Can Financial Services Teams Prove DORA Resilience Without Packet-Level Evidence?

DORA has changed operational resilience from a periodic compliance exercise into a daily responsibility for financial services teams. Banks, insurers, payment firms, investment firms, and ICT providers now need to show that risk management, incident response, third-party oversight, and monitoring are supported by clear evidence.

One of the biggest challenges is not policy creation, but proof. Logs, quarterly attestations, and self-reported telemetry often leave gaps, especially during incidents or across hybrid cloud, data center, branch, and containerized environments.

Some practical observations:
• Continuous ICT monitoring must cover every asset and flow
• Incident reconstruction needs evidence that survives a compromise
• Third-party and AI service usage must be visible in real time
• Encryption posture needs constant validation across systems
• Detection must happen fast enough to meet reporting timelines

The key takeaway is simple: DORA does not demand a specific technology. It demands continuous, defensible, and demonstrable resilience. Packet-level network visibility helps close that evidence gap by showing what is actually happening across the ICT environment.

Read the full guide to understand how packet-derived evidence can support stronger DORA compliance workflows. https://aviznetworks.com/guide/cisos-guide-to-dora-compliance-in-financial-services/download

Comments

Post a Comment

Popular posts from this blog

"AI Is Just Another Phase… Right?" 5 Myths About AI for NetOps

Image
I recently went through a detailed discussion around AI in network operations, specifically focused on the skepticism many engineers have seen before with previous technology waves. Some practical observations: • Most networks already generate large volumes of telemetry, logs, and tickets, but correlation remains manual • Troubleshooting often requires switching between multiple vendor tools and systems • AI becomes useful when it can read across telemetry, configurations, and tickets in one workflow • Vendor-specific AI tools are limited to their own ecosystems • A platform approach allows teams to build workflows tailored to their environment One misconception addressed was that AI is just another layer on top of existing tools. In practice, its value comes from connecting data across silos and providing answers that engineers can act on. Another key point was around build versus buy. Building everything internally provides control but creates long-term maintenance overhead. Usin...
Read more

Evolving Packet Brokering for Modern Network Observability

Image
  I recently reviewed a technical overview describing how packet brokering platforms are evolving to support large-scale observability in modern data centers and service provider networks. The discussion focused on scalability, automated deployment, and operational efficiency. Some practical observations: • Network visibility platforms are expanding support for 400G switching hardware used in modern data center fabrics • GRE encapsulation enables mirrored traffic to move across Layer-3 networks while preserving packet metadata • Zero-Touch Provisioning simplifies onboarding for new or factory-reset switches • Packet brokers aggregate traffic from TAPs and SPAN ports and apply filtering and distribution policies • CLI improvements help operators manage large monitoring environments more efficiently One notable element was how GRE tunneling extends observability beyond Layer-2 boundaries. By encapsulating mirrored traffic into GRE tunnels, monitoring systems can receive full packet c...
Read more

How Network Copilot Uses Agentic AI to Correlate FortiGate and Splunk

Image
I recently went through a detailed implementation explaining how Network Copilot correlates FortiGate firewall telemetry with operational data indexed in Splunk . What stood out was how grounded the discussion was in real operational workflows rather than theoretical AI claims. Some practical observations: • Network and security logs are typically distributed across multiple platforms • Troubleshooting often requires manually correlating events between systems • Network Copilot ingests metrics, events, logs, and traces from firewall environments • Operators can interact with the system using natural language questions • Explainable root cause analysis improves operational confidence One misconception addressed during the walkthrough was that AI in operations means replacing engineers. In reality, the system augments teams by surfacing insights faster and correlating information across environments. Another interesting point was how the platform learns from real firewall deployments...
Read more