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									IBM QRadar Reviews - Welcome to Stackinsight community. Join the discussion about products and tools for work Forum				            </title>
            <link>https://communities.stackinsight.net/community/cyber-ibm-qradar/</link>
            <description>Welcome to Stackinsight community. Join the discussion about products and tools for work Discussion Board</description>
            <language>en-US</language>
            <lastBuildDate>Sun, 15 Nov 2026 10:02:13 +0000</lastBuildDate>
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							                    <item>
                        <title>Thoughts on IBM&#039;s push towards QRadar SaaS? Are they letting on-prem rot?</title>
                        <link>https://communities.stackinsight.net/community/cyber-ibm-qradar/thoughts-on-ibms-push-towards-qradar-saas-are-they-letting-on-prem-rot-2/</link>
                        <pubDate>Sat, 26 Sep 2026 01:40:46 +0000</pubDate>
                        <description><![CDATA[Seeing the account team&#039;s new &quot;strategic direction&quot; slides. All the investment is flowing to QRadar SaaS. Roadmap calls it the future, on-prem is &quot;legacy.&quot; Support renewals are up 20% while ...]]></description>
                        <content:encoded><![CDATA[Seeing the account team's new "strategic direction" slides. All the investment is flowing to QRadar SaaS. Roadmap calls it the future, on-prem is "legacy." Support renewals are up 20% while critical on-prem patches are delayed for months.

We're locked into a three-year ELA. My question is simple: is this a deliberate starvation tactic to force a costly migration? Anyone else getting pressured while their on-prem deployment's feature gap widens? The TCO math for SaaS over 5 years looks brutal once you factor in data ingestion and retention.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-ibm-qradar/">IBM QRadar Reviews</category>                        <dc:creator>doray</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-ibm-qradar/thoughts-on-ibms-push-towards-qradar-saas-are-they-letting-on-prem-rot-2/</guid>
                    </item>
				                    <item>
                        <title>Moved from AlienVault to QRadar - 3 month deployment diary</title>
                        <link>https://communities.stackinsight.net/community/cyber-ibm-qradar/moved-from-alienvault-to-qradar-3-month-deployment-diary-2/</link>
                        <pubDate>Fri, 25 Sep 2026 22:50:53 +0000</pubDate>
                        <description><![CDATA[Hey folks, been lurking for a while. I&#039;m new to the whole SIEM game, but my team recently finished moving from AlienVault USM (on-prem) to QRadar over the last quarter. Wanted to share how i...]]></description>
                        <content:encoded><![CDATA[Hey folks, been lurking for a while. I'm new to the whole SIEM game, but my team recently finished moving from AlienVault USM (on-prem) to QRadar over the last quarter. Wanted to share how it went for other beginners.

The setup was... intense. Took way longer than we thought. Getting the log sources right was the hardest part. The QRadar docs are huge but finding the simple "do this first" steps was tricky. Also, the pricing model change was a big adjustment for us. On the plus side, the correlation rules feel much more powerful. I'm still figuring out the dashboards though. Anyone else made a similar jump and have tips for cost tracking or must-have custom rules?]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-ibm-qradar/">IBM QRadar Reviews</category>                        <dc:creator>cloud_infra_rookie</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-ibm-qradar/moved-from-alienvault-to-qradar-3-month-deployment-diary-2/</guid>
                    </item>
				                    <item>
                        <title>Switched from Splunk ES to QRadar. The log normalization is better, but the search feels slower.</title>
                        <link>https://communities.stackinsight.net/community/cyber-ibm-qradar/switched-from-splunk-es-to-qradar-the-log-normalization-is-better-but-the-search-feels-slower/</link>
                        <pubDate>Fri, 25 Sep 2026 17:26:16 +0000</pubDate>
                        <description><![CDATA[Just finished my annual migration ritual. This time, it was out of Splunk Enterprise Security and into IBM&#039;s QRadar. My team thinks I&#039;m insane, but they&#039;ve stopped asking why. The usual susp...]]></description>
                        <content:encoded><![CDATA[Just finished my annual migration ritual. This time, it was out of Splunk Enterprise Security and into IBM's QRadar. My team thinks I'm insane, but they've stopped asking why. The usual suspects drove the change: escalating Splunk license costs, the constant data volume calculus, and a vague promise from an IBM rep about "superior log normalization."

So, here's the six-month verdict, because that's about as long as my patience lasts before I start evaluating the next thing.

The good, which is genuinely good: The log normalization is, in fact, superior. Out of the box, QRadar does a much more consistent job of parsing disparate log sources into a common schema. With Splunk ES, I always felt like I was building or heavily tweaking CIM-compliant props/transforms until the end of time. QRadar's DSM editor is clunky, but once a source is configured, the fields are just... there. Universal and reliable. My security analysts spend less time arguing about field names and more time (theoretically) hunting threats. The offense management workflow also feels more logically integrated with the normalized data, which is a win.

Now, the glaring trade-off that has me side-eyeing my infrastructure: the search feels like wading through treacle. It's not just "a bit slower." It's a fundamentally different paradigm.

*   In Splunk, I could throw any wild, poorly-optimized, ad-hoc search at a massive time range and get *something* back in seconds, then refine. It felt immediate, even if it was brutalizing the indexers.
*   QRadar's AQL (Ariel Query Language) is powerful, but it demands reverence. You must structure your queries with care, think about JOINs, and gods help you if you don't pay attention to your time windows. The performance cliff is real and sudden. What feels like a simple "show me all events from this IP" can grind if you haven't set your ranges right.

It feels like I traded ad-hoc investigative speed for data consistency. For compliance and standardized reporting, QRadar's approach might be "better." For chasing down a live incident? I find myself missing Splunk's raw, chaotic speed. The console itself also contributes to the sluggish perception—it's less responsive than Splunk's web interface.

So, my question for the room isn't "which is better?"—we all know that's a religious war. My specific queries are for the QRadar veterans:

*   What are the non-obvious AQL optimization tricks you've learned to make ad-hoc searches feel less painful? Beyond the basic "limit your time window," are there specific clauses or patterns that avoid performance pitfalls?
*   Is the perceived search latency primarily a function of how QRadar's data stores are architected versus Splunk's, or is it often a deployment/configuration issue (e.g., not enough Ariel nodes, poor retention tuning)?
*   Does anyone run them in tandem? Using QRadar for normalized alerting and compliance, but piping specific raw logs to a smaller Splunk instance for deep-dive forensic speed? Or is that just the fantasy of a chronic hoarder who can't let go?]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-ibm-qradar/">IBM QRadar Reviews</category>                        <dc:creator>crm_hopper_2027</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-ibm-qradar/switched-from-splunk-es-to-qradar-the-log-normalization-is-better-but-the-search-feels-slower/</guid>
                    </item>
				                    <item>
                        <title>QRadar vs FortiSIEM for a mid-sized MSP. Which is easier to manage at scale?</title>
                        <link>https://communities.stackinsight.net/community/cyber-ibm-qradar/qradar-vs-fortisiem-for-a-mid-sized-msp-which-is-easier-to-manage-at-scale-2/</link>
                        <pubDate>Fri, 25 Sep 2026 09:01:06 +0000</pubDate>
                        <description><![CDATA[We run pipelines for dozens of client environments. Need a SIEM that doesn&#039;t create more work for our DevOps team. Evaluating QRadar and FortiSIEM for log aggregation and alerting across ~20...]]></description>
                        <content:encoded><![CDATA[We run pipelines for dozens of client environments. Need a SIEM that doesn't create more work for our DevOps team. Evaluating QRadar and FortiSIEM for log aggregation and alerting across ~200 client instances.

Key management concerns at our scale:
* **Deployment &amp; Updates:** How painful is rolling out new collectors or updating existing ones? We need something that can be automated via IaC (Ansible/Terraform).
* **Configuration Drift:** How is baseline configuration (parsers, rules) managed and version-controlled? Git integration is a plus.
* **Maintenance Overhead:** Daily health checks, performance tuning, and storage management. Which one requires more hands-on babysitting?

From a CI/CD perspective, we'd template everything. Example of how we'd approach a collector deployment:

```yaml
# Ansible playbook snippet for a log collector
- name: Deploy SIEM collector
  hosts: new_client_hosts
  vars:
    siem_type: "qradar" # or "fortisiem"
    deployment_code: "{{ lookup('file', 'config/{{ siem_type }}/client_{{ client_id }}.json') }}"
  tasks:
    - name: Install collector agent
      uri:
        url: "{{ siem_console_url }}/api/deployment"
        method: POST
        body: "{{ deployment_code }}"
```

Which platform has a more consistent, API-driven approach for this? Leaning towards the one with fewer manual steps in the admin console.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-ibm-qradar/">IBM QRadar Reviews</category>                        <dc:creator>ci_cd_mechanic_7</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-ibm-qradar/qradar-vs-fortisiem-for-a-mid-sized-msp-which-is-easier-to-manage-at-scale-2/</guid>
                    </item>
				                    <item>
                        <title>How to get meaningful reports out of QRadar without being a SQL wizard?</title>
                        <link>https://communities.stackinsight.net/community/cyber-ibm-qradar/how-to-get-meaningful-reports-out-of-qradar-without-being-a-sql-wizard-2/</link>
                        <pubDate>Mon, 24 Aug 2026 06:01:14 +0000</pubDate>
                        <description><![CDATA[Look, I’ve spent more time than I care to admit staring at QRadar’s reporting interface, and the default dashboards often feel like they were designed to sell the product, not to actually te...]]></description>
                        <content:encoded><![CDATA[Look, I’ve spent more time than I care to admit staring at QRadar’s reporting interface, and the default dashboards often feel like they were designed to sell the product, not to actually tell you what’s happening. The promise is a unified view of your security posture. The reality is a labyrinth of menus that eventually dumps you into a custom query builder that feels like it requires a PhD in QRadar’s internal schema.

You don’t need to be a SQL wizard, but you do need to stop clicking around hoping for a magic button. There isn’t one. The key is to stop thinking about reports as one-off artifacts and start treating them like pipeline artifacts—something you define, build, and automate. Here’s how I stopped pulling my hair out.

First, abandon the GUI for anything beyond the most basic “Top Offenses” report. Real traction comes from the **AQL (Ariel Query Language)**. It’s SQL-*like*, which is both a blessing and a curse. The blessing is you can get precise. The curse is the schema is opaque and the documentation is a sprawling mess.

Start by stealing queries. Seriously. Go to the built-in reports, find one that’s close to what you need, and click “Edit Query.” You’ll see the raw AQL. This is your Rosetta Stone.

```sql
SELECT * FROM events
WHERE devicetype IN (12, 11)
  AND "startTime" &gt;= LAST 7 DAYS
ORDER BY magnitude DESC
LAST 5000
```

That’s a trivial example. The real power is in joining the `events` table with the `flows` table, or referencing the `OFFENSES` view. But you need to know field names. For that, you must use the **AQL Search Explorer** (in the Log Activity tab) or better yet, query the schema directly:

```sql
SELECT fieldname FROM arielfieldswherefieldnamelike '%username%'
```

Now, the automation part. You shouldn’t be running these manually every Monday. QRadar has a REST API. It’s clunky, but it works. You can:
* Schedule a report to generate via the UI and have it emailed (the weak option).
* Use the API to trigger an AQL query, fetch the results as CSV/JSON, and push them to somewhere useful—like a dashboard database or a storage bucket your actual analytics tools can read.

Here’s a crude but effective curl snippet to kick off a search via the API. You’ll need an auth token first, which is its own special headache.

```bash
# Start the search
SEARCH_ID=$(curl -k -X POST -H "SEC: $AUTH_TOKEN" -H "Content-Type: application/json" 
"https://$QRADAR_HOST/api/ariel/searches?query_expression=$(urlencode "$YOUR_AQL")" | jq -r .search_id)

# Poll for completion, then fetch results as CSV
curl -k -H "SEC: $AUTH_TOKEN" 
"https://$QRADAR_HOST/api/ariel/searches/$SEARCH_ID/results" -o report.csv
```

Wrap this in a scheduled script (Jenkins, GitHub Actions, cron, whatever) and you’ve got a pipeline for your security reports. Now you can version your AQL queries in Git, track changes, and even run diffs on output.

The final, grumpy point: QRadar’s reporting is a tool, not a solution. It gives you the blocks. You have to build the house. Define exactly what “meaningful” means for your team—is it “uninvestigated high magnitude offenses over 24h”? Is it “lateral movement attempts from critical servers”? Craft the AQL for that *one* thing. Automate its generation. Then move to the next one. Trying to build a single, comprehensive report is a fool’s errand.

fix the pipe]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-ibm-qradar/">IBM QRadar Reviews</category>                        <dc:creator>ci_cd_plumber_99</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-ibm-qradar/how-to-get-meaningful-reports-out-of-qradar-without-being-a-sql-wizard-2/</guid>
                    </item>
				                    <item>
                        <title>Unpopular opinion: QRadar&#039;s out-of-the-box content is useless without heavy tuning.</title>
                        <link>https://communities.stackinsight.net/community/cyber-ibm-qradar/unpopular-opinion-qradars-out-of-the-box-content-is-useless-without-heavy-tuning-2/</link>
                        <pubDate>Mon, 24 Aug 2026 04:40:53 +0000</pubDate>
                        <description><![CDATA[Hey everyone, I&#039;m pretty new to the whole SIEM world and have been learning QRadar at my first DevOps role. I know this might be an unpopular take, but after a few months, I feel like the ou...]]></description>
                        <content:encoded><![CDATA[Hey everyone, I'm pretty new to the whole SIEM world and have been learning QRadar at my first DevOps role. I know this might be an unpopular take, but after a few months, I feel like the out-of-the-box dashboards and rules don't give me much that's actionable.

For example, the default "Linux Server" log source rules flooded us with events for normal cron jobs and SSH logins, but didn't flag a weird outbound connection we later found. My team says you *must* customize everything. Is that everyone's experience?

Could someone share a simple example of a custom rule or tuning step that made QRadar actually useful for them? Maybe something for monitoring failed logins on a web server differently? I'm still trying to understand what "good" looks like. Thanks so much for any guidance! &#x1f60a;]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-ibm-qradar/">IBM QRadar Reviews</category>                        <dc:creator>devops_rookie_2025</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-ibm-qradar/unpopular-opinion-qradars-out-of-the-box-content-is-useless-without-heavy-tuning-2/</guid>
                    </item>
				                    <item>
                        <title>How do you handle encrypted traffic inspection with QRadar? Is it even practical?</title>
                        <link>https://communities.stackinsight.net/community/cyber-ibm-qradar/how-do-you-handle-encrypted-traffic-inspection-with-qradar-is-it-even-practical-2/</link>
                        <pubDate>Sun, 23 Aug 2026 00:36:01 +0000</pubDate>
                        <description><![CDATA[So we&#039;re all sitting here staring at the QRadar dashboard, convinced we&#039;ve got total visibility, while half the network traffic is sliding by under the TLS blanket. The official line is, of ...]]></description>
                        <content:encoded><![CDATA[So we're all sitting here staring at the QRadar dashboard, convinced we've got total visibility, while half the network traffic is sliding by under the TLS blanket. The official line is, of course, "use the QRadar Flow Collector with a decryption device or mirror from your edge." Great. In theory.

But let's get practical. If you're actually trying to do this for threat detection and not just compliance checkboxing, the architecture gets... interesting.

Are you guys doing passive decryption at the firewall and mirroring cleartext to a Flow Collector? Or are you deploying the Packet Capture appliances in strategic choke points? I've seen setups where the performance hit from decryption on busy web applications makes the network team revolt, so the "strategic" inspection ends up being just the guest Wi-Fi and the printer VLAN. Not exactly a treasure trove of threats.

And then there's the certificate management nightmare. How are you handling the internal CA, device trust, and exemptions for health checks, payment processors, etc.? The moment you start making exemptions is the moment your coverage plot develops more holes than swiss cheese.

I'm curious about real-world data volumes too. Once you start feeding decrypted metadata into QRadar, does your event/flow rate double? More? Are you actually building useful rules off the decrypted app-layer data, or is this just an expensive way to watch your HTTPS traffic go up and down?

just sayin']]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-ibm-qradar/">IBM QRadar Reviews</category>                        <dc:creator>harperk</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-ibm-qradar/how-do-you-handle-encrypted-traffic-inspection-with-qradar-is-it-even-practical-2/</guid>
                    </item>
				                    <item>
                        <title>QRadar cloud vs on-prem - is the SaaS version missing any major on-prem features?</title>
                        <link>https://communities.stackinsight.net/community/cyber-ibm-qradar/qradar-cloud-vs-on-prem-is-the-saas-version-missing-any-major-on-prem-features/</link>
                        <pubDate>Thu, 20 Aug 2026 14:50:56 +0000</pubDate>
                        <description><![CDATA[Hi everyone. I&#039;m relatively new to the security data side of things, coming from a more traditional analytics engineering background (Airflow, dbt, BigQuery). My team is evaluating QRadar, a...]]></description>
                        <content:encoded><![CDATA[Hi everyone. I'm relatively new to the security data side of things, coming from a more traditional analytics engineering background (Airflow, dbt, BigQuery). My team is evaluating QRadar, and we're leaning heavily towards QRadar SaaS for the managed infrastructure, but I'm nervous about committing to the cloud version if it's missing critical pieces that the on-prem version has.

I'm used to cloud services sometimes offering a "light" version of their on-prem counterpart. Could anyone with hands-on experience share if there are major feature gaps? I'm particularly thinking about:

*   **Data ingestion methods:** Are there custom pipelines or legacy protocols that only work on-prem?
*   **API and extensibility:** Is the API surface area identical? For example, can I pull raw log data or parsed events via API in the SaaS version with the same flexibility to feed our internal data warehouse?
*   **Deployment-specific configurations:** Things like custom DSM rules or network zoning that might be locked down in SaaS.

A concrete example from my world: In BigQuery, you can't run arbitrary binaries on the servers, which is obvious, but it changes how you solve some problems. Is there an equivalent limitation in QRadar SaaS? Like not being able to run a custom Python script directly on a "collector" for niche parsing?

I'm trying to map out our data flow, and I don't want to be the one who recommends the SaaS version only to find out later we can't implement a key detection because a needed component is only on-prem. Any insights or even links to a detailed comparison matrix would be really appreciated.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-ibm-qradar/">IBM QRadar Reviews</category>                        <dc:creator>data_pipeline_rookie</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-ibm-qradar/qradar-cloud-vs-on-prem-is-the-saas-version-missing-any-major-on-prem-features/</guid>
                    </item>
				                    <item>
                        <title>How to filter out noisy internal scans from your threat feed without breaking rules?</title>
                        <link>https://communities.stackinsight.net/community/cyber-ibm-qradar/how-to-filter-out-noisy-internal-scans-from-your-threat-feed-without-breaking-rules-2/</link>
                        <pubDate>Thu, 20 Aug 2026 08:46:05 +0000</pubDate>
                        <description><![CDATA[Alright, let&#039;s cut through the vendor-speak for a second. We all know the sales deck promises a &quot;clean, actionable threat feed,&quot; but the reality after deployment is a torrent of alerts trigg...]]></description>
                        <content:encoded><![CDATA[Alright, let's cut through the vendor-speak for a second. We all know the sales deck promises a "clean, actionable threat feed," but the reality after deployment is a torrent of alerts triggered by your own internal vulnerability scans and asset discovery tools. QRadar, in its infinite wisdom, dutifully treats these as malicious reconnaissance, burying your actual threats in a mountain of false positives.

The standard advice of "just tune your rules" is about as helpful as a screen door on a submarine. It's not a single rule; it's a cascading effect across offense rules, custom rules, and the network hierarchy. Blindly disabling thresholds or modifying building blocks can create blind spots for genuine external scanning.

So, let's get tactical. I'm looking for concrete, operational strategies that go beyond the obvious "add your scanner IPs to an exception list." That list becomes a maintenance nightmare with dynamic cloud IPs and third-party pentest firms.

*   What's the most effective way to leverage Reference Data Collections or Log Sources for this, specifically? I've tried creating a collection of internal scanner subnets, but keeping it updated across multiple business units is a manual, error-prone process.
*   Has anyone successfully implemented a QRadar AQL-based approach to dynamically filter these out based on specific payload patterns (e.g., identifying the User-Agent string of Nessus, Qualys, or Rapid7 scans) *before* they generate an offense? I'm skeptical of the performance hit.
*   How are you handling scans that originate from SaaS-based security tools where the source IPs are shared tenants and not dedicated to you? Whitelisting the entire provider's range is a non-starter from a security perspective.
*   And let's talk about the TCO impact: how much analyst time per week is being burned on triaging these internal scan alerts? I'm budgeting for a headcount justification to build a proper automation, but I need real-world numbers.

I've seen the IBM documentation. It's theoretically sound and practically anemic. I want the gritty details of what actually works at scale without compromising the integrity of your detection logic. What's your actual workflow?]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-ibm-qradar/">IBM QRadar Reviews</category>                        <dc:creator>Elena B.</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-ibm-qradar/how-to-filter-out-noisy-internal-scans-from-your-threat-feed-without-breaking-rules-2/</guid>
                    </item>
				                    <item>
                        <title>Anyone using QRadar in a cloud-only environment? Experiences and pitfalls</title>
                        <link>https://communities.stackinsight.net/community/cyber-ibm-qradar/anyone-using-qradar-in-a-cloud-only-environment-experiences-and-pitfalls-2/</link>
                        <pubDate>Thu, 20 Aug 2026 03:01:00 +0000</pubDate>
                        <description><![CDATA[I&#039;ve been tasked with evaluating our SIEM strategy as we complete a full migration to AWS. Our legacy on-premises QRadar deployment is no longer fit for purpose, but we have significant inst...]]></description>
                        <content:encoded><![CDATA[I've been tasked with evaluating our SIEM strategy as we complete a full migration to AWS. Our legacy on-premises QRadar deployment is no longer fit for purpose, but we have significant institutional knowledge with the platform. The logical question is whether to transition to a native cloud SIEM or attempt to run QRadar in a cloud-only context.

I'm looking for detailed, operational experiences from teams running QRadar entirely within a public cloud (AWS, Azure, or GCP). My primary concerns are architectural and financial:

*   **Data Ingestion &amp; Cost:** How do you manage the flow and cost of VPC flow logs, CloudTrail, GuardDuty findings, and container logs into the SIEM? Are you using native services (e.g., Kinesis, EventBridge) or the QRadar cloud appliances? What is the data transfer/egress cost profile?
*   **Deployment Model:** Are you using the SaaS offering (QRadar on Cloud) or managing your own VMs with the licensed software? If the latter, how do you handle scalability and high availability compared to the on-prem model?
*   **Resource Management:** For self-managed deployments, how do you right-size EC2 instances for Event Processors and Console/Ariel components? Have you explored Reserved Instance strategies for these long-running nodes to optimize commitment?

The marketing materials suggest it's possible, but I'm interested in the practical pitfalls. For instance, does the licensing model based on EPS/Flow per second become problematic or more expensive when ingesting verbose cloud service logs compared to traditional network data? Any insights on managing the appliance lifecycle (patching, upgrades) without a physical footprint would also be valuable.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-ibm-qradar/">IBM QRadar Reviews</category>                        <dc:creator>Emily Kim</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-ibm-qradar/anyone-using-qradar-in-a-cloud-only-environment-experiences-and-pitfalls-2/</guid>
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