What is Flocker

Flocker is an open-source Container Data Volume Manager for your Dockerized applications. By providing tools for data migrations, Flocker gives ops teams the tools they need to run containerized stateful services like databases in production. Flocker manages Docker containers and data volumes together.

Container Ecosystem

Network Architecture for Ceph Storage

 As data continues to grow exponentially storing today’s data volumes in an efficient way is a challenge. Traditional storage solutions neither scale-out nor make it feasible from Capex and Opex perspective, to deploy Peta-Byte or Exa-Byte data stores. OpenStack Ceph Storage is a novel approach to manage present day data volumes and provide users with reasonable access time at a manageable cost.

 

 Ceph is a massively scalable, open source, software-defined storage solution, which uniquely provides object, block and file system services with a single, unified Ceph Storage Cluster.

 Ceph uniquely delivers object, block, and file storage in one unified system. Ceph is highly reliable, easy to manage, and open-source. The power of Ceph can transform your company’s IT infrastructure and your ability to manage vast amounts of data. Ceph delivers extraordinary scalability –thousands of clients accessing petabytes or even Exa-bytes of data. A Ceph Node leverages commodity hardware and intelligent daemons, and a Ceph Storage Cluster accommodates large numbers of nodes, which communicate with each other to replicate and redistribute data dynamically. A Ceph Monitor can also be placed into a cluster of Ceph monitors to oversee the Ceph nodes in the Ceph Storage Cluster, thereby ensuring high availability.

 

 This architecture is a cost effective solution based on HPE Synergy Platform which can scale out to meet multi Peta Byte scale.  

Use Cases of Ceph Block & Ceph Object Storage

OpenStack Ceph was designed to run on general purpose server hardware. Ceph supports elastic provisioning, which makes building and maintaining petabyte-to-exabyte scale data clusters economically feasible.

Many mass storage systems are great at storage, but they run out of throughput or IOPS well before they run out of capacity—making them unsuitable for some cloud computing applications. Ceph scales performance and capacity independently, which enables Ceph to support deployments optimized for a particular use case.

Here, I have listed the most common use cases for Ceph Block & Object Storage.

Unified Storage with OpenStack Ceph

Open Stack Ceph Storage is a massively scalable, programmable storage platform that supports cloud infrastructure, media repositories, backup and restore systems, and data lakes. It can free you from the expensive lock of proprietary, hardware-based storage solutions; consolidate labor and storage costs into a single versatile solution; and introduce cost-effective scalability that modern workloads require.

OpenStack Cloud platforms is now becoming popular for enterprise computing. Enterprise customers are embracing OpenStack Cloud to lower their costs: License costs and eliminates the need for dedicated storage systems. From an enterprise workload perspective, there are multiple storage requirements: 

 1. High performance Block Storage

 2. High throughput File Storage

 3. Cost Effective Object Storage

 
In OpenStack, Ceph storage provides a unified storage interface for Block, File & Object Storage. This plus the ability to scale out to 1000’s of nodes makes Ceph storage a preferred SDS solution when implementing OpenStack Cloud Platform.  

 When OpenStack Solution is built on Scaleout servers like HPE Apollo platform which provides highest storage & compute density per rack, the cost economics of an on premise solution beats a public cloud offerings.

 
OpenStack Ceph Storage is designed to meet the following requirements:

 1. High availability

 2. Security

 3. Cost Effective

 4. Scalability

 5. Configurable

 6. Performance

 7. Usability

 8. Measurable

Storage Virtualization Solutions from HPE

Use Cases of Serverless Computing

Serverless Computing on Common IT Infrastructure

 Customers want flexible deployment options. In this configuration, IT can offer hosting traditional apps – running on VM. In addition, Container based workloads can be deployed on the same underlying infrastructure. The Openstack orchestration frameworks like Kubernetes and Cloudfourms allows great level of flexibility.

On top of Kubernetes cluster, one can also deploy Fission – to create a serverless IT servers to support new IoT & Mobile apps based on-demand services, while retaining a single plane of glass for management APIs – while providing unified multi-tenancy mechanism.

This unified platform provides IT to offer all three application deployment options: Traditional business applications running on VMs; Container Apps and Serverless Computing platform.

Customers want flexible deployment options. In this configuration, IT can offer hosting traditional apps – running on VM. In addition, Container based workloads can be deployed on the same underlying infrastructure. The Openstack orchestration frameworks like Kubernetes and Cloudfourms allows great level of flexibility.

On top of Kubernetes cluster, one can also deploy Fission – to create a serverless IT servers to support new IoT & Mobile apps based on-demand services, while retaining a single plane of glass for management APIs – while providing unified multi-tenancy mechanism.

This unified platform provides IT to offer all three application deployment options: Traditional business applications running on VMs; Container Apps and Serverless Computing platform.


Open source Serverless framework - Fission uses Kurbernetes to manage the serverless functions: Creation, Termination and if needed, parallel invocation of apps. While it is a major technological breakthrough - it is also a very important financial innovation on how compute resources are being offered over the cloud.

Kubernetes event handlers is used to create custom automation in form of backend APIs or Webhooks. Kubernetes cluster manager will then manage the backend delivery based on demand.

I expect to see a significant disruption of cloud service offerings with this serverless computing.

In my next few upcoming blogs, I will write more about the software layers and architecture needed to offer serverless computing.