Still running your databases on underutilized bare metal
servers? Looking to consolidate your databases and reduce license costs, but not create an OS sprawl? If the answers are YES, then join us to see how Linux containers technologies like docker and LXC can help.
We will explore how to use containers to consolidate databases without compromising performance while guaranteeing isolation and no manageability change. We will examine and contrast other prevalent consolidation approaches, along with the roadblocks they present and how containerization helps you overcome those problems.
Additionally, we will show you the following:
1. Configure an Oracle RAC database on LXC
2. Apply IO resource management on your Oracle database running in a container
3. Simplify database lifecycle management tasks with single click clone, time travel.
The database is the quintessential data dependency for any application. Databases in production environments tend to be performance sensitive and expect consistent and predictable performance from their underlying infrastructure. On the other hand, databases in dev/test environments need to be fast, agile and portable.
Due to this paradox, production databases are typically deployed on bare metal servers for maximum performance and predictability. This often leads to underutilization of hardware, idle capacity, and poor isolation. On the other hand, dev/test databases are deployed on VMs which are fast to deploy, improve hardware utilization and consolidation, are fully isolated, and are easy to move across data centers and clouds, but suffer from poor performance, hypervisor overhead and unpredictability.
In this session, we will discuss:
- How NoSQL databases like Cassandra can benefit from container technology
- If the current storage systems can support containerized databases
- How to alleviate data management challenges for large databases
- How the Robin Containerization Platform can deliver bare-metal-like performance, while retaining all virtualization benefits
Jay Lyman, 451 Research and Sushil Kumar, Robin Systems
Applications - the lifeblood of modern business - can be in a sorry state of affairs given today's forced alignment with server, OS, and storage boundaries. This can not only cause deployment delays and complexity, but it also results in underutilized hardware and inflated operational costs. There is a drive to embrace new technologies and methodologies in the enterprise, but this presents significant challenges. Limited application-awareness at the infrastructure level makes it nearly impossible to deliver on the promised SLAs and the tight coupling of applications and underlying operating software (OS or hypervisors) compromises application portability as well as developer productivity.
A growing number of enterprises are turning to application containers to support more efficient and effective development and deployment in an application-centric IT paradigm. By abstracting applications from the underlying infrastructure, containers can simplify application deployment, and enable seamless portability across machines and clouds. Containers can also enable significant cost savings by consolidating multiple applications per machine without compromising performance or predictability. Join us to learn more about container adoption in the enterprise and how a container-based server and storage virtualization environment can help take your software-defined datacenter transformation to the next level of an application-defined datacenter.
Container-powered, Application-Defined Data Center
Robin is heralding a new data center era with its Application-Defined Data Center software. Robin’s application-centric, software-defined compute and storage infrastructure leverages containers to make server, storage and VM boundaries invisible to applications. The result? Dramatically simplified application lifecycle management, maximum hardware utilization, and guaranteed application-to-spindle QoS.
Robin is the first company to bring the benefits of containerization to mission-critical enterprise applications -- such as databases and Big Data clusters -- to enable high-performance workload consolidation with the agility and flexibility previously available only to stateless microservices applications.