Automating Information Management

The exponential growth of data is driving efforts to reduce redundant, obsolete, or trivial data, also known as ROT. Nyxeia products simplify ROT reduction, with a single interface that scans documents across the network. Using natural language processing (NLP), text pattern matching, and context matching, Nyxeia analyzes metadata as well as document text to identify duplicates, saving valuable time, money, and tedious manual effort.

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Machine Learning and Natural Language Processing

Governing terabytes or even petabytes of data requires automatic classification. Discover uses artificial intelligence to enhance metadata, create structured information out of unstructured data, and rapidly tag and classify millions of documents automatically, wherever they live. This enables organizations to mitigate risk, enhance efficiency, and lower IT costs.

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Open Source Security And Risk Analysis Report

Synopsys helps development teams build secure, high-quality software, minimizing risks while maximizing speed and productivity. Synopsys, a recognized leader in application security, provides static analysis, software composition analysis, and dynamic analysis solutions that enable teams to quickly find and fix vulnerabilities and defects in proprietary code, open source components, and application behavior.

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Navigating the Open Source Risk Landscape

Open source use isn’t risky, but unmanaged use of open source is.

Open source software forms the backbone of nearly every application in every industry. Chances are that includes the applications your company develops as well. If you can’t produce an accurate inventory of the licenses, versions, and patch status of the open source components in your applications, it’s time to assess your open source management policies.

This paper provides insights and recommendations to help organizations and their development and IT teams better manage the open source risk landscape. It covers:

  • Open source license risk and the need to identify and catalog open source licenses
  • Security risk that comes with open source use and inadequate vulnerability management
  • Operational open source risk, version control, and the dangers of using inactive components

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The DIY Guide to Open Source Vulnerability Management

According to SAP, more than 80% of all cyber attacks are happening on the application layer,1 specifically targeting software applications rather than the network.

Hackers take the easiest path when determining exploits and choose applications that offer the best attack surface opportunities. Those opportunities are generally created by unpatched or outdated software.

For example, Heartbleed, a dangerous security flaw, critically exposes OpenSSL, an open source project used in hundreds of thousands of applications that need to secure communications over computer networks against eavesdropping. Yet 56% of all OpenSSL versions that Cisco Security Research examined in its 2015 security report2 were still vulnerable to Heartbleed, more than two years after the Heartbleed vulnerability was first disclosed and a patched version issued.

This illustrates the difficulty organizations have in inventorying and managing open source components rather than a lack of security diligence. Without a comprehensive list of open source components in use, it is nearly impossible for any organization to identify specific applications that use vulnerable components.

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Know Your Code: Don’t Get Blindsided by Open Source Security Risks During Development

Application security is a strategic imperative for organizations developing internal and public-facing software. Exploits of software security vulnerabilities can result in loss of customer or company information, disruption of business operations, damage to public image, regulatory penalties, and costly litigation.

Adding to the management challenge, the software development life cycle (SDLC) is increasingly complex. Demands for agility and faster time to market, distributed development teams, and rapidly evolving languages and technologies are all contributing factors.

To remain competitive, development teams increasingly rely on open source software—cost-effective, reusable software building blocks created and maintained by global communities of developers.

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Navigating the Open Source Risk Landscape

Open source use isn’t risky, but unmanaged use of open source is.

Open source software forms the backbone of nearly every application in every industry. Chances are that includes the applications your company develops as well. If you can’t produce an accurate inventory of the licenses, versions, and patch status of the open source components in your applications, it’s time to assess your open source management policies.

This paper provides insights and recommendations to help organizations and their development and IT teams better manage the open source risk landscape. It covers:

  • Open source license risk and the need to identify and catalog open source licenses.
  • Security risk that comes with open source use and inadequate vulnerability management.
  • Operational open source risk, version control, and the dangers of using inactive components.

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2019 Open Source Security And Risk Analysis

Can you say with confidence that the open source components used in your applications are up-to-date with all crucial patches applied? It’s impossible to patch software when you don’t know you’re using it.

The 2019 OSSRA report offers an in-depth look at the state of open source security, compliance, and code quality risk in commercial software. Based on the anonymized data of over 1,200 audited codebases, this report provides:

  • The latest insights and surprising statistics about open source security and license risk.
  • The components most likely to have identified vulnerabilities.
  • Six key recommendations to improve your application risk management processes.

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The Future of IT Ops is Autonomous

Today’s IT stack is more complex and more dynamic than ever before. This means that IT Ops teams must support both the legacy infrastructure accumulated over the years, and modern, ephemeral technologies mandated by cloud-first architectures. Stretched thin, and relying on legacy IT Ops tools, IT Ops teams are unable to effectively do this, resulting in a rising tide of outages, poor app performance and service disruptions. This takes a toll on the business, IT leaders and IT Ops teams.

What’s the answer? Artificial Intelligence (AI) and Machine Learning (ML). AI and ML can help IT Ops teams handle and resolve IT problems at scale, by intelligently automating various aspects of IT incident management. But that’s not all. Over time, as IT Ops teams and enterprises experience the benefits of automation, IT Ops will be able to move from simple automation to a more autonomous mode of operation. In this white paper, noted industry analyst Nancy Gohring from 451 Research describes how AI and ML help drive automation in IT Ops, why IT Ops will move from automation to autonomous over time, and key considerations for IT leaders as they embrace automation and autonomous operations.

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The Future of IT Ops is Autonomous

Today’s IT stack is more complex and more dynamic than ever before. This means that IT Ops teams must support both the legacy infrastructure accumulated over the years, and modern, ephemeral technologies mandated by cloud-first architectures. Stretched thin, and relying on legacy IT Ops tools, IT Ops teams are unable to effectively do this, resulting in a rising tide of outages, poor app performance and service disruptions. This takes a toll on the business, IT leaders and IT Ops teams.

What’s the answer? Artificial Intelligence (AI) and Machine Learning (ML). AI and ML can help IT Ops teams handle and resolve IT problems at scale, by intelligently automating various aspects of IT incident management. But that’s not all. Over time, as IT Ops teams and enterprises experience the benefits of automation, IT Ops will be able to move from simple automation to a more autonomous mode of operation. In this white paper, noted industry analyst Nancy Gohring from 451 Research describes how AI and ML help drive automation in IT Ops, why IT Ops will move from automation to autonomous over time, and key considerations for IT leaders as they embrace automation and autonomous operations.

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Use AIOps for a Data-Driven Approach

Having multiple monitoring tools often inhibits the collaboration that is critical to resolving problems quickly. What's the answer? AIOps tools.

AIOps tools, or IT Ops tools powered by AI and ML, provide a consistent view of monitoring data. This helps I&O leaders improve collaboration and resolution times, support internal service owners and delight external customers.

Download this Gartner report to learn more.

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Market Guide for AIOps Platforms

AIOps platforms enhance IT operations through greater insights by combining big data, machine learning and visualization. I&O leaders should initiate AIOps deployment to refine performance analysis today and augment to IT service management and automation over the next two to five years.

But which AIOps platforms can you trust, and which ones should you consider? Download this Gartner report to learn more.

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IT Ops reporting is broken

This is a serious problem for IT execs.

They need to transform IT Ops to catch up with software and infrastructure modernization. In order to transform IT Ops, they must have easy and ready access to insight-rich, actionable IT Ops performance reports and analytics. But because IT Ops reporting is broken, there’s no easy way to do that.

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Can AIOps Reduce The Noise?

If you’re part of an IT Ops or NOC team, or if you manage one, you know that overwhelming IT noise is your #1 enemy. Flooded with false positives overwhelming IT noise means that IT Ops and NOC teams are flooded with false positives on an everyday basis. The problem gets significantly worse when outages and disruptions cause alert storms or alert floods and NOC techs and engineers can't isolate root cause.

Can AIOps tools, or IT Ops tools powered by AI and ML, help?

Download this solution brief to learn more.

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