How Mezmo Gives Developers Easy Access To The Information They Need

4 MIN READ
MIN READ

Developers of any skill set find it frustrating when we don’t have access to the information we need. We want easy and complete access to application logs so that we can troubleshoot application problems. Quickly resolving issues requires a complete picture of what’s going on. Using the wrong tools limits our ability to determine what’s wrong, slowing the repair process. We often have to fend for ourselves with limited access to logs or no direct access to logging tools, forcing us to access applications directly.

Using something like kubectl for Kubernetes containers is direct, but it’s time-consuming. In some cases, a dependency on IT Ops/SREs to gather production information makes diagnosing issues even more problematic. Not having full access to basic system information, including events leading up to an incident, delays getting applications up and running.

Mezmo, formerly known as LogDNA, provides a fast and easy-to-use solution for developers looking to get more out of their application logs. We can find the information we need to solve an issue independently, ultimately reducing the time to resolution.

Why Developers Need Logs

Developers working with companies who have a DevOps mindset spend their time debugging, troubleshooting, and monitoring applications. There’s still a disconnect in some companies between developers and operations contributors, but it’s becoming common to expect us to take on production issues. DevOps is an integration of operations, development, and security. This integration has exploded in the market recently, with companies using it seeing a decrease of five times in their failure rate.

Companies expect developers to do more than conjure up their operations skills. But, to do more, we need tools made for workflows to help do these tasks. Far too many legacy logging and monitoring tools have only operations in mind, making them less than ideal for us. Operations folks have different needs than developers, and developer tools should reflect that. DevOps logging tools also need to be palatable for new developers. Approachable tools allow us to onboard a new developer quickly, ensuring that the tool multiplies the value it brings to the organization right from the start. Fortunately, Mezmo has many tools to help with speedy onboarding! One of these features is the Template Library that provides pre-configured Views, Boards, and Screens for some types of logs to provide a jumping off point for new users.

Beyond that, developers must have quick access to whatever they want to find. Outages are expensive in terms of lost revenue, reputation harm, and employee strain. Having developers dig through mountains of logs increases these expenses. Mezmo gives us the ability to search logs using natural-language queries. We can search for what we’re looking for in plain words, much like asking an operations teammate for help. Mezmo expert search engine lets us comb our logs with precision, enabling us to find what we need as fast as possible. We can conduct simple searches, like for single keywords, or compound searches, keyword exclusions, and even use AND and OR operations. Finally, searches can use an order of operations, which returns highly refined logs.

Forward-thinking developers take advantage of Mezmo's tags to make searching logs faster and easier. We can use a tag to group lines, and we can apply more than one tag to a given line. Logs that have been parsed and tagged are much easier to search through than raw log output.

Mezmo parses loglines on ingestion, making searching even more efficient. The system uses Automatic Parsing for the most common application and system types and provides Custom Parsing templates for everything else.

Beyond that, Mezmo provides highly technical controls like Usage Quotas, Exclusion Rules, and Automatic Archiving. These features allow us to debug, troubleshoot, and monitor applications without worrying about how much we are spending on the tool.

Conclusion

As a job title, “developer” is evolving. No longer are we isolated from IT operations professionals and site reliability engineers. Even when organizations employ both roles, companies that streamline communication reap benefits in productivity, application quality, and incident resolution times.

Proper logging is one of the most immediately valuable ways for us to add operations value. Developers who can access production data for their applications are miles ahead of those who have to get basic data from operations teammates. Even so, viewing raw application logs is only so helpful, especially for those new to IT operations. Mezmo provides a logging platform that makes application logs easy to view and search, which makes it easy for developers to find crucial information.

If you’re ready to supercharge your team’s operations capabilities, sign up for a fully-featured 14-day free trial or join our community to see how other organizations use Mezmo.


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.
    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
    Enhancing Datadog Observability with Telemetry Pipelines
    Transforming Your Data With Telemetry Pipelines
    6 Steps to Implementing a Telemetry Pipeline
    Webinar Recap: Taming Data Complexity at Scale