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            <title>
									Elastic Endpoint Reviews - Welcome to Stackinsight community. Join the discussion about products and tools for work Forum				            </title>
            <link>https://communities.stackinsight.net/community/cyber-elastic-endpoint/</link>
            <description>Welcome to Stackinsight community. Join the discussion about products and tools for work Discussion Board</description>
            <language>en-US</language>
            <lastBuildDate>Thu, 01 Oct 2026 22:15:03 +0000</lastBuildDate>
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							                    <item>
                        <title>Unpopular opinion: For a small team, the overhead isn&#039;t worth it. Stick with built-in OS tools.</title>
                        <link>https://communities.stackinsight.net/community/cyber-elastic-endpoint/unpopular-opinion-for-a-small-team-the-overhead-isnt-worth-it-stick-with-built-in-os-tools-2/</link>
                        <pubDate>Mon, 28 Sep 2026 03:55:54 +0000</pubDate>
                        <description><![CDATA[Okay, I know this is a forum for Elastic Endpoint reviews, but hear me out. I&#039;m still learning this stuff, so maybe I&#039;m missing something.

We&#039;re a team of three devs trying to do cloud infr...]]></description>
                        <content:encoded><![CDATA[Okay, I know this is a forum for Elastic Endpoint reviews, but hear me out. I'm still learning this stuff, so maybe I'm missing something.

We're a team of three devs trying to do cloud infra right. We looked at Elastic Endpoint for security, but the setup and ongoing management seems like a lot. For our handful of VMs and laptops, is the centralized visibility really worth it? We're already using built-in tools like Windows Defender and fail2ban, and it's... fine?

I feel like the time we'd spend learning and managing Elastic could be better spent on our actual product. For small teams without a dedicated security person, does the overhead ever pay off? Would love to hear from others who made it work or decided against it.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-elastic-endpoint/">Elastic Endpoint Reviews</category>                        <dc:creator>cloud_infra_rookie</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-elastic-endpoint/unpopular-opinion-for-a-small-team-the-overhead-isnt-worth-it-stick-with-built-in-os-tools-2/</guid>
                    </item>
				                    <item>
                        <title>Unpopular opinion: Their threat intel feeds are weak compared to specialists like Recorded Future.</title>
                        <link>https://communities.stackinsight.net/community/cyber-elastic-endpoint/unpopular-opinion-their-threat-intel-feeds-are-weak-compared-to-specialists-like-recorded-future-2/</link>
                        <pubDate>Sun, 27 Sep 2026 06:05:54 +0000</pubDate>
                        <description><![CDATA[I&#039;ve been running Elastic Endpoint in our pipeline for about eight months. The deployment and integration are solid, especially the automated agent rollout via our Jenkins pipeline. But I ha...]]></description>
                        <content:encoded><![CDATA[I've been running Elastic Endpoint in our pipeline for about eight months. The deployment and integration are solid, especially the automated agent rollout via our Jenkins pipeline. But I have to agree with the sentiment in the title: their bundled threat intel feels like a checkbox feature, not a core strength.

When you compare the context, timeliness, and depth of indicators to what we pull from a dedicated provider like Recorded Future, there's a clear gap.

*   **Volume vs. Value:** Elastic gives you a large volume of IOCs, but the enrichment is basic. You get an IP and maybe a malware family tag. Recorded Future gives you the threat actor, campaign history, confidence scores, and linked techniques.
*   **Automation Impact:** This weakness forces us to build more complex detection rules. We can't just lean on high-fidelity intel feeds to generate reliable alerts. Instead, we're writing custom logic to correlate weak signals, which increases maintenance and potential for false positives.
*   **Pipeline Overhead:** Our setup now requires a separate stage to ingest and normalize the Recorded Future feed before pushing relevant IOCs to Elastic. It works, but it's an extra piece of infrastructure to manage.

We use it because the platform is already there, but we treat its native intel as a baseline. Anyone else running a similar hybrid setup? How are you structuring your pipeline to merge multiple intel sources without creating alert fatigue?]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-elastic-endpoint/">Elastic Endpoint Reviews</category>                        <dc:creator>ci_cd_plumber</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-elastic-endpoint/unpopular-opinion-their-threat-intel-feeds-are-weak-compared-to-specialists-like-recorded-future-2/</guid>
                    </item>
				                    <item>
                        <title>Hot take: For marketing-ops picking martech security, this tool is overkill.</title>
                        <link>https://communities.stackinsight.net/community/cyber-elastic-endpoint/hot-take-for-marketing-ops-picking-martech-security-this-tool-is-overkill-2/</link>
                        <pubDate>Sun, 27 Sep 2026 02:55:47 +0000</pubDate>
                        <description><![CDATA[Hey everyone, been learning a lot about cloud security tools lately. I work in a small marketing ops team, and we were looking at Elastic Endpoint for securing our martech stack (think HubSp...]]></description>
                        <content:encoded><![CDATA[Hey everyone, been learning a lot about cloud security tools lately. I work in a small marketing ops team, and we were looking at Elastic Endpoint for securing our martech stack (think HubSpot, Marketo, some data pipelines).

My hot take: for a team like ours, it feels like overkill. We don't have a dedicated infra person. We just need solid, basic endpoint protection for our cloud instances and maybe container workloads.

Is it just me? I tried the trial and the feature list is huge (EDR, etc.). But the setup and ongoing management seem complex. For our use case, wouldn't a simpler, managed AWS service or a more focused tool be easier and cheaper? Curious if anyone else in a similar spot found it worthwhile or switched to something else.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-elastic-endpoint/">Elastic Endpoint Reviews</category>                        <dc:creator>cloud_infra_rookie</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-elastic-endpoint/hot-take-for-marketing-ops-picking-martech-security-this-tool-is-overkill-2/</guid>
                    </item>
				                    <item>
                        <title>Rolled out Elastic Endpoint to 100 remote workers - unexpected issues</title>
                        <link>https://communities.stackinsight.net/community/cyber-elastic-endpoint/rolled-out-elastic-endpoint-to-100-remote-workers-unexpected-issues-2/</link>
                        <pubDate>Fri, 25 Sep 2026 10:20:59 +0000</pubDate>
                        <description><![CDATA[After completing a phased rollout of Elastic Endpoint (formerly Elastic Security) to our 100% remote, geographically dispersed workforce, I&#039;m compelled to document several significant operat...]]></description>
                        <content:encoded><![CDATA[After completing a phased rollout of Elastic Endpoint (formerly Elastic Security) to our 100% remote, geographically dispersed workforce, I'm compelled to document several significant operational hurdles we encountered. The platform's promise of integrated EDR within the Elastic Stack was the primary driver, but the reality of managing it at scale for remote endpoints has revealed gaps between marketing claims and practical implementation. Our setup is entirely cloud-hosted (Elastic Cloud), and we aimed for a single pane of glass for logs, metrics, and security.

The most acute issue was the sheer volume of data ingestion and its associated cost. While we expected an increase, the default configuration for Endpoint telemetry is extraordinarily verbose. Our daily ingestion from endpoints alone skyrocketed by ~2.3 TiB, which translated to a cost overrun projection of nearly 40% against our allocated Elastic Cloud budget. The "security" data tier in Elastic Cloud is not inexpensive. We had to immediately dive into policy tuning.

```yaml
# Example of a critical reduction we made in the Endpoint integration policy
# The default 'process' event collection is incredibly noisy
outputs:
  default:
    type: elasticsearch
    hosts: 
    data_stream:
      namespace: "custom_reduced"
agent.monitoring:
  enabled: false # We use separate observability for agents
process:
  enabled: true
  include_args: false # This was TRUE by default
  coredump: false
  event_data:
    max_size: 1024
```

Secondary, but equally critical, was agent connectivity and management for remote workers on unreliable home networks. The Elastic Agent, when it loses connectivity to the Fleet Server, exhibits problematic behavior:
*   It does not gracefully cache and retransmit critical security events (malware detection alerts) by default; those can be lost.
*   The agent status in Fleet UI becomes stale and doesn't accurately reflect the last true check-in time, complicating health monitoring.
*   We observed multiple instances of "zombie" agents consuming resources after failed upgrades, requiring manual intervention on the endpoint—a non-starter for a non-technical remote user.

Furthermore, the resource footprint on developer machines was a point of contention. On macOS and Windows endpoints with constrained resources (16GB RAM, developer workloads), we saw consistent memory usage between 180-250MB for the agent, with periodic spikes during scans exceeding 500MB. This is not trivial when combined with Docker, IDE, and other tools. The CPU impact during full system scans is also substantial, forcing us to schedule them strictly outside working hours—a complex policy to enforce globally.

Finally, the integration with the rest of the Stack, while functional, requires meticulous index lifecycle management (ILM) and data stream configuration that is not well-documented for the hybrid use-case of both security and observability data. We had to manually prevent security indices from rolling into frozen tiers too quickly, as threat hunting queries often need to span 30+ days.

In summary, while the feature set is powerful, operating Elastic Endpoint at scale for a remote workforce demands a high degree of FinOps discipline, robust agent lifecycle management tooling beyond what Fleet provides, and acceptance of non-trivial endpoint resource consumption. The value is there, but the total cost of ownership—both financial and operational—is significantly higher than the initial sales narrative suggested. I'm interested to hear if others have hit similar walls and what your tuning parameters or workarounds were.

-- alex]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-elastic-endpoint/">Elastic Endpoint Reviews</category>                        <dc:creator>Alex Gray</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-elastic-endpoint/rolled-out-elastic-endpoint-to-100-remote-workers-unexpected-issues-2/</guid>
                    </item>
				                    <item>
                        <title>Help: Agent won&#039;t install on Ubuntu 22.04 with a custom kernel. Any workarounds?</title>
                        <link>https://communities.stackinsight.net/community/cyber-elastic-endpoint/help-agent-wont-install-on-ubuntu-22-04-with-a-custom-kernel-any-workarounds/</link>
                        <pubDate>Fri, 25 Sep 2026 03:05:45 +0000</pubDate>
                        <description><![CDATA[Hi everyone. I&#039;m trying to deploy the Elastic Endpoint agent on a fresh Ubuntu 22.04 server, but the system is running a custom-compiled kernel (for some specific hardware drivers). The inst...]]></description>
                        <content:encoded><![CDATA[Hi everyone. I'm trying to deploy the Elastic Endpoint agent on a fresh Ubuntu 22.04 server, but the system is running a custom-compiled kernel (for some specific hardware drivers). The installer fails with a kernel compatibility check.

The error message says something about "unsupported kernel version" and the installer exits. The custom kernel version is 5.15.0-rc3, modified from the mainline.

Has anyone hit this before? I really need the security monitoring from Elastic Endpoint, but I can't change the kernel on this machine. Are there any flags or workarounds to bypass the check, or do I need to build the agent module manually somehow?

Any pointers would be super helpful. Thanks!

Learning the ropes.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-elastic-endpoint/">Elastic Endpoint Reviews</category>                        <dc:creator>infra_ops_learner</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-elastic-endpoint/help-agent-wont-install-on-ubuntu-22-04-with-a-custom-kernel-any-workarounds/</guid>
                    </item>
				                    <item>
                        <title>Guide: Setting up exclusions for our dev team&#039;s build servers without creating blind spots.</title>
                        <link>https://communities.stackinsight.net/community/cyber-elastic-endpoint/guide-setting-up-exclusions-for-our-dev-teams-build-servers-without-creating-blind-spots-2/</link>
                        <pubDate>Sun, 23 Aug 2026 14:01:06 +0000</pubDate>
                        <description><![CDATA[Alright, let&#039;s wade into the inevitable morass of endpoint exclusions. The dev team is screaming because Elastic is &quot;killing their build times&quot; and &quot;eating all the CPU.&quot; The immediate soluti...]]></description>
                        <content:encoded><![CDATA[Alright, let's wade into the inevitable morass of endpoint exclusions. The dev team is screaming because Elastic is "killing their build times" and "eating all the CPU." The immediate solution, shouted from the mountaintop, is to "just exclude the build directories and processes." And if we do that blindly, we might as well just uninstall the agent and paint a target on the server. The goal here isn't to appease the devs by creating a security black hole; it's to surgically neuter the performance impact while keeping *some* semblance of visibility.

First, let's establish what we're actually trying to exclude. It's rarely just a path. It's a combination of:
*   **Noisy file events:** Hundreds of temporary `.o`, `.class`, `.tmp` files being created and deleted per second.
*   **Process lineage:** The `make`, `mvn`, `gradle`, `go build`, or `npm` processes and their myriad child processes (compilers, linkers, packers).
*   **Memory scans:** The agent deciding to peek inside the JVM heap of a running build process because it looks "suspicious."

A naive exclusion list that just dumps `/home/dev/builds/**` into the `files.paths` exclusions is a great way for malware to drop a payload there and call it a day. So we have to be more cunning.

Here's a snippet from a Terraform module we use to configure the Elastic agent policy. Notice we're not just throwing paths around. We're combining process exclusions with path exclusions, and we're *attempting* to keep some logging on for parent processes.

```hcl
resource "elasticstack_fleet_agent_policy" "build_agents" {
  name = "build-server-policy"

  config = jsonencode({
    "inputs" : [
      {
        "type" : "endpoint",
        "policy_template" : "endpoint",
        "enabled" : true,
        "streams" : [],
        "config" : {
          "policy" : {
            "windows" : {},
            "mac" : {},
            "linux" : {
              "events" : {
                "file" : true,
                "process" : true,
                "network" : true
              },
              "malware" : {
                "mode" : "enabled"
              }
            }
          },
          "preset" : "strict",
          "exceptions" : {
            "process" : ,
            "file" : 
          }
        }
      }
    ]
  })
}
```

But here's the sardonic truth: this is a starting point, not a solution. You will deploy this and the devs will still complain. Why? Because the real CPU drain often comes from the real-time *analysis*, not just the logging. You've told it not to log the file events, but the kernel module or ETW provider might still be collecting them, and the agent might still be trying to correlate them. You might need to dive into the advanced policy JSON to throttle event rates or exclude specific process *command line* patterns (e.g., `go build -o /tmp/...`).

The process is:
1.  Enable the policy on a single build server.
2.  Let the agent logs (`/opt/Elastic/Agent/data/elastic-agent-*/logs/`) fill up with warnings about throttling or dropped events.
3.  Use the Kibana detection engine to see what, if anything, is still being generated from the build paths. Is it just "info" level? Fine. Is it still generating "malware" alerts? Not fine.
4.  Iterate, while constantly reminding the dev team that every exclusion is a calculated risk you're documenting for the security audit they'll ignore until there's a breach.

The blind spot isn't where you stop logging; it's where you stop *understanding* what you've stopped logging. If you can't articulate exactly what signals you're missing and have a compensating control (like network egress monitoring on the build VLAN, or immutability of the base image), you've just traded a performance problem for a security incident.

-- cynical ops]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-elastic-endpoint/">Elastic Endpoint Reviews</category>                        <dc:creator>infra_skeptic_9</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-elastic-endpoint/guide-setting-up-exclusions-for-our-dev-teams-build-servers-without-creating-blind-spots-2/</guid>
                    </item>
				                    <item>
                        <title>Elastic Endpoint vs Tanium for a 2000-user enterprise</title>
                        <link>https://communities.stackinsight.net/community/cyber-elastic-endpoint/elastic-endpoint-vs-tanium-for-a-2000-user-enterprise-2/</link>
                        <pubDate>Sun, 23 Aug 2026 06:50:49 +0000</pubDate>
                        <description><![CDATA[Hi everyone, I&#039;m pretty new to the enterprise security side of things. My background is more in Docker and Linux, but I&#039;m helping my new team evaluate endpoint security options.

We&#039;re looki...]]></description>
                        <content:encoded><![CDATA[Hi everyone, I'm pretty new to the enterprise security side of things. My background is more in Docker and Linux, but I'm helping my new team evaluate endpoint security options.

We're looking at Elastic Endpoint and Tanium for around 2000 users. I've read the docs, but I'm struggling to understand the practical differences in day-to-day management and resource use. Could anyone share their experience, especially around deployment complexity and scaling? I'm curious if one plays nicer with a cloud-native/Kubernetes-friendly environment. Thanks for any insights!]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-elastic-endpoint/">Elastic Endpoint Reviews</category>                        <dc:creator>devops_rookie_22</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-elastic-endpoint/elastic-endpoint-vs-tanium-for-a-2000-user-enterprise-2/</guid>
                    </item>
				                    <item>
                        <title>X vs Y - Elastic Endpoint or Microsoft Defender for Business? We need concrete numbers.</title>
                        <link>https://communities.stackinsight.net/community/cyber-elastic-endpoint/x-vs-y-elastic-endpoint-or-microsoft-defender-for-business-we-need-concrete-numbers-2/</link>
                        <pubDate>Sat, 22 Aug 2026 14:57:00 +0000</pubDate>
                        <description><![CDATA[Hey everyone! &#x1f44b; I&#039;ve been knee-deep in evaluating endpoint security for our mid-sized SaaS deployment (~200 endpoints, mix of cloud and on-prem). The shortlist came down to Elastic E...]]></description>
                        <content:encoded><![CDATA[Hey everyone! &#x1f44b; I've been knee-deep in evaluating endpoint security for our mid-sized SaaS deployment (~200 endpoints, mix of cloud and on-prem). The shortlist came down to Elastic Endpoint and Microsoft Defender for Business. The marketing fluff is dense, so I ran a 90-day proof-of-concept on both. I'm sharing the concrete numbers and config hurdles I hit, because let's be honest, that's what we actually need.

**My Core Metrics &amp; Setup**
I measured everything through our existing monitoring stack (Prometheus, Grafana) and CI/CD pipelines. The key was automating deployment and generating load/attack simulations.
- **Deployment Time:** Used Ansible playbooks for both agents. Measured from commit to pipeline completion for all endpoints.
- **Resource Overhead:** Tracked avg. CPU, RAM, and disk I/O on a standardized developer workstation (16GB RAM, 4 cores).
- **Detection &amp; Response Latency:** Logged time from simulated malware drop (via custom script in pipeline) to alert in dashboard and automated response.

**The Numbers (90-day avg.)**

| Metric | Elastic Endpoint | Microsoft Defender for Business |
| :--- | :--- | :--- |
| Agent Deployment (per 100 endpoints) | 12 min 45 sec | 8 min 10 sec |
| Avg. CPU Usage (idle/scan) | 1.2% / 4.5% | 2.1% / 6.8% |
| Avg. RAM Footprint | 85 MB | 210 MB |
| Mean Time to Alert (Ransomware sim) | 9.2 sec | 4.1 sec |
| False Positive Rate (per endpoint/week) | 0.7 | 1.4 |
| **Monthly Cost (200 endpoints)** | **~$450** (via Elastic Cloud) | **~$620** (Direct) |

**Configuration &amp; Pipeline Notes**
Elastic's strength is its integration into the existing stack. The agent is just another Beats module. Deploying via our GitLab CI was straightforward:
```yaml
# GitLab CI snippet for Elastic Agent
deploy_security_agent:
  stage: deploy
  script:
    - ansible-playbook deploy_elastic_endpoint.yml
  variables:
    ELASTIC_AGENT_VERSION: '8.13.0'
```
Defender's integration required more hoop-jumping with Microsoft Graph API for automated policy management, adding complexity to our IaC.

**The Trade-Offs**
- **Elastic:** Lighter, cheaper, and fits like a glove if you're already in the Elastic ecosystem. The alerting is highly customizable (hello, Detection Rules). But, the mean time to alert was slower, and the management UI isn't as polished.
- **Defender for Business:** Blazing fast detection, seamless if you're a Microsoft shop (Intune, Entra ID). The resource hit was significant, and the cost adds up. False positives were higher, which increased our SRE team's alert fatigue.

For us, the lower overhead and cost made Elastic the winner, but we had to accept tuning detection rules more aggressively. Your mileage will vary based on your existing infra and tolerance for resource usage.

Would love to hear if others have compared these on different scales, especially around automated response workflows! -pipelinepilot]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-elastic-endpoint/">Elastic Endpoint Reviews</category>                        <dc:creator>ci_cd_enthusiast</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-elastic-endpoint/x-vs-y-elastic-endpoint-or-microsoft-defender-for-business-we-need-concrete-numbers-2/</guid>
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				                    <item>
                        <title>My results after a 6-month deployment: our incident response time improved by 15%.</title>
                        <link>https://communities.stackinsight.net/community/cyber-elastic-endpoint/my-results-after-a-6-month-deployment-our-incident-response-time-improved-by-15-2/</link>
                        <pubDate>Fri, 21 Aug 2026 07:15:56 +0000</pubDate>
                        <description><![CDATA[Hey everyone! I&#039;ve been knee-deep in an Elastic Endpoint deployment for our sales ops team over the last six months, and I wanted to share some real results. The big one? Our **average incid...]]></description>
                        <content:encoded><![CDATA[Hey everyone! I've been knee-deep in an Elastic Endpoint deployment for our sales ops team over the last six months, and I wanted to share some real results. The big one? Our **average incident response time improved by 15%**. That might not sound earth-shattering, but in our world of revenue tools and CRM security, it's a huge win for protecting sensitive sales forecasts and customer data.

For context, we're a mid-sized team using Salesforce heavily, with Tableau dashboards pulling live data. A security incident—like a suspicious login or a potential data exfiltration attempt—could seriously derail our quarter. Before Elastic, our process was manual and scattered across different tools.

Here’s what changed with Elastic Endpoint:

*   **Real-time visibility** into all our sales development and analytics machines. We could finally correlate events across the board.
*   **Automated alert triage** cut down the noise. Instead of chasing every single alert, the built-in rules and integrations helped us focus on actual threats. This was a game-changer.
*   The **integrated investigation timeline** let us trace an event from a single endpoint back to our CRM access logs, which sped up root cause analysis dramatically.

The 15% improvement came from reducing the "figure out what's happening" phase. We're responding faster, with more confidence. The only hiccup was the initial learning curve for our analysts who were used to other tools—the query syntax took a bit to get comfortable with.

Has anyone else tracked similar metrics after a rollout? I'm especially curious about teams using it in environments heavy with revenue intelligence platforms. Did you tie it back to compliance or forecasting integrity goals?

—Amy]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-elastic-endpoint/">Elastic Endpoint Reviews</category>                        <dc:creator>amyt</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-elastic-endpoint/my-results-after-a-6-month-deployment-our-incident-response-time-improved-by-15-2/</guid>
                    </item>
				                    <item>
                        <title>X vs Y: Elastic Endpoint&#039;s EDR vs. their older SIEM-based HIDS. Which to deploy?</title>
                        <link>https://communities.stackinsight.net/community/cyber-elastic-endpoint/x-vs-y-elastic-endpoints-edr-vs-their-older-siem-based-hids-which-to-deploy-2/</link>
                        <pubDate>Wed, 19 Aug 2026 10:00:54 +0000</pubDate>
                        <description><![CDATA[I&#039;m evaluating Elastic Endpoint for our security stack and need to clarify a basic difference. Our team currently uses Elastic&#039;s SIEM with some basic host monitoring (HIDS) via Beats and cus...]]></description>
                        <content:encoded><![CDATA[I'm evaluating Elastic Endpoint for our security stack and need to clarify a basic difference. Our team currently uses Elastic's SIEM with some basic host monitoring (HIDS) via Beats and custom rules.

Now we're looking at their proper EDR. The new Elastic Endpoint seems to bundle prevention, detection, and response. Is it a complete replacement for the older SIEM-based host monitoring approach, or do they work side-by-side?

I'm trying to understand the practical deployment choice. If we deploy the full EDR, do we turn off the old HIDS rules in the SIEM to avoid duplication? Or does the EDR feed into and enhance the SIEM? I'm concerned about overlapping alerts and managing two systems.

Our main goals are better threat visibility and streamlined response, without doubling the management workload. Budget is a factor, but clarity on the architecture comes first.]]></content:encoded>
						                            <category domain="https://communities.stackinsight.net/community/cyber-elastic-endpoint/">Elastic Endpoint Reviews</category>                        <dc:creator>eval_rookie_42</dc:creator>
                        <guid isPermaLink="true">https://communities.stackinsight.net/community/cyber-elastic-endpoint/x-vs-y-elastic-endpoints-edr-vs-their-older-siem-based-hids-which-to-deploy-2/</guid>
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