Managing the Complexity of Machine Data Storage

Managing the Complexity of Machine Data Storage

Managing the Complexity of Machine Data StorageManaging the Complexity of Machine Data Storage

Data storage can’t handle the capacity of future machine data. Without fast access to data analytics, it is hard to draw insights from growing volumes of data.

Determine How Much Storage Your Apps Will NeedDetermine How Much Storage Your Apps Will Need

Before updating your storage infrastructure, take a good look at your current demands in order to anticipate the individual storage requirements for each application.

Put Your IT Budget Into PerspectivePut Your IT Budget Into Perspective

What did you spend on storage last year? Did costs increase or decrease? How much of that spending supports machine data storage? Knowing how storage and machine data costs have affected IT spending over time can help set limits for current projects.

Consider the Storage Impact of Machine Data AnalyticsConsider the Storage Impact of Machine Data Analytics

More than 50% of investments in analytics applications are spent on storage to support the platform. If you can’t balance machine data demands with its projected growth, it will be hard to identify the true total cost of ownership.

Consider New Investments in Old-School HardwareConsider New Investments in Old-School Hardware

Storage hardware faces a serious challenge when scaled to support machine data growth. Leveraging the cloud and pay-as-you-grow models can open new doors—if you find a winning hybrid strategy tailored for your machine data.

Evaluate Public Cloud Services for ScalabilityEvaluate Public Cloud Services for Scalability

Moving some machine data to a public cloud can deliver flexibility and scalability, enabling you to increase and decrease storage capacity as needed. Since not all applications are suited for the cloud, determine which will apps thrive and which will fall flat.

Take a Hybrid ApproachTake a Hybrid Approach

Your company can benefit from the performance and security of on-premise infrastructure, plus the elasticity, scalability and economics of the cloud. But be sure there’s an easy way to move that data between hot, warm and cold storage so your data doesn’t get trapped in one location.

Don't Settle for a Quick FixDon’t Settle for a Quick Fix

Migrating machine data to the cloud can involve complex application rewrites, more high-bandwidth connectivity or the shipment of storage devices to cloud-connected data centers. Don’t settle for a quick fix when none of these make cloud adoption less complicated or more economical.

Try a Dedicated High-Speed NetworkTry a Dedicated High-Speed Network

Firms should automatically move workloads to the cloud (or any other location) with a simple click. Dedicated, single-hop, high-speed networks can provide the low latency, built-in data optimization, high throughput and security your data needs to be mobile, agile and available.

Gain an Advantage With Edge ComputingGain an Advantage With Edge Computing

Enterprises are moving data to the edge of their networks by leveraging metro-based data centers using tactics originally developed by content delivery networks. The result: Companies can realize the elasticity and economics of the cloud, plus the low latency and high availability of on-premise.

Partner With a Managed Services ProviderPartner With a Managed Services Provider

Most IT budgets can’t cover an entire in-house storage management team, so an MSP may be able to deliver the resources your team needs, such as dedicated network access, edge computing tactics and hybrid cloud strategies.

Karen A. Frenkel
Karen A. Frenkel
Karen A. Frenkel is a contributor to CIO Insight. She covers cybersecurity topics such as digital transformation, vulnerabilities, phishing, malware, and information governance.

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