop? Yes. Apache Iceberg is an open table format, not a storage system. It can sit on the HDFS storage you already run, use the Hive Metastore you...
In the rapidly evolving environment of artificial intelligence, maybe the most exciting development is that of multi-modal agents. Next-generation AI agents can process and integrate different kinds...
Unlocking the Power of Multimodal AI with Snowflake AI applications receive unprecedented opportunities through text, image, video, and structured data, which are exploding across the market today....
Agentic AI in robotics is the use of AI agents that let robots perceive their surroundings, reason about a goal and act on their own, replacing fixed scripts with adaptive behaviour. Agentic AI is...
How Is Agentic AI in DevOps Transforming Software Delivery and Automation? Agentic AI in DevOps is the use of autonomous AI agents to plan, run and monitor software delivery work, such as testing,...
Database DevOps means treating database changes like application changes: every schema change lives in version control, is tested, and reaches each environment through the same automated pipeline....
Overview of Persistent Storage Persistent Storage is critical for running stateful containers. Kubernetes is an open-source system for automating the deployment and management of containerized...
Why Doesn’t Your Security System Know What Your Safety System Knows? (Unified Security and Safety Intelligence) Same Cameras. Same Facility. Two Separate Worlds. That’s the Problem. In most...
How Does Agentic Video Intelligence Enable Remote Facility Monitoring Without the Headcount? You Can’t Put Staff at Every Substation, Warehouse, and Construction Site. You Can Put Intelligence There.
What Are Autonomous Security Patrols — And Why Are They Transforming Facility Security? The Case for Autonomous Security Patrols A security guard conducting foot patrols moves at approximately 3 mph....
Synthetic data is artificially generated data that reproduces the statistical patterns of a real dataset without copying its records. Enterprises use synthetic data generation to fill test...
Introduction to Intelligent Automation Intelligent Automation is one of the most recent trends in the broad field of Technology. It is also called Hyper Automation or Cognitive Automation. It is much...
Real-time anomaly detection means scoring each new event, metric or log line against a learned notion of normal while the data is still arriving, so that an operator or an automated workflow can act...
What is a private LLM council? It is an AI assistant in which several role-specific models debate a question, critique each other and hand a chairman model a decision space rather than a single...
What does it mean to call AI the "miracle material" of our era? Steel shaped the Gilded Age and semiconductors built the digital age; AI is the structural material of this one. It is not a better...
Why do enterprise AI agents fail? Not because they lack intelligence, but because organisations lack infrastructure for meaning, memory and governed execution. The cause is the schema-truth gap: the...
Human Resources (HR) professionals are constantly adapting to an ever-changing business landscape. To stay ahead in this competitive field, attending the top conferences in human resources 2025 can...
The main computer vision conferences of 2026 are now mostly behind us: WACV ran in Tucson in March, CVPR in Denver from 3 to 7 June, ECCV in Malmö from 8 to 12 September and IEEE ICIP in Tampere from...
The manufacturing industry is transforming rapidly, driven by technological advancements, sustainability initiatives, and globalization. Attending industry conferences becomes essential as...
Introduction to Streaming Data Visualization Streaming Data Visualization gives users Real-Time Data Analytics to see the trends and patterns in the data to take action rapidly. It is the control of...
Data visualization best practices for executive dashboards come down to two things: design that lets a senior reader see the state of the business in one glance, and governance that lets them trust...
What is user Experience Testing? User experience testing is having actual people engage with a website, app, or other product you've created and analyzing their behaviours and reactions. It is a...
Why do enterprise AI programmes stall? Because teams are asked to build AI on broken context, scattered data and unclear ownership. They struggle not because AI is hard, but because their data is not...
What is the real problem with agentic AI? Broken business context. It is not intelligence, access or automation: models are capable, data is plentiful and workflows are everywhere. Agents must know...
Why is 2026 the year of context and ontology? Because enterprises are realising that models were never the bottleneck. AI systems with clean data, strong models and working demos still fail in...
Find out more about levaraging the true potential of AI
Argo CD
Knative
KubeEdge
KubeLess
ArgoCD is a declarative Kubernetes GitOps continuous distribution platform that standardized GitOps workflows.
Knative supports enterprises to run serverless applications with workload autoscaling, and traffic monitoring deployment capacities.
Kubernetes Native Edge Computing Platform facilitates efficient edge application development and deployment.
Kubeless provides auto-scaling, routing, monitoring, and troubleshooting.
AI continuously monitors systems for risks before they escalate. It correlates signals across logs, metrics, and traces. This ensures faster detection, fewer incidents, and stronger reliability
Proactive detection of performance and availability issues
Root-cause analysis across microservices and environments
Automated remediation playbooks to reduce MTTR
AI converts camera feeds into instant situational awareness. It detects unusual motion and unsafe behavior in real time. Long hours of video become searchable and summarized instantly
Real-time detection of suspicious motion or intrusion
Natural language video search and instant playback
Smart summaries for audits, investigations, and compliance
Your data stack becomes intelligent and conversational. Agents surface insights, detect anomalies, and explain trends. Move from dashboards to autonomous, always-on analytics
Connects to warehouses, lakes, and streaming sources
Question-answering in natural language
Continuous monitoring for anomalies and KPI deviations
Agents identify recurring failures and performance issues. They trigger workflows that resolve common problems automatically. Your infrastructure evolves into a self-healing environment
Automated diagnostics for recurring errors
Playbook execution: restart services, scale pods, clear queues
Feedback loop for improving remediation strategies
AI continuously checks controls and compliance posture. It detects misconfigurations and risks before they escalate. Evidence collection becomes automatic and audit-ready
Continuous control checks across infrastructure and SaaS
Automated evidence collection for audits
Risk scoring and prioritized remediation recommendations
Financial and procurement workflows become proactive and insight-driven. Agents monitor spend, vendors, and contracts in real time. Approvals and sourcing decisions become faster and smarter
Real-time visibility into spend and commitments
Anomaly detection on invoices and vendor performance
Intelligent workflows for approvals and sourcing decisions
