Data and cloud strategies must go hand in hand cloud yes, but please with plan!
The benefits of cloud for businesses of all sizes and industries are well known. The crisis year in particular has shown that digital transformation is only feasible with the cloud. But it’s not that simple. Companies first need a well thought-out data strategy and the right platform.
Companies on the topic
A good data platform correctly combines technical and business information and turns unused data into valuable information.
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Last year, digitization projects were implemented at an unprecedented speed, sometimes in just a few weeks. The cloud plays an important role in responding quickly to changing IT and customer needs. As a result, SaaS apps are usually easier to set up, use and manage than on-premises IT systems. And scaling cloud services is also easier than buying and setting up new hardware.
Cloud as a decisive success factor for digitization.
(Picture: Splunk)
By outsourcing services to the cloud, organizations can invest more time and resources to grow their business and accelerate development. Unfortunately, the migration to the cloud is often more complex than expected, because some apps and services still exist exclusively locally, while others can be outsourced to the cloud infrastructure. However, many, especially business-critical applications, need to be fundamentally redesigned or replaced in order to make them usable in the new, decentralized world – a not to be underestimated effort that requires time and care.
The migration to the cloud employs the entire IT team
Various challenges have to be overcome, because companies have to link their different systems together as comprehensively as never before – including numerous new dependencies and code changes and this virtually in real time. All of this requires DevOps developers who are available on demand and need to manage complex applications with up to thousands of interdependent micro-services. Security should also be ensured, not only locally, but across an ever-increasing number of locations, third-party applications and devices.
Even small errors in this design can lead to the costs escalating or – even worse – to system crashes, up to the total failure of the company. Companies therefore need a clear strategy to manage the complexity of cloud migration. The basis of this strategy is the company’s own machine data. Although data is collected on an ongoing basis, it is often not used profitably. In addition, data is now mostly scattered across many systems and endpoints. However, with the right data platform, the IT department can bring order to its flood of data.
Data platform scales as needed
The ideal data platform works regardless of how far the cloud migration has already progressed in the company. It also scales as needed to meet the growing needs of the organization. Effective protection of data flow from on-premises infrastructure to cloud infrastructure to cloud-based applications and services is also essential. With a data platform like Splunk’s Data-to-Everything platform, organizations can monitor their spending in real time, forecast costs, and identify inefficiencies.
In short: Companies benefit from the enormous cost advantages of the cloud. Security and IT teams use remote solutions to ensure productivity and services in changing global challenges. DevOps teams significantly improve your innovation rate and deliver an improved user experience. A good data platform combines the various data sources over any desired period of time and thus enables maximum transparency and full control of all data.
The right platform correctly combines technical and business information and turns unused data into valuable information that supports the business goal. Studies show that a mature data strategy has a positive impact, resulting in more revenue, lower operating costs, more innovation, faster time to market, and better customer satisfaction and loyalty.
Observability in the Cloud
The cloud also poses a challenge for monitoring. Traditional monitoring tools are overwhelmed with the sheer volume of services, applications, and infrastructure changes and cannot manage them. An application that consists of thousands of loosely coupled microservices and serverless functions that exist in multiple on-premises and cloud environments cannot be monitored with classic monitoring.
Modern observability solutions help teams visualize and analyze relevant performance metrics for infrastructure, services, and applications.
(Picture: Splunk)
In addition, they focus on already known dangers. However, the still unknown dangers are important for IT teams. Observability can do that. This “observability” is made possible by the comprehensive analysis, summary and presentation of all cloud-specific metrics, traces and logs. And this is the only way to see in real time when, where and why a problem occurs or is likely to occur. Security, IT operations and DevOps teams can monitor and analyze all relevant data in the Observability Cloud, for example, and take appropriate measures if necessary. For example, they can quickly deal with peaks in demand and immediately eliminate technical problems and possible security threats.
Matthias Maier, Data Evangelist, Splunk. (Picture: Geckeler Photography)
Splunk customer Lenovo uses the Observability Cloud for its own website and saw a clear difference, especially during the last Black Friday, as Ben Leong, Director of Online & Ecommerce Operations at Lenovo confirms: Splunk Observability has reduced the Mean time-to-Resolution (MTTR) from 30 to less than 5 minutes. This allowed 100 percent uptime to be maintained during Black Friday traffic, which was 300 percent higher than the previous year. Thus, with Splunk Observability, Lenovo’s operational efficiency, team collaboration and time for troubleshooting have been significantly improved.
* The author Matthias Maier is a data evangelist at Splunk Services Germany GmbH.
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