How Tyrone Cloud Suite can Overcome Data Center Management Challenges

The emergence of digital transformation has made organizations realize the importance of data in making strategies, analyzing market trends, creating better experiences for customers, and finding out ways to stay ahead from their competitors. Data is becoming the key to competitive advantage.

However, the data that is being generated after technological advancements is way more different and evolved from the earlier one in terms of transactions, structure, availability, methods of collection, and value derived from the ability to aggregate and analyze it. The data is extensive and can easily dominate any aspect of business decision making. To make it usable in a cohesive environment, it can be divided into two categories – big data and fast data.

Big data is large collected data sets used for batch analytics, whereas, fast data is collected from many sources and is used to drive immediate decision making. Despite having advanced ways of storing and using this data, there are some challenges that data centers face and needs to be addressed for the effective utilization of data. Let’s check them out.

Monitoring and Reporting in Real-time

The data centers have a lot of applications, connecting cables, network connectivity, cooling systems, power distribution, storage units, and much more things running at the same time. This heavy load could lead to unexpected failures. Therefore, constant monitoring and reporting different metrics become a must-do for data center operators and managers.

Planning and Management in Terms of Capacity

Datacenter managers tend to overprovision to avoid downtimes. As a result, resources, space, power, and energy is wasted. The increase in data has always questioned the capacity of a data center making it a challenge for data center managers. However, this was only until the data center infrastructure management solution came into being.

Performance Maintenance and Uptime

One of the major concerns for data center managers and operators is to measure the performance and ensure uptime. This includes maintaining power and cooling accuracy ensuring energy efficiency of the overall structure too. In such cases, any manual management is simply cost-prohibitive at the scale that they operate at.

Staff Productivity and Management

The activities of data center infrastructure involve tracking, analyzing and reporting performances which if done by non-automated or manual systems need facilities and IT staff to spend an extraordinary amount of time logging activities into spreadsheets. This can become a hindrance in the time that can be spent making strategic decisions for improving data center services.

Energy Efficiency and Cost Cutting

The data center is estimated to account for 1.4% of the global electricity consumption.
The industry is often accused of using a massive amount of energy and rising temperature problems. There are times when energy is found to be wasted than used at a data center site. This is due to a lack of proper energy monitoring tools and environmental sensors.

How to overcome these challenges?

Tyrone Cloud suite has been designed to meet the modern-day challenges and unique needs of a data center which it does by the following ways:

● It comes with a tailored-to-build approach. Sustainability, customer’s IT information flow, and architecture is followed while designing a cloud machine.

● It allows the implementation and deployment of your cloud machines on a variety of technologies.

● The suite machines build the cloud architecture from the ground up with absolute ease.

● It can hand-hold any architectural changes with the existing infrastructure that might require modifications, OS and technology upgrades, and deeper design revisions.

● It is flexible and can be tightly turned to meet unique needs.

Why Use Kubernetes for Your Container Management?

Kubernetes, or popularly known as k8s (k, 8 characters, s…get it?), or “Kube” is an open-source platform that automates Linux container operations. Kubernetes is a portable, extensible, open-source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available. It functions to eliminate many manual processes involved in deploying and scaling containerized applications. You can also cluster together groups of hosts running Linux containers, and Kubernetes helps you manage those clusters easily and efficiently. Kubernetes clusters can span hosts across public, private, or hybrid clouds. Kubernetes, therefore, is an ideal platform for hosting cloud-native applications that require rapid scaling, like real-time data streaming through Apache Kafka.

Kubernetes was originally developed and designed by engineers at the Google R & D center. Google was one of the early contributors to Linux container technology and has talked publicly about how everything at Google runs in containers. (This is the technology behind Google’s cloud services.) Google generates more than 2 billion container deployments a week, all powered by an internal platform: Borg. Borg was the predecessor to Kubernetes and the lessons learned from developing Borg over the years became the primary influence behind much of Kubernetes technology.

The primary advantage of using Kubernetes in your environment, especially if you are optimizing app dev for the cloud, is that it gives you the platform to schedule and run containers on clusters of physical or virtual machines (VMs). More broadly, it helps you fully implement and rely on a container-based infrastructure in production environments. And because Kubernetes is all about automation of operational tasks, you can do many of the same things that other application platforms or management systems let you do, but for your containers.

With Kubernetes you can:

  • Orchestrate containers across multiple hosts.
  • Make better use of hardware to maximize the resources needed to run your enterprise apps.
  • Control and automate application deployments and updates.
  • Mount and add storage to run stateful apps.
  • Scale containerized applications and their resources on the fly.
  • Declaratively manage services, which guarantees the deployed applications are always running the way you deployed them to run.
  • Health-check and self-heal your apps with auto-placement, auto-restart, auto replication, and autoscaling.

Containers are a good way to bundle and run your applications. In a production environment, you need to manage the containers that run the applications and ensure that there is no downtime. For example, if a container goes down, another container needs to start. Wouldn’t it be easier if this behavior was handled by a system? That’s how Kubernetes comes to the rescue! Kubernetes provides you with a framework to run distributed systems resiliently. It takes care of scaling and failover for your application provides deployment patterns and more. For example, Kubernetes can easily manage a canary deployment for your system.

Kubernetes provides you with:

  1. Service discovery and load balancing

Kubernetes can expose a container using the DNS name or using its own IP address. If traffic to a container is high, Kubernetes is able to load balance and distribute the network traffic so that the deployment is stable.

  1. Storage orchestration

Kubernetes allows you to automatically mount a storage system of your choice, such as local storage, public cloud providers, and more.

  1. Automated rollouts and rollbacks

You can describe the desired state for your deployed containers using Kubernetes, and it can change the actual state to the desired state at a controlled rate. For example, you can automate Kubernetes to create new containers for your deployment, remove existing containers, and adopt all their resources to the new container.

  1. Automatic bin packing

You provide Kubernetes with a cluster of nodes that it can use to run containerized tasks. You tell Kubernetes how much CPU and memory (RAM) each container needs. Kubernetes can fit containers onto your nodes to make the best use of your resources.

  1. Self-healing

Kubernetes restarts containers that fail, replaces containers, kills containers that don’t respond to your user-defined health check, and doesn’t advertise them to clients until they are ready to serve.

  1. Secret and configuration management

Kubernetes lets you store and manage sensitive information, such as passwords, OAuth tokens, and SSH keys. You can deploy and update secrets and application configuration without rebuilding your container images, and without exposing secrets in your stack configuration.