The Problem: Your Logs Are Out of Control

If you manage more than a handful of servers, you already know the pain: logs piling up on disk, critical errors buried in noise, and no easy way to search for what went wrong when something breaks. You SSH in, scroll through journalctl or tail /var/log/syslog, and hope you spot the needle in the haystack.

At some point, “just grep the logs” stops scaling. You need a centralized log management platform — a single place where every server sends its logs, where you can search across all of them at once, set alerts for problems, and build dashboards to understand what is happening across your infrastructure.

The two most popular options for self-hosted log management are the ELK Stack (Elasticsearch, Logstash, Kibana) and Graylog. Both are open-source. Both can be self-hosted on your own servers. Both support Canadian data sovereignty. But they take very different approaches, and the right choice depends on your team size, technical depth, and what you actually need from your logs.

We help customers make this call every week at Canadian Web Hosting. Here is our honest breakdown.

Quick Answer: TL;DR

Choose ELK Stack if: You have dedicated DevOps time, need the most powerful search and visualization, are comfortable tuning JVM memory and managing a cluster, and plan to scale beyond 100 GB/day of log ingestion.

Choose Graylog if: You are a smaller team with limited ops bandwidth, want good alerting out of the box without paying extra, prefer a single integrated package over stitching three tools together, and need AI-assisted log analysis with MCP/LLM integration.

Both are excellent. Both support Canadian data centres. The difference is in operational complexity and where each tool invests its design effort — ELK in raw search power, Graylog in making log management accessible.

Candidate Overview

ELK Stack — The Industry Standard

The ELK Stack has been the dominant self-hosted logging solution for over a decade. It is actually three separate tools that work together: Elasticsearch stores and indexes log data with Lucene-based full-text search, Logstash ingests, parses, and transforms logs with 200+ plugins, and Kibana provides visualization, dashboards, and alerting. You can also use Elastic Agent or Beats (lightweight shippers) instead of Logstash.

Strengths:

  • Fastest full-text search of any open-source log platform — Elasticsearch is purpose-built for this
  • Massive ecosystem: 200+ Logstash plugins, extensive community, integrations with everything
  • Kibana is the gold standard for log visualization: Lens, TSVB, Canvas, Maps
  • Proven at extreme scale — handles 500+ GB/day in production
  • SIEM, APM, and Observability modules are mature (paid, but built on the same platform)

Limitations:

  • Resource-hungry: Elasticsearch runs on JVM, requires GC tuning, vm.max_map_count, and careful memory allocation
  • Complex setup: Deploying with Docker Compose involves multi-step certificate generation, enrollment tokens, three+ separate services
  • Alerting in the free tier is basic — you need Platinum license for Watcher (full alerting) and Machine Learning
  • Three separate tools means three separate configuration files, three separate upgrade paths
  • Elastic License 2.0 is not pure open-source — has usage restrictions on managed service providers

Best for: Teams with dedicated DevOps or SRE resources who need maximum search performance and visualization power at scale.

Graylog — Integrated Simplicity

Graylog takes a different approach: a single integrated package that bundles log ingestion, parsing, search, alerting, and dashboards into one application. Instead of Elasticsearch, Graylog uses DataNode (built on OpenSearch) for storage, and MongoDB for metadata and configuration. It supports syslog, GELF (Graylog Extended Log Format), Beats, Kafka, and AWS services as input sources.

Strengths:

  • Simpler operations: single integrated package with 3 Docker services (graylog, mongo, datanode) vs. ELK’s 8+ services for a full stack
  • Built-in pipeline processor: routing, parsing, and transforming logs happens inside Graylog — no separate Logstash needed

    • Strengths (continued):

    • Streams architecture: intuitive routing where logs matching certain criteria are automatically sorted into different streams. Much easier to manage than Logstash pipelines for most teams
    • Better alerting in the free tier: threshold alerts, field-based conditions, and multiple notification channels (email, Slack, HTTP webhooks, PagerDuty) without a paid license
    • MCP/LLM integration included: Graylog’s free tier allows AI-assisted log analysis — ask natural-language questions about your logs
    • Lower resource requirements at small scale — runs comfortably on 6 GB RAM for a small setup

    Limitations:

    • Smaller ecosystem: ~50 plugins compared to ELK’s 200+ — some niche integrations may be missing
    • Search is good but not as powerful as Elasticsearch — Lucene-based via OpenSearch lacks some advanced aggregation capabilities
    • Dashboards are functional but less polished than Kibana — widgets (bar, pie, line, charts, maps) cover the basics but not advanced visualization
    • Less proven at extreme scale — ELK is the default choice for 500+ GB/day deployments
    • SSPL license notice: same licensing model as MongoDB and Elasticsearch pre-relicense, with similar managed-service restrictions

    Best for: Small to medium teams, MSPs managing multiple client environments, and anyone who wants centralized logging without a dedicated DevOps person to maintain it.

    Feature Comparison Table

    Feature ELK Stack Graylog
    Storage Engine Elasticsearch (Lucene) OpenSearch via DataNode
    Log Ingestion Logstash, Beats, Elastic Agent (200+ plugins) Syslog, GELF, Beats, Kafka, AWS, Sidecar (50+ inputs)
    Log Parsing Grok patterns, dissect, Ingest Pipelines Extractors, Pipeline Rules Engine, Grok
    Search Speed Excellent — purpose-built full-text Very good — Lucene-based via OpenSearch
    Aggregations Advanced (pipeline, nested, geo, fuzzy) Basic (time-range, boolean, simple stats)
    Dashboards Kibana Lens, TSVB, Canvas, Maps — gold standard Functional widgets — bar, pie, line, stats, map
    Alerting (Free) Basic (query threshold, email/Slack via webhook) Good (threshold, field, multiple channels)
    Alerting (Paid) Watcher — full alerting (Platinum license) Enterprise — advanced correlation, data lake
    AI Integration No built-in MCP support Yes — MCP/LLM integration in free tier
    Setup Complexity Complex — 1-2 hours, multi-step cert gen Moderate — 15-30 minutes, 3 Docker services
    License Elastic License 2.0 SSPL v1

    Decision Guide: Which Scenario Fits You?

    Your Scenario Recommendation Why
    Small team, no dedicated DevOps ? Graylog Single package, easier ops, 15-minute setup, built-in alerting
    Large team with SRE resources ? ELK Stack Best search speed, proven at scale, richest ecosystem
    You need AI-assisted log analysis ? Graylog Free MCP/LLM integration — ask questions in natural language
    You need advanced dashboards and visualizations ? ELK Stack Kibana Lens, TSVB, Canvas, Maps are unmatched
    You need good alerting without paying extra ? Graylog Better free-tier alerting with email, Slack, webhooks, PagerDuty
    You process 500+ GB of logs per day ? ELK Stack Proven at extreme scale, Elasticsearch cluster best-in-class
    You manage logs for multiple clients (MSP) ? Graylog Streams architecture makes multi-tenant log routing intuitive
    You prefer a pure open-source license ?? Neither Both use non-OSI licenses. Consider OpenSearch + OpenSearch Dashboards for pure Apache 2.0
    Canadian data sovereignty required ? Both Both can be fully self-hosted in Vancouver/Toronto with telemetry disabled

    Ops Note: Centralized Logs Need Retention Discipline

    Centralized logging solves search, but it can create a new storage problem if retention is not planned. Before sending every server log into ELK or Graylog, decide what you need for troubleshooting, what you need for audit review, and how long each class of log should live. Disk growth is one of the first operational failures we see in logging platforms.

    Hosting Requirements Comparison

    Component ELK Stack Graylog
    Minimum RAM (all-in-one, dev/test) 8 GB 6 GB
    Recommended RAM (small production) 16 GB 12-16 GB
    Minimum CPU 4 cores 2 cores
    Recommended CPU 4-8 cores 4-6 cores
    Storage 200 GB+ SSD 200 GB+ SSD
    Required Services Elasticsearch, Logstash, Kibana (+ cert gen, enrollment) Graylog, MongoDB, DataNode
    Docker Compose Services 8+ 3
    Setup Time 1-2 hours 15-30 minutes
    Recommended CWH Product Cloud VPS PSS1 (16 GB RAM) or higher Cloud VPS VPS5 (8 GB RAM) or higher
    Recommended Management Managed Support Tier 2 (complex ops) Managed Support Tier 1 (basic setup sufficient)

    Both platforms benefit from SSD storage — all Canadian Web Hosting Cloud VPS plans include SSD by default. If you are running large-scale Elasticsearch clusters, consider our E-Series Dedicated Servers starting at 32 GB RAM for dedicated log processing capacity.

    Our Recommendation

    For most Canadian small and medium businesses, we recommend starting with Graylog. Here is why:

    The operational simplicity of a single integrated package means you can go from “no centralized logging” to “searching all your logs in one place” in under 30 minutes. The free-tier alerting — with email, Slack, webhooks, and PagerDuty — covers what ELK users typically need a Platinum license for. And the MCP/LLM integration means your non-DevOps team members can ask questions about logs in plain English without learning Kibana query syntax.

    When to choose ELK: If you already have DevOps experience, need the absolute fastest search performance, plan to scale beyond 100 GB/day of log ingestion, or want Kibana’s unmatched visualization ecosystem — ELK Stack is the right choice. It is the industry standard for a reason. Just budget for the operational overhead. We recommend pairing it with our Tier 2 Managed Support if you do not have in-house Elasticsearch expertise.

    Both platforms keep your data in Canada when hosted in our Vancouver or Toronto data centres, with telemetry that can be fully disabled for compliance-sensitive environments.

    Getting Started

    Both ELK Stack and Graylog are available as Docker Compose deployments. Here is a quick-start guide for each:

    Graylog Quick Start (15 min):

    # Create docker-compose.yml with 3 services: graylog, mongo, datanode
# Set GRAYLOG_PASSWORD_SECRET and GRAYLOG_ROOT_PASSWORD_SHA2
# Configure inputs (syslog on 5140, GELF on 12201, Beats on 5044)
docker compose up -d

    Access the web UI at http://YOUR_SERVER:9000 and configure your first input. Logs start flowing immediately.

    ELK Stack Quick Start (1-2 hours):

    # Set vm.max_map_count on host
sudo sysctl -w vm.max_map_count=262144

# Generate certificates and enrollment tokens (multi-step)
# Create docker-compose.yml with elasticsearch, kibana, logstash, setup service
docker compose up -d

    Kibana UI at http://YOUR_SERVER:5601. Expect to spend time configuring Logstash pipelines and tweaking JVM heap settings.

    For detailed setup guides, see our server monitoring roundup (upcoming dedicated ELK and Graylog tutorials) and the troubleshooting guide for when Graylog disk fills up.

    Sources and Version Notes

    This comparison was refreshed in June 2026 against Elastic and Graylog documentation. Both platforms move quickly, and deployment details differ between self-managed Docker, packages, and managed services. Validate memory, storage, JVM, and vm.max_map_count guidance against the current vendor docs before production deployment.

    Conclusion

    ELK Stack and Graylog both solve the same core problem — centralized log management — but they do it very differently. ELK is a powerful Swiss Army knife that requires expertise to wield effectively. Graylog is a purpose-built tool designed to get the job done with less overhead.

    If you are a small team getting started with centralized logging, start with Graylog on a Canadian Web Hosting Cloud VPS. You will have your logs centralized in 30 minutes. If you outgrow it — and some teams do — ELK Stack will be waiting, and your logging infrastructure will already be in the right data centre.

    Need help setting either platform up? Our Managed Support team handles the full installation, configuration, and ongoing maintenance so you can focus on what your logs are telling you — not on configuring your log tool.