Open Distro for Elasticsearch: What it Means and Why it's Important

4 MIN READ
MIN READ

Recently Amazon launched Open Distro for Elasticsearch, a distribution of Elasticsearch with a number of additional features. The project was created out of concern that Elasticsearch was starting to include proprietary features, and that Elastic was straying from its open source roots. Open Distro for Elasticsearch contains a significant set of additions including:

  • Node-to-node encryption
  • User authentication, including single sign on (SSO)
  • Role-based access control (RBAC)
  • Audit logging
  • Support for SQL searches
  • Cluster performance analysis tools

Why is Amazon Releasing an Elasticsearch Distribution?

Amazon's main motivation for releasing Open Distro for Elasticsearch is a matter of license. Elasticsearch is an open source product that contains proprietary components. These features are entirely optional and are only made available after activating a license through the Kibana web UI.

The problem, according to Amazon, is that there is a blurred line between these proprietary components and the open source components. This makes it difficult for developers to know whether the code they're contributing to Elasticsearch improves the open source product or a proprietary component. Amazon also believes that Elastic is focusing their development efforts on their proprietary solutions and spending less effort on open source.

Adrian Cockcroft, VP of Cloud Architecture Strategy at AWS, says that "the innovation focus has shifted from furthering the open source [Elasticsearch] distribution to making the proprietary distribution popular. This means the majority of new Elasticsearch users are now, in fact, running proprietary software." The post continues, "[Elastic's direction] has created uncertainty about the longevity of the open source project as it is getting less innovation focus."

Elastic responded by stating their commitment to open source and how they've openly communicated the use of proprietary software in Elasticsearch. They specifically called out Amazon for "[asking] for special working relationship[s] in order to collaborate on code, demanding preferential treatment that would place them above our users." Considering Amazon hosts a widely used managed Elasticsearch service, it's easy to see why they would want to play a bigger role in Elasticsearch's development.

What Does this Mean for Elasticsearch?

With Amazon pushing its own open source Elasticsearch toolkit, the question is: how will this impact the development of Elasticsearch? Right now, it's difficult to say. Many of the features Amazon provides in their distribution implement features found in Elastic's commercial offerings. If Open Distro for Elasticsearch draws customers away from Elasticsearch's proprietary offerings, it could jeopardize not only Elastic's control over Elasticsearch's development, but also their ability to monetize it.

This also risks fragmenting the Elasticsearch community, especially if Amazon decides to modify Elasticsearch itself. Amazon stated their commitment to open sourcing their tools and pushing changes upstream, but if those changes aren't accepted by Elastic, it could lead to a fork. Amazon has stated that Open Distro for Elasticsearch is not a fork, but they're effectively putting pressure on Elastic to accept these additions despite conflicting interests.
Here at LogDNA, we're very familiar with Elasticsearch and its role in the log management industry. We're interested in seeing what Amazon has planned for their Elasticsearch distribution, and how it might help the Elasticsearch community grow. We'll keep an eye out for any new developments.

Table of Contents

    Share Article

    RSS Feed

    Next blog post
    You're viewing our latest blog post.
    Previous blog post
    You're viewing our oldest blog post.
    New Year, New Telemetry: Resolve to Stop Breaking Dashboards
    The Observability Stack is Collapsing: Why Context-First Data is the Only Path to AI-Powered Root Cause Analysis
    Mezmo + Catchpoint deliver observability SREs can rely on
    Mezmo’s AI-powered Site Reliability Engineering (SRE) agent for Root Cause Analysis (RCA)
    What is Active Telemetry
    Launching an agentic SRE for root cause analysis
    Paving the way for a new era: Mezmo's Active Telemetry
    The Answer to SRE Agent Failures: Context Engineering
    Empowering an MCP server with a telemetry pipeline
    The Debugging Bottleneck: A Manual Log-Sifting Expedition
    The Smartest Member of Your Developer Ecosystem: Introducing the Mezmo MCP Server
    Your New AI Assistant for a Smarter Workflow
    The Observability Problem Isn't Data Volume Anymore—It's Context
    Beyond the Pipeline: Data Isn't Oil, It's Power.
    The Platform Engineer's Playbook: Mastering OpenTelemetry & Compliance with Mezmo and Dynatrace
    From Alert to Answer in Seconds: Accelerating Incident Response in Dynatrace
    Taming Your Dynatrace Bill: How to Cut Observability Costs, Not Visibility
    Architecting for Value: A Playbook for Sustainable Observability
    How to Cut Observability Costs with Synthetic Monitoring and Responsive Pipelines
    Unlock Deeper Insights: Introducing GitLab Event Integration with Mezmo
    Introducing the New Mezmo Product Homepage
    The Inconvenient Truth About AI Ethics in Observability
    Observability's Moneyball Moment: How AI Is Changing the Game (Not Ending It)
    Do you Grok It?
    Top Five Reasons Telemetry Pipelines Should Be on Every Engineer’s Radar
    Is It a Cup or a Pot? Helping You Pinpoint the Problem—and Sleep Through the Night
    Smarter Telemetry Pipelines: The Key to Cutting Datadog Costs and Observability Chaos
    Why Datadog Falls Short for Log Management and What to Do Instead
    Telemetry for Modern Apps: Reducing MTTR with Smarter Signals
    Transforming Observability: Simpler, Smarter, and More Affordable Data Control
    Datadog: The Good, The Bad, The Costly
    Mezmo Recognized with 25 G2 Awards for Spring 2025
    Reducing Telemetry Toil with Rapid Pipelining
    Cut Costs, Not Insights:   A Practical Guide to Telemetry Data Optimization
    Webinar Recap: Telemetry Pipeline 101
    Petabyte Scale, Gigabyte Costs: Mezmo’s Evolution from ElasticSearch to Quickwit
    2024 Recap - Highlights of Mezmo’s product enhancements
    My Favorite Observability and DevOps Articles of 2024
    AWS re:Invent ‘24: Generative AI Observability, Platform Engineering, and 99.9995% Availability
    From Gartner IOCS 2024 Conference: AI, Observability Data, and Telemetry Pipelines
    Our team’s learnings from Kubecon: Use Exemplars, Configuring OTel, and OTTL cookbook
    How Mezmo Uses a Telemetry Pipeline to Handle Metrics, Part II
    Webinar Recap: 2024 DORA Report: Accelerate State of DevOps
    Kubecon ‘24 recap: Patent Trolls, OTel Lessons at Scale, and Principle Platform Abstractions
    Announcing Mezmo Flow: Build a Telemetry Pipeline in 15 minutes
    Key Takeaways from the 2024 DORA Report
    Webinar Recap | Telemetry Data Management: Tales from the Trenches
    What are SLOs/SLIs/SLAs?
    Webinar Recap | Next Gen Log Management: Maximize Log Value with Telemetry Pipelines
    Creating In-Stream Alerts for Telemetry Data
    Creating Re-Usable Components for Telemetry Pipelines
    Optimizing Data for Service Management Objective Monitoring
    More Value From Your Logs: Next Generation Log Management from Mezmo
    A Day in the Life of a Mezmo SRE
    Webinar Recap: Applying a Data Engineering Approach to Telemetry Data
    Dogfooding at Mezmo: How we used telemetry pipeline to reduce data volume
    Unlocking Business Insights with Telemetry Pipelines
    Why Your Telemetry (Observability) Pipelines Need to be Responsive
    How Data Profiling Can Reduce Burnout
    Data Optimization Technique: Route Data to Specialized Processing Chains
    Data Privacy Takeaways from Gartner Security & Risk Summit
    Mastering Telemetry Pipelines: Driving Compliance and Data Optimization
    A Recap of Gartner Security and Risk Summit: GenAI, Augmented Cybersecurity, Burnout
    Why Telemetry Pipelines Should Be A Part Of Your Compliance Strategy
    Pipeline Module: Event to Metric
    Telemetry Data Compliance Module
    OpenTelemetry: The Key To Unified Telemetry Data
    Data optimization technique: convert events to metrics
    What’s New With Mezmo: In-stream Alerting
    How Mezmo Used Telemetry Pipeline to Handle Metrics
    Webinar Recap: Mastering Telemetry Pipelines - A DevOps Lifecycle Approach to Data Management
    Open-source Telemetry Pipelines: An Overview
    SRECon Recap: Product Reliability, Burn Out, and more
    Webinar Recap: How to Manage Telemetry Data with Confidence
    Webinar Recap: Myths and Realities in Telemetry Data Handling
    Using Vector to Build a Telemetry Pipeline Solution
    Managing Telemetry Data Overflow in Kubernetes with Resource Quotas and Limits
    How To Optimize Telemetry Pipelines For Better Observability and Security
    Gartner IOCS Conference Recap: Monitoring and Observing Environments with Telemetry Pipelines
    AWS re:Invent 2023 highlights: Observability at Stripe, Capital One, and McDonald’s
    Webinar Recap: Best Practices for Observability Pipelines
    Introducing Responsive Pipelines from Mezmo
    My First KubeCon - Tales of the K8’s community, DE&I, sustainability, and OTel
    Modernize Telemetry Pipeline Management with Mezmo Pipeline as Code
    How To Profile and Optimize Telemetry Data: A Deep Dive
    Kubernetes Telemetry Data Optimization in Five Steps with Mezmo
    Introducing Mezmo Edge: A Secure Approach To Telemetry Data
    Understand Kubernetes Telemetry Data Immediately With Mezmo’s Welcome Pipeline
    Unearthing Gold: Deriving Metrics from Logs with Mezmo Telemetry Pipeline
    Webinar Recap: The Single Pane of Glass Myth
    Empower Observability Engineers: Enhance Engineering With Mezmo
    Webinar Recap: How to Get More Out of Your Log Data
    Unraveling the Log Data Explosion: New Market Research Shows Trends and Challenges
    Webinar Recap: Unlocking the Full Value of Telemetry Data
    Data-Driven Decision Making: Leveraging Metrics and Logs-to-Metrics Processors
    How To Configure The Mezmo Telemetry Pipeline
    Supercharge Elasticsearch Observability With Telemetry Pipelines
    Enhancing Grafana Observability With Telemetry Pipelines
    Optimizing Your Splunk Experience with Telemetry Pipelines
    Webinar Recap: Unlocking Business Performance with Telemetry Data