Detect Lateral Movement Faster and Expose All Blind Spots in the Hybrid Cloud

Let’s face it — moving to the cloud is not just a fancy IT project anymore; it is the reality for most businesses. But with all the perks come some serious headaches, especially when it comes to security. Think of it like moving into a house with tons of rooms but leaving some windows open. Not ideal, right? The point being that the cloud service providers are responsible for security of the cloud infrastructure, but the customers are responsible for ensuring that their workloads running on that infrastructure are fully secure and monitored. Gigamon helps you serve as your extra set of eyes and ears in the cloud, making sure no sneaky cyber threats slip through the cracks — with GigaVUE® Enriched Metadata (GEM) for Cloud Workloads.

What’s the Problem Here?

As businesses move to multi-cloud environments, security risks increase, making it easier for cybercriminals to exploit sensitive data like customer info and financial records. Advanced persistent threats (APTs) often go undetected due to limited visibility into lateral traffic, and insider threats add further complexity. For teams managing these environments, identifying performance issues, optimizing resources, and ensuring compliance are all difficult due to the dynamic nature of cloud services.

GEM for Cloud Workloads in Action: A Real-World Example

Imagine you are part of a security operations team, and your organization just moved to the cloud. You are monitoring traffic, but all of a sudden, you notice a slight slowdown in performance. A regular day, right? Not quite. What you didn’t see is a hacker sneaking in through lateral traffic, using malware to establish control. Without proper visibility, you would not even know this happened. GEM for Cloud Workloads helps avoid these disasters by giving you deep insight into all your cloud traffic, providing the extra context you need to catch threats early.

Why It Matters to You

Here’s the kicker — GEM for Cloud Workloads doesn’t just give you comprehensive visibility; it also cuts down on the time it takes to detect and respond to threats. We are talking exponential time shaved off from the moment you notice something fishy to when you resolve it. In an age where a few minutes can cost millions (or your reputation), this matters big time.

Also, if you have ever had to manage cloud resources, you need to scale up when needed but not overdo it, or you are wasting money. GEM for Cloud Workloads helps make this easier by optimizing resource allocation and keeping your cloud running smoothly without surprise costs.

The Payoff: A Closer Look with Use Cases

With GEM for Cloud Workloads, you are not just keeping the bad guys out — you are also making your life easier. Whether you are in CloudOps, DevOps, CloudSecOps, or Cloud SOC, GEM for Cloud Workloads provides a correlated feed with business context to monitor traffic, identify performance bottlenecks, and ensure compliance without losing sleep over what is happening in your cloud environment.

GEM for Cloud Workloads provides additional context enrichment to the Gigamon Application Metadata Intelligence L2 to L7 network traffic metadata. It uses APIs as a source from cloud applications such as VMware, AWS, Azure, versus only packets as a source, ingests that data into the Gigamon Deep Observability Pipeline where the ‘enrich’ function derives the additional context such as host environment details and feeds the enriched metadata into your security, observability tools.

Faster Threat Detection: GEM for Cloud Workloads taps into network-derived metadata, giving security teams real-time insights into cloud traffic. This enriched data enables faster detection of Advanced Persistent Threats (APTs) and helps reduce Mean-Time-To-Detect (MTTD) and Mean-Time-To-Respond (MTTR).

Use Case: A potential data breach because of misconfigured WAF, and excessive permissions granted to it by the user. There was no flag raised for the misconfigured IAM policy. GEM for Cloud Workloads enables the user to monitor traffic based on the tagging policy and hence, could set up an alert when there is traffic exchange between the web app and cloud object storage that the attacker is trying to access. Users with GEM for Cloud Workloads can also pinpoint the security group of web application and object storage, raising alert on suspicious connections.

Enhanced Cloud Performance: Managing cloud resources is a constant balancing act, but GEM for Cloud Workloads simplifies things by centralizing performance metrics. It helps CloudOps and DevOps teams optimize workloads, reduce over-provisioning, and identify performance bottlenecks.

Use Case: A distributed app slows down, but the team doesn’t know why. GEM for Cloud Workloads provides real-time performance data, showing exactly where the bottleneck occurs, helping teams fix it fast.

Compliance and Governance: Ensuring that your cloud environment meets security policies and regulatory requirements can be a pain. GEM for Cloud Workloads makes it easier by providing deep observability into all network traffic, making audits smoother and reducing compliance risks.

Use Case: During a security audit, a company must demonstrate that all sensitive data transfers are secure. GEM for Cloud Workloads provides enriched metadata, proving compliance and helping avoid hefty fines.

“Modern application environments are highly distributed, and the use of multiple public/private cloud environments is commonplace. As a result, operations teams (Cloud, Dev, Sec, Net, etc.) require solutions with API access across the public/private cloud ecosystem to ensure the requisite level of observability into these workloads, enabling operations teams to optimize performance and security while also ensuring compliance.”
— Bob Laliberte, Principal Analyst, theCUBE Research

In essence, GEM for Cloud Workloads is the solution that turns the complex hybrid cloud landscape into something you can manage and secure confidently—without burning out your team. It is a win-win for both security and operational efficiency. CloudOps and DevOps teams have common goals for monitoring and troubleshooting performance and latency issues and monitoring the cost of their environments. GEM for Cloud Workloads can help to provide deep observability not only with reference to the various applications they monitor, but also with reference to the various environments and locations they manage.

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