Top 7 Logstash Alternatives in 2025: Best Tools for Log Management, Observability & Cost Efficiency

Logstash, part of the Elastic Stack, is an open-source pipeline tool that ingests, transforms, and routes data from multiple sources to outputs like Elasticsearch. With its wide plugin ecosystem, it supports real-time log enrichment, durable queues, and flexible codecs, making it a core component in enterprise observability setups.

But users increasingly face pain points. High CPU/memory usage, complex scaling in Kubernetes, and steep learning curves slow adoption. Storage and retention costs in ELK environments add up quickly, while JVM issues and plugin instability create operational risk.

CubeAPM is the best Logstash alternative, solving these challenges with full OTEL and MELT support, smart sampling, and self-hosting options. It offers predictable flat pricing, strong compliance, and real-time support, cutting costs by up to 60% while improving reliability.

In this article, we’ll explore the top Logstash alternatives based on performance, cost transparency, compliance, and scalability.

Top 7 Logstash Alternatives 

1. CubeAPM
2. Datadog
3. New Relic
4. Dynatrace
5. Graylog
6. Fluentd
7. Rsyslog

Why Look for Logstash Alternatives

Difficulties with Pricing & Cost Predictability

Users commonly complain that while Logstash/Elastic starts with appealing pricing, actual monthly costs can escalate quickly and unpredictably due to retention, egress, and scaling. The break-ups in Elastic’s Serverless Observability pricing (ingest, retention, egress) make forecasting hard. Elastic’s public pricing page gives numbers like $0.105-$0.150/GB for ingest; $0.018-$0.020/GB-month for retention; $0.05/GB for egress after a free threshold. 

Example Cost Estimation for 10 TB/month Ingestion

For a mid-size business ingesting 10 TB of logs per month with 90-day retention and 1 TB of monthly egress, Elastic Serverless Observability would cost about $1,536 for ingestion, $614 for retention, and $50 for egress, bringing the total to roughly $2,200 per month. 

In contrast, a flat-rate alternative such as CubeAPM, with $0.15/GB ingestion plus small infra and transfer fees (~$0.19/GB all-in) and unlimited retention, would cost about $1,546 per month. This shows that Elastic’s tiered model can quickly outpace a predictable per-GB model, with differences widening further at larger volumes or longer retention windows.

Resource Consumption & Infrastructure Overhead

Many users report that Logstash becomes resource-hungry under high log volume. Because it’s JVM-based and often uses heavy filters (e.g., grok), CPU and RAM usage rise steeply. In Kubernetes or cloud-native deployments, teams must over-provision memory or tune heap sizes constantly to avoid pipeline failures. This raises the infrastructure and maintenance burden. G2 reviews mention “resource-intensive, especially as data volume grows” for Logstash. 

Scaling & Operational Complexity

While Logstash can be scaled horizontally, Elastic’s documentation shows that scaling is not always straightforward. Pipeline and plugin design affect whether you can simply add more instances; JVM tuning and version compatibility are also frequent pain points. Debugging pipeline failures and plugin issues becomes tougher as your setup grows, increasing the burden on SRE or infrastructure teams. 

Increasing Preference for OpenTelemetry / MELT

More teams are moving toward unified pipelines that handle Metrics, Events, Logs, and Traces (MELT), often using OpenTelemetry-based collectors instead of using Logstash for logs + other agents/systems for metrics/traces. The community feedback suggests OTEL collectors often have lower overhead, better multi-backend export flexibility, and improved signal correlation. 

Criteria for Selecting Logstash Alternatives

Comprehensive MELT Capabilities

The next solution should handle metrics, events, logs, and traces in one place. Having all signals under a single roof speeds up root-cause analysis and reduces the hassle of juggling multiple tools.

OpenTelemetry as a First-Class Citizen

Support for OpenTelemetry is essential in 2025. Tools that can natively ingest OTEL data give teams flexibility to standardize instrumentation across services while staying free from vendor lock-in.

Intelligent Sampling for Cost Control

Not every log or trace needs to be stored forever. Platforms that apply context-aware sampling keep the most valuable data—such as errors or high-latency requests—while trimming out the noise, reducing costs without compromising insight.

Deployment Flexibility and Data Ownership

For businesses working under strict compliance rules like GDPR or India’s DPDP, having the option to self-host or deploy in your own cloud ensures data never leaves your environment and avoids surprise egress bills.

Predictable and Transparent Pricing

Budgeting gets tricky when fees are scattered across ingestion, retention, and egress. Favor solutions with clear per-GB pricing and included retention, so finance teams know exactly what the monthly spend will be.

Ease of Management and Responsive Support

Logstash often requires careful tuning and expertise to keep pipelines stable. Look for alternatives that are lightweight to run on Kubernetes and backed by real-time support channels, helping teams resolve incidents faster.

Logstash Overview

Known for

Logstash is known for being an open-source data ingestion and transformation pipeline. It collects logs and events from multiple sources, parses and enriches them, then ships them to destinations such as Elasticsearch or other analytics systems.

Standout Features

• Over 200 plugins: supports a wide range of input, filter, codec, and output plugins.
  
• Rich filtering & transformation: grok parsing, geo-IP enrichments, field manipulation.
  
• Durability & reliability: persistent queues, dead-letter queues, safe delivery.

Key Features

• Inputs & Outputs: connects to numerous data sources and multiple output destinations.
  
• Filters & Codecs: parse unstructured data, apply schemas, transform fields.
  
• Extensibility: plugin framework for custom development.
  
• Security & Monitoring: monitoring of pipelines, encryption in transit, RBAC, secure keystores.

Pros

• Highly flexible pipelines & transformations
  
• Large ecosystem & plugin support
  
• Strong integration with Elasticsearch, Beats, and Kibana
  
• Free open-source version for self-managed use

Cons

• Resource-intensive at high volumes
  
• Steep learning curve for configuration and tuning
  
• Complex scaling for large pipelines
  
• Managed service pricing can escalate with scale

Best for

Logstash is best for organizations already invested in the Elastic Stack that need flexible log ingestion and transformation pipelines. It suits teams with engineering capacity to manage complex infrastructure, where customization and extensibility matter more than ease of use or predictable costs.

Logstash Pricing & Customer Reviews

• Pricing: Logstash itself is free to use when self-managed, but costs include infrastructure and operations. On Elastic Cloud, pricing follows a usage-based model: data ingestion is typically $0.15–$0.50 per GB, retention is $0.02–$0.04 per GB-month, and egress is $0.05/GB after 50 GB free. Entry-level Elastic Cloud plans begin around $95/month, with costs scaling quickly as ingestion and retention grow.
  
• G2 rating: 4.5/5
  
• Praised for: flexible pipelines, plugin ecosystem, strong integrations, real-time log processing
  
• Criticized for: high resource usage, complexity in setup, debugging challenges, rising costs at scale

Top 7 Logstash Alternatives

1. CubeAPM

Known for

CubeAPM is known for being a modern, OpenTelemetry-native observability platform that unifies Metrics, Events, Logs, and Traces (MELT). It helps teams simplify monitoring with transparent pricing and full-stack coverage while offering both SaaS and self-hosted options.

Standout Features

• Full MELT observability: supports metrics, events, logs, and distributed traces in one platform.
  
• Smart sampling engine: context-aware sampling that reduces cost while keeping critical data.
  
• Data localization compliance: BYOC/self-hosting ensures data never leaves your cloud.

Key Features

• Distributed Tracing: deep visibility into service dependencies and performance bottlenecks.
  
• Infrastructure Monitoring: built-in dashboards for servers, Kubernetes, and cloud resources.
  
• Log Monitoring: real-time log ingestion, search, and correlation with traces.
  
• Synthetic Monitoring: test endpoints and flows with uptime and performance checks.
  
• Real User Monitoring (RUM): front-end performance tracking across browsers and devices.
  
• Error Tracking: detect and resolve application errors with detailed context.

Pros

• Transparent, predictable pricing ($0.15/GB ingestion, infra, and transfer minimal)
  
• Unlimited data retention at no extra cost
  
• 800+ integrations with popular agents and platforms
  
• Responsive support channels via Slack/WhatsApp with core developers

Cons

• Less suited for teams that prefer exclusively vendor-managed SaaS with no self-hosting option
  
• Primarily focused on observability and does not cover adjacent areas like cloud security management

Best for

CubeAPM is best for organizations seeking an affordable, OpenTelemetry-native alternative to Logstash and Elastic Stack. It is especially useful for teams in regulated industries that require data localization compliance and those looking to consolidate MELT observability into one platform without hidden costs.

CubeAPM Pricing & Customer Reviews

• Pricing: $0.15/GB ingestion, unlimited retention included; no egress surprises
  
• Rating: 4.7/5
  
• Praised for: predictable pricing, fast support, modern OTEL-native architecture, flexible deployment options

CubeAPM vs Logstash

While Logstash specializes in log pipelines and transformations, CubeAPM provides a complete MELT observability suite with logs, metrics, traces, RUM, synthetics, and error tracking. CubeAPM also offers smarter sampling to keep costs low, flat pricing with unlimited retention, and data-localization compliance through self-hosted/BYOC deployments. For teams struggling with Logstash’s complexity, scaling overhead, or unpredictable Elastic Cloud pricing, CubeAPM is the more modern and cost-effective choice.

2. Datadog

Known for

Datadog is a cloud-native, SaaS observability platform that unifies infrastructure monitoring, APM, log management, RUM, synthetics, error tracking, security, and more—accessible through one UI and APIs. It’s widely adopted for its breadth (900+ built-in integrations) and strong product velocity across MELT and adjacent categories.

Standout Features

• 900+ integrations: prebuilt collectors and dashboards cover major clouds, runtimes, databases, and platforms.
  
• AI assistance & anomaly detection: Bits AI and Watchdog accelerate triage and surface outliers automatically.
  
• Unified MELT workspace: correlate metrics, logs, traces, user sessions, and synthetic tests in one place for faster RCA.

Key Features

• APM & Tracing: distributed tracing, flamegraphs, service maps, dynamic instrumentation, and continuous profiler.
  
• Log Management: real-time ingestion, pipelines, multiple indexing/retention tiers, archive/rehydration workflows.
  
• Infrastructure Monitoring: host/container/Kubernetes monitoring, autoscaling insights, network, and cloud cost views.
  
• Digital Experience: browser and mobile RUM, session replay, product analytics, and synthetic monitoring.

Pros

• Broad, mature product suite across observability and security
  
• 900+ integrations and a strong ecosystem
  
• Robust APM with profiling and database monitoring
  
• Powerful dashboards, alerts, notebooks, and collaboration

Cons

• Pricing can become complex and higher at scale (hosts, indexed spans/events, retention, egress)
  
• SaaS-only; no self-hosted deployment option
  
• High-cardinality metrics and custom metrics may increase spend
  
• Requires careful guardrails to control ingestion and indexing costs

Best for

Datadog fits teams that want a full-featured, SaaS observability platform with rapid time-to-value, extensive integrations, and deep APM/log/RUM capabilities, especially in cloud-first environments where centralized control and AI-assisted triage matter.

Datadog Pricing & Customer Reviews

• Pricing: Infrastructure Monitoring Pro starts at $15/host/month (annual) or $18/host/month on-demand; Enterprise is $23/host/month (annual) or $27/host/month on-demand. Logs ingestion is $0.10/GB; indexing and retention are charged additionally, depending on the plan. APM & Continuous Profiler start at about $31/host/month. RUM begins around $1.50 per 1,000 sessions.
  
• G2 rating: 4.4/5
  
• Praised for: wide product coverage, integration depth, powerful APM/log workflows, quality dashboards, and alerting
  
• Criticized for: cost control at scale, pricing complexity (hosts vs indexed logs vs spans vs retention), overage risks when logs/events spike

Datadog vs Logstash

Both handle logs, but they solve different problems. Logstash is an open-source pipeline focused on ingest/transform/route; you own the deployment, tuning, and scaling. Datadog is a managed end-to-end observability platform with APM, infra, logs, RUM, synthetics, and AI assistance, priced per hosts/spans/events with multiple retention tiers. If you want a turnkey SaaS with broad MELT coverage and are comfortable with usage-based pricing, Datadog is compelling; if you prefer to self-operate log pipelines and avoid vendor billing complexity, Logstash remains a fit.

3. New Relic

Known for

New Relic is a full-stack, SaaS observability platform that brings APM, infrastructure, logs, RUM (browser & mobile), synthetics, error tracking, and business journey mapping (Pathpoint) into one workspace—now with first-class OpenTelemetry (OTLP) ingest.

Standout Features

• Unified data + user model: access 50+ capabilities with one platform and user tiers, avoiding per-host licensing.
  
• Native OTLP ingest: send OpenTelemetry traces, metrics, and logs directly to New Relic’s OTLP endpoint.
  
• Pathpoint (business observability): visualize customer/product/service journeys to tie telemetry to business outcomes.

Key Features

• APM & Tracing: distributed tracing, code-level profiling, service maps, and Transaction/APM 360 workflows.
  
• Log Management: centralized, AI-assisted log analytics with “logs in context.”
  
• Infrastructure Monitoring: host/container/Kubernetes visibility, change tracking, cloud integrations.
  
• Digital Experience: browser RUM, mobile monitoring, session replay, and synthetics for proactive testing.

Pros

• Broad, mature suite across MELT with strong product velocity
  
• Usage-based pricing model with a generous free tier
  
• Native OTLP support and rich integrations
  
• Good dashboards, alerting, and troubleshooting workflows

Cons

• Costs can rise with higher data ingest or premium options
  
• Pricing model (users + data or compute + data) can be complex to forecast
  
• Can feel overwhelming for new teams; tuning needed for noisy data
  
• Advanced retention/governance features require Data Plus

Best for

Teams that want a single, cloud-hosted observability hub covering apps, infra, logs, and user experience, with native OTEL pipelines and options to tie reliability to business journeys. Strong fit for cloud-first orgs consolidating multiple tools into one platform.

New Relic Pricing & Customer Reviews

• Pricing: Free tier includes 100 GB/month of data ingest and one full-platform user. Beyond that, Original Data is $0.40/GB, while Data Plus is $0.60/GB. Core users are $49/user/month, and Full Platform users are $99/user/month.
  
• G2 rating: 4.4/5
  
• Praised for: real-time monitoring, ease of use, integrations, insightful dashboards, and troubleshooting
  
• Criticized for: expense at scale, pricing complexity, learning curve/initial setup, occasional UI responsiveness feedback

New Relic vs Logstash

Logstash is a self-managed ingest/transform/route pipeline—great for building custom log flows, but it stops short of end-to-end observability. New Relic delivers a managed, full-stack platform: APM, infra, logs, RUM, and synthetics, plus native OTLP ingest and Pathpoint to map telemetry to business journeys. Choose New Relic if you want a turnkey MELT with AI-assisted workflows and are comfortable with usage-based pricing; choose Logstash if you specifically need customizable pipelines you host and operate yourself.

4. Dynatrace

Known for

Dynatrace is known for a unified, AI-powered observability and security platform that automates discovery, context generation, and root-cause analysis at scale. Its OneAgent and Grail data lakehouse are central to delivering full-stack insights across apps, infra, logs, and business metrics.

Standout Features

• AI-powered causal analysis (Davis®): automatic anomaly detection, causal insights, and prescriptive guidance.
  
• Grail data lakehouse: indexless, schema-on-read storage for high-performance analytics across signals.
  
• OneAgent single deployment: one install per host for automatic instrumentation and continuous collection.

Key Features

• Full-Stack Monitoring: combine application, infrastructure, network, and security telemetry for contextual answers.
  
• Log Management & Analytics: ingest, process, and query logs with fast, contextual correlation to traces and metrics.
  
• Digital Experience (RUM & synthetics): real user monitoring, session replay, and synthetic checks for UX and availability.
  
• Business Observability: tie telemetry to business KPIs and customer journeys using built-in analytics.

Pros

• Automated, AI-driven root-cause analysis and causal insights
  
• Single-agent instrumentation that reduces setup toil
  
• High-performance analytics via Grail for correlated MELT queries
  
• Broad platform capabilities across observability, security, and automation

Cons

• Pricing and deployment geared toward enterprise consumption and commitment models
  
• Platform breadth can be heavyweight for very small teams or minimal monitoring needs
  
• Some advanced features require a platform subscription and configuration

Best for

Dynatrace is best for large and enterprise organizations that need deep, automated observability and causal AI across complex cloud-native and hybrid environments, and who want a single platform that covers observability, AIOps, and security at scale.

Dynatrace Pricing & Customer Reviews

• Pricing: Full-Stack Monitoring costs approximately $0.08 per 8GiB-hour for host-based metric collection; Infrastructure Monitoring costs around $0.04 per host-hour; Logs ingest & process at about $0.20 per GiB; Traces ingest & process also around $0.20 per GiB; RUM sessions are priced at approximately $0.00225 per session; synthetic monitoring requests ~ $0.001 each. Retention and query options depend on usage/commit volume.
  
• G2 rating: 4.5/5
  
• Praised for: automated instrumentation and discovery, AI-driven insights, unified analytics, high-throughput log/trace handling
  
• Criticized for: perceived platform complexity for very small teams, enterprise-oriented pricing, and commitments

Dynatrace vs Logstash

Dynatrace offers a managed, AI-driven platform that ingests, analyzes, and correlates MELT signals out of the box—with built-in automation, tracing, and a unified data lake—whereas Logstash is a self-managed pipeline focused on log ingestion, parsing, and routing. If you want automated causal analysis, a single-agent install model, and integrated business observability, Dynatrace is compelling; if you need lightweight, customizable, self-hosted log pipelines without vendor lock-in, Logstash remains the simpler, more DIY choice.

5. Graylog

Known for

Graylog is known for centralized log management with source-available Graylog Open, plus commercial offerings—Graylog Enterprise, Graylog Security (SIEM), and Graylog API Security—that add enterprise features for observability and security. It emphasizes flexible deployment (cloud, on-prem, or hybrid) and cost control through data tiering and consumption-based licensing.

Standout Features

• Source-available core: Graylog Open (SSPL) provides a free, self-managed foundation you can run on-prem or in your cloud.
  
• Consumption-based licensing: “Store everything, pay only for what you analyze” with Active Data vs. standby tiers for predictable spend.
  
• Flexible deployment: Same experience whether you choose Graylog Cloud (AWS) or self-managed/on-prem, with hybrid options.

Key Features

• Pipelines & enrichment: parse, normalize, enrich, and route logs in real time to improve searchability and context.
  
• Search, dashboards & investigations: fast search, curated dashboards, and investigation workflows for operations and security.
  
• Events, alerts & correlations: rules, detections, and alerting to surface anomalies and reduce time to response.
  
• Data management & tiering: intelligent routing to active or standby storage to balance performance with cost.

Pros

• Free, source-available core with upgrade path
  
• Cloud, on-prem, and hybrid deployment flexibility
  
• Consumption model focused on Active Data
  
• Security offerings (SIEM, API Security) built on the same platform

Cons

• Entry pricing for commercial editions is annual and may exceed very small-team budgets
  
• Advanced security and API protection features require paid editions
  
• Self-managed deployments still require operational ownership

Best for

Teams that want full control over log data with the freedom to deploy on-prem, in their own cloud, or as a managed service—while keeping costs predictable through Active/standby tiering. A strong fit for organizations seeking an enterprise log platform that can expand into SIEM and API security without switching stacks.

Graylog Pricing & Customer Reviews

• Pricing: Graylog Enterprise starts at $15,000/year (paid annually), Graylog Security starts at $18,000/year, and Graylog API Security starts at $18,000/year. Graylog Small Business offers free up to 2 GB/day. Graylog Cloud is available (including via AWS Marketplace), and the newer consumption-based model focuses on spending on the Active Data you analyze, not everything you store.
  
• G2 rating: 4.4/5
• Praised for: Easy to install, good customer support, efficient log management
• Criticized for: Dashboard issues, difficul to navigate, issues with searching and filtering

Graylog vs Logstash

Logstash is a self-managed pipeline focused on ingest/transform/route, great for custom log flows, but limited to logs without turnkey security features. Graylog adds enterprise log management with built-in dashboards, alerting, investigations, and optional Security and API Security capabilities, plus cloud/on-prem flexibility and a consumption-based pricing approach that can simplify cost planning.

6. Fluentd

Known for

Fluentd is known for being an open-source, cloud-native data/log collector that builds a unified logging layer. It decouples data sources from backends, treats logs as JSON for easy parsing/enrichment, and ships data to many destinations across the stack.

Standout Features

• Unified logging layer: decouples producers and consumers so you can route the same data to multiple backends simultaneously.
  
• Plugin architecture: input, filter, and output plugins enable flexible parsing, enrichment, and delivery.
  
• LTS packages & cross-platform installers: official LTS channels and installers (including Windows MSI) for stable enterprise adoption.

Key Features

• Data collection & transformation: collect from apps, syslog, containers; parse and enrich events in-stream.
  
• JSON-first processing: treats logs as JSON for consistent structure, searchability, and schema evolution.
  
• Buffering & reliability: memory/disk buffers, retries, and backpressure controls to prevent data loss.
  
• Broad integrations: connectors for 125+ systems via plugins to outputs like object storage, message queues, and analytics backends.

Pros

• Open source and widely adopted in cloud-native environments
  
• Flexible plugin model for parsing, enrichment, and routing
  
• Reliable buffering and delivery semantics
  
• Available LTS and official installers for stable operations
  

Cons

• No built-in UI, dashboards, or analytics
  
• Configuration and plugin management may require engineering expertise
  
• Logs/events focused; metrics/traces require additional components
  
• Operational ownership is on the user team

Best for

Teams that want a lightweight, open-source alternative to Logstash for log collection and routing—especially in Kubernetes or hybrid environments—while keeping control of configuration, scaling, and destination choice. Fluentd fits well where you already have or prefer your own search/analytics backend and need a flexible, reliable pipeline.

Fluentd Pricing & Customer Reviews

• Pricing: Fluentd is free and open source (Apache 2.0). Commercial Enterprise Services (support, custom plugins, managed services with SLAs) are available through official partners; pricing is by inquiry.
  
• G2 rating: 4.4/5
  
• Praised for: unified logging layer, plugin ecosystem, JSON-first design, LTS availability
  
• Criticized for: no native UI/analytics, hands-on configuration, and plugin lifecycle management

Fluentd vs Logstash

Both are powerful log collectors with rich plugins, but Fluentd emphasizes a lightweight, JSON-first, cloud-native pipeline with LTS channels and broad plugin coverage. Logstash offers deep filter plugins and tight Elastic Stack integration, but is heavier to run. Choose Fluentd when you want an open-source collector that’s easy to run at the edge and in Kubernetes, and pair it with your preferred analytics/storage backend.

7. Rsyslog

Known for

Rsyslog is known for being a high-performance, modular syslog daemon and log pipeline widely deployed across Linux systems. It provides reliable log collection, transformation, and routing while maintaining a lightweight footprint, making it a staple in enterprise and cloud environments.

Standout Features

• High-performance, multithreaded engine: near wire-speed ingestion with disk-assisted queues for reliability.
  
• Flexible routing & filtering: property- and expression-based filters, rulesets, and templating for dynamic outputs.
  
• Broad output integrations: modules for Elasticsearch, Kafka, databases, cloud endpoints, and more.

Key Features

• Secure transport: TCP, TLS/SSL, and RELP for reliable, encrypted delivery.
  
• Structured logging: JSON support, parsing/enrichment modules, and powerful templating.
  
• Action queues & buffering: in-memory/disk queues, rate limiting, and backpressure controls.
  
• Linux-native design: lightweight, widely adopted as the default syslog daemon in many Linux distributions.

Pros

• Mature, fast, and lightweight
  
• Highly configurable with a rich module ecosystem
  
• Reliable delivery with buffering and retries
  
• Free and open source for Linux

Cons

• No built-in UI, dashboards, or analytics
  
• Complex configurations can be hard to maintain
  
• Logs-only without native traces/metrics support
  
• Commercial Windows Agent requires licensing

Best for

Rsyslog is best for organizations that want a stable, Linux-native log collector and forwarder with minimal resource use, especially in environments where logs need to be shipped reliably to Elasticsearch, Kafka, or an observability backend. It’s well-suited as an edge collector or central relay in larger pipelines.

Rsyslog Pricing & Customer Reviews

• Pricing: Rsyslog for Linux is completely free and open source. The Rsyslog Windows Agent is commercially licensed per machine, with editions priced at Basic $55, Professional $79, and Enterprise $109.
  
• G2 rating: 4.2/5
  
• Praised for: speed, reliability, flexible configuration, long-term stability on Linux
  
• Criticized for: steep configuration learning curve, lack of built-in analytics, and commercial licensing requirement for Windows

Rsyslog vs Logstash

Rsyslog is a lightweight, Linux-native pipeline designed for high-speed log forwarding, reliability, and minimal overhead. Logstash, on the other hand, provides a richer plugin ecosystem and is more advanced in-pipeline transformations, but is heavier to run. Teams seeking simplicity, performance, and stability often lean toward Rsyslog, while those needing advanced enrichment and Elastic Stack integration favor Logstash.

Conclusion

Logstash remains powerful for log ingestion and routing, but its complexity, heavy resource use, and unpredictable Elastic Cloud costs push many teams to seek better options. CubeAPM directly addresses these pain points with a modern, OpenTelemetry-native platform that unifies metrics, events, logs, and traces (MELT). 

With unlimited retention, smart sampling, and compliance-ready self-hosting, CubeAPM offers clarity, cost savings, and simplicity that Logstash lacks. It stands out as the best Logstash alternative, giving engineering teams everything they need in one affordable, easy-to-manage platform.

Ready to cut complexity and costs while gaining full-stack observability? Start your journey with CubeAPM today.