Kubernetes improves data management strategies

To meet data requirements, customers choose modern application deployment and administration across multiple clouds and clusters; however, this composite architecture greatly complicates the management of these applications and the data they store. Faced with growing demand for innovative features, faster data analysis, and faster software deployment, everyone is looking to collect as much actionable information as possible.

With the rapid acceleration of cloud computing, enterprises must be able to manage these new workloads while leveraging the added value of their data. They have a turnkey solution available: Kubernetes, an open source system that now powers more than three-quarters of containerized applications, according to a report. Therefore, companies need to understand how containers and Kubernetes can help them modernize and succeed by providing them with automation features and strategic insights.

Get strategic insights with Kubernetes

To get the most out of this strategic information, companies need to think about a method that will enable them to optimize data management, data protection and services. Thus, the Kubernetes data management platform can enter the market. Once installed, Kubernetes greatly improves collaboration and allows DevOps teams to do what they want so they can focus on innovation rather than monotonous day-to-day management and maintenance tasks.

Why should organizations choose Kubernetes? With this powerful platform that can easily run cloud applications, digital innovators can quickly extract strategic insights from their data and capitalize on actionable elements to accelerate development as well as launch production. In fact, they encourage creativity and increase productivity in their departments.

Kubernetes evolves with modern applications

Whether it’s privately or professionally, we all rely on modern applications. Therefore, it is not surprising that companies are emphasizing the development and availability of such applications in their future strategies.

Modern applications, sometimes consisting of tens or even hundreds of microservices, are often supported by one or more data services such as databases, artificial intelligence or machine learning pipelines, search or streaming, and message queues.

Managing so many services turns out to be very complex, and this complexity is especially evident when observing the number of database instances that need to be managed and adapted to suit different environments.

By automating simple and repetitive tasks, a unified platform for managing data services in Kubernetes helps simplify day-to-day operations. Thus, it can analyze data in real time and act according to different situations, individually or simultaneously.

On the contrary, with their semi-annual updates and noticeably slow deployment operations, legacy and monolithic architectures make it difficult to get data that can be used. For corporate IT departments tired of relying on such slow processes, modern applications are a lifesaver.

Refrain from bribing microservices with micromanagement

By building applications based on microservices, many organizations have been able to adopt a DevOps culture and distribute members of very large teams to more cohesive teams tasked with running those applications.

However, these DevOps teams may find it difficult to create and run these microservices, for example, when creating a package of applications designed to be deployed in any type of environment, in particular on a developer’s laptop.

To solve this problem, the solution would be to use containers, which, however, implies the need to ensure their constant management. This is where Kubernetes comes into play.

Innovate by deploying Kubernetes

To succeed, the company now relies on four well-defined criteria: speed, reliability, flexibility and scalability. Thus, by combining shared containers with Kubernetes, companies can create a single, easy-to-use management platform that simplifies collaboration between operations and development teams.

If, on the one hand, flexible and thorough data management speeds up decision making, then poor data management can, on the other hand, negatively affect the work of teams.

Adding more efficient and manageable self-service automation capabilities allows companies to help their DevOps teams focus on innovation and better meet operational needs rather than keeping systems up and running.

Kubernetes provides a crystal-clear, more efficient and flexible data management environment, and plans to provide the ability to extract more business-critical insights from data in the future.

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