On October 9, 2025, when Azure Front Door failed, security leaders across industries weren’t just worried about uptime — they were flying blind.
Administrators were locked out of the Azure Portal. Entra ID authentications failed.
Just eleven days later, an AWS DNS error in us-east-1 triggered a 15-hour outage that rippled across dependent services worldwide.
In both cases, infrastructure went dark. And for organizations running their security operations centers (SOCs) and SIEMs within those same cloud ecosystems, visibility disappeared too.
We’ve long treated multi-cloud redundancy as non-negotiable for application resilience. Yet we rarely apply that same rigor to security visibility.
When your SIEM sits inside the infrastructure it’s meant to monitor, you’ve built a single point of failure into your defensive core.
It’s not a hypothetical risk — it’s a structural one. And it’s time security leaders addressed it with the same urgency as business continuity.
This isn’t just an IT operations concern — it’s a board-level resilience issue.
The question executives now ask isn’t “Are we in the cloud?” but “Can we operate securely if one of our clouds fails?”
When your SIEM provider suffers the outage, your mean time to respond (MTTR) becomes undefined.
You can’t investigate, contain, or communicate.
Regulators are starting to take note. The European Banking Authority has already issued guidance around “concentration risk” — the exposure created when critical systems depend on a single cloud provider.
Similar attention is emerging in the U.S. through the FFIEC and NIST SP 800-34 frameworks, both underscoring operational continuity as a measurable security outcome.
The irony is sharp: the more “native” your tooling, the more exposed you become.
If your SOC runs on Azure Sentinel and Azure’s authentication layer fails, your visibility fails with it.
Auditors will soon begin asking for proof that your security monitoring is both independent and resilient.
The takeaway: security visibility now falls under the same regulatory scrutiny as uptime.
The problem isn’t only architectural — it’s economic.
Legacy SIEMs like Splunk and QRadar were built for on-prem data volumes and static infrastructures. Today, they’ve become both technically outdated and financially punitive.
Security leaders face two simultaneous battles:
According to Gartner — a figure still widely cited by industry sources such as Atlassian — the average downtime cost at $5,600 per minute, amplifying the financial risk of delayed response.
Yet legacy economics keep teams flying blind to save on ingestion.
It’s a model that financially disincentivizes good security hygiene — and it’s no longer sustainable.
Recognizing this, many organizations are replacing their legacy SIEMs. But a new trap has emerged: ecosystem lock-in disguised as “next-gen” modernization.
Platforms like Palo Alto XSIAM and CrowdStrike Falcon offer sleek detection pipelines and strong XDR capabilities — but their architectures and commercial models favor their own telemetry.
They work brilliantly if you commit to the full stack.
Try to integrate third-party data at scale, and you’ll discover hidden penalties in both cost and complexity.
The security leader’s litmus test is simple:
“What’s my five-year TCO if I keep my current best-of-breed EDR, identity, and network stack?”
If the answer involves heavy integration fees or punitive data pricing, you’ve found the new walled garden.
Security operations need a platform — not a prison.
That’s where Google SecOps offers a fundamentally different approach: open, data-agnostic, and engineered for resilience.
Built originally as Chronicle, it was designed from day one to ingest petabytes of data from any source — AWS, Azure, Palo Alto, CrowdStrike, or on-prem. It doesn’t care whose logo is on the log.
And its pricing model reflects that openness: flat-rate, per-terabyte ingestion — predictable, scalable, and transparent. No hidden ingest penalties.
A Forrester TEI Study found that organizations adopting Google SecOps achieved 240 % ROI and over $1.2 M in savings compared to legacy SIEM costs.
It decouples your SOC from your infrastructure provider. If one cloud goes down, your visibility remains intact.
No ingest penalty means you can finally “ingest it all.” Every log. Every flow. Every identity event.
Data is normalized at ingest — your AWS.user_principal and Azure.UserPrincipalName become one schema.
Unified context = faster detection, better automation.
Gemini (Google’s AI) isn’t bolted on; it’s foundational.
L1 analysts cut triage from 30 minutes to 3 — a 90% reduction — with AI-driven summaries.
L3 hunters query natural language:
“Find all failed logins from North Korea to admin accounts in the last six months.”
Sub-second search. Cross-platform visibility.
Gemini now analyzes malware scripts, summarizes complex incidents, and even secures generative-AI workloads.
The SOC of the future won’t just detect — it will reason.
Technology alone doesn’t deliver resilience — execution does.
A platform this powerful isn’t plug-and-play; it’s operational transformation.
That’s where Foresite comes in.
As a Google Cloud Premier SecOps Partner, we’ve helped hundreds of organizations move from legacy systems and cloud lock-ins to modern, multi-cloud security operations built on Google SecOps.
Foresite has already done the hard work.
For one Fortune 500 manufacturer, we helped migrate 40TB of SIEM data to Google SecOps in 90 days — reducing MTTR by 70% and cutting SIEM spend in half within the first year.
That’s the last mile: where technology becomes outcome.
Where security becomes operational resilience.
An outage in your IaaS shouldn’t mean a blackout for your security team. Visibility shouldn’t vanish when your provider stumbles.
The next generation of security operations will be defined not by uptime alone, but by autonomy — the ability to see, decide, and act even when everything else is dark.
That’s what Google SecOps makes possible.
That’s what Foresite delivers.