IBM Case Studies Major retailer reduces time to patch 27,000 endpoints from weeks to hours

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	Major retailer reduces time to patch 27,000 endpoints from weeks to hours IBM

Major retailer reduces time to patch 27,000 endpoints from weeks to hours

IBM

Technology Category	Platform as a Service (PaaS) - Device Management Platforms
Applicable Industries	Retail
Use Cases	Inventory Management
Services	Cloud Planning, Design & Implementation Services
Challenge	The leading national retail chain, with over 3,000 stores and 27,000 endpoints, was looking to streamline and automate its daily tasks required to control its servers, including provisioning, configuration management, and inventory of hardware and software. The company was using a legacy IBM solution that required manual registration of clients before they could be controlled. The retailer was interested in IBM’s latest offering for managing servers and hoped that the new solution would help streamline and automate the daily tasks required to control its servers. Read More
About Customer	The customer is one of the largest retailers in the United States, with 2013 revenue of more than USD100 billion, and over 3,000 stores staffed by 343,000 full-time associates. Each store depends on Virtual Store Architecture (VSA) as its computing platform. The VSA at each store consists of two IBM blade servers hosting at least five virtual machines (VMs) and sometimes more, for an enterprise total of 27,000 endpoints. In the company’s data center, a two-person IT team centrally manages all automation functions for VSA, using a legacy IBM solution. Read More
Solution	The company deployed the IBM BigFix solution because it enabled near-real-time visibility into the state of systems. IBM assisted with solution migration planning. The client then deployed the BigFix agent into its VSA infrastructure to achieve near-real-time visibility into the state of its servers. The IBM BigFix solution uses a bottom-up model so that when a client comes online, the agent automatically reports on its status. In contrast, the legacy solution used a top-down model, where clients had to be registered manually before they could be controlled. Read More Log in to view content
Contents

Technology Category

Platform as a Service (PaaS) - Device Management Platforms

Applicable Industries

Retail

Use Cases

Inventory Management

Services

Cloud Planning, Design & Implementation Services

Challenge

The leading national retail chain, with over 3,000 stores and 27,000 endpoints, was looking to streamline and automate its daily tasks required to control its servers, including provisioning, configuration management, and inventory of hardware and software. The company was using a legacy IBM solution that required manual registration of clients before they could be controlled. The retailer was interested in IBM’s latest offering for managing servers and hoped that the new solution would help streamline and automate the daily tasks required to control its servers.

About Customer

The customer is one of the largest retailers in the United States, with 2013 revenue of more than USD100 billion, and over 3,000 stores staffed by 343,000 full-time associates. Each store depends on Virtual Store Architecture (VSA) as its computing platform. The VSA at each store consists of two IBM blade servers hosting at least five virtual machines (VMs) and sometimes more, for an enterprise total of 27,000 endpoints. In the company’s data center, a two-person IT team centrally manages all automation functions for VSA, using a legacy IBM solution.

Solution

The company deployed the IBM BigFix solution because it enabled near-real-time visibility into the state of systems. IBM assisted with solution migration planning. The client then deployed the BigFix agent into its VSA infrastructure to achieve near-real-time visibility into the state of its servers. The IBM BigFix solution uses a bottom-up model so that when a client comes online, the agent automatically reports on its status. In contrast, the legacy solution used a top-down model, where clients had to be registered manually before they could be controlled.

Impact #1	The new solution has simplified many tasks but especially software distribution and configuration management.
Impact #2	It’s also much easier to collect inventory on 27,000 endpoints for compliance purposes.
Impact #3	Near-real-time insights enable the team to identify software and hardware versions on endpoints before rolling out changes.

Impact #1

The new solution has simplified many tasks but especially software distribution and configuration management.

Impact #2

It’s also much easier to collect inventory on 27,000 endpoints for compliance purposes.

Impact #3

Near-real-time insights enable the team to identify software and hardware versions on endpoints before rolling out changes.

Benefit #1	In the prior environment, it took 2,400 staff hours to deploy software on 1,500 endpoints. Now, it takes just 32 hours.
Benefit #2	More than 59 weeks of staff time have been reclaimed so that the team can work on more valuable tasks.
Benefit #3	Four days of staff work have been reduced to 10 minutes for inventory collection.

Benefit #1

In the prior environment, it took 2,400 staff hours to deploy software on 1,500 endpoints. Now, it takes just 32 hours.

Benefit #2

More than 59 weeks of staff time have been reclaimed so that the team can work on more valuable tasks.

Benefit #3

Four days of staff work have been reduced to 10 minutes for inventory collection.

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Overview

Major retailer reduces time to patch 27,000 endpoints from weeks to hours

Operational Impact

Quantitative Benefit