Global Financial Services Leader Modernizes Big Data on Robin

Global Financial Services Leader Modernizes Big Data on Robin

Migrating from Cloud to Cloud-Native; Accelerating your ELK deployment; Modernize Your Financial Stack

April 2020: Newsletter

April 2020 Newsletter

Migrating from Cloud to Cloud-Native; Accelerating your ELK deployment; Modernize Your Financial Stack

In this issue:
  • [Intellyx Analyst Brief] Migrating from Cloud to Cloud-Native
  • [White Paper] Unlocking the Full Potential of Your ELK Stack on Kubernetes
  • [Blog] App Modernization is an Imperative for Financial Services

Download Now

March 2020: Newsletter

March 2020 Newsletter

With over 12 million customers and $125 billion in assets under management, this Fortune 500 financial services organization is America’s leading homeowner and auto insurance company.

In this issue:
  • Forcing Functions: Economic Uncertainty and Infrastructure Modernization
  • Wasted Cloud Spend to Exceed $17.6 Billion in 2020
  • Modernize Your ELK Stack
  • Application and Infrastructure
  • Topology Awareness

Download Now

Global Fortune 500 Financial Services Leader Gains Efficiency and Agility on Robin

Global Fortune 500 Financial Services Leader Gains Efficiency and Agility on Robin

With over 12 million customers and $125 billion in assets under management, this Fortune 500 financial services organization is America’s leading homeowner and auto insurance company.

Offering a full range of financial products and services to its constituents, this company uses technology platforms and solutions to enable its customers to access the services any way they like, including by telephone, Internet, mail, fax, any bank’s ATM machines, and their own mobile devices. To provide this level of access and flexibility, the company maintains an IT Infrastructure that processes petabytes of data, and has moved its data center architecture from hardware-defined to software-defined in order to increase business agility.

This financial company processes billions of security events each day and leverages the Elasticsearch, Logstash, and Kibana (ELK) stack for event aggregation, monitoring, and visualization for cybersecurity threat detection. The company also operates an IBM Db2 data warehouse for business analytics and a Kafka cluster for stream processing.

Download Now

Financial Services with Kubernetes – Solution Brief

Big Data-as-a-Service with Kubernetes - Solution Brief

Cloud native Financial Services Applications

Robin enables financial institutions to automate deployment, scaling and lifecycle management of enterprise applications on Kubernetes. Robin simplifies the containerization of critical application pipelines including fraud analytics, real-time risk detection, & deep learning which are composed of multiple stateless and stateful applications.


  • Define & deploy applications stack or data pipeline as a bundle on Kubernetes on-prem or in the cloud »Enable self-service provisioning and management capabilities for the entire stack.
  • Accelerate & enhance Dev/Test collaboration with application-aware cloning
  • Monitor the health of infrastructure, containers, and the entire application stacks
  • Dynamically scale-up/ scale-out in minutes, without interrupting application operations
  • Consolidate multiple Databases like Oracle RAC clusters to reduce hardware and licensing cost
  • Migrate your customized and legacy application stacks to cloud without refactoring
  • Protect your critical application stack with application aware snapshots and backup

Digital Transformation Demands Fast-paced Innovation Digital Transformation requires IT services to be delivered in a fast, agile and streamlined manner across the entire organization. Enterprises in the Financial Services industry constantly need to innovate to attract and retain customers demanding a rich digital and mobile experience. It is also critical to analyze security threats across diverse systems and applications in real-time and at the same time meet all the compliance requirements as well as achieve continous availability for critical applications.

The industry is looking at containerization and kubernetes to achieve IT agility, however, there are many challenges that significantly impact the ability of technology leaders to innovate: Infrastructure silos – Owing to years of organic growth, the application infrastructure landscape is very diverse.

Managing legacy applications and modern cloud-native applications at the same time can be challenging. Traditional methods take weeks to provision legacy applications or to provide dev/test refreshes. With release cycles shrinking due to the DevOps culture and modern architecture, developers need much faster turnaround times for their application pipeline that often include legacy applications, as many modern applications depend on legacy applications.

High licensing and Infrastructure costs – Creating dedicated clusters for individual “tenants” (teams, workloads, applications, etc.) is required due to challenges with performance isolation. Each cluster is deployed for peak capacity, leading to significant licensing and hardware costs.

Infrastructure lock-in – Migrating customized applications to the cloud is not easy. Locked into infrastructure choice limits your ability to scale and experiment with new ideas.

Robin Platform Enables “As-a-Service” Experience

Robin is a Software Platform for Automating Deployment, Scaling and Life Cycle Management of Enterprise Applications on Kubernetes. Robin automates the provisioning and day-2 operations so that you can deliver a “Self-Service” experience with 1-click deployment simplicity for developers, DBAs, and Data Scientists


Robin Platform

Robin Platform

Robin Platform Datasheet

Automate Enterprise Applications on Kubernetes

Extend Kubernetes for data-intensive applications such as Oracle, Cloudera, Elastic stack, RDBMS, NoSQL, and other stateful applications.

Robin Platform

Robin is a Software Platform for Automating Deployment, Scaling and Life Cycle Management of Enterprise Applications on Kubernetes. Robin provides a self-service App-store experience and combines containerized storage, networking, compute (Kubernetes), and the application management layer into a single system. helps enterprises increase productivity, lower costs – CAPEX and OPEX, and enables always-on automation with technology solutions for big data, databases, indexing and search, and industry solutions for financial services and telco.

This software-only solution runs on-premises in your private data center or in public-cloud (AWS, Azure, GCP) environments and enables 1-click deployment of any application. Robin enables 1-click simplicity for lifecycle management operations such as snapshot, clone, patch, upgrade, backup, restore, scale, & QoS control of the entire application. Robin solves fundamental challenges of running big data & databases in Kubernetes & enables deployment of an agile & flexible Kubernetes-based infrastructure for Enterprise Applications.

Key Benefits

  • Increase Productivity
  • Lower Cost – CAPEX and OPEX
  • Gain Always-on Availability
  • Run data-heavy applications on Kubernetes

Robin Platform Stack Components

Application Management Layer – Manage Applications and configure Kubernetes, Storage & Networking with Application workflows.

Kubernetes – Run big data and databases in extended Kubernetes, eliminating limitations that restrict Kubernetes to micro-services applications.

Built-in Storage – Allocate storage while deploying an application or cluster, share storage among apps and users,  get SLA guarantees when consolidating, support for data locality, affinity, anti-affinity and isolation constraints, and tackle storage for applications that modify the Root filesystem.

Built-in Networking – Set networking options while deploying apps and clusters in Kubernetes and preserve IP addresses during restarts.

Robin Platform Features and Benefits



Rapid Deployment – Self-service 1-click
App-store experience.

Slash deployment and management times from weeks and hours to minutes. Deploy and manage data-heavy apps and services in Kubernetes.

Control QoS – Dynamic control QoS for every resource – CPU, Memory, Network and Storage.

Get complete visibility into the underlying infrastructure, set min and max IOPs, eliminate noisy neighbor issue, and gain performance guarantee.

Rapid clones – Clone the entire application along with its data – thick, thin, or deferred.

No performance penalties, backup data with ease, share data among users and applications, among dev, test, and prod, with no additional storage.

Application Snapshots – Take unlimited full application cluster snapshots, which include application configuration + data

Restore or refresh a cluster to any point-in-time using snapshots. Roll back easily with 1-click to the last snapshot in case of data corruption.

Scale – Decouple compute and storage,
scale independently.

Scale out – add nodes. Scale up – increase CPU, Memory and IOPs.

High Availability – No single point of failure – get reliable crossover and detect failures.

Get automatic App-aware data failover for complex distributed applications on bare metal – Robin is the ONLY product to provide HA for apps that persist state inside Docker images.

Upgrade – Automated rolling upgrade of application containers that is integrated with
CI/CD pipeline.

Safe-Upgrade technology guarantees that failed upgrades can be rolled back without disrupting the application.

Enterprise Data Apps-as-a-Service – Sample Customer Deployments

Fortune 500 Financial Services Leader

  • 11 billion security events ingested and analyzed in a day
  • DevOps simplicity for Elasticsearch, Logstash, Kibana, Kafka

Global Networking and Security Leader

  • 6 Petabytes under active management in a single Robin cluster
  • Agility, consolidation for Cloudera, Impala, Kafka, Druid

Global Technology Company – Travel Industry

  • 400 Oracle RAC databases managed by a single Robin cluster
  • Self-service environment for Oracle, Oracle RAC

Robin Platform Datasheet

Hyperconverged Kubernetes

Hyperconverged Kubernetes

Executive Summary – Hyperconverged Kubernetes White Paper

Kubernetes is the de-facto standard for container orchestration for microservices and applications. However, enterprise adoption of big data and databases using containers and Kubernetes is hindered by multiple challenges such as complexity of persistent storage, network, and application lifecycle management. Kubernetes provides the agility and scale modern enterprises need. Although, it provides the building blocks for infrastructure, not a turnkey solution.

On the other hand, Hyper-converged Infrastructure (HCI) provides a turnkey solution by combining virtualized compute(hypervisor), storage, and network in a single system. It eliminates the complexity of integrating infrastructure components by providing an out of the box solution that runs enterprise applications.

We believe combining Kubernetes and the principles of HCI brings simplicity to Kubernetes and creates a turnkey solution for data-heavy workloads. Hyper-converged Kubernetes technology with built-in enterprise-grade container storage and flexible overlay networking extends Kubernetes’ multi-cloud portability to big data, databases, and AI/ML.

Introducing: Hyper-Converged Kubernetes

What is hyper-convergence? Hyper-converged Infrastructure is a software-defined IT framework that combines compute, storage, and networking in a single system. HCI virtualizes all components of the traditional hardware-defined IT infrastructure. Typically, HCI systems consist of a hypervisor for virtualized computing, a software-defined storage (SDS) component, and a software-defined networking (SDN) component.

Hyper-converged Infrastructure software runs on X-86 based commodity hardware. It provides a complete environment for running enterprise applications, which means IT teams do not have to stitch together various pieces needed to to run the applications. All the required components are provided out of the box.

What is Kubernetes?

Kubernetes (also commonly referred to as K8s) is a container orchestration system that automates lifecycle operations such as deployment, scaling, and management for containerized applications. It was initially developed by Google, and later open-sourced. It is now managed by Cloud Native Computing Foundation (CNCF).

Kubernetes groups containers into logical units called “Pod”s. A pod is a collection of containers that belong together and should run on the same node. Kubernetes provides a Pod-centric management environment. It orchestrates compute, storage, and networking resources for workloads defined as Pods. Kubernetes can be used as a platform for containers, microservices, and private clouds.

Kubernetes for Stateful Applications Running databases, big data and AI/ML workloads in enterprise

Kubernetes for Stateful Applications Running databases, big data and AI/ML workloads in enterprise

Enterprise cloud-native requirements demand a robust platform that can support stateless and stateful workloads along with the necessary performance and SLA guarantees. Robin Hyper-Converged Kubernetes platform is built from the ground up to deploy enterprise applications. With an App-Store model for deploying stateful applications, Robin provides agility to DevOps teams with enterprise-grade performance. Introduction In today’s competitive market, enterprise IT faces an unenviable task of supporting innovation while enabling support for a variety of complex applications. Whether it is new applications with stateless architectures or existing stateful data-intensive applications, IT is expected to be the core part of the innovation team by empowering developers with right abstractions and enabling an agile workflow from developer laptop to production. In order to meet the demands of modern enterprise, IT has embraced cloud-native as the core pillar of their modernization strategy.

Kubernetes is the standard for container orchestration in the cloud-native ecosystem. Kubernetes, developed by Google and now part of Cloud Native Computing Foundation (CNCF), is an open source container orchestration engine used for the deployment, scaling and management of containers. The increase in market demand for Kubernetes is driving the platform as the standard for container orchestration. A vibrant ecosystem has emerged around Kubernetes, increasing the momentum of the project.

In the past two years, more organizations are using Kubernetes in production. According to a recent CNCF survey, 58% of respondents are using Kubernetes in production. This number will increase in the coming years as more enterprises go cloud-native. This trend is further highlighted by the report released by Dice and Their report claims Kubernetes was the top job searched in 2018 and this trend will grow further in 2019. The advantage of Kubernetes lies in the low operational overhead, easier DevOps and a better abstraction for developers to deploy their applications. Kubernetes supports both on-premises and cloud-based deployments. The support for hybrid/multi-cloud deployments makes Kubernetes attractive for enterprises.

Get the White Paper – Kubernetes for Stateful Workloads

Big Data-as-a-Service with Kubernetes – Solution Brief

Big Data-as-a-Service with Kubernetes - Solution Brief

Automate your Big Data infrastructure using cloud-native architecture and Robin big data-as-a-service. Improve the agility and efficiency of your Data Scientists, Data Engineers, and Developers.

Highlights – Big Data-as-a-Serivice with Robin

  • Decouple compute and storage and scale independently to achieve public cloud flexibility
  • Migrate big data clusters to public cloud or leverage public cloud to off-load compute
  • Provision/Decommission compute-only clusters within minutes for ephemeral workloads
  • Provide self-service experience to improve developer and data scientist productivity
  • Eliminate planning delays, start small and dynamically scale-up/out nodes to meet demand
  • Consolidate multiple workloads on shared infrastructure to reduce hardware footprint
  • Trade resources among big data clusters to manage surges & periodic compute requirements

Top 5 Challenges for Big Data Management

Big data has transformed how we store and process data. However, following challenges keep organizations from unlocking the full potential of big data and maximizing ROI:

»Provisioning agility for ephemeral workloads: Certain workloads, such as ad-hoc analysis, require significant compute resources for a short period of time. Developers need the ability to quickly provision and decommission compute-only clusters for such workloads.

»Separation of compute and storage: Big data needs converged nodes with both compute and storage for data locality. However, compute is significantly more expensive than storage, and with ever-increasing data volumes, infrastructure costs are rising.

»Dynamic scaling to meet sudden demands: If critical services such as the NameNode run out of resources, it is not easy to scale-up nodes on the fly to add more memory or CPU.

»Cluster sprawl and hardware underutilization: Due to lack of reliable multi-tenancy and performance isolation, Hadoop Admins often deploy separate clusters for critical workloads, resulting in cluster sprawl and poor utilization of server resources.

»Cloud migration: There is no easy way to migrate big data clusters to public clouds, or leverage public cloud compute and storage as needed for on-prem clusters.

Robin Hyper-converged Kubernetes Platform

Robin platform extends Kubernetes with built-in storage, networking, and application management to deliver a production-ready solution for big data. Robin automates the provisioning and management of big data clusters so that you can deliver an “as-a-service” experience with 1-click simplicity to data engineers, data scientists, and developers.

Get big data-as-a-service with Robin

Solution Benefits and Business Impact

Robin brings together the simplicity of hyper-convergence and the agility of Kubernetes for big data-as-a-service.

Deliver Insights Faster

Self-service experience

Robin provides self-service provisioning and management capabilities to developers, data engineers, and data scientists, significantly improving their productivity. It saves valuable time at each stage of the application lifecycle.

Provision clusters in minutes

Robin has automated the end-to-end cluster provisioning process for Hortonworks, Cloudera, Spark, Kafka, and custom stacks. The entire provisioning process takes only a few minutes.

Provision compute-only clusters

You can create and decommission compute-only clusters for Hortonworks, Cloudera, and your custom big data stacks. Perfect for ephemeral workloads, these clusters simply point to existing data lake cluster in your organization, do the required processing, and store the data in the target systems.

Eliminate “right-size” planning delays

DevOps and IT teams can start with small deployments, and as applications grow, they can add more resources. Robin runs on commodity hardware, making it easy to scale-out by adding commodity servers to existing deployments.

Scale on-demand during surges

No need to create IT tickets wait for days to scale-up NameNodes, or to add more DataNodes. Cut the response time to few minutes with 1-click scale-up and scale-out.

Reduce Costs with Robin Big Data-as-a-Service

Decouple compute and storage

Enjoy the cost efficiencies by decoupling compute (CPU and memory) and storage. Store massive data volumes on storage-only inexpensive hardware, and use compute efficiently to process the data when needed. Simply turn on data locality with 1-click when you really need it.

Improve hardware utilization

Robin provides multi-tenancy and role-based access controls (RBAC) to consolidate multiple big data and database workloads without compromising SLAs and QoS, increasing hardware utilization.

Simplify lifecycle operations

Native integration between Kubernetes, storage, network, and application management layer enables 1-click operations to scale, snapshot, clone, backup, migrate applications, reducing the administrative cost of your big data infrastructure.

Trade resources among clusters

Reduce your hardware cost by sharing the compute between clusters. If a cluster runs the majority of its batch jobs during the night-time, it can borrow a resource from an adjacent application cluster with day-time peaks, and vice versa.

Future-Proof Your Enterprise

Migrate or extend to public cloud

Robin provides 1-click lift-and-shift for big data clusters. Simply clone your entire cluster and migrate to the public cloud of your choice. You can also scale-out your clusters to the public cloud from on-prem to create hybrid cloud environment.

Standardize on Kubernetes

Modernize your data infrastructure using cloud-native technologies such as Kubernetes and Docker. Robin solves the storage and network persistency challenges in Kubernetes to enable its use in the provisioning, management, high availability and fault tolerance of mission-critical Hadoop deployments.

No vendor lock-in

Kubernetes-based architecture gives you complete control of your infrastructure. With the freedom to move your workloads across private and public clouds, you avoid vendor lock-in.

Get Robin Solution Brief – Big Data-as-a-Service with Kubernetes