For many organizations, customer satisfaction, competitiveness, operational efficiency, and profitability all rely on secure and responsive applications. That in turn makes comprehensive network observability critical, because it’s impossible to manage, monitor or secure what you can’t see.
These facts are just as true when it comes to the cloud. Migrating and operating in the cloud can be a daunting prospect, where lack of visibility can cause service disruptions resulting in revenue loss and customer churn.
Notoriously Opaque Public Cloud
Yet cloud environments – particularly public cloud environments – can be notoriously opaque, making them effectively a “black box” for operations teams. This is problematic, as public cloud customers are still responsible for securing all data and applications in their respective virtual private cloud (VPC) environments. Understanding why visibility is difficult, and what to do about it, can thus be crucial to maintaining data integrity and application responsiveness in the cloud.
When it comes to network observability, both packet and flow data is critical. It provides the actionable visibility and data needed to thoroughly understand cyber-attacks, malware behavior, and the interactions between end-users, IoT devices, applications and services. But accessing network traffic can be challenging in public cloud environments. In fact, until recently it was impossible; traffic could be monitored in private corporate networks, but what happened once that data went into the public cloud was a mystery.
Traffic Forwarding Agents Or Using Log-Based Monitoring?
To compensate for this lack of visibility, companies use various hacks, such as deploying traffic forwarding agents (or container-based sensors) or using log-based monitoring. Both have limitations. Forwarding agents and sensors must be deployed for every instance and every tool – a costly IT management headache – or there is a risk of blind spots and inconsistent insight.
Event logging only provides snapshots in time, and even then, must be well-planned and instrumented in advance. Neither provides the high-quality, continuous or deep data needed to troubleshoot complex application, security or user experience issues. And as mentioned, there is significant cost involved.
Amazon, Google and Microsoft recognize the problems cause by this lack of visibility and have taken different paths to solving the challenge on their respective public cloud platforms.
AWS and Google Cloud use similar approaches: referred to as VPC traffic (AWS) or packet (GCP) mirroring service, which are available as part of their respective VPC offerings. Simply stated, this traffic/packet mirroring duplicates network traffic to and from the client’s applications and forwards it to cloud-native performance and security monitoring tool sets for assessment. This eliminates the need to deploy ad-hoc forwarding agents or sensors in each VPC instance for every monitoring tool. Compared to log data, it delivers much richer and deeper situational awareness.
Traffic or packet mirroring on its own isn’t sufficient, however. Just like the agent or sensor approach, it simply provides the access to raw packet data, basically creating the equivalent of a virtual Tap. This raw data is not quite ready to feed directly into monitoring and security tools and requires a virtual or cloud packet broker to handle the pre-processing operations to ensure the right data gets to the right tools.
Solving Visibility Challenge with Azure
Solving this visibility challenge with Azure requires a different approach: using what’s known as “inline mode” on certain virtual packet brokers. This allows the packet broker itself to monitor subnet ingress and egress traffic to capture, pre-process, and deliver packet data in real-time to security, performance management, analytics and other solutions. Importantly, this actually minimizes cloud visibility costs by eliminating unnecessary traffic mirroring.
Regardless of whether inline or non-inline, there’s much the virtual packet broker can do with the traffic. It can provide a lossless feed to a packet-to-flow gateway to generate flow data for those tools that prefer it, such as AIOps, ITOM or SIEM solutions. It can provide packet feeds for security tools that need to monitor the cloud environment, or facilitate packet capture to cloud storage for Network Detection and Response (NDR), or later forensic analysis.
As importantly, these solutions allow use of rich analytics when it comes to the public cloud. Tools that consume the fine-grain metadata extracted from the above middleware can in turn produce visualizations and dashboards that enable IT NetOps, SecOps, AppOps and CloudOps teams to effectively perform their jobs.
The high-quality metadata can also be exported to other tools such as threat detection, behavioral analytics and service monitoring solutions for monitoring, baselining, dependency-mapping and optimizing. This intra-cloud visibility also facilitates the application performance monitoring that’s critical when it comes to successfully migrating existing workloads to the cloud or deploying new cloud-first solutions.
However, you choose to get there, observability is critical for both strong security and improved user satisfaction in the cloud. On the security front it enables a robust posture by reliably delivering data and intelligence for rapid Network Detection and Response. Conversely, it bolsters satisfaction (and efficiency) by ensuring application availability and responsiveness.
All of which lowers operational risk while contributing to growth and profitability – the ultimate business benefit. Achieving high-fidelity network observability in Azure requires a slightly more complex solution than AWS or Google Cloud, but the benefits more than justify the additional coordination. You can find out more about such an observability solution here.